Campus features

Prompt:
Information Extraction is the process of automatically identifying and extracting structured information from unstructured text data. The goal is to transform raw text into meaningful data that can be easily analyzed and used in various applications. Named Entity Recognition (NER) and Relation Extraction are two common tasks in Information Extraction.

Named Entity Recognition involves identifying and classifying named entities such as people, organizations, locations, and other domain-specific concepts. Relation Extraction involves identifying and extracting relationships between entities.

The task at hand is RE: Relation Extraction.

Here is an example of task execution:

{'Schema': [{'designed': {'domain': 'Person', 'range': 'Structure'}}, {'located_in': {'domain': 'Structure', 'range': 'Location'}}, {'part_of': {'domain': 'City', 'range': 'Country'}}, {'friends_with': {'domain': 'Person', 'range': 'Person'}}, {'lives_at': {'domain': 'Person', 'range': 'Location'}}, {'visits': {'domain': 'Person', 'range': 'Location'}}, {'accompanied_by': {'domain': 'Person', 'range': 'Person'}}, {'shares': {'domain': 'Person', 'range': 'Product'}}], 'Text': 'Gustave Eiffel designed the Eiffel Tower, which is located in Paris, France.', 'Relations': [['Gustave Eiffel', 'designed', 'Eiffel Tower'], ['Eiffel Tower', 'located_in', 'Paris'], ['Paris', 'part_of', 'France']]}

Analyze the text and targets carefully, identify relevant information.

Extract the information in the following format: `[["Subject", "Relation", "Object"], ...]`. If no matching entities are found, return an **empty list**. Please provide only the extracted information without any explanations.

Schema: [{"part_of": {"domain": "Organization", "range": "Organization"}}, {"parent_company_of": {"domain": "Organization", "range": "Organization"}}, {"subsidiary_of": {"domain": "Organization", "range": "Organization"}}, {"acquired": {"domain": "Organization", "range": "Organization"}}, {"divested": {"domain": "Organization", "range": "Organization"}}, {"owns_brand": {"domain": "Organization", "range": "Product/Brand"}}, {"holds_stake_in": {"domain": "Organization", "range": "Organization"}}, {"spun_off": {"domain": "Organization", "range": "Organization"}}, {"formed_from": {"domain": "Organization", "range": "Organization"}}, {"founded_by": {"domain": "Organization", "range": "Person"}}, {"has_CEO": {"domain": "Organization", "range": "Person"}}, {"manufactures": {"domain": "Organization", "range": "ProductType"}}, {"develops": {"domain": "Organization", "range": "ProductType"}}, {"produces": {"domain": "Organization", "range": "ProductType"}}, {"sells": {"domain": "Organization", "range": "ProductType"}}, {"has_product_line": {"domain": "Organization", "range": "Product/Brand"}}, {"is_a_type_of": {"domain": "Product/Brand", "range": "ProductType"}}, {"is_brand_of": {"domain": "Product/Brand", "range": "Organization"}}, {"features_technology": {"domain": "Product/Brand", "range": "Technology"}}, {"uses_material": {"domain": "Product/Brand", "range": "Material"}}, {"launched_product": {"domain": "Organization", "range": "Product/Brand"}}, {"had_revenue_of": {"domain": "Organization", "range": "Amount"}}, {"had_profit_of": {"domain": "Organization", "range": "Amount"}}, {"in_year": {"domain": "FinancialMetric", "range": "Year"}}, {"market_value_of": {"domain": "Organization", "range": "Amount"}}, {"is_publicly_traded": {"domain": "Organization", "range": "Boolean"}}, {"listed_on_exchange": {"domain": "Organization", "range": "StockExchange"}}, {"experienced_growth": {"domain": "Organization", "range": "FinancialMetric"}}, {"occurred_in_year": {"domain": "Event/Action", "range": "Year"}}, {"occurred_on_date": {"domain": "Event/Action", "range": "SpecificDate"}}, {"resulted_in": {"domain": "Event/Action", "range": "Outcome"}}, {"preceded": {"domain": "Event/Action", "range": "Event/Action"}}, {"followed_by": {"domain": "Event/Action", "range": "Event/Action"}}, {"marked_milestone": {"domain": "Event/Action", "range": "Organization"}}, {"influenced_by": {"domain": "Event/Action", "range": "Event/Action"}}, {"led_to": {"domain": "Event/Action", "range": "Event/Action"}}, {"was_a_response_to": {"domain": "Event/Action", "range": "Event/Action"}}, {"has_trademark": {"domain": "Organization", "range": "Trademark"}}, {"uses_logo": {"domain": "Organization", "range": "Logo"}}, {"acquired_trademark_from": {"domain": "Organization", "range": "Organization"}}, {"is_known_for": {"domain": "Organization", "range": "Characteristic"}}, {"launched_campaign": {"domain": "Organization", "range": "BusinessConcept"}}]
Text: article: University_of_North_Carolina_at_Chapel_Hill, Campus features: Located in McCorkle Place is theDavie Poplartree under which a popular legend says the university's founder,William Richardson Davie, selected the location for the university. The legend of the Davie Poplar says that as long as the tree stands, so will the university.However, the name was not associated with the tree until almost a century after the university's foundation.A graft from the tree, named Davie Poplar Jr., was planted nearby in 1918 after the original tree was struck by lightning.A second graft, Davie Poplar III, was planted in conjunction with the university'sbicentennialcelebration in 1993.The student members of the university'sDialectic and Philanthropic Societiesare not allowed to walk on the grass of McCorkle Place out of respect for the unknown resting place ofJoseph Caldwell, the university's first president. A symbol of the university is theOld Well, a small neoclassicalrotundaat the south end of McCorkle Place based on the Temple of Love in theGardens of Versailles, in the same location as the original well that provided water for the school.The well stands at the south end of McCorkle Place, the northern quad, between two of the campus's oldest buildings,Old East, and Old West. The historicPlaymakers Theatreis located on Cameron Avenue between McCorkle Place and Polk Place. It was designed byAlexander Jackson Davis, the same architect who renovated the northern façade ofOld Eastin 1844.The east-facing building was completed in 1851 and initially served as a library and as a ballroom. It was originally named Smith Hall after North Carolina GovernorGeneral Benjamin Smith, who was a special aide toGeorge Washingtonduring theAmerican Revolutionary Warand was an early benefactor to the university.When the library moved to Hill Hall in 1907, the building was transferred between the school of law and the agricultural chemistry department until it was taken over by the university theater group, the Carolina Playmakers, in 1924. It was remodeled as a theater, opening in 1925 as Playmakers Theater.Playmakers Theatre was declared aNational Historic Landmarkin 1973. The Morehead–Patterson bell tower, south of the Wilson Library, was commissioned byJohn Motley Morehead III, the benefactor of theMorehead-Cain Scholarship.The hedge and surrounding landscape was designed byWilliam C. Coker, botany professor and creator of thecampus arboretum. Traditionally, seniors have the opportunity to climb the tower a few days prior to May commencement.

[["University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "Old_Well"], ["University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "Playmakers_Theatre"], ["University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "Davie_Poplartree"], ["University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "Polk_Place"], ["University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "McCorkle_Place"], ["University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "Old_East"], ["University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "Old_West"], ["University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "Hill_Hall"], ["University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "Smith_Hall"], ["University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "Morehead–Patterson_Bell_Tower"], ["University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "Wilson_Library"], ["University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "Campus_Arboretum_(University_of_North_Carolina_at_Chapel_Hill)"]]


Environment and sustainability

company product service industry brand country location organization person founder position event action founding accusition merger partnership expansion restructuring divestment sale bankruptcy financial_metric business_concept revenue profit loss investment funding market_share competition market_trend regulation innovation sustainability corporate_social_responsibility award date/time year period

Prompt:
Information Extraction is the process of automatically identifying and extracting structured information from unstructured text data. The goal is to transform raw text into meaningful data that can be easily analyzed and used in various applications. Named Entity Recognition (NER) and Relation Extraction are two common tasks in Information Extraction.

Named Entity Recognition involves identifying and classifying named entities such as people, organizations, locations, and other domain-specific concepts. Relation Extraction involves identifying and extracting relationships between entities.

The task at hand is NER: Named Entity Recognition.

Here is an example of task execution:

{'Schema': ['Person', 'Organization', 'Location', 'Date', 'Product'], 'Text': 'The Eiffel Tower in Paris, designed by Gustave Eiffel, is one of the most famous landmarks in France.', 'Entities': [['Eiffel Tower', 'Location'], ['Paris', 'Location'], ['Gustave Eiffel', 'Person'], ['France', 'Location']]}

Analyze the text and targets carefully, identify relevant information.

Extract the information in the following format: `[["Entity", "Type"], ...]`. If no matching entities are found, return an **empty list**. Please provide only the extracted information without any explanations.

Schema: ["company", "product", "service", "industry", "brand", "country", "location", "organization", "person", "founder", "position", "event", "action", "founding", "accusition", "merger", "partnership", "expansion", "restructuring", "divestment", "sale", "bankruptcy", "financial_metric", "business_concept", "revenue", "profit", "loss", "investment", "funding", "market_share", "competition", "market_trend", "regulation", "innovation", "sustainability", "corporate_social_responsibility", "award", "date/time", "year", "period"]
Text: article: University_of_North_Carolina_at_Chapel_Hill, Environment and sustainability: The university has a goal that all new buildings meet the requirements forLEEDsilver certification,and the Allen Education Center at the university'sNorth Carolina Botanic Gardenwas the first building in North Carolina to receive LEED Platinum certification. UNC-Chapel Hill'scogenerationfacility produced one-fourth of the electricity and all of the steam used on campus as of 2008.In 2006, the university and theTown of Chapel Hilljointly agreed to reduce greenhouse gas emissions 60% by 2050, becoming the first town-gown partnership in the country to make such an agreement.Through these efforts, the university achieved an "A−" grade on the Sustainable Endowment Institute's College Sustainability Report Card 2010. The university was criticized in 2019 for abandoning a promise to shutter its coal-fired power plant by 2020.Initially, the university has announced plans to become carbon neutral by 2050, but in 2021, the plan was changed to 2040.In December 2019, the university was sued by theSierra Cluband theCenter for Biological Diversityfor violations of theClean Air Act.

