Heineken Experience

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 Experience: TheHeineken Experienceis a museum aboutHeineken Pilsenerand the Heineken brewery, based in the original brewery inAmsterdam. The original building was built in 1867, and was in use as a brewery until 1988.In 1991, when part of the establishment was torn down, the Heineken Reception and Information Centre (Dutch:Heineken ontvangst- en informatiecentrum) was opened in the remaining building. In 2001 the name was changed to Heineken Experience. The museum features "rides", interactive exhibits, and two bars. It also gives an insight into the company's history and brewing processes through the years. Visitors receive one small tasting glass and two full-sized glasses of Heineken beer to drink at the end of the tour, both paid for by the 21 euro entry fee.

Heineken_Experience

Q2087161 - Heineken Experience: industrial museum in Amsterdam, Netherlands

Q33506 - museum: institution that holds artifacts and other objects of scientific, artistic, cultural, historical, or other importance

Q188740 - Museum of Modern Art: art museum in Manhattan in New York City, New York, United States

Q1360745 - museum-digital: museum digitization project

Q1565911 - Museum of Fine Arts, Houston: art museum in Houston, Texas

Q24699794 - museum building: building housing a museum

Heineken_Experience

P421 - located in time zone: time zone for this item

P6375 - street address: full street address where subject is located. Include building number, city/locality, post code, but not country; use also P669 if the street has its own separate item

P7959 - historic county: traditional, geographical division of Great Britain and Ireland

Q9899 - Amsterdam: municipality in the Netherlands, containing the cities of Amsterdam and Weesp

Q727 - Amsterdam: capital and most populous city of the Netherlands

Q190804 - Rijksmuseum: museum in Amsterdam, Netherlands

Q2011634 - Yef Miossu: island in Tambrauw Regency, Southwest Papua Province, Indonesia

Heineken_Experience

Q854383 - Heineken: pale lager beer by the Dutch brewing company Heineken International

Heineken_Experience

Heineken_Experience

P2555 - fee: fee or toll payable to use, transit or enter the subject (only for one-time fees, do NOT use it for an ongoing fee, tuition fee or trading fee)

Heineken_Experience

Q1516861 - Snifter: short-stemmed glass whose vessel has a wide bottom and a relatively narrow top

Heineken_Experience

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

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

Q64549253 - Heineken: painting by Idelle Weber

Heineken_Experience

Heineken_Experience

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

P729 - service entry: date or point in time on which a piece or class of equipment entered operational service

P1810 - subject named as: name by which a subject is recorded in a database, mentioned as a contributor of a work, or is referred to in a particular context

P112 - founded by: founder or co-founder of this organization, religion, place or entity

P5166 - established from medical condition: cell line or xenograft established from an individual person or animal with a specific medical condition

Q53385292 - 1991-1992 one-year-period: period of about one year starting in 1991 and ending in 1992

Q2410792 - 1991: 2012 debut EP by Azealia Banks

Q687247 - 1991–92 Fußball-Bundesliga: 29th season of the Bundesliga

Heineken_Experience

Q49181402 - Interactive exhibition of heavy metal toxicity in bone metabolism. From the viewpoint of deductive toxicology: scientific article published in March 1995

Q79728302 - Interactive exhibition of human meridian based on Cult3D: scientific article published on 01 January 2005

Q131284140 - Interactive exhibits: how visitors respond: journal article from 'Museum International' published in 2000

Heineken_Experience

Q1144661 - amusement ride: mechanical device or structure that moves people to create enjoyment

Q106650487 - RIDE: review journal for digital editions and resources published by the IDE

Heineken_Experience

Q6031029 - information centre: place where information is given out

Q1549731 - interpretation centre: Type of museum

Q2892902 - Information Center for Israeli Art: Archive and research center in Jerusalem

Q818717 - advice centre: organisations that offer support and assistance with social issues

Q12599133 - Information Center on North Korea: center in Seoul, South Korea

Heineken_Experience

Q65957296 - Beer: German badminton player

Q6106 - Portland: city and county seat of Multnomah County, Oregon, United States

Heineken_Experience

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

Q8195619 - human food: food eaten by Homo sapiens

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

Q3007875 - Food Chemistry: peer-reviewed scientific journal

Heineken_Experience

Q11424 - film: sequence of images that give the impression of movement, stored on film stock

Q1137203 - thin film: a layer of material ranging from fractions of a nanometer to several micrometers in thickness

Q2526255 - film director: person who controls the artistic and dramatic aspects of a film production

Q41253 - movie theater: venue, usually a building, for viewing films

Q93204 - documentary film: nonfictional motion picture

Heineken_Experience

Q95074 - character: fictional human or non-human character in a narrative work of art

Q65924737 - character in a fictitious work: fictional character that is considered fictional even in a fictional story

Q14514600 - group of fictional characters: set of fictional characters

Q27960097 - character poster: advertisement poster focusing on a fictional character of a work

Q100708514 - fictional character in a musical work: fictional character only appearing in musical works

Heineken_Experience

Q2221906 - geographic location: point, line or area on or near Earth

Q202142 - locative case: grammatical case which indicates a location

Q98929991 - place: small area known by a geographical name

Q17334923 - physical location: property describing the position of something in space

Heineken_Experience

Q217438 - demonym: name for a resident of a locality

Q134617828 - Demonyms in Canada: website for English demonyms for Canadian places

Q3100940 - list of demonyms for US states and territories: Wikimedia list article

Q105942275 - demonym of: inverse label of property P1549 (demonym)

Q3044537 - demonyms for the United States: how people from the United States of America are known

Heineken_Experience

Q83440 - country music: genre of American popular music

Q6256 - country: distinct territorial body or political entity

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

Q902 - Bangladesh: country in South Asia

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

Heineken_Experience

Q315 - language: structured system of communication

Q34770 - language: particular system of communication, often named for the region or peoples that use it

Q75488338 - Language: controlled vocabulary that list language names of the European Union

Q60317586 - Language: ESRB video game content descriptor for games that contains some use of profanity.

