PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT DISTINCT ?headquartersLocation ?headquartersLocationLabel WHERE {
  wd:Q7184 wdt:P159 ?headquartersLocation .
  OPTIONAL {
    ?headquartersLocation rdfs:label ?headquartersLocationLabel FILTER ( LANG( ?headquartersLocationLabel ) = "en" )
  }
}

Got 1 row and 2 columns:
| headquartersLocation       | headquartersLocationLabel |
| -------------------------- | ------------------------- |
| City of Brussels (wd:Q239) | City of Brussels (en)     |

The NATO headquarters are located in the City of Brussels.

[System]
You are a question answering assistant. Your job is to generate a SPARQL query to answer a given user question.

You have access to the following knowledge graphs:
wikidata at https://qlever.cs.uni-freiburg.de/api/wikidata

You can use the following SPARQL prefixes implicitly in all functions:
cc: <http://creativecommons.org/ns#
data: <https://www.wikidata.org/wiki/Special:EntityData/
dct: <http://purl.org/dc/terms/
geo: <http://www.opengis.net/ont/geosparql#
geof: <http://www.opengis.net/def/function/geosparql/
imdb: <https://www.imdb.com/
math: <http://www.w3.org/2005/xpath-functions/math#
ontolex: <http://www.w3.org/ns/lemon/ontolex#
owl: <http://www.w3.org/2002/07/owl#
p: <http://www.wikidata.org/prop/
pq: <http://www.wikidata.org/prop/qualifier/
pqn: <http://www.wikidata.org/prop/qualifier/value-normalized/
pqv: <http://www.wikidata.org/prop/qualifier/value/
pr: <http://www.wikidata.org/prop/reference/
prn: <http://www.wikidata.org/prop/reference/value-normalized/
prov: <http://www.w3.org/ns/prov#
prv: <http://www.wikidata.org/prop/reference/value/
ps: <http://www.wikidata.org/prop/statement/
psn: <http://www.wikidata.org/prop/statement/value-normalized/
psv: <http://www.wikidata.org/prop/statement/value/
qfn: <http://qlever.cs.uni-freiburg.de/function#
ql: <http://qlever.cs.uni-freiburg.de/builtin-functions/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
ref: <http://www.wikidata.org/reference/
s: <http://www.wikidata.org/entity/statement/
schema: <http://schema.org/
skos: <http://www.w3.org/2004/02/skos/core#
v: <http://www.wikidata.org/value/
wd: <http://www.wikidata.org/entity/
wdno: <http://www.wikidata.org/prop/novalue/
wdt: <http://www.wikidata.org/prop/direct/
wdtn: <http://www.wikidata.org/prop/direct-normalized/
wikibase: <http://wikiba.se/ontology#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
dc: <http://purl.org/dc/elements/1.1/
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
qb: <http://purl.org/linked-data/cube#
void: <http://rdfs.org/ns/void#

You should follow a step-by-step approach to generate the SPARQL query:
1. Determine possible entities and properties implied by the user question.
2. Use the functions to search for entities and properties in the knowledge graphs. Where applicable, constrain the searches with already identified entities and properties.
3. Gradually build up the SPARQL query using the identified entities and properties. Start with simple queries and add more complexity as needed. Use the execute function to get feedback on intermediate queries. You can go back and forth between knowledge graph searches and SPARQL query executions to refine the query.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

Additional rules:
1. Explain your thought process before and after each step and function call.
2. Do not assume or make up any entities or properties without verifying them with the knowledge graphs and functions.
3. The SPARQL query should always return the actual identifiers / IRIs of the items in its result. It additionally may return labels or other human-readable information, but they are optional and should be put within optional clauses unless explicitly requested by the user.
4. Do not stop early if there are still obvious improvements to be made to the SPARQL query. For example, keep refining your SPARQL query if its result contains irrelevant items or is missing items you expected.
5. Do not perform additional computation (e.g. filtering, sorting, calculations) on the result of the SPARQL query to determine the answer. All computation should be done solely within SPARQL.
6. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
7. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] where are the nato headquarters located?

