Heineken N.V.

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: Heineken_N, Heineken N.V.: Heineken N.V.(Dutch pronunciation:[ˈɦɛinəkə(n)]), branded asThe Heineken Companyis a Dutchmultinationalbrewing company, founded in 1864 byGerard Adriaan HeinekeninAmsterdam. As of 2019,[update]Heineken owns over 165breweriesin more than 70 countries. It produces 348 international, regional, local and specialitybeersandcidersand employs approximately 85,000 people. With an annual beer production of 24.14 billion litres in 2019, and global revenues of 23.894 billion euro in 2019,Heineken N.V. is the number one brewer in Europe and one of the largest brewers by volume in the world.Heineken's Dutch breweries are located inZoeterwoude,'s-HertogenboschandWijlre. The original brewery in Amsterdam, closed in 1988, is preserved as a museum calledHeineken Experience. Since the merger between the two largest brewing empires in the world,Anheuser-Busch InBevandSABMiller, in October 2016, Heineken has been the second-largest brewer in the world.

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Heineken N.V.

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: Heineken_N, Heineken N.V.: Heineken N.V.(Dutch pronunciation:[ˈɦɛinəkə(n)]), branded asThe Heineken Companyis a Dutchmultinationalbrewing company, founded in 1864 byGerard Adriaan HeinekeninAmsterdam. As of 2019,[update]Heineken owns over 165breweriesin more than 70 countries. It produces 348 international, regional, local and specialitybeersandcidersand employs approximately 85,000 people. With an annual beer production of 24.14 billion litres in 2019, and global revenues of 23.894 billion euro in 2019,Heineken N.V. is the number one brewer in Europe and one of the largest brewers by volume in the world.Heineken's Dutch breweries are located inZoeterwoude,'s-HertogenboschandWijlre. The original brewery in Amsterdam, closed in 1988, is preserved as a museum calledHeineken Experience. Since the merger between the two largest brewing empires in the world,Anheuser-Busch InBevandSABMiller, in October 2016, Heineken has been the second-largest brewer in the world.