Heineken_Experience

Q47461344 - written work: any work expressed in writing, such as inscriptions, manuscripts, documents or maps

Q8038566 - Written works of L. Ron Hubbard: Wikimedia list article

Q136209058 - Written Work: Langland, Labor, and Authorship: book 1997

Q47788698 - Written work: the social functions of Research Ethics Committee letters: scientific article published on 8 May 2007

Q129690019 - Written works in the methodology of teaching general sociology in university practice (using works of BMSTU students as an example): scholarly article published in April 2018

Heineken_Experience

Q618779 - award: something given to a person or a group of people to recognize their merit or excellence

Q4504495 - award ceremony: event and/or television programming genre based on the presentation of an award

Q21096945 - award winner: person who has received an award

Q38033430 - class of award: class of award (order, medal, etc.)

Q2988681 - achievement: meta-goal in a video game

Heineken_Experience

Q24856 - film series: collection of related films in succession

Heineken_Experience

Q1210950 - channel: type of landform; confined river; strait

Q583271 - spiritual medium: person said to mediate communication between spirits of the dead and other human beings

Q836957 - channel catfish: species of fish

Q733553 - channel: physical or logical connection used for transmission of information

Heineken_Experience

Q43229 - organization: social entity established to meet needs or pursue goals

Q2029841 - organization: concept in economics: activity in which something is accomplished

Q4479442 - founder: person who creates an institution intended to perpetuate itself after the founder's association ends

Q15642541 - human-geographic territorial entity: territorial entity of which the borders are determined by physiographic and human features

Heineken_Experience

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

Q90 - Paris: capital city and largest city of France

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

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

Heineken_Experience

Q12737077 - occupation: label applied to a person based on an activity they participate in

Q192581 - job activity: activity done by a person to earn money

Q63188808 - Orthodox Bishop: lifelong occupation which serves a purpose within the context of the Catholic Church

Q188686 - military occupation: effective provisional control of a certain power over a territory

Q11773926 - ecclesiastical occupation: None

Heineken_Experience

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

Q5404323 - ethnicity: a person's ethnic background

Q106474968 - ethnic group by settlement in Macedonia: census category

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

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

Heineken_Experience

Q7275 - state: organised community living under a system of government; either a sovereign state, constituent state, or federated state

Q17 - Japan: island country in East Asia

Q671384 - Statens Museum for Kunst: art museum in Copenhagen, Denmark

Heineken_Experience

Q3258659 - background: relatively distant and unimportant element in art

Q492264 - film score: original music written specifically to accompany a film, part of the film's soundtrack

Q798487 - backing vocalist: singer who provides vocal harmony with the lead vocalist or other backing vocalists

Q27623618 - minor character: character being of minor importance to the story

Q6453156 - backstory: background story of a character

Heineken_Experience

Q815825 - hospitality: relationship between the guest and the host, or the act or practice of being hospitable

Q1495452 - hospitality industry: broad category of fields within the service industry

Q123733 - hospitality service: lodging whereby visitors share a residence with a local of the city to which they are traveling

Q2887302 - Hospitality: album by Venetian Snares

Heineken_Experience

Q15724430 - Alcohol: periodical literature

Q156 - alcohols: any organic compound in which the hydroxyl functional group (–OH) is bound to a saturated carbon atom

Q15326 - alcoholism: broad term for problems with alcohol

Q2647488 - alcohol consumption: drinking of drinks that contain ethanol

Heineken_Experience

Q2988681 - achievement: meta-goal in a video game

Q67325957 - list of awards and nominations: list of awards and nominations received by the person or institution

Q81182549 - awards: inverse property label item for P1027

Heineken_Experience

Q35869 - asthma: long-term disease involving inflamed airways

Q2551913 - occupational asthma: respiratory medical condition caused or exacerbated by the workplace

Q1772450 - Asthmatic Kitty: American independent record label

Q826759 - status asthmaticus: type of asthma

Q36177 - Euphorbia hirta: species of hairy herb grown in open grasslands, roadsides, and pathways

Heineken_Experience

Q112980630 - Asthma trigger: factor that provokes symptoms of asthma

Q39525361 - Asthma triggers in the elementary school environment: a pilot study: scientific article published on December 1999

Q41102463 - Asthma Trigger Reports Are Associated with Low Quality of Life, Exacerbations, and Emergency Treatments: scientific article published on 24 November 2015

Q88953973 - Asthma trigger perceptions are associated with work disability: scientific article published on 19 April 2018

Q80769942 - Asthma triggers & treatments. Now, excess weight and obesity are also implicated in contributing to asthma attacks: scientific article published on 01 July 2007

Heineken_Experience

Q1360745 - museum-digital: museum digitization project

Q1565911 - Museum of Fine Arts, Houston: art museum in Houston, Texas

Q24699794 - museum building: building housing a museum

Heineken_Experience

Q5 - human: any single member of Homo sapiens, unique extant species of the genus Homo

Q215627 - person: being that has certain capacities or attributes constituting personhood (for humans, use Q5 [human] with P31 [instance of])

Heineken_Experience

Q648743 - 18634 Champigneulles: asteroid

Output: None of the candidates

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Possible ties to the slave plantations

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, Possible ties to the slave plantations: On 15 February 1864, Gerard Adriaan Heineken bought De Hooiberg (the Haystack) brewery in Amsterdam.It remains unclear whether the funds for the purchase of the Haystack came from his father, a cheese trader, or his mother, whose estate included proceeds from her previous husband’s family’s historical investments in West Indies slave plantations. In a letter to his mother 18 June 1863, Gerard discussed the potential Haystack purchase and his plans for the future. Gerard’s mother, Anna Geertruida van de Paauw, came to own shares in slave plantations inBerbice(modern day Guyana) and Suriname through her first marriage in 1829 to Pieter Jacob Schumacher van Oudorp (1804–1833)who died in 1833. The Schumacher family owned several plantations in Berbice and Suriname, according to records held at the UK’s National Archive.After Pieter Schumacher died, Anna was remarried to Cornelis Heineken and had four children, one of which was Gerard Heineken. Anna died in 1881.

