Mars Food UK Limited

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: Mars_Inc, Mars Food UK Limited: In 1932, Forrest Mars Sr. opened what was then Mars (Europe) headquarters, and remains Mars (UK) headquarters in Slough,Berkshireon the then-newSlough Trading Estate, after a disagreement with his father,Franklin Clarence Mars. In this factory, he produced the firstMars bar, based on the AmericanMilky Way.The company branch is currently known asMars Food UK Limitedin the United Kingdom. Mars brands manufactured for the United Kingdom market but not for the United States includeTunes. Many brands first created and sold in the United Kingdom were later introduced in the United States, includingStarburst(original UK brand name Opal Fruits) andSkittles. The brandsTwixandTopicwere UK based. Milky Wayin Europe and worldwide is known as the3 Musketeersin America. Similarly, theSnickersbar was previously marketed inIrelandand theUnited Kingdomas Marathon until 1990; in the UK, France, Germany and the Netherlands, also until 1990;Galaxyin the Middle East is known asDovein America and worldwide. Chocolate and peanutM&M'swere introduced in 1980s.

Mars,_Inc.

Mars_Food_UK_Limited

P625 - coordinate location: geocoordinates of the subject. For Earth, please note that only the WGS84 geodetic datum is currently supported

P276 - location: location of the object, structure or event; use P131 to indicate the containing administrative entity, P8138 for statistical entities, or P706 for geographic entities; use P7153 for locations associated with the object

P937 - work location: location where persons or organisations were actively participating in employment, business or other work

P3005 - valid in place: place where a statement is valid

P304 - page(s): page number of source referenced for statement. Note "column(s)" (P3903) and "folio(s)" (P7416) for other numbering systems

Q211907 - Slough: town in Berkshire, England, UK

Q21163036 - Slough: unitary authority area in Berkshire, England

Q7541461 - slough: a wetland, usually a swamp or shallow lake, often a backwater to a larger body of water

Q989007 - Slough: Parliamentary constituency in the United Kingdom, 1983 onwards

Mars,_Inc.

P1056 - product or material produced: material or product, including services, produced or provided by an organization, industry, facility, or process

P176 - manufacturer: (main or final) manufacturer or producer of this product

P2079 - fabrication method: method, process or technique used to grow, cook, weave, build, assemble, manufacture the item

P272 - production company: company that produced this film, audio or performing arts work

P1071 - location of creation: place where the item was conceived or made; where applicable, location of final assembly

Mars,_Inc.

Q739550 - M&M's: brand of chocolate candy pieces

Q6711826 - M&M's Adventure: 2008 video game

Q16737028 - M&M's Kart Racing: 2007 video game

Q3272256 - M&M's World: store that sells "M&M's"

Q252623 - Pennsylvania 400: NASCAR Cup Series stock car race held in Long Pond, Pennsylvania, USA

Mars,_Inc.

Q8921300 - skittles: old European lawn game

Q868612 - Skittles: brand of sugar-coated fruit flavored candy

Q29810085 - Skittles Dmel_CG9985: protein found in Drosophila melanogaster

Q29711548 - sktl: protein-coding gene in the species Drosophila melanogaster

Q106797987 - Skittles: painting by Jan Both

Mars,_Inc.

Q726611 - starburst galaxy: galaxy undergoing an exceptionally high rate of star formation

Q1186164 - spin-off company: type of organization which is the outcome of a corporate spin-off

Q7601502 - Starburst: British science fiction magazine and webzine

Mars,_Inc.

Q869733 - Twix: chocolate-coated cookie candy bar

Q2408534 - Twixt: 2011 film directed by Francis Ford Coppola

Q1362781 - TwixT: One of the two-player strategy board games in the 3M bookshelf game series

Mars,_Inc.

Q714179 - Snickers: brand name chocolate bar made by Mars, Incorporated

Q886003 - Bluemont: unincorporated village in Loudoun County, Virginia, United States

Q1748734 - Snickers Workwear: clothing brand

Q4405719 - Snickers salad: US dessert dish of Snickers bars, apples, and whipped cream

Mars,_Inc.

Mars,_Inc.

Q181761 - deep-fried Mars bar: deep fried Scottish confectionery

Q110778062 - March carrying the front part of a litter: drawing by Francesco Primaticcio

Mars,_Inc.

P3342 - significant person: person linked to the item in any possible way

Q2578399 - Forrest Mars: American businessman (1904–1999)

Mars,_Inc.

Q7541490 - Slough Trading Estate: business park in Slough, Berkshire, England, UK

Mars,_Inc.

P355 - child organization/unit: child organization/unit or subsidiary of a company or organization/unit; generally a fully owned separate corporation. Compare with "business division" (P199). Opposite of parent organization/unit (P749).

P749 - parent organization: parent organization of an organization, opposite of subsidiaries (P355)

Q30 - United States: country located primarily in North America

Q637413 - United States Census Bureau: U.S. agency responsible for the census and related statistics

Q11703 - United States Virgin Islands: unincorporated territory of the United States of America

Q4917 - United States dollar: official currency of the United States

Q214867 - National Gallery of Art: national art museum in Washington, D.C.

Mars,_Inc.

Mars,_Inc.

Mars,_Inc.

Q145 - United Kingdom: country in north-west Europe

Q174193 - United Kingdom of Great Britain and Ireland: historical sovereign state (1801–1922)

Q7979 - British English: forms of the English language used in Britain

Q161885 - Kingdom of Great Britain: constitutional monarchy in Western Europe (1707–1800)

Q11010 - Parliament of the United Kingdom: supreme legislative body of the United Kingdom

Mars,_Inc.

Q1443054 - Franklin Clarence Mars: American businessman (1883–1934)

Mars,_Inc.

Q67284726 - Berkshire: historic county of England, United Kingdom

Q23220 - Berkshire: ceremonial and non-metropolitan but non-administrative county of England

Q217583 - Berkshire Hathaway: American multinational conglomerate holding company

Q60578252 - Berkshire: Constituency of the Parliament of England (to 1707)

Mars,_Inc.

Mars,_Inc.

Mars,_Inc.

Q2245288 - 3 Musketeers: 2011 film by Cole S. McKay

Output: None of the candidates

Output: None of the candidates

Output: None of the candidates


Mars Drinks UK

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: Mars_Inc, Mars Drinks UK: Mars Drinks UK, the beverages division of Mars Limited, operates fromSloughinBerkshireand specializes in office vending machines. Mars Drinks UK comprises the FLAVIA and KLIX brands which offer branded drinks such as theStarburst Orange Drink, theMaltesers Hot Chocolateand theGalaxydrinks. Mars Drinks also produces coffee and the equipment used to make it. In 1982 FLAVIA was created out of the high demand for coffee in the United Kingdom. Initially marketed asDimension 3until 1989, FLAVIA was introduced in France and Germany in 1986 and Japan in 1992 then brought to the United States in 1996 and to Canada in 1997. Other products such as cappuccino were introduced in 2002 and tea in 2004. In 2018, the Drinks division was sold toLavazza.