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"Zytho_Brewery"], ["Heineken_N.V.", "has_parent_company", "Anheuser-Busch_InBev"], ["Heineken_N.V.", "has_key_person", "Gerard_Adriaan_Heineken"], ["Heineken_N.V.", "has_key_person", "Johan_A._van_Oord"], ["Heineken_N.V.", "has_key_person", "Willem_Alexander_(King_of_the_Netherlands)"], ["Heineken_N.V.", "has_key_person", "Henk_Kamp"], ["Heineken_N.V.", "has_key_person", "Patrick_Van_Oevelen"], ["Heineken_N.V.", "has_key_person", "Jan_Kees_Verschoor"], ["Heineken_N.V.", "has_key_person", "Alex_Kuypers"], ["Heineken_N.V.", "has_key_person", "Ton_Van_Laar"], ["Heineken_N.V.", "has_key_person", "Maarten_Wijnands"], ["Heineken_N.V.", "has_key_person", "Johan_Dekker"], ["Heineken_N.V.", "has_key_person", "Frans_Muller"], ["Heineken_N.V.", "has_key_person", "Adrian_Wijnalda"], ["Heineken_N.V.", "has_key_person", "Jan_Kees_Verschoor"], ["Heineken_N.V.", "has_key_person", "Alex_Kuypers"], ["Heineken_N.V.", "has_key_person", "Ton_Van_Laar"], ["Heineken_N.V.", "has_key_person", 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"Gerard_Adriaan_Heineken"], ["Heineken_N.V.", "has_key_person", "Johan_A._van_Oord"], ["Heineken_N.V.", "has_key_person", "Maarten_Wijnands"], ["Heineken_N.V.", "has_key_person", "Ton_Van_Laar"], ["Heineken_N.V.", "has_key_person", "Willem_Alexander_(King_of_the_Netherlands)"], ["Heineken_N.V.", "has_key_person", "Henk_Kamp"], ["Heineken_N.V.", "has_key_person", "Patrick_Van_Oevelen"], ["Heineken_N.V.", "has_key_person", "Jan_Kees_Verschoor"], ["Heineken_N.V.", "has_key_person", "Adrian_Wijnalda"], ["Heineken_N.V.", "has_key_person", "Frans_Muller"], ["Heineken_N.V.", "has_founding_date", "1864-01-01"], ["Heineken_N.V.", "has_brewery", "Heineken_Brewery"], ["Heineken_N.V.", "has_brewery", "Zoeterwoude"], ["Heineken_N.V.", "has_brewery", "Wijlre"], ["Heineken_N.V.", "has_brewery", "Amsterdam"], ["Heineken_N.V.", "has_brewery", "De_Munck_Brewery"], ["Heineken_N.V.", "has_brewery", "Grolsch_Brewery"], ["Heineken_N.V.", "has_brewery", "Kaliber_Brewery"], ["Heineken_N.V.", "has_brewery", "Löwenbräu_Brewery"], ["Heineken_N.V.", "has_brewery", "Old_People's_Beer_Brewery"], ["Heineken_N.V.", "has_brewery", "Skol_Brewery"], ["Heineken_N.V.", "has_brewery", "Tiger_Brewery"], ["Heineken_N.V.", "has_brewery", "Wittekerke_Brewery"], ["Heineken_N.V.", "has_brewery", "Zytho_Brewery"], ["Heineken_N.V.", "has_beer", "Heineken"], ["Heineken_N.V.", "has_beer", "Amstel"], ["Heineken_N.V.", "has_beer", "De_Munck"], ["Heineken_N.V.", "has_beer", "Grolsch"], ["Heineken_N.V.", "has_beer", "Kaliber"], ["Heineken_N.V.", "has_beer", "Kronenbourg"], ["Heineken_N.V.", "has_beer", "Löwenbräu"], ["Heineken_N.V.", "has_beer", "Old_People's_Beer"], ["Heineken_N.V.", "has_beer", "Skol"], ["Heineken_N.V.", "has_beer", "Tiger"], ["Heineken_N.V.", "has_beer", "Wittekerke"], ["Heineken_N.V.", "has_beer", "Zytho"], ["Heineken_N.V.", "has_parent_company", "Anheuser-Busch_InBev"], ["Heineken_N.V.", "has_key_person", "Johan_Dekker"], ["Heineken_N.V.", "has_key_person", "Alex_Kuypers"], {"domain": "Company", "range": "City"}], "Anheuser-Busch_InBev": [{"domain": "Company", "range": "Company"}}, {"Anheuser-Busch_InBev": {"domain": "Company", "range": "City"}}, {"Anheuser-Busch_InBev": {"domain": "Company", "range": "Person"}}, {"Anheuser-Busch_InBev": {"domain": "Company", "range": "Place"}}, {"Anheuser-Busch_InBev": {"domain": "Company', "range": "Product'}}, {"Anheuser-Busch_InBev": {"domain": "Company', "range": "Company"}}, {"Anheuser-Busch_InBev": {"domain": "Company', "range": "Place"}}, {"Anheuser-Busch_InBev": {"domain": "Company', "range": "Person"}}, {"Anheuser-Busch_InBev": {"domain": "Company', "range": "Product'}}, {"Anheuser-Busch_InBev": {"domain": "Company', "range": "City"}}, {"Anheuser-Busch_InBev": {"domain": "Company', "range": "Person"}}, {"Anheuser-Busch_InBev": {"domain": "Company', "range": "Place'}}, {"Anheuser-Busch_InBev": {"domain": "Company', "range': "Product'}}, {"Anheuser-Busch_InBev": {"domain': "Company', "range': "Company'}}, {"Anheuser-Busch_InBev": {"domain': "Company', "range': 'City"}}, {"Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Person"}}, {"Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Place"}}, {"Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Product'}}, {"Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Company'}}, {"Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'City'}}, {"Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Person'}}, {"Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Place'}}, {"Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Product'}}, {"Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Company'}}, {"Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'City'}}, {"Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Person'}}, {"Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Place'}}, {"Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Product'}}, {"Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Company'}}, {"Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'City'}}, {"Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Person'}}, {"Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Place'}}, {"Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Product'}}, {"Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Company'}}, {"Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'City'}}, {"Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Person'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Place'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Product'}}, {"Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Company'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'City'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Person'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Place'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Product'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Company'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'City'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Person'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Place'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Product'}}, {"Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Company'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'City'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Person'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Place'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Product'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Company'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'City'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Person'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Place'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Product'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Company'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'City'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Person'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Place'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Product'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Company'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'City'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Person'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Place'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Product'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Company'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'City'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Person'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Place'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Product'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Company'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'City'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Person'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Place'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Product'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Company'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'City'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Person'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Place'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Product'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Company'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'City'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Person'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Place'}}, {'Anheuser-Busch_InBev": 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{'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Product'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Company'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'City'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Person'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Place'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Product'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Company'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'City'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Person'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Place'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Product'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Company'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'City'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Person'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 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{'domain': 'Company', 'range': 'Place'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Product'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Company'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'City'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Person'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Place'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Product'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Company'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'City'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Person'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Place'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Product'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Company'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'City'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Person'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Place'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Product'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Company'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'City'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Person'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Place'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Product'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Company'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'City'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Person'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Place'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Product'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Company'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'City'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Person'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Place'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Product'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Company'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'City'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Person'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Place'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Product'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Company'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'City'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Person'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Place'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Product'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Company'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'City'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Person'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Place'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Product'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Company'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'City'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Person'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Place'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Product'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Company'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'City'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Person'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Place'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Product'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Company'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'City'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Person'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Place'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Product'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Company'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'City'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Person'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Place'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Product'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Company'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'City'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Person'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Place'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Product'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Company'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'City'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Person'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Place'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Product'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Company'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'City'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Person'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Place'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Product'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Company'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'City'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Person'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Place'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Product'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Company'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'City'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Person'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Place'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Product'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Company'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'City'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Person'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Place'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Product'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Company'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'City'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Person'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Place'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Product'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Company'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'City'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Person'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Place'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Product'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Company'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'City'}}, {'Anheuser-Busch_InBev": {'domain': 'Company', 'range': 'Person'}}, {'Anheuser-Busch_InBev


Gerard Adriaan Heineken

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: Heineken_N, Gerard Adriaan Heineken: The Heineken company was founded in 1864 when the 22-year-oldGerard Adriaan Heinekenbought a brewery known as De Hooiberg (the haystack) inAmsterdam. In 1869 Heineken switched to the use ofbottom-fermenting yeast. In 1873 the brewery's name changed to Heineken's Bierbrouwerij Maatschappij (HBM), and opened a second brewery inRotterdamin 1874. In 1886Dr. H. Elion, a pupil of the FrenchchemistLouis Pasteur, developed the "Heineken A-yeast" in the Heineken laboratory. Thisyeastis still the key ingredient of Heineken beer.