[Assistant] Let's start by looking at some similar examples.

[Tool]
Example 1:
Question:
where is eu headquarters located?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q458 wdt:P159 ?x .
}

Using entities:
European Union, also known as E.U., Europe, eu (wd:Q458): political and economic union of 27 European states

Using properties:
headquarters location, also known as headquarters locality, seat, headquarters town, HQ, HQ location (wd:P159 as wdt): city or town where an organization's headquarters is or has been situated. Use P276 qualifier for specific building, significant place

Example 2:
Question:
where are the headquarters of the united nations organization found?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q1065 wdt:P159 ?x .
}

Using entities:
United Nations, also known as the U.N., the UN, U.N., UN, United Nations Organization (wd:Q1065): global international and intergovernmental organization

Using properties:
headquarters location, also known as headquarters locality, seat, headquarters town, HQ, HQ location (wd:P159 as wdt): city or town where an organization's headquarters is or has been situated. Use P276 qualifier for specific building, significant place

Example 3:
Question:
where is the main headquarters of the un?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q1065 wdt:P159 ?x .
}

Using entities:
United Nations, also known as the U.N., the UN, U.N., UN, United Nations Organization (wd:Q1065): global international and intergovernmental organization

Using properties:
headquarters location, also known as headquarters locality, seat, headquarters town, HQ, HQ location (wd:P159 as wdt): city or town where an organization's headquarters is or has been situated. Use P276 qualifier for specific building, significant place

[Assistant] From the similar examples, the property "headquarters location" (wdt:P159) is used to find the location of the headquarters of an organization. The entity for NATO needs to be identified first. I will search for the entity "NATO" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. NATO, also known as North Atlantic Treaty Organization, North Atlantic Treaty Organisation, NATO Alliance, North Atlantic Alliance (wd:Q7184): intergovernmental military alliance between 32 member states
2. .nato (wd:Q753137): top-level domain
3. NATO (wd:Q1940923): 1994 studio album by Laibach
4. National Association of Theatre Owners, also known as NATO (wd:Q2076915): American motion picture exhibition trade organization
5. nato wood, also known as mora, mora wood, nato (wd:Q3337031): the wood from tropical trees in the genus Mora
6. Nåtö (wd:Q24453737): island in Finland Proper, Finland
7. Nato (wd:Q6980174): human settlement in Madagascar
8. Nato (wd:Q10605515): island in Lemland, Åland Islands, Finland
9. Jeanne Natoire, also known as Mademoiselle Natoire, Mlle Natoire, Nato (wd:Q34725664): French Painter (c. 1700–1776), painter
10. naTo, also known as Cinématèque in der naTo (wd:Q1961846): cultural centre and cinema in Leipzig

[Assistant] The entity for NATO is wd:Q7184. Based on the similar examples, the property for headquarters location is wdt:P159. I will now construct a SPARQL query to find the headquarters location of NATO.

[Tool]
Got 1 row and 2 columns:
| headquartersLocation       | headquartersLocationLabel |
| -------------------------- | ------------------------- |
| City of Brussels (wd:Q239) | City of Brussels (en)     |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the location of NATO headquarters using the property 'headquarters location' (wdt:P159) for the NATO entity (wd:Q7184). The query returns the City of Brussels, which is the accurate and complete answer to the user's question. The query also optionally retrieves the English label for better readability. The output is correct and complete.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?book ?bookLabel ?publicationDate WHERE {
  ?book wdt:P50 wd:Q207 .
  OPTIONAL {
    ?book wdt:P577 ?publicationDate .
  }
  OPTIONAL {
    ?book rdfs:label ?bookLabel FILTER ( LANG( ?bookLabel ) = "en" )
  }
}
ORDER BY DESC ( ?publicationDate )
LIMIT 1

The title of George Bush's newest book is "Portraits of Courage" published in 2017.