[
    "Q695087 - Mars, Incorporated: American global food company and manufacturer",
    "Q123255524 - Mars Inc. awards $4 million for health care in Ukraine: scientific article published in 2023"
]

[
    "Q29123751 - Mars (United Kingdom): subsidiary of Mars, Incorporated"
]

[
    "Q29123751 - Mars (United Kingdom): subsidiary of Mars, Incorporated"
]

[
    "Q574510 - Flavia: female given name",
    "Q4934135 - Selma Abrahamsson: Finnish writer writing in Swedish (1872-1911)",
    "Q87190956 - Flavia: genus of plant",
    "Q109759381 - Flavia: person identified in the Museu da Pessoa collection",
    "Q105080873 - Flavià: family name"
]

[
    "Q145 - United Kingdom: country in north-west Europe",
    "Q174193 - United Kingdom of Great Britain and Ireland: historical sovereign state (1801–1922)",
    "Q7979 - British English: forms of the English language used in Britain",
    "Q161885 - Kingdom of Great Britain: constitutional monarchy in Western Europe (1707–1800)",
    "Q11010 - Parliament of the United Kingdom: supreme legislative body of the United Kingdom"
]

[
    "Q29123751 - Mars (United Kingdom): subsidiary of Mars, Incorporated"
]

[
    "Q123596197 - Dimension-3: periodical",
    "Q125610479 - Dimension 3 Festival: None",
    "Q130586433 - Dimension 3: None",
    "Q99746146 - Dimensión 354-X: None"
]

[
    "Q142 - France: country in Western Europe and other continents (through its overseas territories in America, Africa and Oceania)",
    "Q3080569 - France: unisex given name",
    "Q16275867 - France: family name",
    "Q47774 - France men's national association football team: national association football team representing France",
    "Q2268455 - Francesco: male given name"
]

[
    "Q183 - Germany: country in Central Europe",
    "Q1206012 - German Reich: official name for the German nation state from 1871 to 1945, and name of Germany until 1949",
    "Q41304 - Weimar Republic: Germany in the years 1918/1919–1933",
    "Q37444958 - Germany: family name",
    "Q133933103 - Germany: male given name"
]

[
    "Q17 - Japan: island country in East Asia",
    "Q13989 - Honshu: largest island of Japan",
    "Q5287 - Japanese: language spoken in East Asia",
    "Q188712 - Empire of Japan: Empire in the Asia-Pacific region from 1868 to 1947",
    "Q205662 - Tokugawa shogunate: 1603–1868 Japanese military government"
]

[
    "Q30 - United States: country located primarily in North America",
    "Q637413 - United States Census Bureau: U.S. agency responsible for the census and related statistics",
    "Q11703 - United States Virgin Islands: unincorporated territory of the United States of America",
    "Q4917 - United States dollar: official currency of the United States",
    "Q214867 - National Gallery of Art: national art museum in Washington, D.C."
]

[
    "Q16 - Canada: country in North America",
    "Q14624136 - Canada: moth genus of Pteromalidae",
    "Q13265725 - Canada: family name",
    "Q54856571 - Canada: unisex given name",
    "Q2003 - Newfoundland and Labrador: province of Canada"
]

[
    "Q37013093 - Cappuccino: family name",
    "Q1034878 - Cappuccino: German rapper",
    "Q437724 - Bernardo Strozzi: Italian painter (1581-1644)",
    "Q159774 - cappuccino: coffee drink",
    "Q29820425 - Cappuccino Dmel_CG3399: protein found in Drosophila melanogaster"
]

[
    "Q1987 - 2002: calendar year",
    "Q841347 - 2002: natural number",
    "Q52160856 - 2002: 2018 song by Anne-Marie Rose Nicholson",
    "Q111967692 - 2002: cover of Martha Helen",
    "Q9668 - 2002 Winter Olympics: 19th edition of Winter Olympics, in Salt Lake City, Utah, United States"
]

[
    "Q15885810 - Tea: female given name",
    "Q101815 - Camellia sinensis: species of plant",
    "Q6097 - tea: brewed drink made from tea leaves",
    "Q37226 - teacher: person who helps others to acquire knowledge, competences or values",
    "Q1622272 - university teacher: person teaching at a university or college"
]

[
    "Q2430 - 1986: year",
    "Q2813507 - 1986: natural number",
    "Q4582812 - 1986: 2001 debut studio album by Genie Chuo",
    "Q15697872 - 1986: 1999 studio album by One Last Wish",
    "Q46938 - 1986 FIFA World Cup: 13th FIFA World Cup, held in Mexico"
]

[
    "Q21510170 - Lavazza: family name",
    "Q543750 - Lavazza: Italian coffee company",
    "Q50557071 - Lavazza Premium Coffees Corp.: company, United States subsidiary of Lavazza",
    "Q50977065 - Lavazza Australia Pty Ltd.: company, Australian subsidiary of Lavazza",
    "Q50843317 - Lavazza Coffee (UK) Ltd.: company, United Kingdom subsidiary of Lavazza"
]

[
    "Q2425 - 1989: year on the Gregorian calendar",
    "Q5371787 - 1989: natural number",
    "Q10844029 - 1989: 1989 studio album by Lowell Lo",
    "Q17544553 - 1989: 2014 studio album by Taylor Swift",
    "Q186437 - Game Boy: 1989 portable video game console"
]

[
    "Q145 - United Kingdom: country in north-west Europe",
    "Q174193 - United Kingdom of Great Britain and Ireland: historical sovereign state (1801–1922)",
    "Q7979 - British English: forms of the English language used in Britain",
    "Q161885 - Kingdom of Great Britain: constitutional monarchy in Western Europe (1707–1800)",
    "Q11010 - Parliament of the United Kingdom: supreme legislative body of the United Kingdom"
]

[
    "Q211907 - Slough: town in Berkshire, England, UK",
    "Q37467501 - Slough: family name",
    "Q21163036 - Slough: unitary authority area in Berkshire, England",
    "Q7541461 - slough: a wetland, usually a swamp or shallow lake, often a backwater to a larger body of water",
    "Q989007 - Slough: Parliamentary constituency in the United Kingdom, 1983 onwards"
]

[
    "Q67284726 - Berkshire: historic county of England, United Kingdom",
    "Q37232540 - Berkshire: family name",
    "Q23220 - Berkshire: ceremonial and non-metropolitan but non-administrative county of England",
    "Q217583 - Berkshire Hathaway: American multinational conglomerate holding company",
    "Q60578252 - Berkshire: Constituency of the Parliament of England (to 1707)"
]

[
    "Q2014 - 2004: year",
    "Q906911 - 2004: natural number",
    "Q8558 - 2004 Summer Olympics: Games of the XXVIII Olympiad, in Athens, Greece",
    "Q28878253 - 2004 Moroccan census: census in Morocco",
    "Q109719080 - 2004 Indonesian People's Representative Council election: None"
]

Output: None of the candidates


Mars Drinks UK

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: Mars_Inc, Mars Drinks UK: Mars Drinks UK, the beverages division of Mars Limited, operates fromSloughinBerkshireand specializes in office vending machines. Mars Drinks UK comprises the FLAVIA and KLIX brands which offer branded drinks such as theStarburst Orange Drink, theMaltesers Hot Chocolateand theGalaxydrinks. Mars Drinks also produces coffee and the equipment used to make it. In 1982 FLAVIA was created out of the high demand for coffee in the United Kingdom. Initially marketed asDimension 3until 1989, FLAVIA was introduced in France and Germany in 1986 and Japan in 1992 then brought to the United States in 1996 and to Canada in 1997. Other products such as cappuccino were introduced in 2002 and tea in 2004. In 2018, the Drinks division was sold toLavazza.

Mars_Inc

Q695087 - Mars, Incorporated: American global food company and manufacturer

Q123255524 - Mars Inc. awards $4 million for health care in Ukraine: scientific article published in 2023

Q29123751 - Mars (United Kingdom): subsidiary of Mars, Incorporated

Mars_Drinks_UK

Q211907 - Slough: town in Berkshire, England, UK

Q21163036 - Slough: unitary authority area in Berkshire, England

Q7541461 - slough: a wetland, usually a swamp or shallow lake, often a backwater to a larger body of water

Q989007 - Slough: Parliamentary constituency in the United Kingdom, 1983 onwards

Mars_Drinks_UK

Mars_Drinks_UK

Q921623 - Sazerac: cognac or whiskey cocktail

Q1259070 - Drinks: periodical literature

Q112951877 - Drinks On Me: British music producer and DJ

Mars_Drinks_UK

Q4934135 - Selma Abrahamsson: Finnish writer writing in Swedish (1872-1911)

Q109759381 - Flavia: person identified in the Museu da Pessoa collection

FLAVIA

Q46934 - 1982 FIFA World Cup: 12th FIFA World Cup, held in Spain

Q49103 - 1982 Lebanon War: 1982 war between Israel and forces in Lebanon

FLAVIA

P131 - located in the administrative territorial entity: the item is located on the territory of the following administrative entity. Use P276 for specifying locations that are non-administrative places and for items about events. Use P1382 if the item falls only partially into the administrative entity.