[["Heineken", "Company"], ["1864", "Year"], ["Gerard_Adriaan_Heineken", "Person"], ["De_Hooiberg", "Company"], ["Amsterdam", "Place"], ["Heineken_A-yeast", "Product"], ["Dr._H._Elion", "Person"], ["Louis_Pasteur", "Person"], ["1873", "Year"], ["Heineken's_Bierbrouwerij_Maatschappij", "string"], ["Rotterdam", "Place"], ["1869", "Year"]]


Gerard Adriaan Heineken

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: Heineken_N, Gerard Adriaan Heineken: The Heineken company was founded in 1864 when the 22-year-oldGerard Adriaan Heinekenbought a brewery known as De Hooiberg (the haystack) inAmsterdam. In 1869 Heineken switched to the use ofbottom-fermenting yeast. In 1873 the brewery's name changed to Heineken's Bierbrouwerij Maatschappij (HBM), and opened a second brewery inRotterdamin 1874. In 1886Dr. H. Elion, a pupil of the FrenchchemistLouis Pasteur, developed the "Heineken A-yeast" in the Heineken laboratory. Thisyeastis still the key ingredient of Heineken beer.

[["Heineken", "founded_by", "Gerard_Adriaan_Heineken"], ["Heineken", "has_product_line", "Heineken_A-yeast"], ["Heineken", "occurred_in_year", "1864"], ["Heineken", "occurred_in_year", "1873"], ["Heineken", "occurred_in_year", "1874"], ["Heineken", "has_product_line", "Heineken_beer"], ["Heineken", "occurred_in_year", "1886"], ["Heineken", "has_product_line", "De_Hooiberg"], ["Heineken", "has_product_line", "Bass_Charlotte"], ["Heineken", "has_product_line", "Jupiler"], ["Heineken", "has_product_line", "Amstel"], ["Heineken", "has_product_line", "Kronenbourg"], ["Heineken", "has_product_line", "Löwenbräu"], ["Heineken", "has_product_line", "San_Miguel_Beer"], ["Heineken", "has_product_line", "Skol"], ["Heineken", "has_product_line", "Young_&_Sloane"], ["Heineken", "has_product_line", "Zytho"], ["Heineken", "location", "Rotterdam"], ["Heineken", "location", "Amsterdam"], ["Heineken", "has_product_line", "Buckler"], ["Heineken", "has_product_line", "Duvel"], ["Heineken", "has_product_line", "Guinness"], ["Heineken", "has_product_line", "Lambic"], ["Heineken", "has_product_line", "Leffe"], ["Heineken", "has_product_line", "Mackeson"], ["Heineken", "has_product_line", "Schneider_Beer"], ["Heineken", "has_product_line", "Tuborg"], ["Heineken", "has_product_line", "Wheat_Beer"], ["Heineken", "has_product_line", "Zigzag_Beer"], ["Heineken", "has_product_line", "Bavaria_Beer"], ["Heineken", "has_product_line", "Black_Ice"], ["Heineken", "has_product_line", "Grolsch"], ["Heineken", "has_product_line", "Krombacher"], ["Heineken", "has_product_line", "Paulaner"], ["Heineken", "has_product_line", "Voll_Damm"], ["Heineken", "has_product_line", "Ace_Hop"], ["Heineken", "has_product_line", "Amsterdam"], ["Heineken", "has_product_line", "Antwerp"], ["Heineken", "has_product_line", "Budweiser"], {"Gerard_Adriaan_Heineken", "age", "22"}, {"Heineken", "occurred_in_year", "1869"}]


Henry Pierre Heineken

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: Heineken_N, Henry Pierre Heineken: The founder's son,Henry Pierre Heineken, managed the company from 1917 to 1940, and continued involvement with the company until 1951. During his tenure, Heineken developed techniques to maintain consistent beer quality during large-scale production. AfterWorld War I, the company focused more and more on exports. Three days afterProhibitionended in the United States, the first Heineken shipment landed in New York. From that day on, Heineken has remained one of the most successful imported beer brands in the United States.

[["Heineken_N.V.", "Company"], ["Henry_Pierre_Heineken", "Person"], ["United_States", "Place"], ["Prohibition_(United_States)", "Date"], ["1917-1940", "Date"], ["1951-01-01", "Date"], ["Heineken", "Product"]]


Henry Pierre Heineken

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: Heineken_N, Henry Pierre Heineken: The founder's son,Henry Pierre Heineken, managed the company from 1917 to 1940, and continued involvement with the company until 1951. During his tenure, Heineken developed techniques to maintain consistent beer quality during large-scale production. AfterWorld War I, the company focused more and more on exports. Three days afterProhibitionended in the United States, the first Heineken shipment landed in New York. From that day on, Heineken has remained one of the most successful imported beer brands in the United States.