[System]
You are a question answering assistant. Your job is to generate a SPARQL query to answer a given user question.

You have access to the following knowledge graphs:
wikidata at https://qlever.cs.uni-freiburg.de/api/wikidata

You can use the following SPARQL prefixes implicitly in all functions:
cc: <http://creativecommons.org/ns#
data: <https://www.wikidata.org/wiki/Special:EntityData/
dct: <http://purl.org/dc/terms/
geo: <http://www.opengis.net/ont/geosparql#
geof: <http://www.opengis.net/def/function/geosparql/
imdb: <https://www.imdb.com/
math: <http://www.w3.org/2005/xpath-functions/math#
ontolex: <http://www.w3.org/ns/lemon/ontolex#
owl: <http://www.w3.org/2002/07/owl#
p: <http://www.wikidata.org/prop/
pq: <http://www.wikidata.org/prop/qualifier/
pqn: <http://www.wikidata.org/prop/qualifier/value-normalized/
pqv: <http://www.wikidata.org/prop/qualifier/value/
pr: <http://www.wikidata.org/prop/reference/
prn: <http://www.wikidata.org/prop/reference/value-normalized/
prov: <http://www.w3.org/ns/prov#
prv: <http://www.wikidata.org/prop/reference/value/
ps: <http://www.wikidata.org/prop/statement/
psn: <http://www.wikidata.org/prop/statement/value-normalized/
psv: <http://www.wikidata.org/prop/statement/value/
qfn: <http://qlever.cs.uni-freiburg.de/function#
ql: <http://qlever.cs.uni-freiburg.de/builtin-functions/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
ref: <http://www.wikidata.org/reference/
s: <http://www.wikidata.org/entity/statement/
schema: <http://schema.org/
skos: <http://www.w3.org/2004/02/skos/core#
v: <http://www.wikidata.org/value/
wd: <http://www.wikidata.org/entity/
wdno: <http://www.wikidata.org/prop/novalue/
wdt: <http://www.wikidata.org/prop/direct/
wdtn: <http://www.wikidata.org/prop/direct-normalized/
wikibase: <http://wikiba.se/ontology#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
dc: <http://purl.org/dc/elements/1.1/
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
qb: <http://purl.org/linked-data/cube#
void: <http://rdfs.org/ns/void#

You should follow a step-by-step approach to generate the SPARQL query:
1. Determine possible entities and properties implied by the user question.
2. Use the functions to search for entities and properties in the knowledge graphs. Where applicable, constrain the searches with already identified entities and properties.
3. Gradually build up the SPARQL query using the identified entities and properties. Start with simple queries and add more complexity as needed. Use the execute function to get feedback on intermediate queries. You can go back and forth between knowledge graph searches and SPARQL query executions to refine the query.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

Additional rules:
1. Explain your thought process before and after each step and function call.
2. Do not assume or make up any entities or properties without verifying them with the knowledge graphs and functions.
3. The SPARQL query should always return the actual identifiers / IRIs of the items in its result. It additionally may return labels or other human-readable information, but they are optional and should be put within optional clauses unless explicitly requested by the user.
4. Do not stop early if there are still obvious improvements to be made to the SPARQL query. For example, keep refining your SPARQL query if its result contains irrelevant items or is missing items you expected.
5. Do not perform additional computation (e.g. filtering, sorting, calculations) on the result of the SPARQL query to determine the answer. All computation should be done solely within SPARQL.
6. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
7. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] what is the title of george bush's new book?

[Assistant] Let's start by looking at some similar examples.