P518 - applies to part: part, aspect, or form of the item to which the claim applies

P2541 - operating area: geographic area or jurisdiction an organisation or industry operates in, serves, or has responsibility for

Q145 - United Kingdom: country in north-west Europe

Q174193 - United Kingdom of Great Britain and Ireland: historical sovereign state (1801–1922)

Q7979 - British English: forms of the English language used in Britain

Q161885 - Kingdom of Great Britain: constitutional monarchy in Western Europe (1707–1800)

Q11010 - Parliament of the United Kingdom: supreme legislative body of the United Kingdom

FLAVIA

Q142 - France: country in Western Europe and other continents (through its overseas territories in America, Africa and Oceania)

Q47774 - France men's national association football team: national association football team representing France

FLAVIA

Q183 - Germany: country in Central Europe

Q1206012 - German Reich: official name for the German nation state from 1871 to 1945, and name of Germany until 1949

Q41304 - Weimar Republic: Germany in the years 1918/1919–1933

FLAVIA

Q17 - Japan: island country in East Asia

Q13989 - Honshu: largest island of Japan

Q5287 - Japanese: language spoken in East Asia

Q188712 - Empire of Japan: Empire in the Asia-Pacific region from 1868 to 1947

Q205662 - Tokugawa shogunate: 1603–1868 Japanese military government

FLAVIA

Q8531 - 1996 Summer Olympics: Games of the XXVI Olympiad, in Atlanta, USA

Q431657 - 1996 Taiwanese presidential election: Republic of China presidential election

Q174397 - 1996 Summer Paralympics: 1996 edition of the Summer Paralympics

FLAVIA

Q14624136 - Canada: moth genus of Pteromalidae

Q2003 - Newfoundland and Labrador: province of Canada

FLAVIA

Q437724 - Bernardo Strozzi: Italian painter (1581-1644)

Q29820425 - Cappuccino Dmel_CG3399: protein found in Drosophila melanogaster

FLAVIA

Q52160856 - 2002: 2018 song by Anne-Marie Rose Nicholson

Q111967692 - 2002: cover of Martha Helen

Q9668 - 2002 Winter Olympics: 19th edition of Winter Olympics, in Salt Lake City, Utah, United States

FLAVIA

Q101815 - Camellia sinensis: species of plant

Q6097 - tea: brewed drink made from tea leaves

Q37226 - teacher: person who helps others to acquire knowledge, competences or values

Q1622272 - university teacher: person teaching at a university or college

Mars_Drinks_UK

Mars_Drinks_UK

Mars_Drinks_UK

Mars_Drinks_UK

Q543750 - Lavazza: Italian coffee company

Q50557071 - Lavazza Premium Coffees Corp.: company, United States subsidiary of Lavazza

Q50977065 - Lavazza Australia Pty Ltd.: company, Australian subsidiary of Lavazza

Q50843317 - Lavazza Coffee (UK) Ltd.: company, United Kingdom subsidiary of Lavazza

FLAVIA

Q8558 - 2004 Summer Olympics: Games of the XXVIII Olympiad, in Athens, Greece

Q28878253 - 2004 Moroccan census: census in Morocco

Q109719080 - 2004 Indonesian People's Representative Council election: None

Output: None of the candidates

Output: None of the candidates

Output: None of the candidates

Output: None of the candidates

Output: None of the candidates

Output: None of the candidates

Output: None of the candidates

Output: None of the candidates

Output: None of the candidates

Output: None of the candidates

Output: None of the candidates

Output: None of the candidates

Output: None of the candidates

Output: None of the candidates

Output: None of the candidates

Output: None of the candidates

Output: None of the candidates


Mars Petcare

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: Mars_Inc, Mars Petcare: Forrest Mars started the pet food industry inEurope, and his Mars Candy Company boughtKal Kan. Forrest Mars changed the name of Kal Kan dog food to Pedigree, and Kal Kan cat food toWhiskas. As of 1991, Mars controlled 60 percent of the pet food market, both in volume and value. Whiskas was the number one brand. As of 1994, Mars was the leading pet food company worldwide with $4 billion in sales. In February 2003, Mars acquired Aquarium Pharmaceuticals, Inc.(API, incorporated in 1964) and in 2007 it was renamed Mars Fishcare, Inc. The company manufactures and supplies homeaquariumandpondproducts.Mars Fishcare brands include:Aquarium Pharmaceuticals (API),RENA,AQUARIAN,andPondCare. The company introduced a genetic test for dogs usingcheek swabsto identify breed breakdown, trait tests and health risks in 2007 known as Wisdom Panel.In 2018, Mars Petcare acquired Genoscoper Laboratories, a Finnish animal molecular diagnostics company, "to form the basis for future practical applications in enabling precision healthcare for pets" under itsgenetic testingunit, Wisdom Health.Wisdom Panel DNA testing expanded to include cats in mid 2021. InAustralia, the division operates three sites that are located inWodonga, Victoria(established in 1967 for manufacture of wet pet food);Bathurst, New South Wales(established in the 1980s for manufacture of dry pet food); andBrisbane, Queensland(for manufacture of birdcare products). Mars Petcare manufactures the 'Trill' birdseed range.

[
    "Q695087 - Mars, Incorporated: American global food company and manufacturer",
    "Q123255524 - Mars Inc. awards $4 million for health care in Ukraine: scientific article published in 2023"
]

[
    "Q16412771 - Pedigree: Estonian musical group",
    "Q189977 - family tree: chart representing family relationships in a conventional tree structure",
    "Q38829 - breed: group of domestic animals with a distinctive phenotype",
    "Q3242583 - pedigree chart: diagram showing the occurrence and appearance or phenotypes of a particular gene or organism, in generations",
    "Q2027177 - Pedigree Petfoods: UK dog food manufacturer"
]

[
    "Q163355 - Whiskas: Cat food brand",
    "Q55874247 - Kal Kan: brand name for pet foods manufactured by Kal Kan Foods, Inc. and later by Mars, Inc.",
    "Q35438176 - Kal Kaneeco: None"
]

[
    "Q695087 - Mars, Incorporated: American global food company and manufacturer",
    "Q123255524 - Mars Inc. awards $4 million for health care in Ukraine: scientific article published in 2023"
]

[
    "Q106116788 - Petfood industry: magazine of pet food manufacturing and merchandising"
]

[
    "Q46 - Europe: continent in the Northern Hemisphere",
    "Q185144 - Europe: Swedish rock band",
    "Q458 - European Union: political and economic union of 27 European states",
    "Q5412157 - Europe PubMed Central: database of biomedical research",
    "Q198697 - Europe: 1983 debut studio album by Europe"
]

[
    "Q163355 - Whiskas: Cat food brand"
]

[
    "Q19617603 - February 1, 2007: date",
    "Q17892073 - 2007-02-01: Polscy szczypiorniści pokonali w półfinale MŚ Danię: Wikinews article",
    "Q17892069 - 2007-02-01: Polacy na czele komisji w Parlamencie Europejskim: Wikinews article",
    "Q17892063 - 2007-02-01: Członkowie nieistniejącej sejmowej komisji bankowej pobierają diety: Wikinews article",
    "Q17892082 - 2007-02-01: Powrót pociągów na trasę Piła Główna - Wałcz: Wikinews article"
]