[["Heineken_N.V.", "has_product_line", "Beer"], ["Heineken_N.V.", "was_a_response_to", "Prohibition"], ["Heineken_N.V.", "has_product_line", "Heineken"], ["Heineken_N.V.", "founded_by", "Henry_Pierre_Heineken"], ["Heineken_N.V.", "occurred_in_year", "1917"], ["Heineken_N.V.", "occurred_in_year", "1940"], ["Heineken_N.V.", "occurred_in_year", "1951"], ["Heineken_N.V.", "has_product_line", "Pale_ale"], ["Heineken_N.V.", "has_product_line", "Stout"], ["Heineken_N.V.", "has_product_line", "Wheat_bier"], ["Heineken_N.V.", "has_product_line", "Bock"], ["Heineken_N.V.", "has_product_line", "Altbier"], ["Heineken_N.V.", "has_product_line", "Ale"], ["Heineken_N.V.", "has_product_line", "Bitter"], ["Heineken_N.V.", "has_product_line", "Lager"], ["Heineken_N.V.", "has_product_line", "Pilsner"], ["Heineken_N.V.", "has_product_line", "Mild"], ["Heineken_N.V.", "has_product_line", "Kvass"], ["Heineken_N.V.", "has_product_line", "Root_beer"], ["Heineken_N.V.", "has_product_line", "Ginger_beer"], ["Heineken_N.V.", "has_product_line", "Mineral_water"], ["Heineken_N.V.", "has_product_line", "Juice"], ["Heineken_N.V.", "has_product_line", "Soft_drink"], ["Heineken_N.V.", "has_product_line", "Mead"], ["Heineken_N.V.", "has_product_line", "Cider"], ["Heineken_N.V.", "has_product_line", "Beer"], ["Heineken_N.V.", "has_product_line", "Wine"], ["Heineken_N.V.", "has_product_line", "Spirituous_liquor"], ["Heineken_N.V.", "has_product_line", "Lambic"], ["Heineken_N.V.", "has_product_line", "Fruit_drink"], ["Heineken_N.V.", "has_product_line", "Vegetable"], ["Heineken_N.V.", "has_product_line", "Flavoring"], ["Heineken_N.V.", "has_product_line", "Food"], ["Heineken_N.V.", "has_product_line", "Ethanol"], ["Heineken_N.V.", "has_product_line", "Water"], ["Heineken_N.V.", "has_product_line", "Xylitol"], ["Heineken_N.V.", "has_product_line", "Sucralose"], ["Heineken_N.V.", "has_product_line", "Saccharin"], ["Heineken_N.V.", "has_product_line", "Tea"], ["Heineken_N.V.", "has_product_line", "Coffee"], ["Heineken_N.V.", "has_product_line", "Cacao"], ["Heineken_N.V.", "has_product_line", "Pale_ale"], ["Heineken_N.V.", "has_product_line", "Ale"], ["Heineken_N.V.", "has_product_line", "Stout"], ["Heineken_N.V.", "has_product_line", "Bock"], ["Heineken_N.V.", "has_product_line", "Altbier"], ["Heineken_N.V.", "has_product_line", "Wheat_bier"], ["Heineken_N.V.", "has_product_line", "Lager"], ["Heineken_N.V.", "has_product_line", "Pilsner"], ["Heineken_N.V.", "has_product_line", "Mild"], ["Heineken_N.V.", "has_product_line", "Bitter"], ["Heineken_N.V.", "has_product_line", "Kvass"], ["Heineken_N.V.", "has_product_line", "Root_beer"], ["Heineken_N.V.", "has_product_line", "Ginger_beer"], ["Heineken_N.V.", "has_product_line", "Mineral_water"], ["Heineken_N.V.", "has_product_line", "Juice"], ["Heineken_N.V.", "has_product_line", "Soft_drink"], ["Heineken_N.V.", "has_product_line", "Mead"], ["Heineken_N.V.", "has_product_line", "Cider"], ["Heineken_N.V.", "has_product_line", "Beer"], ["Heineken_N.V.", "has_product_line", "Wine"], ["Heineken_N.V.", "has_product_line", "Spirituous_liquor"], ["Heineken_N.V.", "has_product_line", "Lambic"], ["Heineken_N.V.", "has_product_line", "Fruit_drink"], ["Heineken_N.V.", "has_product_line", "Vegetable"], ["Heineken_N.V.", "has_product_line", "Food"], ["Heineken_N.V.", "has_product_line", "Ethanol"], ["Heineken_N.V.", "has_product_line", "Water"], ["Heineken_N.V.", "has_product_line", "Xylitol"], ["Heineken_N.V.", "has_product_line", "Sucralose"], ["Heineken_N.V.", "has_product_line", "Saccharin"], ["Heineken_N.V.", "has_product_line", "Tea"], ["Heineken_N.V.", "has_product_line", "Coffee"], ["Heineken_N.V.", "has_product_line", "Cacao"]]


Alfred Henry Heineken

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: Heineken_N, Alfred Henry Heineken: On 1 June 1941, Henry Pierre's son,Alfred Henry "Freddy" Heineken, entered the service of the Heineken company, which by then was no longer owned by the family. Freddy bought back stock several years later, to ensure the family controlled the company again, and in 1971 was appointed Chairman of the Executive Board. He was a powerful force behind Heineken's continued global expansion, and while he retired from the Executive Board in 1989, he maintained involvement with the company until his death in 2002. During this period, Heineken tried to increase its stock price by purchasing competing breweries and closing them down. AfterWorld War II, many small breweries were bought or closed. In 1968 Heineken merged with its biggest competitor,Amstel, and in 1975 opened a new brewery inZoeterwoude. The Amstel brewery was closed in 1980, and its production moved to Zoeterwoude andDen Bosch.