[Tool]
Example 1:
Question:
when did george w bush take office?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q207 p:P39 ?y .
  ?y ps:P39 wd:Q11696 ; pq:P580 ?x .
}

Using entities:
President of the United States, also known as US President, U.S. President, United States President, the president of the United States, President of the U.S. (wd:Q11696): head of state and head of government of the United States of America
George W. Bush, also known as GWB, POTUS 43, George Bush, President Bush, Bush Jr. (wd:Q207): President of the United States from 2001 to 2009, motivational speaker, rugby union player, military officer, autobiographer, businessperson, statesperson, politician, financier, painter

Using properties:
position held, also known as function, held position, holds position, job, office held (wd:P39 as p/ps): subject currently or formerly holds the object position or public office
start time, also known as start date, since, valid, join time, joined (wd:P580 as pq): time an entity begins to exist or a statement starts being valid, point in time

Example 2:
Question:
where is george bush from?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q207 wdt:P19 ?x .
}

Using entities:
George W. Bush, also known as GWB, POTUS 43, George Bush, President Bush, Bush Jr. (wd:Q207): President of the United States from 2001 to 2009, motivational speaker, rugby union player, military officer, autobiographer, businessperson, statesperson, politician, financier, painter

Using properties:
place of birth, also known as POB, location of birth, location born, born in, birthplace (wd:P19 as wdt): most specific known birth location of a person, animal or fictional character, location

Example 3:
Question:
when was george w bush sworn in?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q207 p:P39 ?y .
  ?y ps:P39 wd:Q11696 ; pq:P580 ?x .
}

Using entities:
President of the United States, also known as US President, U.S. President, United States President, the president of the United States, President of the U.S. (wd:Q11696): head of state and head of government of the United States of America
George W. Bush, also known as GWB, POTUS 43, George Bush, President Bush, Bush Jr. (wd:Q207): President of the United States from 2001 to 2009, motivational speaker, rugby union player, military officer, autobiographer, businessperson, statesperson, politician, financier, painter

Using properties:
position held, also known as function, held position, holds position, job, office held (wd:P39 as p/ps): subject currently or formerly holds the object position or public office
start time, also known as start date, since, valid, join time, joined (wd:P580 as pq): time an entity begins to exist or a statement starts being valid, point in time

[Assistant]
The examples show how to query information about George W. Bush (wd:Q207) and his properties. To find the title of George Bush's new book, I need to identify the entity for George Bush and find a property related to books or authored works. Then I can filter for the most recent book.

First, I will search for the entity "George Bush" to confirm the correct entity. Then I will search for properties related to books or authored works for that entity.

[Tool]
Top 10 entity alternatives:
1. George W. Bush, also known as GWB, POTUS 43, George Bush, President Bush, Bush Jr. (wd:Q207): President of the United States from 2001 to 2009, motivational speaker, rugby union player, military officer, autobiographer, businessperson, statesperson, politician, financier, painter
2. George H. W. Bush, also known as G H W Bush, George W. Bush Senior, GHWB, GHW Bush, G.H.W. Bush (wd:Q23505): President of the United States from 1989 to 1993, baseball player, aircraft pilot, autobiographer, naval officer, statesperson, entrepreneur, politician, diplomat
3. George Bush (wd:Q5537488): American biblical scholar and pastor (1796–1859), pastor, writer
4. George Bush, also known as George Edward Bush (wd:Q28445429): association football player (1883-1936), association football player
5. George Bush (wd:Q5537484): racing driver, engineer
6. George Bush, also known as Simmons (wd:Q107224832): person in the Aberdeen Register of Returned Convicts 1869-1939
7. George Bush (wd:Q47512688): painting by Daniel Bennett Schwartz
8. George Bush (wd:Q47509378): painting by Ronald N. Sherr
9. George Bush (wd:Q100766406): basketball player
10. George Bush [bushgeorg0026233] (wd:Q103871655): article in Electronic Enlightenment

[Assistant]
There are multiple entities for George Bush. The two most relevant are:
- George W. Bush (wd:Q207), former President of the United States from 2001 to 2009
- George H. W. Bush (wd:Q23505), former President of the United States from 1989 to 1993

Since the question does not specify which George Bush, I will assume it refers to George W. Bush (wd:Q207), the more commonly referenced one.

Next, I will search for properties related to books or authored works for George W. Bush (wd:Q207).

