Adidas

Recent years

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: Adidas, Recent years: By the end of 2012, Adidas was reporting their highest revenues ever and Chief Executive Herbert Hainer expressed optimism for the year ahead. Adidas now has global corporate headquarters inHerzogenaurach, Germany and many other business locations around the world such asLondon,Portland,Toronto,Tokyo,Australia,TaiwanandSpain. In January 2015, Adidas launched the footwear industry's first reservation mobile app. The Adidas Confirmed app allows consumers to get access to and reserve the brand's limited edition sneakers by using geo targeting technology. In March 2015, Adidas and McDonald's unveiled the 2015 McDonald's All-American uniforms. For the third year in a row, players will be wearing short-sleeved jerseys, made with the same lightweight and breathable material as the ones used in the NBA. In August 2015, Adidas acquired fitness technology firmRuntasticfor approximately $240 million. In May 2017, Adidas soldTaylorMadegolf company (includingAshworth) to KPS Capital Partners for $425 million. In February 2021, Adidas banned fur from their products, responding to pressure from animal welfare groups. In March 2022, Adidas sold Reebok to theAuthentic Brands Group,for ca. $2.5 billion. In August 2022, the company announced that CEO Kasper Rørsted would step down in 2023.Bjørn Gulden became CEO in January 2023.

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Adidas

Recent years

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: Adidas, Recent years: By the end of 2012, Adidas was reporting their highest revenues ever and Chief Executive Herbert Hainer expressed optimism for the year ahead. Adidas now has global corporate headquarters inHerzogenaurach, Germany and many other business locations around the world such asLondon,Portland,Toronto,Tokyo,Australia,TaiwanandSpain. In January 2015, Adidas launched the footwear industry's first reservation mobile app. The Adidas Confirmed app allows consumers to get access to and reserve the brand's limited edition sneakers by using geo targeting technology. In March 2015, Adidas and McDonald's unveiled the 2015 McDonald's All-American uniforms. For the third year in a row, players will be wearing short-sleeved jerseys, made with the same lightweight and breathable material as the ones used in the NBA. In August 2015, Adidas acquired fitness technology firmRuntasticfor approximately $240 million. In May 2017, Adidas soldTaylorMadegolf company (includingAshworth) to KPS Capital Partners for $425 million. In February 2021, Adidas banned fur from their products, responding to pressure from animal welfare groups. In March 2022, Adidas sold Reebok to theAuthentic Brands Group,for ca. $2.5 billion. In August 2022, the company announced that CEO Kasper Rørsted would step down in 2023.Bjørn Gulden became CEO in January 2023.