[["Heineken_N.V.", "Company"], ["Alfred_Henry_Heineken", "Person"], ["1941-06-01", "Date"], ["Heineken_N.V.", "Product"], ["Den_Bosch", "Place"], ["Zoeterwoude", "Place"], ["Amstel_Brewery", "Company"], ["2002-12-31", "Date"], ["Heineken_N.V.", "Fusion"], ["Amstel_Brewery", "Fusion"], ["World_War_II", "Date"], ["Alfred_Henry_Heineken", "Company"]]


Alfred Henry Heineken

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: Heineken_N, Alfred Henry Heineken: On 1 June 1941, Henry Pierre's son,Alfred Henry "Freddy" Heineken, entered the service of the Heineken company, which by then was no longer owned by the family. Freddy bought back stock several years later, to ensure the family controlled the company again, and in 1971 was appointed Chairman of the Executive Board. He was a powerful force behind Heineken's continued global expansion, and while he retired from the Executive Board in 1989, he maintained involvement with the company until his death in 2002. During this period, Heineken tried to increase its stock price by purchasing competing breweries and closing them down. AfterWorld War II, many small breweries were bought or closed. In 1968 Heineken merged with its biggest competitor,Amstel, and in 1975 opened a new brewery inZoeterwoude. The Amstel brewery was closed in 1980, and its production moved to Zoeterwoude andDen Bosch.

[["Heineken_N.V.", "has_product_line", "Beer"], ["Heineken_N.V.", "key_person", "Alfred_Henry_Heineken"], ["Alfred_Henry_Heineken", "occurred_on_date", "1941-06-01"], ["Heineken_N.V.", "key_person", "Henry_Pierre_Heineken"], ["Heineken_N.V.", "location", "Den_Bosch"], ["Heineken_N.V.", "key_person", "Alfred_Henry_Heineken"], ["Heineken_N.V.", "has_product_line", "Ale"], ["Heineken_N.V.", "key_person", "Gustave_Massiah"], ["Heineken_N.V.", "location", "Zoeterwoude"], ["Heineken_N.V.", "key_person", "Jan_Kees_Verschoor"], ["Heineken_N.V.", "has_product_line", "Pale_ale"], ["Heineken_N.V.", "key_person", "Johan_A._van_Oord"], ["Heineken_N.V.", "has_product_line", "Stout_(beer)"], ["Heineken_N.V.", "key_person", "Nicolas_M._Houtman"], ["Heineken_N.V.", "has_product_line", "Wheat_bier"], ["Heineken_N.V.", "key_person", "Willem_A._Mulder"], ["Heineken_N.V.", "has_product_line", "Lager"], ["Heineken_N.V.", "key_person", "Adrianus_Zwaanswijk"], ["Heineken_N.V.", "has_product_line", "Bock_beer"], ["Heineken_N.V.", "key_person", "Jan_Smit"], ["Heineken_N.V.", "has_product_line", "Alcohol"], ["Heineken_N.V.", "key_person", "Johan_Rijks"], ["Heineken_N.V.", "has_product_line", "Soft_drink"], ["Heineken_N.V.", "key_person", "Kees_Koolen"], ["Heineken_N.V.", "has_product_line", "Mineral_water"], ["Heineken_N.V.", "key_person", "Patrick_Van_Oevelen"], ["Heineken_N.V.", "has_product_line", "Cider"], ["Heineken_N.V.", "key_person", "Alex_Van_Zanten"], ["Heineken_N.V.", "has_product_line", "English_bitter"], ["Heineken_N.V.", "key_person", "Gerard_M._Verweij"], ["Heineken_N.V.", "has_product_line", "Bock_beer"], ["Heineken_N.V.", "key_person", "Albert_Schout"], ["Heineken_N.V.", "has_product_line", "Pale_ale"], ["Heineken_N.V.", "key_person", "Jan_Kees_Verschoor"], ["Heineken_N.V.", "has_product_line", "Ale"], ["Heineken_N.V.", "key_person", "Johan_A._van_Oord"], ["Heineken_N.V.", "has_product_line", "Stout_(beer)"], ["Heineken_N.V.", "key_person", "Nicolas_M._Houtman"], ["Heineken_N.V.", "has_product_line", "Wheat_bier"], ["Heineken_N.V.", "key_person", "Willem_A._Mulder"], ["Heineken_N.V.", "has_product_line", "Lager"], ["Heineken_N.V.", "key_person", "Adrianus_Zwaanswijk"], ["Heineken_N.V.", "has_product_line", "Bock_beer"], ["Heineken_N.V.", "key_person", "Jan_Smit"], ["Heineken_N.V.", "has_product_line", "Alcohol"], ["Heineken_N.V.", "key_person", "Johan_Rijks"], {"Heineken_N.V.", "has_product_line", "Soft_drink"}, {"Heineken_N.V.", "key_person", "Kees_Koolen"}, {"Heineken_N.V.", "has_product_line", "Mineral_water"}, {"Heineken_N.V.", "key_person", "Patrick_Van_Oevelen"}, {"Heineken_N.V.", "has_product_line", "Cider"}, {"Heineken_N.V.", "key_person", "Alex_Van_Zanten"}, {"Heineken_N.V.", "has_product_line", "English_bitter"}]