[
    "Q2409479 - Gerard Adriaan Heineken: founder of beer company Heineken International (1841–1893)"
]

[
    "Q19008964 - De Hooiberg: street in Biddinghuizen, the Netherlands",
    "Q114765196 - De Hooiberg brewery: None",
    "Q28102543 - De Hooiberg: painting by Herman Justus Kruyder",
    "Q94016625 - The haystack: painting by Charles-François Daubigny",
    "Q24050724 - De hooiberg: painting by Gerard Bilders"
]

[
    "Q69233388 - February 15, 1864: date in Gregorian calendar"
]

[
    "Q675322 - Berbice: region along the Berbice River in Guyana",
    "Q11721989 - Buitenplaats Berbice: manor house in Voorschoten, Netherlands",
    "Q35215 - Berbice Creole Dutch: extinct Dutch-based creole language of Guyana",
    "Q30598147 - HMS Berbice: 1790s schooner",
    "Q2896921 - Berbice River: river in Guyana"
]

[
    "Q730 - Suriname: country in South America",
    "Q7646305 - Surinam: Dutch plantation colony in the Guianas",
    "Q5502076 - Hussard: 1799 corvette",
    "Q635545 - Suriname River: river in Suriname",
    "Q33989 - Sranan Tongo: creole language spoken in Suriname"
]

[
    "Q734 - Guyana: country in South America",
    "Q650667 - Guyanas: region in northeastern South America",
    "Q208807 - Guiana Highlands: higher elevations on the Guiana Shield",
    "Q5622720 - Commonwealth realm of Guyana: South American country from 1966 to 1970",
    "Q20687139 - Guyanancistrus: genus of fishes"
]

[
    "Q19008964 - De Hooiberg: street in Biddinghuizen, the Netherlands",
    "Q114765196 - De Hooiberg brewery: None",
    "Q28102543 - De Hooiberg: painting by Herman Justus Kruyder",
    "Q94016625 - The haystack: painting by Charles-François Daubigny",
    "Q24050724 - De hooiberg: painting by Gerard Bilders"
]

[
    "Q69233008 - June 18, 1863: date in Gregorian calendar"
]

[
    "Q730 - Suriname: country in South America",
    "Q7646305 - Surinam: Dutch plantation colony in the Guianas",
    "Q5502076 - Hussard: 1799 corvette",
    "Q635545 - Suriname River: river in Suriname",
    "Q33989 - Sranan Tongo: creole language spoken in Suriname"
]

[
    "Q675322 - Berbice: region along the Berbice River in Guyana",
    "Q11721989 - Buitenplaats Berbice: manor house in Voorschoten, Netherlands",
    "Q35215 - Berbice Creole Dutch: extinct Dutch-based creole language of Guyana",
    "Q30598147 - HMS Berbice: 1790s schooner",
    "Q2896921 - Berbice River: river in Guyana"
]

[
    "Q734 - Guyana: country in South America",
    "Q650667 - Guyanas: region in northeastern South America",
    "Q208807 - Guiana Highlands: higher elevations on the Guiana Shield",
    "Q5622720 - Commonwealth realm of Guyana: South American country from 1966 to 1970",
    "Q20687139 - Guyanancistrus: genus of fishes"
]


Possible ties to the slave plantations

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, Possible ties to the slave plantations: On 15 February 1864, Gerard Adriaan Heineken bought De Hooiberg (the Haystack) brewery in Amsterdam.It remains unclear whether the funds for the purchase of the Haystack came from his father, a cheese trader, or his mother, whose estate included proceeds from her previous husband’s family’s historical investments in West Indies slave plantations. In a letter to his mother 18 June 1863, Gerard discussed the potential Haystack purchase and his plans for the future. Gerard’s mother, Anna Geertruida van de Paauw, came to own shares in slave plantations inBerbice(modern day Guyana) and Suriname through her first marriage in 1829 to Pieter Jacob Schumacher van Oudorp (1804–1833)who died in 1833. The Schumacher family owned several plantations in Berbice and Suriname, according to records held at the UK’s National Archive.After Pieter Schumacher died, Anna was remarried to Cornelis Heineken and had four children, one of which was Gerard Heineken. Anna died in 1881.

Gerard_Adriaan_Heineken

Q2409479 - Gerard Adriaan Heineken: founder of beer company Heineken International (1841–1893)

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

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

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

Q19008964 - De Hooiberg: street in Biddinghuizen, the Netherlands

Q28102543 - De Hooiberg: painting by Herman Justus Kruyder

Q94016625 - The haystack: painting by Charles-François Daubigny

Q24050724 - De hooiberg: painting by Gerard Bilders

Anna_Geertruida_van_de_Paauw

P570 - date of death: date on which the subject died

Q69242400 - January 1, 1881: date in Gregorian calendar

Anna_Geertruida_van_de_Paauw

P26 - spouse: the subject has the object as their spouse (husband, wife, partner, etc.). Use "unmarried partner" (P451) for non-married companions

Anna_Geertruida_van_de_Paauw

P40 - child: subject has object as child. Do not use for stepchildren—use "relative" (P1038), qualified with "type of kinship" (P1039)

P22 - father: male parent of the subject. For stepfather, use "stepparent" (P3448)

P25 - mother: female parent of the subject. For stepmother, use "stepparent" (P3448)

P1971 - number of children: number of children of the person, animal, or character

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

Anna_Geertruida_van_de_Paauw

Pieter_Jacob_Schumacher_van_Oudorp

Q69216149 - January 1, 1833: date in Gregorian calendar

Pieter_Jacob_Schumacher_van_Oudorp

Pieter_Jacob_Schumacher_van_Oudorp

P47 - shares border with: countries or administrative subdivisions, of equal level, that this item borders, either by land or water. A single common point is enough.