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"hasProductLine", "S.S._Chieti"], ["Adidas", "hasProductLine", "A.S._Gubbio_1910"], ["Adidas", "hasProductLine", "A.S._Delfino_Pescara_1936"], ["Adidas", "hasProductLine", "U.C._Sampdoria"], ["Adidas", "hasProductLine", "A.C._Fiori"], ["Adidas", "hasProductLine", "A.C._Siena"], ["Adidas", "hasProductLine", "A.S._Livorno_Calcio"], ["Adidas", "hasProductLine", "S.S._Chieti"], ["Adidas", "hasProductLine", "A.S._Gubbio_1910"], ["Adidas", "hasProductLine", "A.S._Delfino_Pescara_1936"], ["Adidas", "hasProductLine", "U.C._Sampdoria"], ["Adidas", "hasProductLine", "A.C._Fiori"], ["Adidas", "hasProductLine", "A.C._Siena"], ["Adidas", "hasProductLine", "A.S._Livorno_Calcio"], ["Adidas", "hasProductLine", "S.S._Chieti"], ["Adidas", "hasProductLine", "A.S._Gubbio_1910"], ["Adidas", "hasProductLine", "A.S._Delfino_Pescara_1936"], ["Adidas", "hasProductLine", "U.C._Sampdoria"], ["Adidas", "hasProductLine", "A.C._Fiori"], ["Adidas", "hasProductLine", "A.C._Siena"], ["Adidas", "hasProductLine", "A.S._Livorno_Calcio"], ["Adidas", "hasProductLine", "S.S._Chieti"], ["Adidas", "hasProductLine", "A.S._Gubbio_1910"], ["Adidas", "hasProductLine", "A.S._Delfino_Pescara_1936"], ["Adidas", "hasProductLine", "U.C._Sampdoria"], ["Adidas", "hasProductLine", "A.C._Fiori"], ["Adidas", "hasProductLine", "A.C._Siena"], ["Adidas", "hasProductLine", "A.S._Livorno_Calcio"], ["Adidas", "hasProductLine", "S.S._Chieti"], ["Adidas", "hasProductLine", "A.S._Gubbio_1910"], ["Adidas", "hasProductLine", "A.S._Delfino_Pescara_1936"], ["Adidas", "hasProductLine", "U.C._Sampdoria"], ["Adidas", "hasProductLine", "A.C._Fiori"], ["Adidas", "hasProductLine", "A.C._Siena"], ["Adidas", "hasProductLine", "A.S._Livorno_Calcio"], ["Adidas", "hasProductLine", "S.S._Chieti"], ["Adidas", "hasProductLine", "A.S._Gubbio_1910"], ["Adidas", "hasProductLine", "A.S._Delfino_Pescara_1936"], ["Adidas", "hasProductLine", "U.C._Sampdoria"], ["Adidas", "hasProductLine", "A.C._Fiori"], ["Adidas", "hasProductLine", "A.C._Siena"], ["Adidas", "hasProductLine", "A.S._Livorno_Calcio"], ["Adidas", "hasProductLine", "S.S._Chieti"], ["Adidas", "hasProductLine", "A.S._Gubbio_1910"], ["Adidas", "hasProductLine", "A.S._Delfino_Pescara_1936"], ["Adidas", "hasProductLine", "U.C._Sampdoria"], ["Adidas", "hasProductLine", "A.C._Fiori"], ["Adidas", "hasProductLine", "A.C._Siena"], ["Adidas", "hasProductLine", "A.S._Livorno_Calcio"], ["Adidas", "hasProductLine", "S.S._Chieti"], ["Adidas", "hasProductLine", "A.S._Gubbio_1910"], ["Adidas", "hasProductLine", "A.S._Delfino_Pescara_1936"], ["Adidas", "hasProductLine", "U.C._Sampdoria"], ["Adidas", "hasProductLine", "A.C._Fiori"], ["Adidas", "hasProductLine", "A.C._Siena"], ["Adidas", "hasProductLine", "A.S._Livorno_Calcio"], ["Adidas", "hasProductLine", "S.S._Chieti"], ["Adidas", "hasProductLine", "A.S._Gubbio_1910"], ["Adidas", "hasProductLine", "A.S._Delfino_Pescara_1936"], ["Adidas", "hasProductLine", "U.C._Sampdoria"], ["Adidas", "hasProductLine", "A.C._Fiori"], ["Adidas", "hasProductLine", "A.C._Siena"], ["Adidas", "hasProductLine", "A.S._Livorno_Calcio"], ["Adidas", "hasProductLine", "S.S._Chieti"], ["Adidas", "hasProductLine", "A.S._Gubbio_1910"], ["Adidas", "hasProductLine", "A.S._Delfino_Pescara_1936"], ["Adidas", "hasProductLine", "U.C._Sampdoria"], ["Adidas", "hasProductLine", "A.C._Fiori"], ["Adidas", "hasProductLine", "A.C._Siena"], ["Adidas", "hasProductLine", "A.S._Livorno_Calcio"], ["Adidas", "hasProductLine", "S.S._Chieti"], ["Adidas", "hasProductLine", "A.S._Gubbio_1910"], ["Adidas", "hasProductLine", "A.S._Delfino_Pescara_1936"], ["Adidas", "hasProductLine", "U.C._Sampdoria"], ["Adidas", "hasProductLine", "A.C._Fiori"], ["Adidas", "hasProductLine", "A.C._Siena"], ["Adidas", "hasProductLine", "A.S._Livorno_Calcio"], ["Adidas", "hasProductLine", "S.S._Chieti"], ["Adidas", "hasProductLine", "A.S._Gubbio_1910"], ["Adidas", "hasProductLine", "A.S._Delfino_Pescara_1936"], ["Adidas", "hasProductLine", "U.C._Sampdoria"], ["Adidas", "hasProductLine", "A.C._Fiori"