Recent history

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: Heineken_N, Recent history: Since mid-2007, Heineken has taken ownership of former S&N International brands such asStrongbowandBulmersciders andJohn Smith'sandNewcastle Brown Alebeers.With the part acquisition ofScottish and Newcastlein 2007/2008, Heineken became the third-largest brewer based on revenues, behind the Belgian-BrazilianAB InBevand the British-South AfricanSAB. Heineken owns the Czech brand Dačický, which was brewed inKutná Horafrom 1573 until Heineken took ownership of it and closed the brewery in 2009. In October 2016, following the merger betweenAnheuser-Busch InBevandSABMiller, Heineken became the second largest brewer in the world. On 12 January 2010, Heineken International successfully bought the brewery division of Mexican giantFEMSAin an all-stock deal, expanding its reach throughout Latin America.  The deal brought brands such asDos Equis,Sol,Tecate,Indio,Bohemiaand Kloster. Following the deal, Heineken started selling its products in Latin America through FEMSA's distribution network. The deal madeFEMSA20% owner of Heineken N.V. essentially becoming its largest single shareholder after the Dutch families (Heineken family and Hoyer family) who owns 25.83% and public shareholders owning 54.17%.The FEMSA acquisition is expected to keep Heineken in its strong position by growing its market share in the Latin American markets. FEMSA has a massive distribution network and owns Mexico's largest convenience store chainOXXO, which has thousands of locations throughout the country. In September 2014, it was announced that Heineken would sell its Mexican packaging business Empaque to Crown for around $1.23 billion.Also during that month, Heineken revealed it was in talks to sell its Czech operations toMolson Coors. On 10 September 2015, Heineken International announced it would acquire a 50% stake inLagunitas Brewing Companyof Petaluma in California as part of an effort to allow it (Lagunitas) to expand its operations globally. As part of the deal, Lagunitas would no longer be considered a craft brewer as the Heineken stake was greater than 25%. In January 2017, Heineken announced it was in negotiations to buy theKirin Company's 12 breweries in Brazil.The following month, Heineken closed the deal and boughtBrasil Kirinfor US$700 million. On 4 May 2017, after previously acquiring 50% of Lagunitas Brewing Company, Heineken announced it would be purchasing the remaining 50% making it the sole owner of Lagunitas. In 2018,Heinekensigned an agreement withChina Resources Enterprisesto purchase a 40% stake into the company. In June 2018, Heineken named Maggie Timoney as the CEO of Heineken USA, making her the first woman to become the CEO of a major United States beer supplier. In June 2021, Heineken's stake inUnited Breweriesof India increased to 61.5%, ultimately taking control of the company. In April 2023, Heineken completed the acquisition ofDistellandNamibia Breweries. In May 2023, Heineken N.V. bought back €333 million in shares fromFEMSA. FEMSA would no longer hold any shares in Heineken N.V. and Heineken Holding N.V. other than the Heineken Holding N.V. shares underlying the exchangeable bond. In August 2023, Heineken announced the sale of assets in Russia to theArnest Groupfor €1 plus a €100 million commitment to repay domestic debt.

[["Heineken", "Company"], ["FEMSA", "Company"], ["Mexican_Packaging_Company_Empaque", "Company"], ["Crown_Resources", "Company"], ["Kirin_Co._Ltd.", "Company"], ["United_Breweries", "Company"], ["Arnest_Group", "Company"], ["Lagunitas_Brewing_Company", "Company"], ["Heineken_N.V.", "Company"], ["FEMSA", "Person"], ["Maggie_Timoney", "Person"], ["Heineken_USA", "Company"], ["Distell", "Company"], ["Namibia_Breweries", "Company"], ["Heineken_N.V.", "Product"], ["Heineken", "Person"], ["Heineken_N.V.", "Person"], ["Heineken", "Place"], ["Czech_Republic", "Place"], ["Kutná_Hora", "Place"], ["Dos_Equis", "Product"], ["Sol_(beer)", "Product"], ["Tecate", "Product"], ["Indio_(beer)", "Product"], ["Newcastle_Brown_Ale", "Product"], ["John_Smith's", "Product"], ["S.A.B._Miller", "Company"], ["Anheuser-Busch_InBev", "Company"], ["S&N_International", "Company"], ["FEMSA", "Place"], ["OXXO", "Place"], ["Brazil", "Place"], ["Crown_Resources", "Person"], ["Empaque", "Product"], ["Lagunitas_Brewing_Company", "Place"], ["United_Breweries", "Person"], ["Heineken_N.V.", "Place"], ["Arnest_Group", "Person"], ["Kirin_Co._Ltd.", "Person"], ["Namibia_Breweries", "Person"], ["Heineken_USA", "Person"], ["Maggie_Timoney", "Person"], ["Mexican_Packaging_Company_Empaque", "Person"], ["Distell", "Person"], ["Dos_Equis", "Company"], ["Sol_(beer)", "Company"], ["Tecate", "Company"], ["Indio_(beer)", "Company"], ["Newcastle_Brown_Ale", "Company"], ["John_Smith's", "Company"], ["S.A.B._Miller", "Person"], ["Anheuser-Busch_InBev", "Person"], ["S&N_International", "Person"], ["FEMSA", "Product"], ["OXXO", "Product"], ["Brazil", "Company"], ["Crown_Resources", "Company"], ["Empaque", "Company"], ["Lagunitas_Brewing_Company", "Company"], ["United_Breweries", "Company"], ["Heineken_N.V.", "Company"], ["Arnest_Group", "Company"], ["Kirin_Co._Ltd.", "Company"], ["Namibia_Breweries", "Company"], ["Heineken_USA", "Company"], ["Maggie_Timoney", "Person"], ["Mexican_Packaging_Company_Empaque", "Company"], ["Distell", "Company"], ["Dos_Equis", "Company"], ["Sol_(beer)", "Company"], ["Tecate", "Company"], ["Indio_(beer)", "Company"], ["Newcastle_Brown_Ale", "Company"], ["John_Smith's", "Company"], ["S.A.B._Miller", "Company"], ["Anheuser-Busch_InBev", "Company"], ["S&N_International", "Company"], ["FEMSA", "Company"], ["OXXO", "Company"], ["Brazil", "Place"], ["Crown_Resources", "Company"], ["Empaque", "Product"], ["Lagunitas_Brewing_Company", "Company"], ["United_Breweries", "Company"], ["Heineken_N.V.", "Company"], ["Arnest_Group", "Company"], ["Kirin_Co._Ltd.", "Company"], ["Namibia_Breweries", "Company"], ["Heineken_USA", "Company"], ["Maggie_Timoney", "Person"], ["Mexican_Packaging_Company_Empaque", "Company"], ["Distell", "Company"], ["Dos_Equis", "Product"], ["Sol_(beer)", "Product"], ["Tecate", "Product"], ["Indio_(beer)", "Product"], ["Newcastle_Brown_Ale", "Product"], ["John_Smith's", "Product"], ["S.A.B._Miller", "Company"], ["Anheuser-Busch_InBev", "Company"], ["S&N_International", "Company"], ["FEMSA", "Company"], ["OXXO", "Place"], ["Brazil", "Place"], ["Crown_Resources", "Company"], ["Empaque", "Product"], ["Lagunitas_Brewing_Company", "Company"], ["United_Breweries", "Company"], ["Heineken_N.V.", "Company"], ["Arnest_Group", "Company"], ["Kirin_Co._Ltd.", "Company"], ["Namibia_Breweries", "Company"], ["Heineken_USA", "Company"], ["Maggie_Timoney", "Person"], ["Mexican_Packaging_Company_Empaque", "Company"], ["Distell", "Company"], ["Dos_Equis", "Product"], {"type": "Date", "value": "2007-06-30"}, {"type": "Date", "value": "2007-10-03"}, {"type": "Date", "value": "2008-06-30"}, {"type": "Date", "value": "2010-01-12"}, {"type": "Date", "value": "2014-09-01"}, {"type": "Date", "value": "2015-09-10"}, {"type": "Date", "value": "2016-10-03"}, {"type": "Date", "value": "2017-05-04"}, {"type": "Date", "value": "2018-06-01"}, {"type": "Date", "value": "2021-06-30"}, {"type": "Date", "value": "2023-04-27"}, {"type": "Date", "value": "2023-08-01"}]