[Tool]
Top 10 property alternatives:
1. SELIBR ID, also known as LIBRIS, National Library of Sweden, SE-LIBR ID (wd:P906 as wdt/p/wdtn): identifier per National Library of Sweden Libris library catalog
2. languages spoken, written or signed, also known as language of expression, language, wrote language, writes language, uses language (wd:P1412 as wdt/p): language(s) that a person or a people speaks, writes or signs, including the native language(s)
3. described by source, also known as mentioned in, source of item, reviewed in, mentioned in news article, talked about in (wd:P1343 as wdt/p): work where this item is described, attested in
4. FAST ID, also known as Faceted Application of Subject Terminology ID, FAST subject heading, fst, worldcat.org/fast (wd:P2163 as wdt/p/wdtn): authority control identifier in WorldCat's “FAST Linked Data” authority file
5. official website, also known as site (official), home page, site official, URL, URL (official) (wd:P856 as wdt/p): URL of the official page of an item (current or former). Usage: ...but see the "Hijacked or dead websites" section of the Talk page, URL
6. writing language, also known as languages of writings, languages written, language written, writing languages, language of works (wd:P6886 as wdt/p): language in which the writer has written their work, languages spoken, written or signed
7. given name, also known as name, proper name, personal name, middle name, forename (wd:P735 as wdt/p): first name or another given name of this person; values used with the property should not link disambiguations nor family names, name
8. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as wdt/p): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
9. Open Library ID, also known as Open Library book ID, OpenLibrary work ID, Open Library work ID, OpenLibrary identifier, Open Library identifier (wd:P648 as wdt/p/wdtn): identifier for a work ("W"), edition ("M") or author ("A") for book data of the Internet Archive
10. sport, also known as play, plays, sport played, sports (wd:P641 as wdt/p): sport that the subject participates or participated in or is associated with

No other items found

[Assistant] The search for properties related to "book" for George W. Bush (wd:Q207) did not return a direct property for authored books or works. I will try searching for properties related to "author" or "written work" for George W. Bush to find a suitable property for his books.

[Tool]
Top 10 property alternatives:
1. Commons Creator page, also known as creator page, creator template (wd:P1472 as wdt/p): name of Commons Infobox template residing in "Creator" namespace on Wikimedia Commons
2. place of birth, also known as POB, location of birth, location born, born in, birthplace (wd:P19 as wdt/p): most specific known birth location of a person, animal or fictional character, location
3. date of birth, also known as year of birth, birthdate, DOB, born on, born (wd:P569 as wdt/p): date on which the subject was born, inception
4. Project Gutenberg author ID, also known as Gutenberg ID, gutenberg.org/ebooks/author/, Project Gutenberg ID (author) (wd:P1938 as wdt/p/wdtn): author identifier at Project Gutenberg
5. educated at, also known as graduated from, graduate of, place of education, school attended, schooled at (wd:P69 as wdt/p): educational institution attended by subject, affiliation
6. given name, also known as name, proper name, personal name, middle name, forename (wd:P735 as wdt/p): first name or another given name of this person; values used with the property should not link disambiguations nor family names, name
7. member of political party, also known as political party member, political party, party membership, party, member of party (wd:P102 as wdt/p): the political party of which a person is or has been a member or otherwise affiliated, member of
8. member of, also known as band member of, membership, member of musical group, in musical group, be member of (wd:P463 as wdt/p): organization, club or musical group to which the subject belongs...ical position, such as a member of parliament (use P39 for that), part of
9. official website, also known as site (official), home page, site official, URL, URL (official) (wd:P856 as wdt/p): URL of the official page of an item (current or former). Usage: ...but see the "Hijacked or dead websites" section of the Talk page, URL
10. SBN author ID, also known as ICCU, SBN, SBN identifier, Servizio Bibliotecario Nazionale (wd:P396 as wdt/p): identifier issued by National Library Service (SBN) of Italy

No other items found

[Assistant] The search for properties related to "author" for George W. Bush (wd:Q207) did not return a direct property for authored books either. I will try a different approach: I will search for books authored by George W. Bush by looking for items that have George W. Bush as an author or creator. This means searching for entities where the property "author" or "creator" points to George W. Bush.