[
    "Q2652 - 1964: year",
    "Q19241625 - 1964: natural number",
    "Q2812340 - 1964: 2004 album by Miossec",
    "Q8420 - 1964 Summer Olympics: Games of the XVIII Olympiad, in Tokyo, Japan",
    "Q9636 - 1964 Winter Olympics: 9th edition of Winter Olympics, Innsbruck, Austria"
]

[
    "Q695087 - Mars, Incorporated: American global food company and manufacturer",
    "Q123255524 - Mars Inc. awards $4 million for health care in Ukraine: scientific article published in 2023"
]

[
    "Q29123751 - Mars (United Kingdom): subsidiary of Mars, Incorporated",
    "Q132067472 - Mars Petcare Uk: None",
    "Q132067473 - Mars Petcare Us Inc: None"
]

[
    "Q606307 - Wodonga: regional city in Victoria, Australia"
]

[
    "Q704978 - Bathurst: city in New South Wales, Australia"
]

[
    "Q4916133 - Birdseed: album by Lou Donaldson",
    "Q65560449 - bird seed: seeds used as bird food",
    "Q2529956 - Birdseed painter: None",
    "Q1785402 - Birdseed workshop: attic geometric pottery workshop",
    "Q1974353 - bird seed agar: culture medium used in microbiology"
]

[
    "Q3289906 - aquatic ecosystem: ecosystem in a body of water",
    "Q15746547 - Aquatic Ecosystem Health and Management: journal",
    "Q35092946 - Aquatic ecosystems: effects of solar ultraviolet radiation and interactions with other climatic change factors: scientific article",
    "Q58191214 - Aquatic ecosystem responses to Holocene climate change and biome development in boreal, central Asia: scientific article",
    "Q59199264 - Aquatic Ecosystem Responses to Rapid Recovery from Extreme Acidification and Metal Contamination in Lakes Near Wawa, Ontario: article"
]

[
    "Q129176283 - Wisdom Health Clinic: healthcare centre in Nigeria",
    "Q90571210 - Wisdom Health (United States): company in Vancouver, United States"
]

[
    "Q2024 - 2007: calendar year",
    "Q907344 - 2007: natural number",
    "Q135047694 - 2007: video game developed by Hit'n'Run Digital Studio",
    "Q53389304 - 2007-2008 one-year-period: period of about one year starting in 2007 and ending in 2008",
    "Q15729072 - 2007 Census of the Philippines: item representing census of Philippines 2007 for source"
]

[
    "Q29123751 - Mars (United Kingdom): subsidiary of Mars, Incorporated",
    "Q132067472 - Mars Petcare Uk: None",
    "Q132067473 - Mars Petcare Us Inc: None"
]

[
    "Q695087 - Mars, Incorporated: American global food company and manufacturer",
    "Q123255524 - Mars Inc. awards $4 million for health care in Ukraine: scientific article published in 2023"
]

[
    "Q1395404 - Forrest Mars: grandson of Frank C. Mars and American billionaire (1931–2016)",
    "Q2578399 - Forrest Mars: American businessman (1904–1999)",
    "Q1437957 - Forrest Mars: Wikimedia disambiguation page",
    "Q3065338 - Mars family: American family"
]

[
    "Q695087 - Mars, Incorporated: American global food company and manufacturer",
    "Q123255524 - Mars Inc. awards $4 million for health care in Ukraine: scientific article published in 2023"
]

[
    "Q8459112 - Category:Finnish language: Wikimedia category",
    "Q10495601 - Finnish language: None",
    "Q55633982 - dictionary of the Finnish language: language version of dictionary",
    "Q106317318 - Finnish teacher: person who teaches the Finnish language",
    "Q31087986 - history of the Finnish language: aspect of history"
]

[
    "Q29123751 - Mars (United Kingdom): subsidiary of Mars, Incorporated",
    "Q132067472 - Mars Petcare Uk: None",
    "Q132067473 - Mars Petcare Us Inc: None"
]

[
    "Q103905406 - Aquarian: shipwreck off the Scottish coast",
    "Q2098277 - Planningtorock: English musician and record producer",
    "Q133805942 - Aquarian Press: book publisher",
    "Q906687 - Aquarian Age: Sign for Evolution: Japanese anime television series",
    "Q11282890 - Aquarian Age Alternative: video game"
]

[
    "Q10811 - Reptilia: class of vertebrate animals (Vertebrata)",
    "Q1825776 - Reptile: character from Mortal Kombat",
    "Q1644501 - Reptile Database: database that provides information of all living reptile species",
    "Q174416 - herpetology: study of amphibians and reptiles",
    "Q76013985 - Reptiles and Amphibians of New Zealand: 1st edition of field guide by van Winkel, Baling, and Hitchmough"
]

[
    "Q163355 - Whiskas: Cat food brand"
]

[
    "Q29123751 - Mars (United Kingdom): subsidiary of Mars, Incorporated",
    "Q132067472 - Mars Petcare Uk: None",
    "Q132067473 - Mars Petcare Us Inc: None"
]

[
    "Q2648 - 1967: year",
    "Q12681701 - 1967: natural number",
    "Q49077 - Six-Day War: 1967 war between Israel and Egypt, Jordan, and Syria",
    "Q322607 - War of Attrition: 1967–1970 war between Israel and Egypt, Syria and Jordan",
    "Q53385119 - 1967-1968 one-year-period: period of about one year starting in 1967 and ending in 1968"
]

Output: None of the candidates

Output: None of the candidates

Output: None of the candidates

Output: None of the candidates

Output: None of the candidates

Output: None of the candidates


Mars Petcare

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: Mars_Inc, Mars Petcare: Forrest Mars started the pet food industry inEurope, and his Mars Candy Company boughtKal Kan. Forrest Mars changed the name of Kal Kan dog food to Pedigree, and Kal Kan cat food toWhiskas. As of 1991, Mars controlled 60 percent of the pet food market, both in volume and value. Whiskas was the number one brand. As of 1994, Mars was the leading pet food company worldwide with $4 billion in sales. In February 2003, Mars acquired Aquarium Pharmaceuticals, Inc.(API, incorporated in 1964) and in 2007 it was renamed Mars Fishcare, Inc. The company manufactures and supplies homeaquariumandpondproducts.Mars Fishcare brands include:Aquarium Pharmaceuticals (API),RENA,AQUARIAN,andPondCare. The company introduced a genetic test for dogs usingcheek swabsto identify breed breakdown, trait tests and health risks in 2007 known as Wisdom Panel.In 2018, Mars Petcare acquired Genoscoper Laboratories, a Finnish animal molecular diagnostics company, "to form the basis for future practical applications in enabling precision healthcare for pets" under itsgenetic testingunit, Wisdom Health.Wisdom Panel DNA testing expanded to include cats in mid 2021. InAustralia, the division operates three sites that are located inWodonga, Victoria(established in 1967 for manufacture of wet pet food);Bathurst, New South Wales(established in the 1980s for manufacture of dry pet food); andBrisbane, Queensland(for manufacture of birdcare products). Mars Petcare manufactures the 'Trill' birdseed range.

Mars_Inc

Q29123751 - Mars (United Kingdom): subsidiary of Mars, Incorporated

Mars_Petcare

Q16412771 - Pedigree: Estonian musical group

Q189977 - family tree: chart representing family relationships in a conventional tree structure

Q38829 - breed: group of domestic animals with a distinctive phenotype

Q3242583 - pedigree chart: diagram showing the occurrence and appearance or phenotypes of a particular gene or organism, in generations

Q2027177 - Pedigree Petfoods: UK dog food manufacturer

Pedigree

Q16412771 - Pedigree: Estonian musical group

Q55874247 - Kal Kan: brand name for pet foods manufactured by Kal Kan Foods, Inc. and later by Mars, Inc.