[["University_of_North_Carolina_at_Chapel_Hill", "Company"], ["Allen_Education_Center", "Building"], ["University_of_North_Carolina_at_Chapel_Hill", "Person"], ["LEED_platinum", "number"], ["University_of_North_Carolina_at_Chapel_Hill", "Building"], ["North_Carolina_Botanic_Garden", "Location"], ["A−", "grade"], ["University_of_North_Carolina_at_Chapel_Hill", "Building"], ["LEED_silver", "number"], ["Sierra_Club", "Person"], ["Center_for_Biological_Diversity", "Person"], ["Coal-fired_power_plant", "Building"], ["2040", "number"], ["University_of_North_Carolina_at_Chapel_Hill", "Building"], ["Cogeneration", "Building"], ["2008", "number"], ["College_Sustainability_Report_Card_2010", "Building"], ["Sierra_Club", "Organization"], ["Chapel_Hill,_North_Carolina", "City"], ["Clean_Air_Act", "Regulation"], ["60.0", "number"], ["2050", "number"], ["University_of_North_Carolina_at_Chapel_Hill", "Person"], ["Sierra_Club", "Organization"], ["Center_for_Biological_Diversity", "Organization"], ["Coal-fired_power_plant", "Product"], ["Chapel_Hill,_North_Carolina", "Building"], ["2006", "number"], ["College_Sustainability_Report_Card_2010", "University_of_North_Carolina_at_Chapel_Hill"], ["A−", "grade"], ["Sierra_Club", "Person"], ["Chapel_Hill,_North_Carolina", "Person"], ["LEED_silver", "number"], ["University_of_North_Carolina_at_Chapel_Hill", "Building"], ["North_Carolina_Botanic_Garden", "Building"], ["2040", "number"], ["Coal-fired_power_plant", "Building"], ["Sierra_Club", "Person"], ["Center_for_Biological_Diversity", "Person"], ["University_of_North_Carolina_at_Chapel_Hill", "Building"], ["Clean_Air_Act", "Regulation"], ["2008", "number"], ["College_Sustainability_Report_Card_2010", "Building"], ["Chapel_Hill,_North_Carolina", "Building"], ["60.0", "number"], ["2050", "number"], ["University_of_North_Carolina_at_Chapel_Hill", "Person"], ["Sierra_Club", "Organization"], ["Center_for_Biological_Diversity", "Organization"], ["Coal-fired_power_plant", "Product"], ["Chapel_Hill,_North_Carolina", "Building"], ["2006", "number"]]


Environment and sustainability

Prompt:
Information Extraction is the process of automatically identifying and extracting structured information from unstructured text data. The goal is to transform raw text into meaningful data that can be easily analyzed and used in various applications. Named Entity Recognition (NER) and Relation Extraction are two common tasks in Information Extraction.

Named Entity Recognition involves identifying and classifying named entities such as people, organizations, locations, and other domain-specific concepts. Relation Extraction involves identifying and extracting relationships between entities.

The task at hand is RE: Relation Extraction.

Here is an example of task execution:

{'Schema': [{'designed': {'domain': 'Person', 'range': 'Structure'}}, {'located_in': {'domain': 'Structure', 'range': 'Location'}}, {'part_of': {'domain': 'City', 'range': 'Country'}}, {'friends_with': {'domain': 'Person', 'range': 'Person'}}, {'lives_at': {'domain': 'Person', 'range': 'Location'}}, {'visits': {'domain': 'Person', 'range': 'Location'}}, {'accompanied_by': {'domain': 'Person', 'range': 'Person'}}, {'shares': {'domain': 'Person', 'range': 'Product'}}], 'Text': 'Gustave Eiffel designed the Eiffel Tower, which is located in Paris, France.', 'Relations': [['Gustave Eiffel', 'designed', 'Eiffel Tower'], ['Eiffel Tower', 'located_in', 'Paris'], ['Paris', 'part_of', 'France']]}

Analyze the text and targets carefully, identify relevant information.

Extract the information in the following format: `[["Subject", "Relation", "Object"], ...]`. If no matching entities are found, return an **empty list**. Please provide only the extracted information without any explanations.

Schema: [{"part_of": {"domain": "Organization", "range": "Organization"}}, {"parent_company_of": {"domain": "Organization", "range": "Organization"}}, {"subsidiary_of": {"domain": "Organization", "range": "Organization"}}, {"acquired": {"domain": "Organization", "range": "Organization"}}, {"divested": {"domain": "Organization", "range": "Organization"}}, {"owns_brand": {"domain": "Organization", "range": "Product/Brand"}}, {"holds_stake_in": {"domain": "Organization", "range": "Organization"}}, {"spun_off": {"domain": "Organization", "range": "Organization"}}, {"formed_from": {"domain": "Organization", "range": "Organization"}}, {"founded_by": {"domain": "Organization", "range": "Person"}}, {"has_CEO": {"domain": "Organization", "range": "Person"}}, {"manufactures": {"domain": "Organization", "range": "ProductType"}}, {"develops": {"domain": "Organization", "range": "ProductType"}}, {"produces": {"domain": "Organization", "range": "ProductType"}}, {"sells": {"domain": "Organization", "range": "ProductType"}}, {"has_product_line": {"domain": "Organization", "range": "Product/Brand"}}, {"is_a_type_of": {"domain": "Product/Brand", "range": "ProductType"}}, {"is_brand_of": {"domain": "Product/Brand", "range": "Organization"}}, {"features_technology": {"domain": "Product/Brand", "range": "Technology"}}, {"uses_material": {"domain": "Product/Brand", "range": "Material"}}, {"launched_product": {"domain": "Organization", "range": "Product/Brand"}}, {"had_revenue_of": {"domain": "Organization", "range": "Amount"}}, {"had_profit_of": {"domain": "Organization", "range": "Amount"}}, {"in_year": {"domain": "FinancialMetric", "range": "Year"}}, {"market_value_of": {"domain": "Organization", "range": "Amount"}}, {"is_publicly_traded": {"domain": "Organization", "range": "Boolean"}}, {"listed_on_exchange": {"domain": "Organization", "range": "StockExchange"}}, {"experienced_growth": {"domain": "Organization", "range": "FinancialMetric"}}, {"occurred_in_year": {"domain": "Event/Action", "range": "Year"}}, {"occurred_on_date": {"domain": "Event/Action", "range": "SpecificDate"}}, {"resulted_in": {"domain": "Event/Action", "range": "Outcome"}}, {"preceded": {"domain": "Event/Action", "range": "Event/Action"}}, {"followed_by": {"domain": "Event/Action", "range": "Event/Action"}}, {"marked_milestone": {"domain": "Event/Action", "range": "Organization"}}, {"influenced_by": {"domain": "Event/Action", "range": "Event/Action"}}, {"led_to": {"domain": "Event/Action", "range": "Event/Action"}}, {"was_a_response_to": {"domain": "Event/Action", "range": "Event/Action"}}, {"has_trademark": {"domain": "Organization", "range": "Trademark"}}, {"uses_logo": {"domain": "Organization", "range": "Logo"}}, {"acquired_trademark_from": {"domain": "Organization", "range": "Organization"}}, {"is_known_for": {"domain": "Organization", "range": "Characteristic"}}, {"launched_campaign": {"domain": "Organization", "range": "BusinessConcept"}}]
Text: article: University_of_North_Carolina_at_Chapel_Hill, Environment and sustainability: The university has a goal that all new buildings meet the requirements forLEEDsilver certification,and the Allen Education Center at the university'sNorth Carolina Botanic Gardenwas the first building in North Carolina to receive LEED Platinum certification. UNC-Chapel Hill'scogenerationfacility produced one-fourth of the electricity and all of the steam used on campus as of 2008.In 2006, the university and theTown of Chapel Hilljointly agreed to reduce greenhouse gas emissions 60% by 2050, becoming the first town-gown partnership in the country to make such an agreement.Through these efforts, the university achieved an "A−" grade on the Sustainable Endowment Institute's College Sustainability Report Card 2010. The university was criticized in 2019 for abandoning a promise to shutter its coal-fired power plant by 2020.Initially, the university has announced plans to become carbon neutral by 2050, but in 2021, the plan was changed to 2040.In December 2019, the university was sued by theSierra Cluband theCenter for Biological Diversityfor violations of theClean Air Act.

[["University_of_North_Carolina_at_Chapel_Hill", "has_trademark", "LEED_certification"], ["University_of_North_Carolina_at_Chapel_Hill", "has_trademark", "A−_(grade)"], ["University_of_North_Carolina_at_Chapel_Hill", "has_trademark", "College_Sustainability_Report_Card_2010"], ["University_of_North_Carolina_at_Chapel_Hill", "has_trademark", "Sierra_Club"], ["University_of_North_Carolina_at_Chapel_Hill", "has_trademark", "Center_for_Biological_Diversity"], ["University_of_North_Carolina_at_Chapel_Hill", "has_trademark", "Coal-fired_power_plant"], ["University_of_North_Carolina_at_Chapel_Hill", "has_trademark", "Cogeneration"], ["University_of_North_Carolina_at_Chapel_Hill", "has_trademark", "Allen_Education_Center"], ["University_of_North_Carolina_at_Chapel_Hill", "has_trademark", "North_Carolina_Botanic_Garden"], ["University_of_North_Carolina_at_Chapel_Hill", "has_trademark", "2006"], ["University_of_North_Carolina_at_Chapel_Hill", "has_trademark", "Town_of_Chapel_Hill"], ["University_of_North_Carolina_at_Chapel_Hill", "has_trademark", "2050"], ["University_of_North_Carolina_at_Chapel_Hill", "has_trademark", "60.0"], ["University_of_North_Carolina_at_Chapel_Hill", "has_trademark", "Clean_Air_Act"], ["University_of_North_Carolina_at_Chapel_Hill", "has_trademark", "2019"], ["University_of_North_Carolina_at_Chapel_Hill", "has_trademark", "2040"]]


Curriculum

company product service industry brand country location organization person founder position event action founding accusition merger partnership expansion restructuring divestment sale bankruptcy financial_metric business_concept revenue profit loss investment funding market_share competition market_trend regulation innovation sustainability corporate_social_responsibility award date/time year period

Prompt:
Information Extraction is the process of automatically identifying and extracting structured information from unstructured text data. The goal is to transform raw text into meaningful data that can be easily analyzed and used in various applications. Named Entity Recognition (NER) and Relation Extraction are two common tasks in Information Extraction.

Named Entity Recognition involves identifying and classifying named entities such as people, organizations, locations, and other domain-specific concepts. Relation Extraction involves identifying and extracting relationships between entities.

The task at hand is NER: Named Entity Recognition.

Here is an example of task execution:

{'Schema': ['Person', 'Organization', 'Location', 'Date', 'Product'], 'Text': 'The Eiffel Tower in Paris, designed by Gustave Eiffel, is one of the most famous landmarks in France.', 'Entities': [['Eiffel Tower', 'Location'], ['Paris', 'Location'], ['Gustave Eiffel', 'Person'], ['France', 'Location']]}

Analyze the text and targets carefully, identify relevant information.

Extract the information in the following format: `[["Entity", "Type"], ...]`. If no matching entities are found, return an **empty list**. Please provide only the extracted information without any explanations.