[Tool]
Top 10 property alternatives:
1. theorized by, also known as author, supported by, suggested by, proposer, proposed by (wd:P8403 as pqv/psv/prv/wdtn/wdt/pq/psn/pr/ps/pqn/p/prn): subject who suggested or proposed this concept or immaterial invention
2. lyricist, also known as text poet, writer (of song lyrics), words by, text writer, text by (wd:P676 as pqv/psv/prv/wdtn/wdt/pq/psn/pr/ps/pqn/p/prn): author of song lyrics, author
3. author, also known as writer, written by, poet, playwright, maker (wd:P50 as pqv/psv/prv/wdtn/wdt/pq/psn/pr/ps/pqn/p/prn): main creator(s) of a written work (use on works, not humans); us...hor name string) when Wikidata item is unknown or does not exist, creator
4. notable work, also known as artwork, wrote, writer of, works, work (wd:P800 as pqv/psv/prv/wdtn/wdt/pq/psn/pr/ps/pqn/p/prn): notable scientific, artistic or literary work, or other work of significance among subject's works
5. author given names, also known as given name, given names, first name, author first names, author first name (wd:P9687 as pqv/psv/prv/wdtn/wdt/pq/psn/pr/ps/pqn/p/prn): qualifier for string representation of given or secondary sortin...presented in a bibliographic reference file (for example BibTeX), given name
6. used by, also known as armiger, user, played by, of (wd:P1535 as pqv/psv/prv/wdtn/wdt/pq/psn/pr/ps/pqn/p/prn): item or concept that makes use of the subject (use sub-properties when appropriate)
7. operator, also known as offered by, operated by, provided by, run by, service operator (wd:P137 as pqv/psv/prv/wdtn/wdt/pq/psn/pr/ps/pqn/p/prn): person, profession, organization or entity that operates the equipment, facility, or service, used by
8. creator, also known as created by, visual artist, sculptor, sculpted by, realized by (wd:P170 as pqv/psv/prv/wdtn/wdt/pq/psn/pr/ps/pqn/p/prn): maker of this creative work or other object (where no more specific property exists)
9. author last names, also known as author last name, surnames, surname, last names, last name (wd:P9688 as pqv/psv/prv/wdtn/wdt/pq/psn/pr/ps/pqn/p/prn): qualifier to provide string representation of family or primary ...presented in a bibliographic reference file (for example BibTeX), family name
10. object named as, also known as original wording, place name string, printed as, reference wording, [sic] (wd:P1932 as pqv/psv/prv/wdtn/wdt/pq/psn/pr/ps/pqn/p/prn): use as qualifier to indicate how the object's value was given in the source, name

[Assistant] The property "author" (wdt:P50) is used to indicate the main creator(s) of a written work. I will use this property to find books authored by George W. Bush (wd:Q207). I will query for items where the author is George W. Bush and retrieve the titles of those items. To find the newest book, I will order by publication date if available.

[Tool]
Got 1 row and 3 columns:
| book                                | bookLabel                 | publicationDate                     |
| ----------------------------------- | ------------------------- | ----------------------------------- |
| Portraits of Courage (wd:Q29097574) | Portraits of Courage (en) | 2017-01-01T00:00:00Z (xsd:dateTime) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly identifies George W. Bush (wd:Q207) as the author and retrieves his books ordered by publication date in descending order, limiting the result to the newest book. The query returns the book's identifier, label, and publication date, which matches the answer given: "Portraits of Courage" published in 2017. The query follows best practices by returning the actual item identifier and optional labels and dates. The answer is accurate and complete based on the query results.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?placeOfBirth ?placeOfBirthLabel WHERE {
  wd:Q36844 wdt:P19 ?placeOfBirth .
  OPTIONAL {
    ?placeOfBirth rdfs:label ?placeOfBirthLabel FILTER ( LANG( ?placeOfBirthLabel ) = "en" )
  }
}

Got 1 row and 2 columns:
| placeOfBirth               | placeOfBirthLabel  |
| -------------------------- | ------------------ |
| Saint Michael (wd:Q819170) | Saint Michael (en) |

Wikidata does not have explicit information about where Rihanna was raised. The only available location information is her place of birth, which is Saint Michael.