Mars_Petcare

Mars_Petcare

Aquarium_Pharmaceuticals

Mars_Fishcare

Mars_Fishcare

Q103905406 - Aquarian: shipwreck off the Scottish coast

Q2098277 - Planningtorock: English musician and record producer

Q133805942 - Aquarian Press: book publisher

Q906687 - Aquarian Age: Sign for Evolution: Japanese anime television series

Q11282890 - Aquarian Age Alternative: video game

Mars_Fishcare

Q6686 - Renault: automotive conglomerate

Mars_Fishcare

Wisdom_Panel

Mars_Petcare

Q3539177 - Trillium erectum: species of plant

Q3539178 - Trillium camschatcense: species of plant

Mars_Petcare

P854 - reference URL: should be used for Internet URLs as references. Use "Wikimedia import URL" (P4656) for imports from WMF sites

P856 - official website: URL of the official page of an item (current or former). Usage: If a listed URL no longer points to the official website, do not remove it, but see the "Hijacked or dead websites" section of the Talk page

P6153 - research site: place where this item was researched

P65 - site of astronomical discovery: the place where an astronomical object was discovered (observatory, satellite)

P189 - location of discovery: where the item was located when discovered

Q606307 - Wodonga: regional city in Victoria, Australia

Mars_Petcare

Q704978 - Bathurst: city in New South Wales, Australia

Mars_Petcare

Q34932 - Brisbane: capital city of Queensland, Australia

Q917682 - City of Brisbane: local government area of Brisbane, in Queensland, Australia

Q12506845 - Metimarang Island: island in Southwest Maluku Regency, Maluku Province, Indonesia

Q917671 - Brisbane: city in San Mateo County, California, United States

Mars_Petcare

Wisdom_Panel

Q7026 - Catalan: Western Romance language

Q4167836 - Wikimedia category: use with 'instance of' (P31) for Wikimedia category

Q32566 - computed tomography: medical imaging procedure using X-rays to produce cross-sectional images

Q207642 - Catha edulis: species of plant, commonly used by humans for its psychoactive effects

Mars_Petcare

Q20717272 - Canis familiaris: species of mammal

Q80019 - double bass: acoustic stringed instrument of the violin family

Mars_Petcare

Q695087 - Mars, Incorporated: American global food company and manufacturer

Q123255524 - Mars Inc. awards $4 million for health care in Ukraine: scientific article published in 2023

Mars_Petcare

Q6648982 - pet food: food for domestic animals

Q106116788 - Petfood industry: magazine of pet food manufacturing and merchandising

Q28368538 - Petfood applications of inulin and oligofructose: scientific article

Mars_Petcare

P2139 - total revenue: income gained by an organization during a given time frame. Not to be confused with fiscal revenue

P2770 - source of income: source of income of an organization or person

Mars_Petcare

Q17683526 - 60.000 запослених у Србији месецима не добија плату: Wikinews article

Q17683514 - 60.000 potpisa za regionalnu saradnju u oblasti životne sredine: Wikinews article

Mars_Petcare

P1642 - acquisition transaction: how the player was acquired; qualifier for P54 (member of sports team)

Aquarium_Pharmaceuticals

P571 - inception: time when an entity begins to exist; for date of official opening use P1619

Q69286470 - January 1, 1964: date in Gregorian calendar

Aquarium_Pharmaceuticals

Mars_Petcare

Mars_Petcare

Q69288020 - January 1, 1967: date in Gregorian calendar

Mars_Petcare

Q1395404 - Forrest Mars: grandson of Frank C. Mars and American billionaire (1931–2016)

Q2578399 - Forrest Mars: American businessman (1904–1999)

Q1437957 - Forrest Mars: Wikimedia disambiguation page

Mars_Petcare

Q34644 - 1980s: decade of the Gregorian calendar that began on January 1, 1980

Q44071823 - 1980s: decade of the Ethiopian calendar

Q13624593 - 1980s in Hong Kong: Hong Kong-related events during the 1980s

Q4579555 - 1980s in Japan: overview of Japan-related events during the 1980s

Mars_Petcare

Mars_Petcare

Mars_Petcare

Q129176283 - Wisdom Health Clinic: healthcare centre in Nigeria

Q90571210 - Wisdom Health (United States): company in Vancouver, United States

Mars_Petcare

Mars_Petcare

Mars_Petcare

Q16412771 - Pedigree: Estonian musical group

Mars_Petcare

Mars_Petcare

Mars_Fishcare

Mars_Fishcare

Mars_Fishcare

Mars_Fishcare

Mars_Fishcare

Mars_Fishcare

Mars_Fishcare

Q69304816 - February 1, 2003: date in Gregorian calendar

Wisdom_Panel

Q20717272 - Canis familiaris: species of mammal

Wisdom_Panel

Q17618947 - Slovenia adopts euro: Wikinews article

Q19768612 - 2007-01-01: Bułgaria i Rumunia nowymi członkami Unii Europejskiej: Wikinews article

Q17891401 - 2007-01-01: Kolarstwo: Nowa kobieca grupa zawodowa w Polsce: Wikinews article

Q17891396 - 2007-01-01: Dwóch nożowników zaatakowało turystów na Gubałówce: Wikinews article

Wisdom_Panel

Wisdom_Panel

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Mars Veterinary Health

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: Mars_Inc, Mars Veterinary Health: In 2007, Mars, Incorporated purchased a significant stake in theBanfield Pet Hospitalchain. In October 2015,BluePearl Veterinary Partnerswas acquired by Mars Petcare division. This acquisition resulted in Mars Petcare becoming the largest pet nutrition and veterinary care provider in the world. In January 2017, Mars Veterinary Health North America announced the US$7.7 billion acquisition of Los Angeles-based animal hospital chainVCA Inc. In June 2018, Mars Veterinary Health International and Diagnostics acquired the Linnaeus Group consolidating its position as a leading veterinary provider in the United Kingdom.

[
    "Q2882416 - Banfield Pet Hospital: chain of veterinary clinics"
]

[
    "Q695087 - Mars, Incorporated: American global food company and manufacturer",
    "Q134584046 - Mars, Inc.: 2013 novel by Ben Bova"
]

[
    "Q2024 - 2007: calendar year",
    "Q907344 - 2007: natural number",
    "Q135047694 - 2007: video game developed by Hit'n'Run Digital Studio",
    "Q53389304 - 2007-2008 one-year-period: period of about one year starting in 2007 and ending in 2008",
    "Q15729072 - 2007 Census of the Philippines: item representing census of Philippines 2007 for source"
]

[
    "Q29123751 - Mars (United Kingdom): subsidiary of Mars, Incorporated",
    "Q132067472 - Mars Petcare Uk: None",
    "Q132067473 - Mars Petcare Us Inc: None"
]

[
    "Q30 - United States: country located primarily in North America",
    "Q637413 - United States Census Bureau: U.S. agency responsible for the census and related statistics",
    "Q11703 - United States Virgin Islands: unincorporated territory of the United States of America",
    "Q4917 - United States dollar: official currency of the United States",
    "Q214867 - National Gallery of Art: national art museum in Washington, D.C."
]

[
    "Q55104023 - Linnaeus Group Limited: Business"
]

[
    "Q145 - United Kingdom: country in north-west Europe",
    "Q174193 - United Kingdom of Great Britain and Ireland: historical sovereign state (1801–1922)",
    "Q7979 - British English: forms of the English language used in Britain",
    "Q161885 - Kingdom of Great Britain: constitutional monarchy in Western Europe (1707–1800)",
    "Q11010 - Parliament of the United Kingdom: supreme legislative body of the United Kingdom"
]

[
    "Q21034764 - October 1, 2015: Thursday in October 2015"
]

Output: None of the candidates

Output: None of the candidates

Output: None of the candidates


Mars Veterinary Health

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: Mars_Inc, Mars Veterinary Health: In 2007, Mars, Incorporated purchased a significant stake in theBanfield Pet Hospitalchain. In October 2015,BluePearl Veterinary Partnerswas acquired by Mars Petcare division. This acquisition resulted in Mars Petcare becoming the largest pet nutrition and veterinary care provider in the world. In January 2017, Mars Veterinary Health North America announced the US$7.7 billion acquisition of Los Angeles-based animal hospital chainVCA Inc. In June 2018, Mars Veterinary Health International and Diagnostics acquired the Linnaeus Group consolidating its position as a leading veterinary provider in the United Kingdom.