Schema: ["company", "product", "service", "industry", "brand", "country", "location", "organization", "person", "founder", "position", "event", "action", "founding", "accusition", "merger", "partnership", "expansion", "restructuring", "divestment", "sale", "bankruptcy", "financial_metric", "business_concept", "revenue", "profit", "loss", "investment", "funding", "market_share", "competition", "market_trend", "regulation", "innovation", "sustainability", "corporate_social_responsibility", "award", "date/time", "year", "period"]
Text: article: University_of_North_Carolina_at_Chapel_Hill, Curriculum: As of 2007,[update]UNC-Chapel Hill offered 71 bachelor's, 107 master's and 74doctoral degreeprograms.The university enrolls students from all 100North Carolina countiesand state law requires that the percentage of students from North Carolina in eachfreshmanclass meet or exceed 82%.The student body consists of 17,981 undergraduate students and 10,935 graduate and professional students (as of Fall 2009).Racial and ethnic minorities comprise 30.8% of UNC-Chapel Hill's undergraduate population as of 2010and applications from international students more than doubled in five years from 702 in 2004 to 1,629 in 2009.Eighty-nine percent of enrolling first year students in 2009 reported a GPA of 4.0 or higher on a weighted 4.0 scale.The most popular majors at UNC-Chapel Hill in 2009 were biology, business administration, psychology, media and journalism, and political science.UNC-Chapel Hill also offers 300 study abroad programs in 70 countries. At the undergraduate level, all students must fulfill a number of general education requirements as part of the Making Connections curriculum, which was introduced in 2006.English, social science, history, foreign language, mathematics, and natural science courses are required of all students, ensuring that they receive a broadliberal artseducation.The university also offers a wide range of first year seminars for incoming freshmen.After their second year, students move on to the College of Arts and Sciences, or choose an undergraduate professional school program within the schools of medicine, nursing, business, education, pharmacy, information and library science, public health, or media and journalism.Undergraduates are held to an eight-semester limit of study.

[["University_of_North_Carolina_at_Chapel_Hill", "Company"], ["300", "number"], ["2009", "year"], ["107", "number"], ["\"Making Connections\"", "Curriculum"], ["\"University of North Carolina at Chapel Hill\"", "string"], ["2006", "year"], ["10,935", "number"], ["Biology", "major"], ["Business", "major"], ["Media_and_Journalism", "major"], ["Political_Science", "major"], ["Psychology", "major"], ["North_Carolina", "Country"], ["2004", "year"], ["702", "number"], ["1,629", "number"], ["30.8%", "number"], ["English_language", "Course"], ["Social_Science", "Course"], ["Natural_Sciences", "Course"], ["History", "Course"], ["Foreign_language", "Course"], ["8", "number"], ["North_Carolina", "University"], ["17,981", "number"], ["82.0%", "number"], ["4.0", "number"], ["2007", "year"], ["74", "number"], ["University_of_North_Carolina_at_Chapel_Hill", "University"], ["All_100_Counties_in_North_Carolina", "number"], ["89.0%", "number"], ["Undergraduate_Professional_School", "School"], ["School_of_Medicine", "School"], ["School_of_Nursing", "School"], ["School_of_Business", "School"], ["School_of_Education", "School"], ["School_of_Pharmacy", "School"], ["School_of_Media_and_Journalism", "School"], ["School_of_Public_Health", "School"], ["70", "number"], ["North_Carolina", "State"], ["English_language", "Language"], ["General_Education", "Curriculum"], ["4.0", "number"], ["2009", "date"], ["300", "number"], ["Biology", "Science"], ["Psychology", "Science"], ["Political_Science", "Science"], ["Media_and_Journalism", "Science"], ["North_Carolina", "Place"], ["School", "Organisation"], ["English_language", "Course"], ["Social_Science", "Course"], ["Natural_Sciences", "Course"], ["History", "Course"], ["Foreign_language", "Course"], ["17,981", "number"], ["10,935", "number"], ["University_of_North_Carolina_at_Chapel_Hill", "University"], ["Biology", "major"], ["Business", "major"], ["Media_and_Journalism", "major"], ["Political_Science", "major"], ["Psychology", "major"], ["North_Carolina", "Country"], ["2004", "year"], ["702", "number"], ["1,629", "number"], ["30.8%", "number"], ["English_language", "Language"], ["General_Education", "Curriculum"], ["4.0", "number"], ["2007", "year"], ["74", "number"], ["University_of_North_Carolina_at_Chapel_Hill", "University"], ["All_100_Counties_in_North_Carolina", "number"], ["89.0%", "number"], ["Undergraduate_Professional_School", "School"], ["School_of_Medicine", "School"], {"School_of_Nursing", "School"}, {"School_of_Business", "School"}, {"School_of_Education", "School"}, {"School_of_Pharmacy", "School"}, {"School_of_Media_and_Journalism", "School"}, {"School_of_Public_Health", "School"}, {"70", "number"}, {"North_Carolina", "State"}]


Curriculum

Prompt:
Information Extraction is the process of automatically identifying and extracting structured information from unstructured text data. The goal is to transform raw text into meaningful data that can be easily analyzed and used in various applications. Named Entity Recognition (NER) and Relation Extraction are two common tasks in Information Extraction.

Named Entity Recognition involves identifying and classifying named entities such as people, organizations, locations, and other domain-specific concepts. Relation Extraction involves identifying and extracting relationships between entities.

The task at hand is RE: Relation Extraction.

Here is an example of task execution:

{'Schema': [{'designed': {'domain': 'Person', 'range': 'Structure'}}, {'located_in': {'domain': 'Structure', 'range': 'Location'}}, {'part_of': {'domain': 'City', 'range': 'Country'}}, {'friends_with': {'domain': 'Person', 'range': 'Person'}}, {'lives_at': {'domain': 'Person', 'range': 'Location'}}, {'visits': {'domain': 'Person', 'range': 'Location'}}, {'accompanied_by': {'domain': 'Person', 'range': 'Person'}}, {'shares': {'domain': 'Person', 'range': 'Product'}}], 'Text': 'Gustave Eiffel designed the Eiffel Tower, which is located in Paris, France.', 'Relations': [['Gustave Eiffel', 'designed', 'Eiffel Tower'], ['Eiffel Tower', 'located_in', 'Paris'], ['Paris', 'part_of', 'France']]}

Analyze the text and targets carefully, identify relevant information.

Extract the information in the following format: `[["Subject", "Relation", "Object"], ...]`. If no matching entities are found, return an **empty list**. Please provide only the extracted information without any explanations.

Schema: [{"part_of": {"domain": "Organization", "range": "Organization"}}, {"parent_company_of": {"domain": "Organization", "range": "Organization"}}, {"subsidiary_of": {"domain": "Organization", "range": "Organization"}}, {"acquired": {"domain": "Organization", "range": "Organization"}}, {"divested": {"domain": "Organization", "range": "Organization"}}, {"owns_brand": {"domain": "Organization", "range": "Product/Brand"}}, {"holds_stake_in": {"domain": "Organization", "range": "Organization"}}, {"spun_off": {"domain": "Organization", "range": "Organization"}}, {"formed_from": {"domain": "Organization", "range": "Organization"}}, {"founded_by": {"domain": "Organization", "range": "Person"}}, {"has_CEO": {"domain": "Organization", "range": "Person"}}, {"manufactures": {"domain": "Organization", "range": "ProductType"}}, {"develops": {"domain": "Organization", "range": "ProductType"}}, {"produces": {"domain": "Organization", "range": "ProductType"}}, {"sells": {"domain": "Organization", "range": "ProductType"}}, {"has_product_line": {"domain": "Organization", "range": "Product/Brand"}}, {"is_a_type_of": {"domain": "Product/Brand", "range": "ProductType"}}, {"is_brand_of": {"domain": "Product/Brand", "range": "Organization"}}, {"features_technology": {"domain": "Product/Brand", "range": "Technology"}}, {"uses_material": {"domain": "Product/Brand", "range": "Material"}}, {"launched_product": {"domain": "Organization", "range": "Product/Brand"}}, {"had_revenue_of": {"domain": "Organization", "range": "Amount"}}, {"had_profit_of": {"domain": "Organization", "range": "Amount"}}, {"in_year": {"domain": "FinancialMetric", "range": "Year"}}, {"market_value_of": {"domain": "Organization", "range": "Amount"}}, {"is_publicly_traded": {"domain": "Organization", "range": "Boolean"}}, {"listed_on_exchange": {"domain": "Organization", "range": "StockExchange"}}, {"experienced_growth": {"domain": "Organization", "range": "FinancialMetric"}}, {"occurred_in_year": {"domain": "Event/Action", "range": "Year"}}, {"occurred_on_date": {"domain": "Event/Action", "range": "SpecificDate"}}, {"resulted_in": {"domain": "Event/Action", "range": "Outcome"}}, {"preceded": {"domain": "Event/Action", "range": "Event/Action"}}, {"followed_by": {"domain": "Event/Action", "range": "Event/Action"}}, {"marked_milestone": {"domain": "Event/Action", "range": "Organization"}}, {"influenced_by": {"domain": "Event/Action", "range": "Event/Action"}}, {"led_to": {"domain": "Event/Action", "range": "Event/Action"}}, {"was_a_response_to": {"domain": "Event/Action", "range": "Event/Action"}}, {"has_trademark": {"domain": "Organization", "range": "Trademark"}}, {"uses_logo": {"domain": "Organization", "range": "Logo"}}, {"acquired_trademark_from": {"domain": "Organization", "range": "Organization"}}, {"is_known_for": {"domain": "Organization", "range": "Characteristic"}}, {"launched_campaign": {"domain": "Organization", "range": "BusinessConcept"}}]
Text: article: University_of_North_Carolina_at_Chapel_Hill, Curriculum: As of 2007,[update]UNC-Chapel Hill offered 71 bachelor's, 107 master's and 74doctoral degreeprograms.The university enrolls students from all 100North Carolina countiesand state law requires that the percentage of students from North Carolina in eachfreshmanclass meet or exceed 82%.The student body consists of 17,981 undergraduate students and 10,935 graduate and professional students (as of Fall 2009).Racial and ethnic minorities comprise 30.8% of UNC-Chapel Hill's undergraduate population as of 2010and applications from international students more than doubled in five years from 702 in 2004 to 1,629 in 2009.Eighty-nine percent of enrolling first year students in 2009 reported a GPA of 4.0 or higher on a weighted 4.0 scale.The most popular majors at UNC-Chapel Hill in 2009 were biology, business administration, psychology, media and journalism, and political science.UNC-Chapel Hill also offers 300 study abroad programs in 70 countries. At the undergraduate level, all students must fulfill a number of general education requirements as part of the Making Connections curriculum, which was introduced in 2006.English, social science, history, foreign language, mathematics, and natural science courses are required of all students, ensuring that they receive a broadliberal artseducation.The university also offers a wide range of first year seminars for incoming freshmen.After their second year, students move on to the College of Arts and Sciences, or choose an undergraduate professional school program within the schools of medicine, nursing, business, education, pharmacy, information and library science, public health, or media and journalism.Undergraduates are held to an eight-semester limit of study.