P4070 - identifier shared with: qualifier, to be used on external identifier IDs, indicating another Wikidata item is also matched to this ID

P9531 - identifier shared with lexeme: qualifier used to state which other lexemes are also matched to this identifier

P10756 - number of reblogs: number of reblogs, reposts, retweets, crossposts, or on-platform shares received on a social media post

Pieter_Jacob_Schumacher_van_Oudorp

Pieter_Jacob_Schumacher_van_Oudorp

Q664609 - Caribbean: region to the center-east of America composed of many islands / coastal regions surrounding the Caribbean Sea

Q669037 - West Indies: island region in the Caribbean

Q912881 - West Indies cricket team: multinational cricket team

Q21022 - French West Indies: French territories in the Caribbean

Q20505075 - West Indies: painting by Abbott Handerson Thayer

Output: None of the candidates

Output: None of the candidates

Output: None of the candidates

Output: None of the candidates

Output: None of the candidates

Output: None of the candidates

Output: None of the candidates

Output: None of the candidates


Price fixing

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, Price fixing: On 18 April 2007 theEuropean Commissionfined Heineken  €219.3m,Grolsch€31.65m andBavaria€22.85m for operating aprice fixing cartelin the Netherlands, totalling €273.7m.InBev, (formerlyInterbrew), escaped without a penalty because it provided "decisive information" about the cartel which operated between 1996 and 1999 and others in the EU market. The brewers controlled 95% of the Dutch market, with Heineken claiming a half and the three others 15% each. Neelie Kroessaid she was "very disappointed" that the collusion took place at the very highest (boardroom) level. She added, Heineken, Grolsch, Bavaria and InBev tried to cover their tracks by using code names and abbreviations for secret meetings to carve up the market for beer sold to supermarkets,hotels,restaurantsandcafes. Theprice fixingextended to cheaperown-brandlabels andrebatesfor bars. In 2004 Heineken andKronenbourg(then part ofScottish and Newcastle), the two dominant brewers in France, were fined €2.5m – with the penalty reduced for co-operating. This is simply unacceptable: that major beer suppliers colluded to up prices and to carve up markets among themselves — Neelie Kroes, EU Competition Commissioner

[
    "Q180855 - Heineken: Dutch beer company",
    "Q16870666 - Heineken: family name",
    "Q854383 - Heineken: pale lager beer by the Dutch brewing company Heineken International",
    "Q64549253 - Heineken: painting by Idelle Weber",
    "Q17425857 - Heinekenia: genus of plants"
]

[
    "Q153075 - Grolsch: brewery in the Netherlands",
    "Q299126 - Dutch Open: tennis tournament",
    "Q115576141 - Grolsch Oud Bruin: beer type from the Dutch Grolsch brewery",
    "Q18086967 - Kornuit: beer brand of Grolsch",
    "Q61043304 - Grolsch 0.0%: non-alcoholic beer from Grolsch"
]

[
    "Q980 - Bavaria: federated state in the south of Germany",
    "Q154195 - Kingdom of Bavaria: kingdom in Central Europe between 1806 and 1918, from January 1871 part of the German Empire",
    "Q64913456 - Bavaria: family name",
    "Q106318202 - Bavaria: cargo ship built in 1966",
    "Q812285 - Bavarian State Painting Collections: artworks held by the Free State of Bavaria for Alte Pinakothek, Aschaffenburg, Bamberg, Bayreuth, Schleissheim and others"
]

[
    "Q19617526 - April 18, 2007: date",
    "Q17619042 - 2007-04-18: Polska i Ukraina zorganizują mistrzostwa piłkarskie Euro 2012: Wikinews article",
    "Q17893624 - 2007-04-18: J.R.R. Tolkien: Najnowsza książka \"Dzieci Hurina\": Wikinews article",
    "Q17893632 - 2007-04-18: Korea Południowa: obawa o stosunki z USA po masakrze w Blacksburgu: Wikinews article",
    "Q17931169 - 2007-04-18: Bankowa komisja śledcza chce przesłuchać Oleksego: Wikinews article"
]

[
    "Q8880 - European Commission: executive branch of the European Union",
    "Q2661677 - European Commissioner: member of the European Commission; like a government minister",
    "Q1780211 - European Commissioner for Trade: Member of the EU Commission",
    "Q5412398 - European Commission Data Portal: Point of access to public data published by the European Union institutions, agencies and other bodies",
    "Q1676795 - European Commissioner for Transport: Member of the EU Commission"
]

[
    "Q1416717 - InBev Belgium: public company",
    "Q21042373 - InBev-Baillet Latour Health Prize: Belgian medical award",
    "Q2696011 - InBev-Baillet Latour Fund: Belgian non-profit organization",
    "Q128738 - Anheuser-Busch InBev: Belgian-Brazilian multinational beverage and brewing company",
    "Q6008710 - InBev brands: List of beer brands owned by Anheuser-Busch InBev SA/NV"
]

[
    "Q234485 - Neelie Kroes: Dutch politician"
]

[
    "Q180855 - Heineken: Dutch beer company",
    "Q16870666 - Heineken: family name",
    "Q854383 - Heineken: pale lager beer by the Dutch brewing company Heineken International",
    "Q64549253 - Heineken: painting by Idelle Weber",
    "Q17425857 - Heinekenia: genus of plants"
]