Mars,_Inc.

Q134584046 - Mars, Inc.: 2013 novel by Ben Bova

Mars,_Inc.

P7888 - merged into: the subject was dissolved and merged into the object, that existed previously

P11812 - afterward owned by: person or institution that owned the subject after stated event. Meant to be used as qualifier of “significant event (P793)” for events like sales, auctions, gifts, etc

P11811 - beforehand owned by: person or institution that owned the subject just before stated event. Meant to be used as qualifier of "significant event (P793)" for events like sales, auctions, gifts, etc

Q2882416 - Banfield Pet Hospital: chain of veterinary clinics

Mars,_Inc.

Mars,_Inc.

P355 - child organization/unit: child organization/unit or subsidiary of a company or organization/unit; generally a fully owned separate corporation. Compare with "business division" (P199). Opposite of parent organization/unit (P749).

P749 - parent organization: parent organization of an organization, opposite of subsidiaries (P355)

Mars,_Inc.

Q55104023 - Linnaeus Group Limited: Business

Mars,_Inc.

Q84397456 - Pet Nutrition Alliance advocates nutritional assessments: scientific article published on May 15, 2012

Q87087986 - Pet nutrition: animation explains how pet food is made: scientific article published on April 11, 2015

Q74376729 - Pet nutrition coming of age. Proceedings of the Waltham International Symposium. August 6-7, 2001. Vancouver, Canada: scientific article published on 01 June 2002

Mars,_Inc.

Q10861889 - Veterinary Care Act: act of parliament in the Czech Republic

Q66182945 - Veterinary Care Records (NAID 6434876): series in the National Archives and Records Administration's holdings

Q59715835 - Veterinary-care events and costs over a 5-year follow-up period for warmblooded riding horses with or without previously recorded locomotor problems in Sweden: scientific article published on 06 August 2007

Q40090095 - Veterinary career ambitions correlate with gender and past experience, with current experience influencing curricular perspectives: scientific article published on 2 February 2013

Mars,_Inc.

Q1706476 - veterinary hospital: health care institution for animals

Q4764820 - Animal Hospital: British television show

Q110054986 - Animal Hospital: sketch from Saturday Night Live

Q30299340 - Animal Hospital Postojna: healthcare organization in Postojna, Slovenia

Q135943153 - Animal Hospital Umi to Sora: None

Mars,_Inc.

Q4928764 - BluePearl Specialty and Emergency Pet Hospital: American pet hospital network

Mars,_Inc.

Mars,_Inc.

Q115921084 - pet supply: supply for pets; product category

Q7171563 - Pet Supplies Plus: pet supply retailing corporation

Mars,_Inc.

Q2095 - food: any substance consumed to provide nutritional support for the body; form of energy stored in chemical

Q8195619 - human food: food eaten by Homo sapiens

Q173710 - esophagus: vertebrate organ through which food passes to the stomach

Q3007875 - Food Chemistry: peer-reviewed scientific journal

Mars,_Inc.

Q12140 - medication: substance used to diagnose, cure, treat, or prevent disease

Q8386 - drug: chemical substance having an effect on the body

Q15724462 - Drug Safety: scientific journal

Q5308946 - Drugs & Aging: peer-reviewed scientific journal

Q188840 - medicinal plant: plants or derivatives used to treat medical conditions in humans or animals

Mars,_Inc.

Q131207 - cosmetics: substances used to enhance the appearance or odor of the human body

Q12752882 - cosmetics industry: industry that manufactures and distributes cosmetic products

Q19787844 - Cosmetics Europe: organization in Brussels, Belgium

Mars,_Inc.

Q1849238 - Toys: 1992 film directed by Barry Levinson

Q6168 - Töysä: former municipality of Finland, now part of Alavus

Q1255568 - toy goods: toys and games intended for retail sale

Q114504341 - Toys: episode of The Mr. Men Show (S2 E11)

Mars,_Inc.

Q15817883 - Medical Devices: Evidence and Research: journal

Q131631913 - Medical devices: US patent 11439494

Q59554230 - Medical Devices & Sensors: journal

Q1421629 - Medical Devices Directive: EU directive

Q55075096 - Medical Devices Park, Hyderabad: industrial estate

Mars,_Inc.

Q61902170 - Nutritional Supplements and Nitric Oxide Bioactivity: clinical trial

Q64717100 - Nutritional Supplements and Hormonal Manipulations for Breast Cancer Prevention: clinical trial

Q62820700 - Nutritional Supplements for Exercise Recovery: clinical trial

Q64675771 - Nutritional Supplements in Improving Quality of Life During First-Line Chemotherapy in Patients With Metastatic Gynecological Cancer: clinical trial

Q65370262 - Nutritional Supplements & Complementary/Alternative Medicine by Prostate & Breast Cancer Patients: clinical trial

Mars,_Inc.

Q34054499 - Sports supplements. Can dietary additives boost athletic performance and potential?: scientific article

Q36133940 - Sports supplements: a modern case of caveat emptor: scientific article

Q89514639 - Sports Supplements: Pearls and Pitfalls: scientific article published on 16 October 2019

Mars,_Inc.

Q189567 - food additive: substances added to food to preserve flavor or enhance its taste, appearance, or other qualities

Q3076429 - Food Additives and Contaminants Part A: peer-reviewed scientific journal

Q15760547 - Food Additives and Contaminants: journal

Q15724517 - Food Additives And Contaminants Part B: Surveillance Communications: journal

Mars,_Inc.

Q115633940 - medical supply: type of product

Q2221810 - medical equipment shop: shop that sells medical equipment

Q64204951 - Medical Supply Purveyor's Retained Invoices (NAID 6106700): series in the National Archives and Records Administration's holdings

Q64401221 - Medical Supply Requisitions and Related Correspondence (NAID 6340630): series in the National Archives and Records Administration's holdings

Q64270636 - Medical Supply Memorandums (NAID 22123849): series in the National Archives and Records Administration's holdings

Mars,_Inc.

Mars,_Inc.

Q12140 - medication: substance used to diagnose, cure, treat, or prevent disease

Q34188324 - Pharmaceutical drug transport: the issues and the implications that it is essentially carrier-mediated only: scientific article

Q34166071 - Pharmaceutical drug promotion: how it is being practiced in India?: scientific article

Q39229403 - Pharmaceutical drugs chatter on Online Social Networks: scientific article published on March 15, 2014

Q92585821 - Pharmaceutical Drugs of Uncertain Value, Lifecycle Regulation at the US Food and Drug Administration, and Institutional Incumbency: scientific article published on 12 August 2019

Mars,_Inc.

Q26324221 - Veterinary pharmaceuticals: conference proceedings item published in 1975

Q43222728 - Veterinary pharmaceuticals and antibiotic resistance of Escherichia coli isolates in poultry litter from commercial farms and controlled feeding trials: scientific article published in January 2010

Q38983583 - Veterinary pharmaceuticals in aqueous systems and associated effects: an update: scientific article

Q92171884 - Veterinary pharmaceuticals and antibiotics in manure and slurry and their fate in amended agricultural soils: Findings from an experimental field site (Baix Empordà, NE Catalonia): scientific article published on 07 November 2018

Q115357505 - Veterinary Pharmaceuticals Sold in Cattle Markets for the Management of Foot-and-Mouth Disease and Flies in Vina Division (Adamawa-Cameroon): scientific article published in 2019

Mars,_Inc.