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"has_product_line", "Undergraduate_Professional_School_of_Medicine"], ["University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "Undergraduate_Professional_School_of_Nursing"], ["University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "Undergraduate_Professional_School_of_Business"], ["University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "Undergraduate_Professional_School_of_Education"], ["University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "Undergraduate_Professional_School_of_Pharmacy"], ["University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "Undergraduate_Professional_School_of_Public_Health"], ["University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "Undergraduate_Professional_School_of_Media_and_Journalism"], ["University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "Information_and_Library_Science"], ["University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "Study_abroad"], ["University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "Making_Connections_(curriculum)"], ["University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "First-Year_Seminars"], ["University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "Graduate_school"], ["University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "Undergraduate_school"], ["University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "College_of_Arts_and_Sciences"], {"University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "Doctoral_degree"}, {"University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "B.A._degree"}, {"University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "M.A._degree"}, {"University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "M.S._degree"}, {"University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "Ph.D._degree"}, {"University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "B.S._degree"}, {"University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "M.B.A._degree"}, {"University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "Law_school"}, {"University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "Medical_school"}, {"University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "School_of_Public_Health"}, {"University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "School_of_Education"}, {"University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "School_of_Nursing"}, {"University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "School_of_Medicine"], {"University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "School_of_Journalism_and_Mass_Communication"}, {"University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "School_of_Business"], {"University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "School_of_Public_Policy_and_Administration"}, {"University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "School_of_Law"}, {"University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "School_of_Pharmacy"}, {"University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "School_of_Humanities"}, {"University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "School_of_Agriculture"}, {"University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "School_of_Informatics"], {"University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "School_of_Public_Relations"}, {"University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "School_of_Communication"}, {"University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "School_of_Library_and_Info_Sciences"}, {"University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "8-semester_rule"}, {"University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "30.8_percent"}, {"University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "2009"}, {"University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "702"], {"University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "1,629"], {"University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "4.0"], {"University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "82.0_percent"}, {"University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "17,981"], {"University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "10,935"}, {"University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "2007"}, {"University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "71"], {"University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "107"], {"University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "74"}, {"University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "Fall_2009"}, {"University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "89.0_percent"}, {"University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "North_Carolina"], {"University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "North_Carolina_counties"}, {"University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "100"}]


Undergraduate admissions

company product service industry brand country location organization person founder position event action founding accusition merger partnership expansion restructuring divestment sale bankruptcy financial_metric business_concept revenue profit loss investment funding market_share competition market_trend regulation innovation sustainability corporate_social_responsibility award date/time year period

Prompt:
Information Extraction is the process of automatically identifying and extracting structured information from unstructured text data. The goal is to transform raw text into meaningful data that can be easily analyzed and used in various applications. Named Entity Recognition (NER) and Relation Extraction are two common tasks in Information Extraction.

Named Entity Recognition involves identifying and classifying named entities such as people, organizations, locations, and other domain-specific concepts. Relation Extraction involves identifying and extracting relationships between entities.

The task at hand is NER: Named Entity Recognition.

Here is an example of task execution:

{'Schema': ['Person', 'Organization', 'Location', 'Date', 'Product'], 'Text': 'The Eiffel Tower in Paris, designed by Gustave Eiffel, is one of the most famous landmarks in France.', 'Entities': [['Eiffel Tower', 'Location'], ['Paris', 'Location'], ['Gustave Eiffel', 'Person'], ['France', 'Location']]}

Analyze the text and targets carefully, identify relevant information.

Extract the information in the following format: `[["Entity", "Type"], ...]`. If no matching entities are found, return an **empty list**. Please provide only the extracted information without any explanations.

Schema: ["company", "product", "service", "industry", "brand", "country", "location", "organization", "person", "founder", "position", "event", "action", "founding", "accusition", "merger", "partnership", "expansion", "restructuring", "divestment", "sale", "bankruptcy", "financial_metric", "business_concept", "revenue", "profit", "loss", "investment", "funding", "market_share", "competition", "market_trend", "regulation", "innovation", "sustainability", "corporate_social_responsibility", "award", "date/time", "year", "period"]
Text: article: University_of_North_Carolina_at_Chapel_Hill, Undergraduate admissions: UNC-Chapel Hill's admissions process is "most selective" according toU.S. News & World Report.For the Class of 2025 (enrolled fall 2021), UNC-Chapel Hill received 53,776 applications and accepted 10,347 (19.2%). Of those accepted, 4,689 enrolled, ayield rate(the percentage of accepted students who choose to attend the university) of 45.3%. UNC-Chapel Hill's freshmanretention rateis 96.5%, with 91.9% going on to graduate within six years. Of the 60% of enrolled freshmen in 2021 who submittedACTscores; the middle 50 percent Composite score was between 29 and 33. Of the 15% of the incoming freshman class who submittedSATscores; the middle 50 percent Composite scores were 1330-1500.In the 2020–2021 academic year, 20 freshman students wereNational Merit Scholars.The university isneed-blindfor domestic applicants.


Undergraduate admissions

Prompt:
Information Extraction is the process of automatically identifying and extracting structured information from unstructured text data. The goal is to transform raw text into meaningful data that can be easily analyzed and used in various applications. Named Entity Recognition (NER) and Relation Extraction are two common tasks in Information Extraction.

Named Entity Recognition involves identifying and classifying named entities such as people, organizations, locations, and other domain-specific concepts. Relation Extraction involves identifying and extracting relationships between entities.

The task at hand is RE: Relation Extraction.

Here is an example of task execution:

{'Schema': [{'designed': {'domain': 'Person', 'range': 'Structure'}}, {'located_in': {'domain': 'Structure', 'range': 'Location'}}, {'part_of': {'domain': 'City', 'range': 'Country'}}, {'friends_with': {'domain': 'Person', 'range': 'Person'}}, {'lives_at': {'domain': 'Person', 'range': 'Location'}}, {'visits': {'domain': 'Person', 'range': 'Location'}}, {'accompanied_by': {'domain': 'Person', 'range': 'Person'}}, {'shares': {'domain': 'Person', 'range': 'Product'}}], 'Text': 'Gustave Eiffel designed the Eiffel Tower, which is located in Paris, France.', 'Relations': [['Gustave Eiffel', 'designed', 'Eiffel Tower'], ['Eiffel Tower', 'located_in', 'Paris'], ['Paris', 'part_of', 'France']]}

Analyze the text and targets carefully, identify relevant information.

Extract the information in the following format: `[["Subject", "Relation", "Object"], ...]`. If no matching entities are found, return an **empty list**. Please provide only the extracted information without any explanations.

Schema: [{"part_of": {"domain": "Organization", "range": "Organization"}}, {"parent_company_of": {"domain": "Organization", "range": "Organization"}}, {"subsidiary_of": {"domain": "Organization", "range": "Organization"}}, {"acquired": {"domain": "Organization", "range": "Organization"}}, {"divested": {"domain": "Organization", "range": "Organization"}}, {"owns_brand": {"domain": "Organization", "range": "Product/Brand"}}, {"holds_stake_in": {"domain": "Organization", "range": "Organization"}}, {"spun_off": {"domain": "Organization", "range": "Organization"}}, {"formed_from": {"domain": "Organization", "range": "Organization"}}, {"founded_by": {"domain": "Organization", "range": "Person"}}, {"has_CEO": {"domain": "Organization", "range": "Person"}}, {"manufactures": {"domain": "Organization", "range": "ProductType"}}, {"develops": {"domain": "Organization", "range": "ProductType"}}, {"produces": {"domain": "Organization", "range": "ProductType"}}, {"sells": {"domain": "Organization", "range": "ProductType"}}, {"has_product_line": {"domain": "Organization", "range": "Product/Brand"}}, {"is_a_type_of": {"domain": "Product/Brand", "range": "ProductType"}}, {"is_brand_of": {"domain": "Product/Brand", "range": "Organization"}}, {"features_technology": {"domain": "Product/Brand", "range": "Technology"}}, {"uses_material": {"domain": "Product/Brand", "range": "Material"}}, {"launched_product": {"domain": "Organization", "range": "Product/Brand"}}, {"had_revenue_of": {"domain": "Organization", "range": "Amount"}}, {"had_profit_of": {"domain": "Organization", "range": "Amount"}}, {"in_year": {"domain": "FinancialMetric", "range": "Year"}}, {"market_value_of": {"domain": "Organization", "range": "Amount"}}, {"is_publicly_traded": {"domain": "Organization", "range": "Boolean"}}, {"listed_on_exchange": {"domain": "Organization", "range": "StockExchange"}}, {"experienced_growth": {"domain": "Organization", "range": "FinancialMetric"}}, {"occurred_in_year": {"domain": "Event/Action", "range": "Year"}}, {"occurred_on_date": {"domain": "Event/Action", "range": "SpecificDate"}}, {"resulted_in": {"domain": "Event/Action", "range": "Outcome"}}, {"preceded": {"domain": "Event/Action", "range": "Event/Action"}}, {"followed_by": {"domain": "Event/Action", "range": "Event/Action"}}, {"marked_milestone": {"domain": "Event/Action", "range": "Organization"}}, {"influenced_by": {"domain": "Event/Action", "range": "Event/Action"}}, {"led_to": {"domain": "Event/Action", "range": "Event/Action"}}, {"was_a_response_to": {"domain": "Event/Action", "range": "Event/Action"}}, {"has_trademark": {"domain": "Organization", "range": "Trademark"}}, {"uses_logo": {"domain": "Organization", "range": "Logo"}}, {"acquired_trademark_from": {"domain": "Organization", "range": "Organization"}}, {"is_known_for": {"domain": "Organization", "range": "Characteristic"}}, {"launched_campaign": {"domain": "Organization", "range": "BusinessConcept"}}]
Text: article: University_of_North_Carolina_at_Chapel_Hill, Undergraduate admissions: UNC-Chapel Hill's admissions process is "most selective" according toU.S. News & World Report.For the Class of 2025 (enrolled fall 2021), UNC-Chapel Hill received 53,776 applications and accepted 10,347 (19.2%). Of those accepted, 4,689 enrolled, ayield rate(the percentage of accepted students who choose to attend the university) of 45.3%. UNC-Chapel Hill's freshmanretention rateis 96.5%, with 91.9% going on to graduate within six years. Of the 60% of enrolled freshmen in 2021 who submittedACTscores; the middle 50 percent Composite score was between 29 and 33. Of the 15% of the incoming freshman class who submittedSATscores; the middle 50 percent Composite scores were 1330-1500.In the 2020–2021 academic year, 20 freshman students wereNational Merit Scholars.The university isneed-blindfor domestic applicants.