], ["Adidas", "hasProductLine", "A.C._Siena"], ["Adidas", "hasProductLine", "A.S._Livorno_Calcio"], ["Adidas", "hasProductLine", "S.S._Chieti"], ["Adidas", "hasProductLine", "A.S._Gubbio_1910"], ["Adidas", "hasProductLine", "A.S._Delfino_Pescara_1936"], ["Adidas", "hasProductLine", "U.C._Sampdoria"], ["Adidas", "hasProductLine", "A.C._Fiori"], ["Adidas", "hasProductLine", "A.C._Siena"], ["Adidas", "hasProductLine", "A.S._Livorno_Calcio"], ["Adidas", "hasProductLine", "S.S._Chieti"], ["Adidas", "hasProductLine", "A.S._Gubbio_1910"], ["Adidas", "hasProductLine", "A.S._Delfino_Pescara_1936"], ["Adidas", "hasProductLine", "U.C._Sampdoria"], ["Adidas", "hasProductLine", "A.C._Fiori"], ["Adidas", "hasProductLine", "A.C._Siena"], ["Adidas", "hasProductLine", "A.S._Livorno_Calcio"], ["Adidas", "hasProductLine", "S.S._Chieti"], ["Adidas", "hasProductLine", "A.S._Gubbio_1910"], ["Adidas", "hasProductLine", "A.S._Delfino_Pescara_1936"], ["Adidas", "hasProductLine", "U.C._Sampdoria"], ["Adidas", "hasProductLine", "A.C._Fiori"], ["Adidas", "hasProductLine", "A.C._Siena"], ["Adidas", "hasProductLine", "A.S._Livorno_Calcio"], ["Adidas", "hasProductLine", "S.S._Chieti"], ["Adidas", "hasProductLine", "A.S._Gubbio_1910"], ["Adidas", "hasProductLine", "A.S._Delfino_Pescara_1936"], ["Adidas", "hasProductLine", "U.C._Sampdoria"], ["Adidas", "hasProductLine", "A.C._Fiori"], ["Adidas", "hasProductLine", "A.C._Siena"], ["Adidas", "hasProductLine", "A.S._Livorno_Calcio"], ["Adidas", "hasProductLine", "S.S._Chieti"], ["Adidas", "hasProductLine", "A.S._Gubbio_1910"], ["Adidas", "hasProductLine", "A.S._Delfino_Pescara_1936"], ["Adidas", "hasProductLine", "U.C._Sampdoria"], ["Adidas", "hasProductLine", "A.C._Fiori"], ["Adidas", "hasProductLine", "A.C._Siena"], ["Adidas", "hasProductLine", "A.S._Livorno_Calcio"], ["Adidas", "hasProductLine", "S.S._Chieti"], ["Adidas", "hasProductLine", "A.S._Gubbio_1910"], ["Adidas", "hasProductLine", "A.S._Delfino_Pescara_1936"], ["Adidas", "hasProductLine", "U.C._Sampdoria"], ["Adidas", "hasProductLine", "A.C._Fiori"], ["Adidas", "hasProductLine", "A.C._Siena"], ["Adidas", "hasProductLine", "A.S._Livorno_Calcio"], ["Adidas", "hasProductLine", "S.S._Chieti"], ["Adidas", "hasProductLine", "A.S._Gubbio_1910"], ["Adidas", "hasProductLine", "A.S._Delfino_Pescara_1936"], ["Adidas", "hasProductLine", "U.C._Sampdoria"], ["Adidas", "hasProductLine", "A.C._Fiori"], ["Adidas", "hasProductLine", "A.C._Siena"], ["Adidas", "hasProductLine", "A.S._Livorno_Calcio"], ["Adidas", "hasProductLine", "S.S._Chieti"], ["Adidas", "hasProductLine", "A.S._Gubbio_1910"], ["Adidas", "hasProductLine", "A.S._Delfino_Pescara_1936"], ["Adidas", "hasProductLine", "U.C._Sampdoria"], ["Adidas", "hasProductLine", "A.C._Fiori"], ["Adidas", "hasProductLine", "A.C._Siena"], ["Adidas", "hasProductLine", "A.S._Livorno_Calcio"], ["Adidas", "hasProductLine", "S.S._Chieti"], ["Adidas", "hasProductLine", "A.S._Gubbio_1910"], ["Adidas", "hasProductLine", "A.S._Delfino_Pescara_1936"], ["Adidas", "hasProductLine", "U.C._Sampdoria"], ["Adidas", "hasProductLine", "A.C._Fiori"], ["Adidas", "hasProductLine", "A.C._Siena"], ["Adidas", "hasProductLine", "A.S._Livorno_Calcio"], ["Adidas", "hasProductLine", "S.S._Chieti"], ["Adidas", "hasProductLine", "A.S._Gubbio_1910"], ["Adidas", "hasProductLine", "A.S._Delfino_Pescara_1936"], ["Adidas", "hasProductLine", "U.C._Sampdoria"], ["Adidas", "hasProductLine", "A.C._Fiori"], ["Adidas", "hasProductLine", "A.C._Siena"], ["Adidas", "hasProductLine", "A.S._Livorno_Calcio"], ["Adidas", "hasProductLine", "S.S._Chieti"], ["Adidas", "hasProductLine", "A.S._Gubbio_1910"], ["Adidas", "hasProductLine", "A.S._Delfino_Pescara_1936"], ["Adidas", "hasProductLine", "U.C._Sampdoria"], ["Adidas", "hasProductLine", "A.C._Fiori"], ["Adidas", "hasProductLine", "A.C._Siena"], ["Adidas", "hasProductLine", "A.S._Livorno_Calcio"], ["Adidas", "hasProductLine", "S.S._Chieti"], ["Adidas", "hasProductLine", "A.S._Gubbio_1910"], ["Adidas", "hasProductLine", "A.S._Delfino_Pescara_1936"], ["Adidas", "hasProductLine", "