[
    "Q153075 - Grolsch: brewery in the Netherlands",
    "Q299126 - Dutch Open: tennis tournament",
    "Q115576141 - Grolsch Oud Bruin: beer type from the Dutch Grolsch brewery",
    "Q18086967 - Kornuit: beer brand of Grolsch",
    "Q61043304 - Grolsch 0.0%: non-alcoholic beer from Grolsch"
]

[
    "Q980 - Bavaria: federated state in the south of Germany",
    "Q154195 - Kingdom of Bavaria: kingdom in Central Europe between 1806 and 1918, from January 1871 part of the German Empire",
    "Q64913456 - Bavaria: family name",
    "Q106318202 - Bavaria: cargo ship built in 1966",
    "Q812285 - Bavarian State Painting Collections: artworks held by the Free State of Bavaria for Alte Pinakothek, Aschaffenburg, Bamberg, Bayreuth, Schleissheim and others"
]

[
    "Q55639079 - 95.0 FM: Wikimedia list article",
    "Q135677142 - 95.0 – Radio Benue, Makurdi: a public radio station located in Makurdi"
]

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

[
    "Q1397604 - Kronenbourg Brewery: france-based brewery",
    "Q795663 - Kronenbourg beer: None",
    "Q83664600 - Rosa 'Flaming Peace': rose cultivar",
    "Q103168271 - Kronenbourg (Samian Ware Discovery Site): Kronenbourg as Samian Ware discovery site",
    "Q795163 - 1664: beer"
]

[
    "Q1777807 - Heineken UK Limited: defunct brewery",
    "Q64657455 - Scottish and Newcastle Anti-emetic Pre-treatment for Paracetamol Poisoning Study (SNAP): clinical trial",
    "Q34654572 - Scottish and Newcastle antiemetic pre-treatment for paracetamol poisoning study (SNAP).: scientific article"
]

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

[
    "Q150 - French: Romance language",
    "Q8447 - French Wikipedia: French-language edition of Wikipedia",
    "Q3083196 - French of France: French language dialect",
    "Q37351 - Oïl: dialect continuum that includes French and its closest relatives",
    "Q101444601 - French teacher: person who teaches the French language"
]

Output: None of the candidates

Output: None of the candidates


Price fixing

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, Price fixing: On 18 April 2007 theEuropean Commissionfined Heineken  €219.3m,Grolsch€31.65m andBavaria€22.85m for operating aprice fixing cartelin the Netherlands, totalling €273.7m.InBev, (formerlyInterbrew), escaped without a penalty because it provided "decisive information" about the cartel which operated between 1996 and 1999 and others in the EU market. The brewers controlled 95% of the Dutch market, with Heineken claiming a half and the three others 15% each. Neelie Kroessaid she was "very disappointed" that the collusion took place at the very highest (boardroom) level. She added, Heineken, Grolsch, Bavaria and InBev tried to cover their tracks by using code names and abbreviations for secret meetings to carve up the market for beer sold to supermarkets,hotels,restaurantsandcafes. Theprice fixingextended to cheaperown-brandlabels andrebatesfor bars. In 2004 Heineken andKronenbourg(then part ofScottish and Newcastle), the two dominant brewers in France, were fined €2.5m – with the penalty reduced for co-operating. This is simply unacceptable: that major beer suppliers colluded to up prices and to carve up markets among themselves — Neelie Kroes, EU Competition Commissioner

Heineken

Q854383 - Heineken: pale lager beer by the Dutch brewing company Heineken International

Q64549253 - Heineken: painting by Idelle Weber

Q17619042 - 2007-04-18: Polska i Ukraina zorganizują mistrzostwa piłkarskie Euro 2012: Wikinews article

Q17893624 - 2007-04-18: J.R.R. Tolkien: Najnowsza książka "Dzieci Hurina": Wikinews article

Q17893632 - 2007-04-18: Korea Południowa: obawa o stosunki z USA po masakrze w Blacksburgu: Wikinews article

Q17931169 - 2007-04-18: Bankowa komisja śledcza chce przesłuchać Oleksego: Wikinews article

Heineken

Q153075 - Grolsch: brewery in the Netherlands

Q115576141 - Grolsch Oud Bruin: beer type from the Dutch Grolsch brewery

Q18086967 - Kornuit: beer brand of Grolsch

Q61043304 - Grolsch 0.0%: non-alcoholic beer from Grolsch

Heineken

Q980 - Bavaria: federated state in the south of Germany

Q154195 - Kingdom of Bavaria: kingdom in Central Europe between 1806 and 1918, from January 1871 part of the German Empire

Q106318202 - Bavaria: cargo ship built in 1966

Q812285 - Bavarian State Painting Collections: artworks held by the Free State of Bavaria for Alte Pinakothek, Aschaffenburg, Bamberg, Bayreuth, Schleissheim and others

Heineken

Q1416717 - InBev Belgium: public company

Q21042373 - InBev-Baillet Latour Health Prize: Belgian medical award

Q2696011 - InBev-Baillet Latour Fund: Belgian non-profit organization

Q128738 - Anheuser-Busch InBev: Belgian-Brazilian multinational beverage and brewing company

Q6008710 - InBev brands: List of beer brands owned by Anheuser-Busch InBev SA/NV


Fake craft beers

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, Fake craft beers: InIreland, Heineken briefly marketed "Blasket Blonde" inCounty Kerryfrom March 2015 to September 2016, andBeanntraí Bruin parts ofCounty Corkin August 2016, as locally madecraft beers, from invented breweries.