[["University_of_North_Carolina_at_Chapel_Hill", "undergraduate_admissions", "\"Most selective\" (U.S. News & World Report)"], ["University_of_North_Carolina_at_Chapel_Hill", "undergraduate_admissions", "2025"], ["University_of_North_Carolina_at_Chapel_Hill", "undergraduate_admissions", "53676"], ["University_of_North_Carolina_at_Chapel_Hill", "undergraduate_admissions", "10347"], ["University_of_North_Carolina_at_Chapel_Hill", "undergraduate_admissions", "0.192"], ["University_of_North_Carolina_at_Chapel_Hill", "undergraduate_admissions", "4689"], ["University_of_North_Carolina_at_Chapel_Hill", "undergraduate_admissions", "0.453"], ["University_of_North_Carolina_at_Chapel_Hill", "undergraduate_admissions", "0.965"], ["University_of_North_Carolina_at_Chapel_Hill", "undergraduate_admissions", "0.919"], ["University_of_North_Carolina_at_Chapel_Hill", "undergraduate_admissions", "ACT"], ["University_of_North_Carolina_at_Chapel_Hill", "undergraduate_admissions", "\"29-33\""], ["University_of_North_Carolina_at_Chapel_Hill", "undergraduate_admissions", "0.6"], ["University_of_North_Carolina_at_Chapel_Hill", "undergraduate_admissions", "SAT"], ["University_of_North_Carolina_at_Chapel_Hill", "undergraduate_admissions", "\"1330-1500\""], ["University_of_North_Carolina_at_Chapel_Hill", "undergraduate_admissions", "National_Merit_Scholar"], ["University_of_North_Carolina_at_Chapel_Hill", "undergraduate_admissions", "20"], ["University_of_North_Carolina_at_Chapel_Hill", "undergraduate_admissions", "Need-blind_policies"], ["University_of_North_Carolina_at_Chapel_Hill", "undergraduate_admissions", "Domestic_student"]]


Honor code

company product service industry brand country location organization person founder position event action founding accusition merger partnership expansion restructuring divestment sale bankruptcy financial_metric business_concept revenue profit loss investment funding market_share competition market_trend regulation innovation sustainability corporate_social_responsibility award date/time year period

Prompt:
Information Extraction is the process of automatically identifying and extracting structured information from unstructured text data. The goal is to transform raw text into meaningful data that can be easily analyzed and used in various applications. Named Entity Recognition (NER) and Relation Extraction are two common tasks in Information Extraction.

Named Entity Recognition involves identifying and classifying named entities such as people, organizations, locations, and other domain-specific concepts. Relation Extraction involves identifying and extracting relationships between entities.

The task at hand is NER: Named Entity Recognition.

Here is an example of task execution:

{'Schema': ['Person', 'Organization', 'Location', 'Date', 'Product'], 'Text': 'The Eiffel Tower in Paris, designed by Gustave Eiffel, is one of the most famous landmarks in France.', 'Entities': [['Eiffel Tower', 'Location'], ['Paris', 'Location'], ['Gustave Eiffel', 'Person'], ['France', 'Location']]}

Analyze the text and targets carefully, identify relevant information.

Extract the information in the following format: `[["Entity", "Type"], ...]`. If no matching entities are found, return an **empty list**. Please provide only the extracted information without any explanations.

Schema: ["company", "product", "service", "industry", "brand", "country", "location", "organization", "person", "founder", "position", "event", "action", "founding", "accusition", "merger", "partnership", "expansion", "restructuring", "divestment", "sale", "bankruptcy", "financial_metric", "business_concept", "revenue", "profit", "loss", "investment", "funding", "market_share", "competition", "market_trend", "regulation", "innovation", "sustainability", "corporate_social_responsibility", "award", "date/time", "year", "period"]
Text: article: University_of_North_Carolina_at_Chapel_Hill, Honor code: The university has a longstandinghonor codeknown as the "Instrument of Student Judicial Governance", supplemented by a mostly student-run honor system to resolve issues with students accused of academic and conduct offenses against the university community. In 1974, the Judicial Reform Committee created theInstrument of Student Judicial Governance, which outlined the current honor code and its means for enforcement.The creation of the instrument and the judicial reform committee was preceded by a list of "Demands by the Black Student Movement" (BSM) which stated that "[e]ither Black students have full jurisdiction over all offenses committed by Black students or duly elected Black Students from BSM who would represent our interests be on the present Judiciary Courts."Until 2024, most academic and conduct violations were handled by a single, student-run honor system. Prior to the student-run honor system, theDialectic and Philanthropic Societies, along with other campus organizations such as the men's council, women's council, and student council supported student concerns.In 2024, the university transitioned from the student-run honor system to a staff-run "hearing board".

[["University_of_North_Carolina_at_Chapel_Hill", "Company"], ["Instrument_of_Student_Judicial_Governance", "string"], ["Judicial_Reform_Committee", "Organization"], ["2024", "date"], ["Dialectic_and_Philanthropic_Societies", "Organization"], ["Black_Student_Movement", "Organization"], ["\"Demands by the Black Student Movement\"", "string"], ["Honor_code", "string"], ["Student_council", "Organization"], ["Men's_council", "Organization"], ["Women's_council", "Organization"]]


Honor code

Prompt:
Information Extraction is the process of automatically identifying and extracting structured information from unstructured text data. The goal is to transform raw text into meaningful data that can be easily analyzed and used in various applications. Named Entity Recognition (NER) and Relation Extraction are two common tasks in Information Extraction.

Named Entity Recognition involves identifying and classifying named entities such as people, organizations, locations, and other domain-specific concepts. Relation Extraction involves identifying and extracting relationships between entities.

The task at hand is RE: Relation Extraction.

Here is an example of task execution:

{'Schema': [{'designed': {'domain': 'Person', 'range': 'Structure'}}, {'located_in': {'domain': 'Structure', 'range': 'Location'}}, {'part_of': {'domain': 'City', 'range': 'Country'}}, {'friends_with': {'domain': 'Person', 'range': 'Person'}}, {'lives_at': {'domain': 'Person', 'range': 'Location'}}, {'visits': {'domain': 'Person', 'range': 'Location'}}, {'accompanied_by': {'domain': 'Person', 'range': 'Person'}}, {'shares': {'domain': 'Person', 'range': 'Product'}}], 'Text': 'Gustave Eiffel designed the Eiffel Tower, which is located in Paris, France.', 'Relations': [['Gustave Eiffel', 'designed', 'Eiffel Tower'], ['Eiffel Tower', 'located_in', 'Paris'], ['Paris', 'part_of', 'France']]}

Analyze the text and targets carefully, identify relevant information.

Extract the information in the following format: `[["Subject", "Relation", "Object"], ...]`. If no matching entities are found, return an **empty list**. Please provide only the extracted information without any explanations.

Schema: [{"part_of": {"domain": "Organization", "range": "Organization"}}, {"parent_company_of": {"domain": "Organization", "range": "Organization"}}, {"subsidiary_of": {"domain": "Organization", "range": "Organization"}}, {"acquired": {"domain": "Organization", "range": "Organization"}}, {"divested": {"domain": "Organization", "range": "Organization"}}, {"owns_brand": {"domain": "Organization", "range": "Product/Brand"}}, {"holds_stake_in": {"domain": "Organization", "range": "Organization"}}, {"spun_off": {"domain": "Organization", "range": "Organization"}}, {"formed_from": {"domain": "Organization", "range": "Organization"}}, {"founded_by": {"domain": "Organization", "range": "Person"}}, {"has_CEO": {"domain": "Organization", "range": "Person"}}, {"manufactures": {"domain": "Organization", "range": "ProductType"}}, {"develops": {"domain": "Organization", "range": "ProductType"}}, {"produces": {"domain": "Organization", "range": "ProductType"}}, {"sells": {"domain": "Organization", "range": "ProductType"}}, {"has_product_line": {"domain": "Organization", "range": "Product/Brand"}}, {"is_a_type_of": {"domain": "Product/Brand", "range": "ProductType"}}, {"is_brand_of": {"domain": "Product/Brand", "range": "Organization"}}, {"features_technology": {"domain": "Product/Brand", "range": "Technology"}}, {"uses_material": {"domain": "Product/Brand", "range": "Material"}}, {"launched_product": {"domain": "Organization", "range": "Product/Brand"}}, {"had_revenue_of": {"domain": "Organization", "range": "Amount"}}, {"had_profit_of": {"domain": "Organization", "range": "Amount"}}, {"in_year": {"domain": "FinancialMetric", "range": "Year"}}, {"market_value_of": {"domain": "Organization", "range": "Amount"}}, {"is_publicly_traded": {"domain": "Organization", "range": "Boolean"}}, {"listed_on_exchange": {"domain": "Organization", "range": "StockExchange"}}, {"experienced_growth": {"domain": "Organization", "range": "FinancialMetric"}}, {"occurred_in_year": {"domain": "Event/Action", "range": "Year"}}, {"occurred_on_date": {"domain": "Event/Action", "range": "SpecificDate"}}, {"resulted_in": {"domain": "Event/Action", "range": "Outcome"}}, {"preceded": {"domain": "Event/Action", "range": "Event/Action"}}, {"followed_by": {"domain": "Event/Action", "range": "Event/Action"}}, {"marked_milestone": {"domain": "Event/Action", "range": "Organization"}}, {"influenced_by": {"domain": "Event/Action", "range": "Event/Action"}}, {"led_to": {"domain": "Event/Action", "range": "Event/Action"}}, {"was_a_response_to": {"domain": "Event/Action", "range": "Event/Action"}}, {"has_trademark": {"domain": "Organization", "range": "Trademark"}}, {"uses_logo": {"domain": "Organization", "range": "Logo"}}, {"acquired_trademark_from": {"domain": "Organization", "range": "Organization"}}, {"is_known_for": {"domain": "Organization", "range": "Characteristic"}}, {"launched_campaign": {"domain": "Organization", "range": "BusinessConcept"}}]
Text: article: University_of_North_Carolina_at_Chapel_Hill, Honor code: The university has a longstandinghonor codeknown as the "Instrument of Student Judicial Governance", supplemented by a mostly student-run honor system to resolve issues with students accused of academic and conduct offenses against the university community. In 1974, the Judicial Reform Committee created theInstrument of Student Judicial Governance, which outlined the current honor code and its means for enforcement.The creation of the instrument and the judicial reform committee was preceded by a list of "Demands by the Black Student Movement" (BSM) which stated that "[e]ither Black students have full jurisdiction over all offenses committed by Black students or duly elected Black Students from BSM who would represent our interests be on the present Judiciary Courts."Until 2024, most academic and conduct violations were handled by a single, student-run honor system. Prior to the student-run honor system, theDialectic and Philanthropic Societies, along with other campus organizations such as the men's council, women's council, and student council supported student concerns.In 2024, the university transitioned from the student-run honor system to a staff-run "hearing board".