Recent history

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: Heineken_N, Recent history: Since mid-2007, Heineken has taken ownership of former S&N International brands such asStrongbowandBulmersciders andJohn Smith'sandNewcastle Brown Alebeers.With the part acquisition ofScottish and Newcastlein 2007/2008, Heineken became the third-largest brewer based on revenues, behind the Belgian-BrazilianAB InBevand the British-South AfricanSAB. Heineken owns the Czech brand Dačický, which was brewed inKutná Horafrom 1573 until Heineken took ownership of it and closed the brewery in 2009. In October 2016, following the merger betweenAnheuser-Busch InBevandSABMiller, Heineken became the second largest brewer in the world. On 12 January 2010, Heineken International successfully bought the brewery division of Mexican giantFEMSAin an all-stock deal, expanding its reach throughout Latin America.  The deal brought brands such asDos Equis,Sol,Tecate,Indio,Bohemiaand Kloster. Following the deal, Heineken started selling its products in Latin America through FEMSA's distribution network. The deal madeFEMSA20% owner of Heineken N.V. essentially becoming its largest single shareholder after the Dutch families (Heineken family and Hoyer family) who owns 25.83% and public shareholders owning 54.17%.The FEMSA acquisition is expected to keep Heineken in its strong position by growing its market share in the Latin American markets. FEMSA has a massive distribution network and owns Mexico's largest convenience store chainOXXO, which has thousands of locations throughout the country. In September 2014, it was announced that Heineken would sell its Mexican packaging business Empaque to Crown for around $1.23 billion.Also during that month, Heineken revealed it was in talks to sell its Czech operations toMolson Coors. On 10 September 2015, Heineken International announced it would acquire a 50% stake inLagunitas Brewing Companyof Petaluma in California as part of an effort to allow it (Lagunitas) to expand its operations globally. As part of the deal, Lagunitas would no longer be considered a craft brewer as the Heineken stake was greater than 25%. In January 2017, Heineken announced it was in negotiations to buy theKirin Company's 12 breweries in Brazil.The following month, Heineken closed the deal and boughtBrasil Kirinfor US$700 million. On 4 May 2017, after previously acquiring 50% of Lagunitas Brewing Company, Heineken announced it would be purchasing the remaining 50% making it the sole owner of Lagunitas. In 2018,Heinekensigned an agreement withChina Resources Enterprisesto purchase a 40% stake into the company. In June 2018, Heineken named Maggie Timoney as the CEO of Heineken USA, making her the first woman to become the CEO of a major United States beer supplier. In June 2021, Heineken's stake inUnited Breweriesof India increased to 61.5%, ultimately taking control of the company. In April 2023, Heineken completed the acquisition ofDistellandNamibia Breweries. In May 2023, Heineken N.V. bought back €333 million in shares fromFEMSA. FEMSA would no longer hold any shares in Heineken N.V. and Heineken Holding N.V. other than the Heineken Holding N.V. shares underlying the exchangeable bond. In August 2023, Heineken announced the sale of assets in Russia to theArnest Groupfor €1 plus a €100 million commitment to repay domestic debt.