Q5448803 - filler: non-nutritive animal food ingredient

Q123130949 - Animal Food Manufacturing: NAICS industry classification

Q34010805 - Animal foods, protein, calcium and prostate cancer risk: the European Prospective Investigation into Cancer and Nutrition: scientific article

Q39310260 - Animal foods in traditional Australian aboriginal diets: polyunsaturated and low in fat.: scientific article

Q36612535 - Animal food intake and cooking methods in relation to endometrial cancer risk in Shanghai: scientific article published on 24 October 2006

Mars,_Inc.

Q6509670 - food preservative: substance capable of inhibiting, retarding or arresting the process of fermentation, acidification or other deterioration of foods

Q43077437 - Food preservatives sodium benzoate and propionic acid and colorant curcumin suppress Th1-type immune response in vitro: scientific article published on 11 May 2010

Q46096934 - Food preservative potential of essential oils and fractions from Cymbopogon citratus, Ocimum gratissimum and Thymus vulgaris against mycotoxigenic fungi.: scientific article published on 4 March 2009

Q53605663 - Food preservatives sodium sulfite and sorbic acid suppress mitogen-stimulated peripheral blood mononuclear cells: scientific article

Q56767006 - Food preservative based on propolis: Bacteriostatic activity of propolis polyphenols and flavonoids upon Escherichia coli: scholarly article by Enzo A. Tosi et al published January 2007 in Food Chemistry

Mars,_Inc.

Q57762218 - Beauty production at the CERN pp̄ collider: article

Q57762311 - Beauty production at the CERN proton-antiproton collider: scientific article

Q48876963 - Beauty product-related exposures and childhood brain tumors in seven countries: results from the SEARCH International Brain Tumor Study: scientific article

Q57718161 - Beauty production in pp collisions ats=2.76TeVmeasured via semi-electronic decays: article by B. Abelev et al published November 2014 in Physics Letters B

Q58958829 - Beauty production at CDF: article

Mars,_Inc.

Q11827455 - agricultural product: plant or animal product that can be grown and harvested extensively for profit or subsistence

Q56299222 - agricultural production: production of agriculture

Q100397080 - Agricultural Products (Regulation of Import) Act, 1938: Act of the Oireachtas No. 14 of 1938

Q110252314 - Agricultural production systems simulation: field of research

Q3816336 - agricultural productivity: quotient between production and productive factors

Mars,_Inc.

Q12582288 - processed food: food which has undergone a cooking or other preparation process to convert it into a different form

Q106200622 - Processed food marketing in Ivory Coast, 1956-1990: Distribution techniques and foreign domination in a developing economy: doctoral thesis by Lars Boe Bosteen

Q136282503 - Processed Foods and the Consumer: Additives, Labeling, Standards, and Nutrition: book 1976

Q38204783 - Processed foods and the nutrition transition: evidence fromAsia: scientific article published on April 15, 2014

Q46627206 - Processed foods: contributions to nutrition.: scientific article published on 23 April 2014

Mars,_Inc.

Mars,_Inc.

Q11707 - restaurant: single establishment which prepares and serves food, located in building

Q256020 - inn: establishment providing lodging, food and drink

Q11666766 - restaurant: type of business under Japan's Food Sanitation Law

Q3427922 - restaurateur: person who manages restaurants professionally

Q18534542 - restaurant chain: set of related restaurants in many different locations that are under shared corporate ownership or franchising agreements

Mars,_Inc.

Q16323605 - food brand: brand name used for food

Q44909760 - Food branding influences ad libitum intake differently in children depending on weight status. Results of a pilot study: scientific article

Q44592282 - Food Branding and Young Children’s Taste Preferences: A Reassessment: scientific article published on August 20, 2013

Q59320133 - Food-branding places – A sensory perspective: None

Q78028703 - Food Brands: Friend or Foe?: scientific article published on 01 March 2002

Mars,_Inc.

Q2585617 - drug class: category of drugs used to classify a drug according to certain criteria

Q2943035 - medication classification: None

Q5308878 - Drug classification: making a hash of it?: report on the Misuse of Drugs Act

Q28473451 - Drug-class specific impact of antivirals on the reproductive capacity of HIV: scientific article

Q51856067 - Drug classification: science, politics, both or neither?: scientific article published on 9 February 2010

Mars,_Inc.

Q6881511 - enterprise: organizational unit producing goods or services, which benefits from a certain degree of autonomy in decision-making, especially for the allocation of its current resources

Q783794 - company: legal entity representing an association of people, whether natural, legal or a mixture of both, with a specific objective

Q102538 - company: military unit size designation

Q1162163 - director: person who leads a particular area of a company or organization

Mars,_Inc.

Q41710 - ethnic group: socially defined category of people who identify with each other

Q5404323 - ethnicity: a person's ethnic background

Q106474968 - ethnic group by settlement in Macedonia: census category

Q83828 - ethnic groups in Indonesia: overview of ethnic groups in Indonesia

Q2531956 - ethnic minority group: ethnic group, minority within a state, especially a single ethnic group within a polyethnic state

Mars,_Inc.

Q83440 - country music: genre of American popular music

Q6256 - country: distinct territorial body or political entity

Q3624078 - sovereign state: state that has the highest authority over a territory

Q902 - Bangladesh: country in South Asia

Q175185 - rural area: geographic area that is located outside towns and cities

Mars,_Inc.

Q50602 - Manchester City F.C.: association football club in Manchester, England

Q90 - Paris: capital city and largest city of France

Q19444 - Birmingham City F.C.: association football club in Birmingham, England

Q18736 - Stoke City F.C.: association football club in Stoke-on-Trent, England

Output: None of the candidates

Output: None of the candidates

Output: None of the candidates

Output: None of the candidates

Output: None of the candidates

Output: None of the candidates

Output: None of the candidates

Output: None of the candidates

Output: None of the candidates

Output: None of the candidates

Output: None of the candidates

Output: None of the candidates

Output: None of the candidates

Output: None of the candidates

Output: None of the candidates


Factories

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: Mars_Inc, Factories: In 1963, a large factory was opened inVeghelin theNetherlands. This factory has currently the biggest production volume of Mars factories and is one of the biggest chocolate factories in the world.Most confectionery products for Europe were produced in Slough and Veghel. The two factories in Slough were located on Liverpool Road and Dundee Road; the one on Liverpool Road closed in 2007, with Twix production moving to the Netherlands and Starburst production moving to theCzech Republic. The major production plant for Mars confectionery products in Australia is inBallarat, Victoria. There is one factory outside ofHershey, Pennsylvania, located inElizabethtown, Pennsylvania.The factory inChicago, Illinois, has its own commuter rail station, simply namedMars. The company announced in early 2022 that it intends to close the Chicago factory in 2024.The building will remain in the hands of Chicago's Galewood neighborhood residents.