[System]
You are a question answering assistant. Your job is to generate a SPARQL query to answer a given user question.

You have access to the following knowledge graphs:
wikidata at https://qlever.cs.uni-freiburg.de/api/wikidata

You can use the following SPARQL prefixes implicitly in all functions:
cc: <http://creativecommons.org/ns#
data: <https://www.wikidata.org/wiki/Special:EntityData/
dct: <http://purl.org/dc/terms/
geo: <http://www.opengis.net/ont/geosparql#
geof: <http://www.opengis.net/def/function/geosparql/
imdb: <https://www.imdb.com/
math: <http://www.w3.org/2005/xpath-functions/math#
ontolex: <http://www.w3.org/ns/lemon/ontolex#
owl: <http://www.w3.org/2002/07/owl#
p: <http://www.wikidata.org/prop/
pq: <http://www.wikidata.org/prop/qualifier/
pqn: <http://www.wikidata.org/prop/qualifier/value-normalized/
pqv: <http://www.wikidata.org/prop/qualifier/value/
pr: <http://www.wikidata.org/prop/reference/
prn: <http://www.wikidata.org/prop/reference/value-normalized/
prov: <http://www.w3.org/ns/prov#
prv: <http://www.wikidata.org/prop/reference/value/
ps: <http://www.wikidata.org/prop/statement/
psn: <http://www.wikidata.org/prop/statement/value-normalized/
psv: <http://www.wikidata.org/prop/statement/value/
qfn: <http://qlever.cs.uni-freiburg.de/function#
ql: <http://qlever.cs.uni-freiburg.de/builtin-functions/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
ref: <http://www.wikidata.org/reference/
s: <http://www.wikidata.org/entity/statement/
schema: <http://schema.org/
skos: <http://www.w3.org/2004/02/skos/core#
v: <http://www.wikidata.org/value/
wd: <http://www.wikidata.org/entity/
wdno: <http://www.wikidata.org/prop/novalue/
wdt: <http://www.wikidata.org/prop/direct/
wdtn: <http://www.wikidata.org/prop/direct-normalized/
wikibase: <http://wikiba.se/ontology#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
dc: <http://purl.org/dc/elements/1.1/
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
qb: <http://purl.org/linked-data/cube#
void: <http://rdfs.org/ns/void#

You should follow a step-by-step approach to generate the SPARQL query:
1. Determine possible entities and properties implied by the user question.
2. Use the functions to search for entities and properties in the knowledge graphs. Where applicable, constrain the searches with already identified entities and properties.
3. Gradually build up the SPARQL query using the identified entities and properties. Start with simple queries and add more complexity as needed. Use the execute function to get feedback on intermediate queries. You can go back and forth between knowledge graph searches and SPARQL query executions to refine the query.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

Additional rules:
1. Explain your thought process before and after each step and function call.
2. Do not assume or make up any entities or properties without verifying them with the knowledge graphs and functions.
3. The SPARQL query should always return the actual identifiers / IRIs of the items in its result. It additionally may return labels or other human-readable information, but they are optional and should be put within optional clauses unless explicitly requested by the user.
4. Do not stop early if there are still obvious improvements to be made to the SPARQL query. For example, keep refining your SPARQL query if its result contains irrelevant items or is missing items you expected.
5. Do not perform additional computation (e.g. filtering, sorting, calculations) on the result of the SPARQL query to determine the answer. All computation should be done solely within SPARQL.
6. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
7. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] where was rihanna raised?