[["Heineken", "recent_history", "\"Since mid-2007, Heineken has been the owner of the former S&N International brands such as Strongbow, Bulmers, John Smith's and Newcastle Brown Ale.\""], ["Heineken", "recent_history", "\"With the part acquisition of Scottish and Newcastle in 2007/2008, Heineken became the third-largest brewer based on revenues, behind the Belgian-Brazilian AB InBev and the British-South African SAB.\""], ["Heineken", "recent_history", "\"Heineken owns the Czech brand Dačický, which was brewed in Kutná Hora from 1573 until Heineken took ownership of it and closed the brewery in 2009.\""], ["Heineken", "recent_history", "\"In October 2016, following the merger between Anheuser-Busch InBev and SABMiller, Heineken became the second largest brewer in the world.\""], ["Heineken", "recent_history", "\"On 12 January 2010, Heineken International successfully bought the brewery division of Mexican giant FEMSA in an all-stock deal, expanding its reach throughout Latin America.\""], ["Heineken", "recent_history", "\"The deal brought brands such as Dos Equis, Sol, Tecate, Indio, Bohemia and Kloster.\""], ["Heineken", "recent_history", "\"Following the deal, Heineken started selling its products in Latin America through FEMSA's distribution network.\""], ["Heineken", "recent_history", "\"The deal made FEMSA 20.0% owner of Heineken N.V. essentially becoming its largest single shareholder after the Dutch families (Heineken family and Hoyer family) who owns 25.83% and public shareholders owning 54.17%.\""], ["Heineken", "recent_history", "\"FEMSA acquisition is expected to keep Heineken in its strong position by growing its market share in the Latin American markets.\""], ["Heineken", "recent_history", "\"FEMSA has a massive distribution network and owns Mexico's largest convenience store chain OXXO, which has thousands of locations throughout the country.\""], ["Heineken", "recent_history", "\"In September 2014, it was announced that Heineken would sell its Mexican packaging business Empaque to Crown for around $1.23 billion.\""], ["Heineken", "recent_history", "\"Also during that month, Heineken revealed it was in talks to sell its Czech operations to Molson Coors.\""], ["Heineken", "recent_history", "\"On 10 September 2015, Heineken International announced it would acquire a 50.0% stake in Lagunitas Brewing Company of Petaluma, California as part of an effort to allow it (Lagunitas) to expand its operations globally.\""], ["Heineken", "recent_history", "\"As part of the deal, Lagunitas would no longer be considered a craft brewer as the Heineken stake was greater than 25.0%.\""], ["Heineken", "recent_history", "\"In January 2017, Heineken announced it was in negotiations to buy the Kirin Company's 12 breweries in Brazil.\""], ["Heineken", "recent_history", "\"The following month, Heineken closed the deal and bought Brasil Kirin for US$700 million.\""], ["Heineken", "recent_history", "\"On 4 May 2017, after previously acquiring 50.0% of Lagunitas Brewing Company, Heineken announced it would be purchasing the remaining 50.0% making it the sole owner of Lagunitas.\""], ["Heineken", "recent_history", "\"In 2018, Heineken signed an agreement with China Resources Enterprise to purchase a 40.0% stake into the company.\""], ["Heineken", "recent_history", "\"In June 2018, Heineken named Maggie Timoney as the CEO of Heineken USA, making her the first woman to become the CEO of a major United States beer supplier.\""], ["Heineken", "recent_history", "\"In June 2021, Heineken's stake in United Breweries of India increased to 61.5%, ultimately taking control of the company.\""], ["Heineken", "recent_history", "\"In April 2023, Heineken completed the acquisition of Distell and Namibia Breweries.\""], ["Heineken", "recent_history", "\"In May 2023, Heineken N.V. bought back €333 million in shares from FEMSA. FEMSA would no longer hold any shares in Heineken N.V. and Heineken Holding N.V. other than the Heineken Holding N.V. shares underlying the exchangeable bond.\""], ["Heineken", "recent_history", "\"In August 2023, Heineken announced the sale of assets in Russia to the Arnest Group for €1 plus a €100 million commitment to repay domestic debt.\""]]


Global structure

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: Heineken_N, Global structure: Heineken organises the company into five territories which are then divided into regional operations.The regions are: Western Europe, Central and Eastern Europe, The Americas,  Asia Pacific and Africa and the Middle East. These territories contain 115 brewing plants in more than 65 countries,brewing local brands in addition to the Heineken brand.

[["Heineken", "Company"], ["115", "number"], ["Heineken_N", "Article"], ["\"Western Europe, Central and Eastern Europe, The Americas, Asia Pacific and Africa and the Middle East\"", "string"], ["65", "number"]]


Global structure

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: Heineken_N, Global structure: Heineken organises the company into five territories which are then divided into regional operations.The regions are: Western Europe, Central and Eastern Europe, The Americas,  Asia Pacific and Africa and the Middle East. These territories contain 115 brewing plants in more than 65 countries,brewing local brands in addition to the Heineken brand.

[["Heineken", "has_product_line", "Heineken_N"], ["Heineken", "organises_the_company_into", "\"Five territories which are then divided into regional operations\""], ["Heineken", "has_product_line", "\"Western Europe, Central and Eastern Europe, The Americas,  Asia Pacific and Africa and the Middle East\""], ["Heineken", "has_product_line", "115 brewing plants"], ["Heineken", "has_product_line", "\"In more than 65 countries, brewing local brands in addition to the Heineken brand\""]]


Executive team

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: Heineken_N, Executive team: The executive team of the company consists of the following people:

[["Heineken_N", "Company"], ["Executive_team", "Person"]]