[
    "Q695087 - Mars, Incorporated: American global food company and manufacturer",
    "Q134584046 - Mars, Inc.: 2013 novel by Ben Bova"
]

[
    "Q9874 - Veghel: former municipality in the Netherlands",
    "Q12557060 - Veghel: village in Meierijstad, the Netherlands",
    "Q114224313 - electoral district Veghel: electoral district in the Netherlands (1888-1918)",
    "Q18773215 - Veghel Roman Catholic Churchyard: roman catholic cemetery in Veghel",
    "Q106220344 - Veghel municipal council: None"
]

[
    "Q695087 - Mars, Incorporated: American global food company and manufacturer",
    "Q134584046 - Mars, Inc.: 2013 novel by Ben Bova"
]

[
    "Q211907 - Slough: town in Berkshire, England, UK",
    "Q37467501 - Slough: family name",
    "Q21163036 - Slough: unitary authority area in Berkshire, England",
    "Q7541461 - slough: a wetland, usually a swamp or shallow lake, often a backwater to a larger body of water",
    "Q989007 - Slough: Parliamentary constituency in the United Kingdom, 1983 onwards"
]

[
    "Q1297 - Chicago: city and county seat of Cook County, Illinois, United States of America",
    "Q371938 - Chicago: American rock band",
    "Q90437849 - Chicago: vocal track by Frank Sinatra; 1957 studio recording; cover version",
    "Q209636 - Chicago Blackhawks: hockey team of the National Hockey League",
    "Q56034748 - Chicago: family name"
]

[
    "Q1133974 - Elizabethtown: borough in northwestern Lancaster County, Pennsylvania, United States"
]

[
    "Q17856 - Ballarat: regional city in Victoria, Australia"
]

[
    "Q49619 - 2024: calendar year",
    "Q19241648 - 2024: natural number",
    "Q124040144 - 2024: 2023 single by Playboi Carti",
    "Q133576379 - 2024: 2025 song by Playboi Carti",
    "Q995653 - 2024 Summer Olympics: games of the XXXIII Olympiad, in Paris, France"
]

[
    "Q213 - Czech Republic: country in Central Europe",
    "Q5201764 - Czech Republic: constituency of the European Parliament",
    "Q3496079 - Czech Republic: member state of the Czech and Slovak Federal Republic (1990–1992)",
    "Q483868 - Czechia men's national football team: men's national association football team representing Czechia",
    "Q1464421 - Czech Republic national under-21 football team: national under-21 association football team representingCzech Republic"
]


Factories

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: Mars_Inc, Factories: In 1963, a large factory was opened inVeghelin theNetherlands. This factory has currently the biggest production volume of Mars factories and is one of the biggest chocolate factories in the world.Most confectionery products for Europe were produced in Slough and Veghel. The two factories in Slough were located on Liverpool Road and Dundee Road; the one on Liverpool Road closed in 2007, with Twix production moving to the Netherlands and Starburst production moving to theCzech Republic. The major production plant for Mars confectionery products in Australia is inBallarat, Victoria. There is one factory outside ofHershey, Pennsylvania, located inElizabethtown, Pennsylvania.The factory inChicago, Illinois, has its own commuter rail station, simply namedMars. The company announced in early 2022 that it intends to close the Chicago factory in 2024.The building will remain in the hands of Chicago's Galewood neighborhood residents.

Mars,_Inc.

Q9874 - Veghel: former municipality in the Netherlands

Q12557060 - Veghel: village in Meierijstad, the Netherlands

Q114224313 - electoral district Veghel: electoral district in the Netherlands (1888-1918)

Q18773215 - Veghel Roman Catholic Churchyard: roman catholic cemetery in Veghel

Q106220344 - Veghel municipal council: None

Mars,_Inc.

Q211907 - Slough: town in Berkshire, England, UK

Q21163036 - Slough: unitary authority area in Berkshire, England

Q7541461 - slough: a wetland, usually a swamp or shallow lake, often a backwater to a larger body of water

Q989007 - Slough: Parliamentary constituency in the United Kingdom, 1983 onwards

Mars,_Inc.

Q1297 - Chicago: city and county seat of Cook County, Illinois, United States of America

Q90437849 - Chicago: vocal track by Frank Sinatra; 1957 studio recording; cover version

Q209636 - Chicago Blackhawks: hockey team of the National Hockey League

Mars,_Inc.

Q1133974 - Elizabethtown: borough in northwestern Lancaster County, Pennsylvania, United States

Mars,_Inc.

Q17856 - Ballarat: regional city in Victoria, Australia

Mars,_Inc.

Q55 - Netherlands: country in Northwestern Europe with territories in the Caribbean

Q29999 - Kingdom of the Netherlands: transcontinental sovereign state and constitutional monarchy

Q476033 - Low Countries: historical coastal landscape in north western Europe

Q16250490 - Netherlands: constituency of the European Parliament

Q170072 - Dutch Republic: predecessor state of the Netherlands (1581–1795)

Mars,_Inc.

Mars,_Inc.

Q213 - Czech Republic: country in Central Europe

Q5201764 - Czech Republic: constituency of the European Parliament

Q3496079 - Czech Republic: member state of the Czech and Slovak Federal Republic (1990–1992)

Q483868 - Czechia men's national football team: men's national association football team representing Czechia

Q1464421 - Czech Republic national under-21 football team: national under-21 association football team representingCzech Republic

Mars,_Inc.

Q30 - United States: country located primarily in North America

Q637413 - United States Census Bureau: U.S. agency responsible for the census and related statistics

Q11703 - United States Virgin Islands: unincorporated territory of the United States of America

Q4917 - United States dollar: official currency of the United States

Q214867 - National Gallery of Art: national art museum in Washington, D.C.

Mars,_Inc.

Q868666 - Hershey: Unincorporated community in Derry Township, Dauphin County, Pennsylvania, United States

Mars,_Inc.

Q3960 - Australian continent: continent in the Earth's Southern Hemisphere

Q104269190 - Australia: unisex given name

Q781542 - Australian Journal of Chemistry: journal

Q167402 - Australian Plant Name Index: online database

Mars,_Inc.

Q53388424 - 1963-1964 one-year-period: period of about one year starting in 1963 and ending in 1964

Q687048 - 1963–64 Fußball-Bundesliga: 1st season of the Bundesliga

Q5760524 - 1963 Costa Rican census: population census in Costa Rica

Mars,_Inc.

Q869733 - Twix: chocolate-coated cookie candy bar

Q2408534 - Twixt: 2011 film directed by Francis Ford Coppola

Q1362781 - TwixT: One of the two-player strategy board games in the 3M bookshelf game series

Mars,_Inc.

Q726611 - starburst galaxy: galaxy undergoing an exceptionally high rate of star formation

Q1186164 - spin-off company: type of organization which is the outcome of a corporate spin-off

Q7601502 - Starburst: British science fiction magazine and webzine

Mars,_Inc.

Q122545378 - Dundee Road Acres: populated place in Cook County, Illinois, United States

Mars,_Inc.

Q6658541 - Liverpool Road: Street in the London Borough of Islington in North London, UK

Q111353731 - Liverpool Road: main road in Sydney

Q83388471 - Liverpool Road Station, Manchester: An historical and architectural survey: book published in 1980

Q7761161 - The Roadrunners: UK musical group

Q6658544 - Liverpool Road Halt railway station: railway station in Staffordshire, England, UK, now closed

Mars,_Inc.

Q124040144 - 2024: 2023 single by Playboi Carti

Q133576379 - 2024: 2025 song by Playboi Carti

Q995653 - 2024 Summer Olympics: games of the XXXIII Olympiad, in Paris, France

Mars,_Inc.

Q695087 - Mars, Incorporated: American global food company and manufacturer

Q134584046 - Mars, Inc.: 2013 novel by Ben Bova

Output: None of the candidates

Output: None of the candidates

Output: None of the candidates


Brands

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: Mars_Inc, Brands: Many Mars products are household, famous-name brands. Some of these product lines are manufactured by Mars; others are manufactured by The Wrigley Company.

[
    "Q695087 - Mars, Incorporated: American global food company and manufacturer",
    "Q134584046 - Mars, Inc.: 2013 novel by Ben Bova"
]

[
    "Q695087 - Mars, Incorporated: American global food company and manufacturer",
    "Q134584046 - Mars, Inc.: 2013 novel by Ben Bova"
]

[
    "Q819241 - Wrigley Company: American company headquartered in Chicago, Illinois"
]