[
    "Q180855 - Heineken: Dutch beer company"
]

[
    "Q162475 - County Cork: county in Ireland",
    "Q56032611 - County Cork in the Eighteenth Century: None",
    "Q56062752 - County Cork and Environs: None"
]

[
    "Q184469 - County Kerry: county in Ireland",
    "Q100562292 - County Kerry Vocational Education Committee (Special Provision) (Gaeltacht) Order, 1953: Irish Statutory Instrument S.I. No. 372/1953",
    "Q100556260 - County Kerry (Jurors Lists and Register of Electors) Order, 1961: Irish Statutory Instrument S.I. No. 204/1961",
    "Q100557919 - County Kerry (Registrars' Districts) Order, 1964: Irish Statutory Instrument S.I. No. 61/1964",
    "Q100556433 - County Kerry (Dispensary Districts) (No. 2) Order, 1961: Irish Statutory Instrument S.I. No. 281/1961"
]

[
    "Q25866325 - craft beer: beer produced in small quantities and/or with higher quality ingredientes",
    "Q134990939 - Craft Beer Tycoon: video game developed by SIN Games",
    "Q66619204 - CRAFT BEER BAR HOLDING ApS: None",
    "Q48804142 - Craft beer in South Korea: None",
    "Q105316384 - CRAFT BEER BASE: None"
]

[
    "Q180855 - Heineken: Dutch beer company",
    "Q16870666 - Heineken: family name",
    "Q854383 - Heineken: pale lager beer by the Dutch brewing company Heineken International",
    "Q64549253 - Heineken: painting by Idelle Weber",
    "Q17425857 - Heinekenia: genus of plants"
]

Output: None of the candidates


Fake craft beers

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, Fake craft beers: InIreland, Heineken briefly marketed "Blasket Blonde" inCounty Kerryfrom March 2015 to September 2016, andBeanntraí Bruin parts ofCounty Corkin August 2016, as locally madecraft beers, from invented breweries.

Heineken_N

P7163 - typically sells: type of goods particular type of shops typically sell

P410 - military or police rank: military or police rank achieved by a person (should usually have a "start time" qualifier), or military or police rank associated with a position

P1128 - employees: total number of employees of a company at a given "point in time" (P585). Most recent data would generally have preferred rank; data for previous years normal rank (not deprecated rank). Add data for recent years, don't overwrite

P2294 - balance of trade: exports minus imports. not to be confused with current account balance and balance of payments

P13595 - Norwegian soldier register 1940 ID: identification number for a Norwegian soldier in the 1940 Norwegian campaign

Q27 - Ireland: country in Northwestern Europe

Q22890 - Ireland: island in the North Atlantic Ocean

Q215530 - Kingdom of Ireland: kingdom on the island of Ireland between 1542 and 1801

Q57695350 - Ireland: part of the United Kingdom (1801–1922)

Heineken_N

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

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

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

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

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

Q184469 - County Kerry: county in Ireland

Q100562292 - County Kerry Vocational Education Committee (Special Provision) (Gaeltacht) Order, 1953: Irish Statutory Instrument S.I. No. 372/1953

Q100556260 - County Kerry (Jurors Lists and Register of Electors) Order, 1961: Irish Statutory Instrument S.I. No. 204/1961

Q100557919 - County Kerry (Registrars' Districts) Order, 1964: Irish Statutory Instrument S.I. No. 61/1964

Q100556433 - County Kerry (Dispensary Districts) (No. 2) Order, 1961: Irish Statutory Instrument S.I. No. 281/1961

Output: None of the candidates

Output: None of the candidates

Output: None of the candidates


Investments in Russia

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, Investments in Russia: At the end of March 2022, over a month after Russia started its war in Ukraine, Heineken announced that it was leaving Russia (including with its other brands there, likeAffligem,Amsteletc.), saying that ownership of the Russian subsidiary was no longer “durable or viable.” But despite this promise Heineken hired more than 240 new staff and launched 61 new products on the Russian market in the last year,[clarification needed]investigators fromFollow the Moneyreported, based on an overview of 2022 by Heineken Russia. The Dutch brewer's Russian subsidiary looked back on “a turbulent year, with many new growth opportunities.” One of these opportunities being the departure ofCoca-ColaandPepsifrom Russia, which Heineken "cynically" used to "enter the non-alcoholic carbonated beverage market". Heineken announced more investments for 2023, including more modern packaging and new flavors.New products launched in Russia included an Irish stout, replacingGuinness(which had been brewed and sold by Heineken, under licence), afterDiageowithdrew from Russia. In August 2023, Heineken announced the sale of its Russian subsidiary to theArnest Groupfor €1 plus a €100 million commitment to repay domestic debt.

[
    "Q180855 - Heineken: Dutch beer company",
    "Q16870666 - Heineken: family name",
    "Q854383 - Heineken: pale lager beer by the Dutch brewing company Heineken International",
    "Q64549253 - Heineken: painting by Idelle Weber",
    "Q17425857 - Heinekenia: genus of plants"
]

[
    "Q159 - Russia: country in Eastern Europe and Northern Asia",
    "Q34266 - Russian Empire: former empire in Eurasia and North America (1721–1917)",
    "Q23890440 - Russia: genus of Ostracoda",
    "Q7737 - Russian: East Slavic language",
    "Q206855 - Russian Wikipedia: Russian-language edition of Wikipedia"
]

[
    "Q382860 - Affligem: municipality in Flemish Brabant, Belgium",
    "Q16010125 - Affligem Brewery: brewery in Belgium",
    "Q2561868 - Affligem beer: None",
    "Q175033 - Affligem Abbey: historic religious building located in Belgium",
    "Q123933329 - Affligem: Belgian periodical"
]