U.C._Sampdoria"], ["Adidas", "hasProductLine", "A.C._Fiori"], ["Adidas", "hasProductLine", "A.C._Siena"], ["Adidas", "hasProductLine", "A.S._Livorno_Calcio"], ["Adidas", "hasProductLine", "S.S._Chieti"], ["Adidas", "hasProductLine", "A.S._Gubbio_1910"], ["Adidas", "hasProductLine", "A.S._Delfino_Pescara_1936"], ["Adidas", "hasProductLine", "U.C._Sampdoria"], ["Adidas", "hasProductLine", "A.C._Fiori"], ["Adidas", "hasProductLine", "A.C._Siena"], ["Adidas", "hasProductLine", "A.S._Livorno_Calcio"], ["Adidas", "hasProductLine", "S.S._Chieti"], ["Adidas", "hasProductLine", "A.S._Gubbio_1910"], ["Adidas", "hasProductLine", "A.S._Delfino_Pescara_1936"], ["Adidas", "hasProductLine", "U.C._Sampdoria"], ["Adidas", "hasProductLine", "A.C._Fiori"], ["Adidas", "hasProductLine", "A.C._Siena"], ["Adidas", "hasProductLine", "A.S._Livorno_Calcio"], ["Adidas", "hasProductLine", "S.S._Chieti"], ["Adidas", "hasProductLine", "A.S._Gubbio_1910"], ["Adidas", "hasProductLine", "A.S._Delfino_Pescara_1936"], ["Adidas", "hasProductLine", "U.C._Sampdoria"], ["Adidas", "hasProductLine", "A.C._Fiori"], ["Adidas", "hasProductLine", "A.C._Siena"], ["Adidas", "hasProductLine", "A.S._Livorno_Calcio"], ["Adidas", "hasProductLine", "S.S._Chieti"], ["Adidas", "hasProductLine", "A.S._Gubbio_1910"], ["Adidas", "hasProductLine", "A.S._Delfino_Pescara_1936"], ["Adidas", "hasProductLine", "U.C._Sampdoria"], ["Adidas", "hasProductLine", "A.C._Fiori"], ["Adidas", "hasProductLine", "A.C._Siena"], ["Adidas", "hasProductLine", "A.S._Livorno_Calcio"], ["Adidas", "hasProductLine", "S.S._Chieti"], ["Adidas", "hasProductLine", "A.S._Gubbio_1910"], ["Adidas", "hasProductLine", "A.S._Delfino_Pescara_1936"], ["Adidas", "hasProductLine", "U.C._Sampdoria"], ["Adidas", "hasProductLine", "A.C._Fiori"], ["Adidas", "hasProductLine", "A.C._Siena"], ["Adidas", "hasProductLine", "A.S._Livorno_Calcio"], ["Adidas", "hasProductLine", "S.S._Chieti"], ["Adidas", "hasProductLine", "A.S._Gubbio_1910"], ["Adidas", "hasProductLine", "A.S._Delfino_Pescara_1936"], ["Adidas", "hasProductLine", "U.C._Sampdoria"], ["Adidas", "hasProductLine", "A.C._Fiori"], ["Adidas", "hasProductLine", "A.C._Siena"], ["Adidas", "hasProductLine", "A.S._Livorno_Calcio"], ["Adidas", "hasProductLine", "S.S._Chieti"], ["Adidas", "hasProductLine", "A.S._Gubbio_1910"], ["Adidas", "hasProductLine", "A.S._Delfino_Pescara_1936"], ["Adidas", "hasProductLine", "U.C._Sampdoria"], ["Adidas", "hasProductLine", "A.C._Fiori"], ["Adidas", "hasProductLine", "A.C._Siena"], ["Adidas", "hasProductLine", "A.S._Livorno_Calcio"], ["Adidas", "hasProductLine", "S.S._Chieti"], ["Adidas", "hasProductLine", "A.S._Gubbio_1910"], ["Adidas", "hasProductLine", "A.S._Delfino_Pescara_1936"], ["Adidas", "hasProductLine", "U.C._Sampdoria"], ["Adidas", "hasProductLine", "A.C._Fiori"], ["Adidas", "hasProductLine", "A.C._Siena"], ["Adidas", "hasProductLine", "A.S._Livorno_Calcio"], ["Adidas", "hasProductLine", "S.S._Chieti"], ["Adidas", "hasProductLine", "A.S._Gubbio_1910"], ["Adidas", "hasProductLine", "A.S._Delfino_Pescara_1936"], ["Adidas", "hasProductLine", "U.C._Sampdoria"], ["Adidas", "hasProductLine", "A.C._Fiori"], ["Adidas", "hasProductLine", "A.C._Siena"], ["Adidas", "hasProductLine", "A.S._Livorno_Calcio"], ["Adidas", "hasProductLine", "S.S._Chieti"], ["Adidas", "hasProductLine", "A.S._Gubbio_1910"], ["Adidas", "hasProductLine", "A.S._Delfino_Pescara_1936"], ["Adidas", "hasProductLine", "U.C._Sampdoria"], ["Adidas", "hasProductLine", "A.C._Fiori"], ["Adidas", "hasProductLine", "A.C._Siena"], ["Adidas", "hasProductLine", "A.S._Livorno_Calcio"], ["Adidas", "hasProductLine", "S.S._Chieti"], ["Adidas", "hasProductLine", "A.S._Gubbio_1910"], ["Adidas", "hasProductLine", "A.S._Delfino_Pescara_1936"], ["Adidas", "hasProductLine", "U.C._Sampdoria"], ["Adidas", "hasProductLine", "A.C._Fiori"], ["Adidas", "hasProductLine", "A.C._Siena"], ["Adidas", "hasProductLine", "A.S._Livorno_Calcio"], ["Adidas", "hasProductLine", "S.S._Chieti"], ["Adidas", "hasProductLine", "A.S._Gubbio_1910"], ["Adidas", "hasProductLine",