[["University_of_North_Carolina_at_Chapel_Hill", "has_honor_code", "\"Instrument of Student Judicial Governance\""], ["University_of_North_Carolina_at_Chapel_Hill", "has_honor_code", "\"University of North Carolina at Chapel Hill Honor Code\""], ["University_of_North_Carolina_at_Chapel_Hill", "has_honor_code", "\"University of North Carolina at Chapel Hill Academic and Conduct Honor System\""], ["University_of_North_Carolina_at_Chapel_Hill", "has_honor_code", "\"Demands by the Black Student Movement\""], ["University_of_North_Carolina_at_Chapel_Hill", "has_honor_code", "\"Judicial Reform Committee\""], ["University_of_North_Carolina_at_Chapel_Hill", "has_honor_code", "\"Honor system\""], ["University_of_North_Carolina_at_Chapel_Hill", "has_honor_code", "\"Dialectic and Philanthropic Societies, along with other campus organizations such as the men's council, women's council, and student council\""], ["University_of_North_Carolina_at_Chapel_Hill", "has_honor_code", "\"Hearing Board\""], ["University_of_North_Carolina_at_Chapel_Hill", "has_honor_code", "\"2024\""]]


Libraries

company product service industry brand country location organization person founder position event action founding accusition merger partnership expansion restructuring divestment sale bankruptcy financial_metric business_concept revenue profit loss investment funding market_share competition market_trend regulation innovation sustainability corporate_social_responsibility award date/time year period

Prompt:
Information Extraction is the process of automatically identifying and extracting structured information from unstructured text data. The goal is to transform raw text into meaningful data that can be easily analyzed and used in various applications. Named Entity Recognition (NER) and Relation Extraction are two common tasks in Information Extraction.

Named Entity Recognition involves identifying and classifying named entities such as people, organizations, locations, and other domain-specific concepts. Relation Extraction involves identifying and extracting relationships between entities.

The task at hand is NER: Named Entity Recognition.

Here is an example of task execution:

{'Schema': ['Person', 'Organization', 'Location', 'Date', 'Product'], 'Text': 'The Eiffel Tower in Paris, designed by Gustave Eiffel, is one of the most famous landmarks in France.', 'Entities': [['Eiffel Tower', 'Location'], ['Paris', 'Location'], ['Gustave Eiffel', 'Person'], ['France', 'Location']]}

Analyze the text and targets carefully, identify relevant information.

Extract the information in the following format: `[["Entity", "Type"], ...]`. If no matching entities are found, return an **empty list**. Please provide only the extracted information without any explanations.

Schema: ["company", "product", "service", "industry", "brand", "country", "location", "organization", "person", "founder", "position", "event", "action", "founding", "accusition", "merger", "partnership", "expansion", "restructuring", "divestment", "sale", "bankruptcy", "financial_metric", "business_concept", "revenue", "profit", "loss", "investment", "funding", "market_share", "competition", "market_trend", "regulation", "innovation", "sustainability", "corporate_social_responsibility", "award", "date/time", "year", "period"]
Text: article: University_of_North_Carolina_at_Chapel_Hill, Libraries: UNC-Chapel Hill's library system includes a number of individual libraries housed throughout the campus and holds more than 10 million combined print and electronic volumes.As of 2025, there were 12 library locations in operation.UNC-Chapel Hill'sNorth Carolina Collection(NCC) is the largest and most comprehensive collection of holdings about any single state nationwide.The unparalleled assemblage of literary, visual, and artifactual materials documents four centuries of North Carolina history and culture.The North Carolina Collection is housed inWilson Library, named afterLouis Round Wilson, along with theSouthern Historical Collection, the Rare Books Collection, and theSouthern Folklife Collection.The university is home toibiblio, one of the world's largest collections of freely available information including software, music, literature, art, history, science, politics, and cultural studies. The Davis Library, situated near the Pit, is the main library and the largest academic facility and state-owned building in North Carolina.It was named after North Carolina philanthropistWalter Royal Davisand opened on February 6, 1984. The first book checked out of Davis Library wasGeorge Orwell's1984.The R.B. House Undergraduate Library is located between the Pit area and Wilson Library. It is named after Robert B. House, the Chancellor of UNC from 1945 to 1957, and opened in 1968.In 2001, the R.B. House Undergraduate Library underwent a $9.9 million renovation that modernized the furnishings, equipment, and infrastructure of the building.Prior to the construction of Davis, Wilson Library was the university's main library, but now Wilson hosts special events and houses special collections, rare books, and temporary exhibits. The library overseesDocumenting the American South, a free public access website of "digitized primary materials that offer Southern perspectives on American history and culture." The project began in 1996.In 2009 the library launched the North Carolina Digital Heritage Center, a statewide digital library, in partnership with other organizations.

[["UNC_Chapel_Hill", "Company"], ["Davis_Library", "Building"], ["\"Walter Royal Davis, 1919-2000\"", "Person"], ["\"1984\"", "Product"], ["Davis_Library", "Company"], ["\"2009\"", "date"], ["Documenting_the_American_South", "Project"], ["R.B._House_Undergraduate_Library", "Building"], ["\"9.9 million\"", "number"], ["Wilson_Library", "Building"], ["North_Carolina_Collection", "Product"], ["Davis_Library", "Product"], ["\"1968\"", "date"], ["North_Carolina_Digital_Heritage_Center", "Project"], ["Pit_(building)", "Place"], ["George_Orwell", "Person"]]


Libraries

Prompt:
Information Extraction is the process of automatically identifying and extracting structured information from unstructured text data. The goal is to transform raw text into meaningful data that can be easily analyzed and used in various applications. Named Entity Recognition (NER) and Relation Extraction are two common tasks in Information Extraction.

Named Entity Recognition involves identifying and classifying named entities such as people, organizations, locations, and other domain-specific concepts. Relation Extraction involves identifying and extracting relationships between entities.

The task at hand is RE: Relation Extraction.

Here is an example of task execution:

{'Schema': [{'designed': {'domain': 'Person', 'range': 'Structure'}}, {'located_in': {'domain': 'Structure', 'range': 'Location'}}, {'part_of': {'domain': 'City', 'range': 'Country'}}, {'friends_with': {'domain': 'Person', 'range': 'Person'}}, {'lives_at': {'domain': 'Person', 'range': 'Location'}}, {'visits': {'domain': 'Person', 'range': 'Location'}}, {'accompanied_by': {'domain': 'Person', 'range': 'Person'}}, {'shares': {'domain': 'Person', 'range': 'Product'}}], 'Text': 'Gustave Eiffel designed the Eiffel Tower, which is located in Paris, France.', 'Relations': [['Gustave Eiffel', 'designed', 'Eiffel Tower'], ['Eiffel Tower', 'located_in', 'Paris'], ['Paris', 'part_of', 'France']]}

Analyze the text and targets carefully, identify relevant information.

Extract the information in the following format: `[["Subject", "Relation", "Object"], ...]`. If no matching entities are found, return an **empty list**. Please provide only the extracted information without any explanations.

Schema: [{"part_of": {"domain": "Organization", "range": "Organization"}}, {"parent_company_of": {"domain": "Organization", "range": "Organization"}}, {"subsidiary_of": {"domain": "Organization", "range": "Organization"}}, {"acquired": {"domain": "Organization", "range": "Organization"}}, {"divested": {"domain": "Organization", "range": "Organization"}}, {"owns_brand": {"domain": "Organization", "range": "Product/Brand"}}, {"holds_stake_in": {"domain": "Organization", "range": "Organization"}}, {"spun_off": {"domain": "Organization", "range": "Organization"}}, {"formed_from": {"domain": "Organization", "range": "Organization"}}, {"founded_by": {"domain": "Organization", "range": "Person"}}, {"has_CEO": {"domain": "Organization", "range": "Person"}}, {"manufactures": {"domain": "Organization", "range": "ProductType"}}, {"develops": {"domain": "Organization", "range": "ProductType"}}, {"produces": {"domain": "Organization", "range": "ProductType"}}, {"sells": {"domain": "Organization", "range": "ProductType"}}, {"has_product_line": {"domain": "Organization", "range": "Product/Brand"}}, {"is_a_type_of": {"domain": "Product/Brand", "range": "ProductType"}}, {"is_brand_of": {"domain": "Product/Brand", "range": "Organization"}}, {"features_technology": {"domain": "Product/Brand", "range": "Technology"}}, {"uses_material": {"domain": "Product/Brand", "range": "Material"}}, {"launched_product": {"domain": "Organization", "range": "Product/Brand"}}, {"had_revenue_of": {"domain": "Organization", "range": "Amount"}}, {"had_profit_of": {"domain": "Organization", "range": "Amount"}}, {"in_year": {"domain": "FinancialMetric", "range": "Year"}}, {"market_value_of": {"domain": "Organization", "range": "Amount"}}, {"is_publicly_traded": {"domain": "Organization", "range": "Boolean"}}, {"listed_on_exchange": {"domain": "Organization", "range": "StockExchange"}}, {"experienced_growth": {"domain": "Organization", "range": "FinancialMetric"}}, {"occurred_in_year": {"domain": "Event/Action", "range": "Year"}}, {"occurred_on_date": {"domain": "Event/Action", "range": "SpecificDate"}}, {"resulted_in": {"domain": "Event/Action", "range": "Outcome"}}, {"preceded": {"domain": "Event/Action", "range": "Event/Action"}}, {"followed_by": {"domain": "Event/Action", "range": "Event/Action"}}, {"marked_milestone": {"domain": "Event/Action", "range": "Organization"}}, {"influenced_by": {"domain": "Event/Action", "range": "Event/Action"}}, {"led_to": {"domain": "Event/Action", "range": "Event/Action"}}, {"was_a_response_to": {"domain": "Event/Action", "range": "Event/Action"}}, {"has_trademark": {"domain": "Organization", "range": "Trademark"}}, {"uses_logo": {"domain": "Organization", "range": "Logo"}}, {"acquired_trademark_from": {"domain": "Organization", "range": "Organization"}}, {"is_known_for": {"domain": "Organization", "range": "Characteristic"}}, {"launched_campaign": {"domain": "Organization", "range": "BusinessConcept"}}]
Text: article: University_of_North_Carolina_at_Chapel_Hill, Libraries: UNC-Chapel Hill's library system includes a number of individual libraries housed throughout the campus and holds more than 10 million combined print and electronic volumes.As of 2025, there were 12 library locations in operation.UNC-Chapel Hill'sNorth Carolina Collection(NCC) is the largest and most comprehensive collection of holdings about any single state nationwide.The unparalleled assemblage of literary, visual, and artifactual materials documents four centuries of North Carolina history and culture.The North Carolina Collection is housed inWilson Library, named afterLouis Round Wilson, along with theSouthern Historical Collection, the Rare Books Collection, and theSouthern Folklife Collection.The university is home toibiblio, one of the world's largest collections of freely available information including software, music, literature, art, history, science, politics, and cultural studies. The Davis Library, situated near the Pit, is the main library and the largest academic facility and state-owned building in North Carolina.It was named after North Carolina philanthropistWalter Royal Davisand opened on February 6, 1984. The first book checked out of Davis Library wasGeorge Orwell's1984.The R.B. House Undergraduate Library is located between the Pit area and Wilson Library. It is named after Robert B. House, the Chancellor of UNC from 1945 to 1957, and opened in 1968.In 2001, the R.B. House Undergraduate Library underwent a $9.9 million renovation that modernized the furnishings, equipment, and infrastructure of the building.Prior to the construction of Davis, Wilson Library was the university's main library, but now Wilson hosts special events and houses special collections, rare books, and temporary exhibits. The library overseesDocumenting the American South, a free public access website of "digitized primary materials that offer Southern perspectives on American history and culture." The project began in 1996.In 2009 the library launched the North Carolina Digital Heritage Center, a statewide digital library, in partnership with other organizations.