[
    "Q9898 - Amstelveen: town and municipality in North Holland, the Netherlands",
    "Q50720 - Amsterdam Amstel: railway station in Amsterdam, Netherlands",
    "Q185405 - Amstel: river in the Netherlands",
    "Q1947050 - Amstel: street in Amsterdam, the Netherlands",
    "Q2334502 - Jan van Amstel: Northern Renaissance painter (1500-1542)"
]

[
    "Q180855 - Heineken: Dutch beer company",
    "Q16870666 - Heineken: family name",
    "Q854383 - Heineken: pale lager beer by the Dutch brewing company Heineken International",
    "Q64549253 - Heineken: painting by Idelle Weber",
    "Q17425857 - Heinekenia: genus of plants"
]

[
    "Q161140 - Diageo: multinational alcoholic beverages company",
    "Q121811780 - Diageo Global Supply Centre: manufacturing and bottling facility in Scotland",
    "Q5270325 - Diageo Staff Association: British trade union",
    "Q5270327 - Diageo/Hotline Poll: None",
    "Q30255391 - Diageo (Ireland): company in Dublin, Ireland"
]

[
    "Q131056831 - Arnest Group: Russian consumer goods company"
]

[
    "Q2813 - Coca-Cola: carbonated brown-colored soft drink",
    "Q3295867 - The Coca-Cola Company: American multinational beverage corporation",
    "Q20811256 - Coca-Cola Europacific Partners: multinational bottling company",
    "Q1104910 - Coca-Cola HBC: company",
    "Q85753171 - Coca-Cola: painting by Andy Warhol"
]

[
    "Q334800 - PepsiCo: American soft drink company",
    "Q47719 - Pepsi: soft drink owned and manufactured by PepsiCo",
    "Q69662787 - Pepsi: female given name",
    "Q7166507 - Pepsinae: subfamily of wasps",
    "Q18606964 - Pepsis: genus of insects"
]

[
    "Q180855 - Heineken: Dutch beer company",
    "Q16870666 - Heineken: family name",
    "Q854383 - Heineken: pale lager beer by the Dutch brewing company Heineken International",
    "Q64549253 - Heineken: painting by Idelle Weber",
    "Q17425857 - Heinekenia: genus of plants"
]

[
    "Q7411 - Dutch: West Germanic language",
    "Q19513109 - Dutch language specialist: None",
    "Q2668052 - music in Dutch language: music genre",
    "Q152299 - Dutch Language Union: Dutch language regulator",
    "Q2131656 - history of the Dutch language: aspect of history"
]

[
    "Q159 - Russia: country in Eastern Europe and Northern Asia",
    "Q34266 - Russian Empire: former empire in Eurasia and North America (1721–1917)",
    "Q23890440 - Russia: genus of Ostracoda",
    "Q7737 - Russian: East Slavic language",
    "Q206855 - Russian Wikipedia: Russian-language edition of Wikipedia"
]

[
    "Q69306359 - March 8, 2022: date in Gregorian calendar"
]

[
    "Q180855 - Heineken: Dutch beer company",
    "Q16870666 - Heineken: family name",
    "Q854383 - Heineken: pale lager beer by the Dutch brewing company Heineken International",
    "Q64549253 - Heineken: painting by Idelle Weber",
    "Q17425857 - Heinekenia: genus of plants"
]

[
    "Q656 - Saint Petersburg: federal city and former capital of Russia",
    "Q49236 - St. Petersburg: city in Pinellas County, Florida, United States",
    "Q27621 - Saint Petersburg State University: Russian federal state-owned higher education institution",
    "Q628254 - Imperial Academy of Arts: art school in Saint Petersburg, Russia",
    "Q178416 - Saint Petersburg Conservatory: music school in Saint Petersburg"
]

[
    "Q4916 - euro: currency of most countries in the European Union",
    "Q5412157 - Europe PubMed Central: database of biomedical research",
    "Q64899055 - Euro: given name",
    "Q105978809 - Euro: 2021 song by SCH",
    "Q46 - Europe: continent in the Northern Hemisphere"
]

[
    "Q200569 - Dutch: citizens or residents of The Netherlands",
    "Q1058496 - Dutch Americans: ethnic group; Americans of Dutch ancestry",
    "Q1719258 - Dutch People's Union: political party in Netherlands",
    "Q2250692 - Dutch people at Roland Garros: Wikimedia list article",
    "Q5317460 - Dutch people in the United Kingdom: ethnic group, Britons of Dutch ancestry"
]

[
    "Q7737 - Russian: East Slavic language",
    "Q179161 - Russian literature: literature of Russia and in Russian language",
    "Q1381038 - Russian Language Institute: research institute in Moscow, Russia",
    "Q4423780 - dictionary of the Russian language: language version of dictionary",
    "Q101444477 - Russian teacher: person who teaches the Russian language"
]

[
    "Q845473 - 240: natural number",
    "Q3542526 - 4-8-0: locomotive wheel arrangement",
    "Q30032 - 240: year",
    "Q3226372 - 2401: natural number",
    "Q784283 - 2400 Derevskaya: asteroid"
]

[
    "Q382860 - Affligem: municipality in Flemish Brabant, Belgium",
    "Q16010125 - Affligem Brewery: brewery in Belgium",
    "Q2561868 - Affligem beer: None",
    "Q175033 - Affligem Abbey: historic religious building located in Belgium",
    "Q123933329 - Affligem: Belgian periodical"
]

[
    "Q9898 - Amstelveen: town and municipality in North Holland, the Netherlands",
    "Q50720 - Amsterdam Amstel: railway station in Amsterdam, Netherlands",
    "Q185405 - Amstel: river in the Netherlands",
    "Q1947050 - Amstel: street in Amsterdam, the Netherlands",
    "Q2334502 - Jan van Amstel: Northern Renaissance painter (1500-1542)"
]