Adidas

Business trends

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: Adidas, Business trends: The key trends for Adidas are (as at the financial year ending December 31):

[["Adidas", "Company"], ["\"The key trends for Adidas are\"", "BusinessTrend"], ["\"as at the financial year ending December 31\"", "Date"]]


Adidas

Business trends

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: Adidas, Business trends: The key trends for Adidas are (as at the financial year ending December 31):


Adidas

Apparel

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: Adidas, Apparel: Adidas manufactures a range ofclothingitems, varying from men's and women'st-shirts,jackets,hoodies,pantsandleggings. The first Adidas item of apparel was theFranz Beckenbauertracksuit created in 1967.Adidas AG is the largest manufacturer of sports bras in Europe, and the second largest manufacturer in the world.

[["Adidas", "Company"], ["Sports_bra", "Product"], ["\"Europe's largest and the world's second largest manufacturer\"", "string"], ["Adidas_Ag", "Company"], ["Franz_Beckenbauer_tracksuit", "Product"], ["1967", "Year"], ["Adidas", "Product"], ["\"Men's and women's t-shirts, jackets, hoodies, pants, leggings\"", "Product"]]


Adidas

Apparel

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: Adidas, Apparel: Adidas manufactures a range ofclothingitems, varying from men's and women'st-shirts,jackets,hoodies,pantsandleggings. The first Adidas item of apparel was theFranz Beckenbauertracksuit created in 1967.Adidas AG is the largest manufacturer of sports bras in Europe, and the second largest manufacturer in the world.

[["Adidas", "manufactures", "Sports_bra"], ["Adidas", "has_product_line", "Clothing"], ["Adidas", "has_product_line", "T-shirt"], ["Adidas", "has_product_line", "Jacket"], ["Adidas", "has_product_line", "Hoodie"], ["Adidas", "has_product_line", "Pants"], ["Adidas", "has_product_line", "Legging"], ["Adidas", "launched_product", "Franz_Beckenbauer_tracksuit"], ["Adidas", "in_year", "1967"], ["Adidas", "has_product_line", "Men's_clothing"], ["Adidas", "has_product_line", "Women's_clothing"], ["Adidas", "market_value_of", "\"Europe's largest manufacturer of sports bras, the second largest in the world\""]]