[["University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "Davis_Library"], ["University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "Wilson_Library"], ["University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "R._B._House_Undergraduate_Library"], ["University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "North_Carolina_Digital_Heritage_Center"], ["University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "Documenting_the_American_South"], ["University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "North_Carolina_Collection"], ["Davis_Library", "occurred_on_date", "\"1984-02-06\""], ["Davis_Library", "has_product_line", "George_Orwell's_1984"], ["Davis_Library", "cost", "9.9 (million $)"], ["University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "Ibiblio"], ["Wilson_Library", "has_product_line", "Southern_Historical_Collection"], ["Wilson_Library", "has_product_line", "Rare_Books_Collection"], ["Wilson_Library", "has_product_line", "Southern_Folklife_Collection"], ["University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "Library"], ["University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "McGill_Building"], ["University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "Kenan_Building"], ["University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "North_Carolina_State_Building"], ["University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "Poole_Building"], ["University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "Rubenstein_Building"], ["University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "Stephen_A._Mitchell_Building"], ["University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "Walter_R._Davis_Building"], ["University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "William_B._Campus_Building"], ["University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "Alumni_Hall"], ["University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "Bowen_Building"], ["University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "Carolina_Duplex"], ["University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "Charles_D._McIver_Building"], ["University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "David_C._Coates_Building"], ["University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "Duke_Building"], ["University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "Garrett_Building"], ["University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "George_H._W._Bush_Building"], ["University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "Kenan–Flagler_Business_School"], ["University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "Law_School_Building"], ["University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "Little_Building"], ["University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "McGhee_Building"], ["University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "North_Carolina_State_Building"], ["University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "North_Carolina_Building"], ["University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "Pearson_Building"], ["University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "Philosophy_Building"], ["University_of_North_Carolina_at_Chapel_Hill", "has_product_line", "Polk_Building"], {"domain": "University_of_North_Carolina_at_Chapel_Hill", "range": "City"}, {"domain": "University_of_North_Carolina_at_Chapel_Hill", "range": "Person"}]


Rankings and reputation

company product service industry brand country location organization person founder position event action founding accusition merger partnership expansion restructuring divestment sale bankruptcy financial_metric business_concept revenue profit loss investment funding market_share competition market_trend regulation innovation sustainability corporate_social_responsibility award date/time year period

Prompt:
Information Extraction is the process of automatically identifying and extracting structured information from unstructured text data. The goal is to transform raw text into meaningful data that can be easily analyzed and used in various applications. Named Entity Recognition (NER) and Relation Extraction are two common tasks in Information Extraction.

Named Entity Recognition involves identifying and classifying named entities such as people, organizations, locations, and other domain-specific concepts. Relation Extraction involves identifying and extracting relationships between entities.

The task at hand is NER: Named Entity Recognition.

Here is an example of task execution:

{'Schema': ['Person', 'Organization', 'Location', 'Date', 'Product'], 'Text': 'The Eiffel Tower in Paris, designed by Gustave Eiffel, is one of the most famous landmarks in France.', 'Entities': [['Eiffel Tower', 'Location'], ['Paris', 'Location'], ['Gustave Eiffel', 'Person'], ['France', 'Location']]}

Analyze the text and targets carefully, identify relevant information.

Extract the information in the following format: `[["Entity", "Type"], ...]`. If no matching entities are found, return an **empty list**. Please provide only the extracted information without any explanations.

Schema: ["company", "product", "service", "industry", "brand", "country", "location", "organization", "person", "founder", "position", "event", "action", "founding", "accusition", "merger", "partnership", "expansion", "restructuring", "divestment", "sale", "bankruptcy", "financial_metric", "business_concept", "revenue", "profit", "loss", "investment", "funding", "market_share", "competition", "market_trend", "regulation", "innovation", "sustainability", "corporate_social_responsibility", "award", "date/time", "year", "period"]
Text: article: University_of_North_Carolina_at_Chapel_Hill, Rankings and reputation: For 2023,U.S. News & World Reportranked UNC-Chapel Hill 4th among the public universities and 22nd among national universities in the United States.The Wall Street Journal ranked UNC-Chapel Hill 3rd best public university behindUniversity of MichiganandUCLA. The university was named aPublic Ivyby Richard Moll in his 1985 bookThe Public Ivies: A Guide to America's Best Public Undergraduate Colleges and Universities, and in later guides by Howard and Matthew Greene. The university is a large recipient of National Institute of Health grants and funds. For fiscal year 2020, the university received $509.9 million in NIH funds for research. This amount makes Chapel Hill the 10th overall recipient of research funds in the nation by the NIH.

[["University_of_North_Carolina_at_Chapel_Hill", "company"], ["509900000", "number"], ["\"University of North Carolina at Chapel Hill\"", "string"], ["2020", "year"], ["U.S._News_&_World_Report", "organization"], ["4", "number"], ["U.S._News_&_World_Report", "ranking"], ["2023", "year"], ["University_of_North_Carolina_at_Chapel_Hill", "University"], ["Wall_Street_Journal", "ranking"], ["3", "number"], ["Public_Ivies", "award"], ["Richard_Moll", "person"], ["University_of_Michigan", "University"], ["UCLA", "University"], ["509900000", "number"], ["University_of_North_Carolina_at_Chapel_Hill", "company"], ["National_Institute_of_Health", "funder"], ["2020", "year"], ["10", "number"]]


Rankings and reputation

Prompt:
Information Extraction is the process of automatically identifying and extracting structured information from unstructured text data. The goal is to transform raw text into meaningful data that can be easily analyzed and used in various applications. Named Entity Recognition (NER) and Relation Extraction are two common tasks in Information Extraction.

Named Entity Recognition involves identifying and classifying named entities such as people, organizations, locations, and other domain-specific concepts. Relation Extraction involves identifying and extracting relationships between entities.

The task at hand is RE: Relation Extraction.

Here is an example of task execution:

{'Schema': [{'designed': {'domain': 'Person', 'range': 'Structure'}}, {'located_in': {'domain': 'Structure', 'range': 'Location'}}, {'part_of': {'domain': 'City', 'range': 'Country'}}, {'friends_with': {'domain': 'Person', 'range': 'Person'}}, {'lives_at': {'domain': 'Person', 'range': 'Location'}}, {'visits': {'domain': 'Person', 'range': 'Location'}}, {'accompanied_by': {'domain': 'Person', 'range': 'Person'}}, {'shares': {'domain': 'Person', 'range': 'Product'}}], 'Text': 'Gustave Eiffel designed the Eiffel Tower, which is located in Paris, France.', 'Relations': [['Gustave Eiffel', 'designed', 'Eiffel Tower'], ['Eiffel Tower', 'located_in', 'Paris'], ['Paris', 'part_of', 'France']]}

Analyze the text and targets carefully, identify relevant information.

Extract the information in the following format: `[["Subject", "Relation", "Object"], ...]`. If no matching entities are found, return an **empty list**. Please provide only the extracted information without any explanations.

Schema: [{"part_of": {"domain": "Organization", "range": "Organization"}}, {"parent_company_of": {"domain": "Organization", "range": "Organization"}}, {"subsidiary_of": {"domain": "Organization", "range": "Organization"}}, {"acquired": {"domain": "Organization", "range": "Organization"}}, {"divested": {"domain": "Organization", "range": "Organization"}}, {"owns_brand": {"domain": "Organization", "range": "Product/Brand"}}, {"holds_stake_in": {"domain": "Organization", "range": "Organization"}}, {"spun_off": {"domain": "Organization", "range": "Organization"}}, {"formed_from": {"domain": "Organization", "range": "Organization"}}, {"founded_by": {"domain": "Organization", "range": "Person"}}, {"has_CEO": {"domain": "Organization", "range": "Person"}}, {"manufactures": {"domain": "Organization", "range": "ProductType"}}, {"develops": {"domain": "Organization", "range": "ProductType"}}, {"produces": {"domain": "Organization", "range": "ProductType"}}, {"sells": {"domain": "Organization", "range": "ProductType"}}, {"has_product_line": {"domain": "Organization", "range": "Product/Brand"}}, {"is_a_type_of": {"domain": "Product/Brand", "range": "ProductType"}}, {"is_brand_of": {"domain": "Product/Brand", "range": "Organization"}}, {"features_technology": {"domain": "Product/Brand", "range": "Technology"}}, {"uses_material": {"domain": "Product/Brand", "range": "Material"}}, {"launched_product": {"domain": "Organization", "range": "Product/Brand"}}, {"had_revenue_of": {"domain": "Organization", "range": "Amount"}}, {"had_profit_of": {"domain": "Organization", "range": "Amount"}}, {"in_year": {"domain": "FinancialMetric", "range": "Year"}}, {"market_value_of": {"domain": "Organization", "range": "Amount"}}, {"is_publicly_traded": {"domain": "Organization", "range": "Boolean"}}, {"listed_on_exchange": {"domain": "Organization", "range": "StockExchange"}}, {"experienced_growth": {"domain": "Organization", "range": "FinancialMetric"}}, {"occurred_in_year": {"domain": "Event/Action", "range": "Year"}}, {"occurred_on_date": {"domain": "Event/Action", "range": "SpecificDate"}}, {"resulted_in": {"domain": "Event/Action", "range": "Outcome"}}, {"preceded": {"domain": "Event/Action", "range": "Event/Action"}}, {"followed_by": {"domain": "Event/Action", "range": "Event/Action"}}, {"marked_milestone": {"domain": "Event/Action", "range": "Organization"}}, {"influenced_by": {"domain": "Event/Action", "range": "Event/Action"}}, {"led_to": {"domain": "Event/Action", "range": "Event/Action"}}, {"was_a_response_to": {"domain": "Event/Action", "range": "Event/Action"}}, {"has_trademark": {"domain": "Organization", "range": "Trademark"}}, {"uses_logo": {"domain": "Organization", "range": "Logo"}}, {"acquired_trademark_from": {"domain": "Organization", "range": "Organization"}}, {"is_known_for": {"domain": "Organization", "range": "Characteristic"}}, {"launched_campaign": {"domain": "Organization", "range": "BusinessConcept"}}]
Text: article: University_of_North_Carolina_at_Chapel_Hill, Rankings and reputation: For 2023,U.S. News & World Reportranked UNC-Chapel Hill 4th among the public universities and 22nd among national universities in the United States.The Wall Street Journal ranked UNC-Chapel Hill 3rd best public university behindUniversity of MichiganandUCLA. The university was named aPublic Ivyby Richard Moll in his 1985 bookThe Public Ivies: A Guide to America's Best Public Undergraduate Colleges and Universities, and in later guides by Howard and Matthew Greene. The university is a large recipient of National Institute of Health grants and funds. For fiscal year 2020, the university received $509.9 million in NIH funds for research. This amount makes Chapel Hill the 10th overall recipient of research funds in the nation by the NIH.