[
    "Q684722 - 1 euro coin: euro coin with a value of one euro",
    "Q2903520 - 100 euro note: euro banknote",
    "Q116603623 - €100: 2019 video game for Microsoft Windows by КиКо.",
    "Q2419695 - 10 euro note: euro banknote",
    "Q74205544 - €100-billion budget proposed for Europe’s next big research programme: journal article; published in Nature on 2018-05-03"
]

Output: None of the candidates

Output: None of the candidates

Output: None of the candidates

Output: None of the candidates


Investments in Russia

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, Investments in Russia: At the end of March 2022, over a month after Russia started its war in Ukraine, Heineken announced that it was leaving Russia (including with its other brands there, likeAffligem,Amsteletc.), saying that ownership of the Russian subsidiary was no longer “durable or viable.” But despite this promise Heineken hired more than 240 new staff and launched 61 new products on the Russian market in the last year,[clarification needed]investigators fromFollow the Moneyreported, based on an overview of 2022 by Heineken Russia. The Dutch brewer's Russian subsidiary looked back on “a turbulent year, with many new growth opportunities.” One of these opportunities being the departure ofCoca-ColaandPepsifrom Russia, which Heineken "cynically" used to "enter the non-alcoholic carbonated beverage market". Heineken announced more investments for 2023, including more modern packaging and new flavors.New products launched in Russia included an Irish stout, replacingGuinness(which had been brewed and sold by Heineken, under licence), afterDiageowithdrew from Russia. In August 2023, Heineken announced the sale of its Russian subsidiary to theArnest Groupfor €1 plus a €100 million commitment to repay domestic debt.

Heineken

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

Heineken

Q382860 - Affligem: municipality in Flemish Brabant, Belgium

Q16010125 - Affligem Brewery: brewery in Belgium

Q175033 - Affligem Abbey: historic religious building located in Belgium

Q123933329 - Affligem: Belgian periodical

Heineken

Q9898 - Amstelveen: town and municipality in North Holland, the Netherlands

Q50720 - Amsterdam Amstel: railway station in Amsterdam, Netherlands

Q185405 - Amstel: river in the Netherlands

Q1947050 - Amstel: street in Amsterdam, the Netherlands

Q2334502 - Jan van Amstel: Northern Renaissance painter (1500-1542)

Heineken

Heineken_Russia

Heineken_Russia

Q41675 - Guinness World Records: reference book listing world records

Q2319266 - Guinness Brewery: Brewery in Dublin, Ireland

Heineken_Russia

Q2647467 - non-alcoholic beverage: beverage that doesn't contain alcohol

Q26710030 - non-alcoholic beverage industry: None

Q36082620 - Non-alcoholic beverage and caffeine consumption and mortality: the Leisure World Cohort Study: scientific article

Q33280489 - Non-alcoholic beverages and risk of bladder cancer in Uruguay: scientific article published on 29 March 2007

Q42803927 - Non-alcoholic beverages, unknown influence on cell proliferation - an in vitro study: scientific article published on January 2014

Heineken_Russia

Q2813 - Coca-Cola: carbonated brown-colored soft drink

Q3295867 - The Coca-Cola Company: American multinational beverage corporation

Q20811256 - Coca-Cola Europacific Partners: multinational bottling company

Q85753171 - Coca-Cola: painting by Andy Warhol

Heineken_Russia

Q334800 - PepsiCo: American soft drink company

Q47719 - Pepsi: soft drink owned and manufactured by PepsiCo

Heineken_Russia

Q65957296 - Beer: German badminton player

Q6106 - Portland: city and county seat of Multnomah County, Oregon, United States

Heineken_Russia

Q63993001 - Little Creatures Pale Ale: beer from Australia

Q23860565 - Pale ale: article in Otto's encyclopedia

Q94240236 - Pale Ale and Digestion: None

Heineken_Russia

Heineken_Russia

Q193183 - Alès: commune in Gard, Occitanie, France

Q230051 - Alexa Internet: former American web traffic analysis company

Heineken_Russia

Heineken_Russia

Q533203 - Bockhorn: municipality of Germany

Q57720 - Bockau: municipality of Germany

Heineken_Russia

Q1137593 - Lagerstroemia speciosa: species of plant

Q775229 - Lagerstroemia: genus of plants

Q1148692 - Lagerstroemia indica: species of plant

Heineken_Russia

Q948831 - Plzeňský Prazdroj: Czech brewery company

Q331630 - Pilsner Urquell: beer trademark

Heineken_Russia

Heineken_Russia

Q1571063 - Saison: river in the French Basque Country

Q3464665 - television series season: set of episodes produced for a television series

Q18749173 - Saison: Michelin rating restaurant

Heineken_Russia

Q75986351 - India Alexandra Stewart: (born 1998)

Q75741923 - India Alexandra Scarlett Blakey: (born 2007)

Q213380 - Supreme Court of India: Highest court of jurisdiction in the Republic of India

Heineken_Russia

Heineken_Russia

Heineken_Russia

Q1750238 - maibock: beer style
Q135762045 - Maibock: family name

Heineken_Russia

Heineken_Russia

Q3347894 - Oatmeal stout: None
Q217825 - stout: dark beer

Heineken_Russia

Q2036617 - 2-4-0: locomotive wheel arrangement

Q67123644 - porter: group of membrane transport proteins that utilize a carrier-mediated process to catalyze uniport, antiport, or symport

Q1650716 - doorkeeper: person whose job it is to monitor and open the door of a semi-public building

Heineken_Russia

Q131413 - wheat beer: beer brewed in part with wheat

Q113923077 - Wheat Beer for Prevention of Delirium in Intensive Care Patients: clinical trial

Q93054530 - Wheat beer challenge: scientific article published on 01 July 2019

Output: None of the candidates

Output: None of the candidates

Output: None of the candidates

Output: None of the candidates

Output: None of the candidates