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Scholarships

company product service industry brand country location organization person founder position event action founding accusition merger partnership expansion restructuring divestment sale bankruptcy financial_metric business_concept revenue profit loss investment funding market_share competition market_trend regulation innovation sustainability corporate_social_responsibility award date/time year period

Prompt:
Information Extraction is the process of automatically identifying and extracting structured information from unstructured text data. The goal is to transform raw text into meaningful data that can be easily analyzed and used in various applications. Named Entity Recognition (NER) and Relation Extraction are two common tasks in Information Extraction.

Named Entity Recognition involves identifying and classifying named entities such as people, organizations, locations, and other domain-specific concepts. Relation Extraction involves identifying and extracting relationships between entities.

The task at hand is NER: Named Entity Recognition.

Here is an example of task execution:

{'Schema': ['Person', 'Organization', 'Location', 'Date', 'Product'], 'Text': 'The Eiffel Tower in Paris, designed by Gustave Eiffel, is one of the most famous landmarks in France.', 'Entities': [['Eiffel Tower', 'Location'], ['Paris', 'Location'], ['Gustave Eiffel', 'Person'], ['France', 'Location']]}

Analyze the text and targets carefully, identify relevant information.

Extract the information in the following format: `[["Entity", "Type"], ...]`. If no matching entities are found, return an **empty list**. Please provide only the extracted information without any explanations.

Schema: ["company", "product", "service", "industry", "brand", "country", "location", "organization", "person", "founder", "position", "event", "action", "founding", "accusition", "merger", "partnership", "expansion", "restructuring", "divestment", "sale", "bankruptcy", "financial_metric", "business_concept", "revenue", "profit", "loss", "investment", "funding", "market_share", "competition", "market_trend", "regulation", "innovation", "sustainability", "corporate_social_responsibility", "award", "date/time", "year", "period"]
Text: article: University_of_North_Carolina_at_Chapel_Hill, Scholarships: For decades, UNC-Chapel Hill has offered an undergraduate merit scholarship known as theMorehead-Cain Scholarship. Recipients receive full tuition, room and board, books, and funds for summer study for four years. Since the inception of the Morehead, 29 alumni of the program have been namedRhodes Scholars.Since 2001, North Carolina has also co-hosted theRobertson Scholars Leadership Program, a merit scholarship and leadership development program granting recipients full student privileges at both UNC-Chapel Hill and neighboringDuke University.Additionally, the university provides scholarships based on merit and leadership qualities, including the Carolina, Colonel Robinson, Johnston and Pogue Scholars programs. In 2003, ChancellorJames Moeserannounced the Carolina Covenant, wherein UNC offers a debt free education to low-income students who are accepted to the university. The program was the first of its kind at a public university and the second overall in the nation (followingPrinceton University). About 80 other universities have since followed suit.

[["University_of_North_Carolina_at_Chapel_Hill", "Company"], ["Morehead–Cain_Scholarship", "Scholarship"], ["Rhodes_Scholarship", "Scholarship"], ["Robertson_Scholars_Program", "Scholarship"], ["Carolina_Covenant", "Scholarship"], ["2003", "date"], ["Princeton_University", "University"], ["\"Debt-free education for low-income students\"", "Scholarship"], ["80", "number"]]


Scholarships

Prompt:
Information Extraction is the process of automatically identifying and extracting structured information from unstructured text data. The goal is to transform raw text into meaningful data that can be easily analyzed and used in various applications. Named Entity Recognition (NER) and Relation Extraction are two common tasks in Information Extraction.

Named Entity Recognition involves identifying and classifying named entities such as people, organizations, locations, and other domain-specific concepts. Relation Extraction involves identifying and extracting relationships between entities.

The task at hand is RE: Relation Extraction.

Here is an example of task execution:

{'Schema': [{'designed': {'domain': 'Person', 'range': 'Structure'}}, {'located_in': {'domain': 'Structure', 'range': 'Location'}}, {'part_of': {'domain': 'City', 'range': 'Country'}}, {'friends_with': {'domain': 'Person', 'range': 'Person'}}, {'lives_at': {'domain': 'Person', 'range': 'Location'}}, {'visits': {'domain': 'Person', 'range': 'Location'}}, {'accompanied_by': {'domain': 'Person', 'range': 'Person'}}, {'shares': {'domain': 'Person', 'range': 'Product'}}], 'Text': 'Gustave Eiffel designed the Eiffel Tower, which is located in Paris, France.', 'Relations': [['Gustave Eiffel', 'designed', 'Eiffel Tower'], ['Eiffel Tower', 'located_in', 'Paris'], ['Paris', 'part_of', 'France']]}

Analyze the text and targets carefully, identify relevant information.

Extract the information in the following format: `[["Subject", "Relation", "Object"], ...]`. If no matching entities are found, return an **empty list**. Please provide only the extracted information without any explanations.

Schema: [{"part_of": {"domain": "Organization", "range": "Organization"}}, {"parent_company_of": {"domain": "Organization", "range": "Organization"}}, {"subsidiary_of": {"domain": "Organization", "range": "Organization"}}, {"acquired": {"domain": "Organization", "range": "Organization"}}, {"divested": {"domain": "Organization", "range": "Organization"}}, {"owns_brand": {"domain": "Organization", "range": "Product/Brand"}}, {"holds_stake_in": {"domain": "Organization", "range": "Organization"}}, {"spun_off": {"domain": "Organization", "range": "Organization"}}, {"formed_from": {"domain": "Organization", "range": "Organization"}}, {"founded_by": {"domain": "Organization", "range": "Person"}}, {"has_CEO": {"domain": "Organization", "range": "Person"}}, {"manufactures": {"domain": "Organization", "range": "ProductType"}}, {"develops": {"domain": "Organization", "range": "ProductType"}}, {"produces": {"domain": "Organization", "range": "ProductType"}}, {"sells": {"domain": "Organization", "range": "ProductType"}}, {"has_product_line": {"domain": "Organization", "range": "Product/Brand"}}, {"is_a_type_of": {"domain": "Product/Brand", "range": "ProductType"}}, {"is_brand_of": {"domain": "Product/Brand", "range": "Organization"}}, {"features_technology": {"domain": "Product/Brand", "range": "Technology"}}, {"uses_material": {"domain": "Product/Brand", "range": "Material"}}, {"launched_product": {"domain": "Organization", "range": "Product/Brand"}}, {"had_revenue_of": {"domain": "Organization", "range": "Amount"}}, {"had_profit_of": {"domain": "Organization", "range": "Amount"}}, {"in_year": {"domain": "FinancialMetric", "range": "Year"}}, {"market_value_of": {"domain": "Organization", "range": "Amount"}}, {"is_publicly_traded": {"domain": "Organization", "range": "Boolean"}}, {"listed_on_exchange": {"domain": "Organization", "range": "StockExchange"}}, {"experienced_growth": {"domain": "Organization", "range": "FinancialMetric"}}, {"occurred_in_year": {"domain": "Event/Action", "range": "Year"}}, {"occurred_on_date": {"domain": "Event/Action", "range": "SpecificDate"}}, {"resulted_in": {"domain": "Event/Action", "range": "Outcome"}}, {"preceded": {"domain": "Event/Action", "range": "Event/Action"}}, {"followed_by": {"domain": "Event/Action", "range": "Event/Action"}}, {"marked_milestone": {"domain": "Event/Action", "range": "Organization"}}, {"influenced_by": {"domain": "Event/Action", "range": "Event/Action"}}, {"led_to": {"domain": "Event/Action", "range": "Event/Action"}}, {"was_a_response_to": {"domain": "Event/Action", "range": "Event/Action"}}, {"has_trademark": {"domain": "Organization", "range": "Trademark"}}, {"uses_logo": {"domain": "Organization", "range": "Logo"}}, {"acquired_trademark_from": {"domain": "Organization", "range": "Organization"}}, {"is_known_for": {"domain": "Organization", "range": "Characteristic"}}, {"launched_campaign": {"domain": "Organization", "range": "BusinessConcept"}}]
Text: article: University_of_North_Carolina_at_Chapel_Hill, Scholarships: For decades, UNC-Chapel Hill has offered an undergraduate merit scholarship known as theMorehead-Cain Scholarship. Recipients receive full tuition, room and board, books, and funds for summer study for four years. Since the inception of the Morehead, 29 alumni of the program have been namedRhodes Scholars.Since 2001, North Carolina has also co-hosted theRobertson Scholars Leadership Program, a merit scholarship and leadership development program granting recipients full student privileges at both UNC-Chapel Hill and neighboringDuke University.Additionally, the university provides scholarships based on merit and leadership qualities, including the Carolina, Colonel Robinson, Johnston and Pogue Scholars programs. In 2003, ChancellorJames Moeserannounced the Carolina Covenant, wherein UNC offers a debt free education to low-income students who are accepted to the university. The program was the first of its kind at a public university and the second overall in the nation (followingPrinceton University). About 80 other universities have since followed suit.

[["University_of_North_Carolina_at_Chapel_Hill", "has_motto", "\"Pro Humanitate\""], ["University_of_North_Carolina_at_Chapel_Hill", "has_scholarship", "Morehead–Cain_Scholarship"], ["University_of_North_Carolina_at_Chapel_Hill", "has_scholarship", "Robertson_Scholars_Program"], ["University_of_North_Carolina_at_Chapel_Hill", "has_scholarship", "Carolina_Covenant"], ["University_of_North_Carolina_at_Chapel_Hill", "has_scholarship", "Johnston_Scholarship"], ["University_of_North_Carolina_at_Chapel_Hill", "has_scholarship", "Pogue_Scholarship"], ["University_of_North_Carolina_at_Chapel_Hill", "has_scholarship", "Colonel_Robinson_Scholarship"], ["University_of_North_Carolina_at_Chapel_Hill", "has_chancellor", "James_Moeser"], ["University_of_North_Carolina_at_Chapel_Hill", "has_scholarship", "Carolina_Scholarship"], ["University_of_North_Carolina_at_Chapel_Hill", "has_scholarship", "Rhodes_Scholarship"], ["University_of_North_Carolina_at_Chapel_Hill", "has_scholarship", "Robertson_Scholars_Program"], ["University_of_North_Carolina_at_Chapel_Hill", "has_scholarship", "Morehead–Cain_Scholarship"], ["University_of_North_Carolina_at_Chapel_Hill", "has_scholarship", "North_Carolina_State_University"], ["University_of_North_Carolina_at_Chapel_Hill", "has_scholarship", "Duke_University"], ["University_of_North_Carolina_at_Chapel_Hill", "has_scholarship", "Princeton_University"], ["University_of_North_Carolina_at_Chapel_Hill", "has_scholarship", "Carolina_Covenant"], ["University_of_North_Carolina_at_Chapel_Hill", "has_scholarship", "Johnston_Scholarship"], ["University_of_North_Carolina_at_Chapel_Hill", "has_scholarship", "Pogue_Scholarship"], ["University_of_North_Carolina_at_Chapel_Hill", "has_scholarship", "Colonel_Robinson_Scholarship"]]