[Assistant] Let's start by looking at some similar examples.

[Tool]
Example 1:
Question:
where did rihanna grow up?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q36844 wdt:P19 ?x .
}

Using entities:
Rihanna, also known as Barbadian singer, Rihana, Robyn Fenty, Robyn Rihanna Fenty (wd:Q36844): Barbadian singer and actress, singer

Using properties:
place of birth, also known as POB, location of birth, location born, born in, birthplace (wd:P19 as wdt): most specific known birth location of a person, animal or fictional character, location

Example 2:
Question:
where did rihanna come from?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q36844 wdt:P19 ?x .
}

Using entities:
Rihanna, also known as Barbadian singer, Rihana, Robyn Fenty, Robyn Rihanna Fenty (wd:Q36844): Barbadian singer and actress, singer

Using properties:
place of birth, also known as POB, location of birth, location born, born in, birthplace (wd:P19 as wdt): most specific known birth location of a person, animal or fictional character, location

Example 3:
Question:
what county is rihanna from?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q36844 wdt:P27 ?x .
}

Using entities:
Rihanna, also known as Barbadian singer, Rihana, Robyn Fenty, Robyn Rihanna Fenty (wd:Q36844): Barbadian singer and actress, singer

Using properties:
country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as wdt): the object is a country that recognizes the subject as its citizen, country

[Assistant]
From the similar examples, I see that Rihanna is identified as wd:Q36844 in Wikidata. The property used to find where she was raised or where she grew up is often the place of birth (wdt:P19). However, place of birth might not always be the same as where someone was raised.

I will now search for properties related to "raised" or "grew up" for the entity Rihanna (wd:Q36844) to find a more accurate property for where she was raised.

[Tool]
Top 10 property alternatives:
1. wears, also known as wore, wearing, uniform, outfit, garment (wd:P3828 as wdt/p): clothing or accessory worn on subject's body, item operated
2. place of birth, also known as POB, location of birth, location born, born in, birthplace (wd:P19 as wdt/p): most specific known birth location of a person, animal or fictional character, location
3. date of birth, also known as year of birth, birthdate, DOB, born on, born (wd:P569 as wdt/p): date on which the subject was born, inception
4. described by source, also known as mentioned in, source of item, reviewed in, mentioned in news article, talked about in (wd:P1343 as wdt/p): work where this item is described, attested in
5. height, also known as heighth, size, depth over terrain (wd:P2048 as wdt/p): vertical length of an entity, length
6. award received, also known as win, winner of, recognition title, received award, prize received (wd:P166 as wdt/p): award or recognition received by a person, organization or creative work
7. owner of, also known as owns, owns property, shareholder of (wd:P1830 as wdt/p): entities owned by the subject
8. child, also known as has son, kids, mother of, kid, issue (wd:P40 as wdt/p): subject has object as child. Do not use for stepchildren—use "relative" (P1038), qualified with "type of kinship" (P1039), significant person, relative
9. influenced by, also known as favorite player, has influence, informed by, role model (wd:P737 as wdt/p): this person, idea, etc. is informed by that other person, idea, etc., e.g. “Heidegger was influenced by Aristotle”
10. languages spoken, written or signed, also known as language of expression, language, wrote language, writes language, uses language (wd:P1412 as wdt/p): language(s) that a person or a people speaks, writes or signs, including the native language(s)

No other items found

[Assistant]
There is no direct property for "raised" or "grew up" for Rihanna in the properties related to her. The closest relevant property is "place of birth" (wdt:P19), which might be used as a proxy for where she was raised.

I will now query the place of birth for Rihanna (wd:Q36844) to see if that can answer the question.

[Tool]
Got 1 row and 2 columns:
| placeOfBirth               | placeOfBirthLabel  |
| -------------------------- | ------------------ |
| Saint Michael (wd:Q819170) | Saint Michael (en) |

[Assistant] Rihanna was born in Saint Michael. Since there is no direct property for where she was raised, the place of birth is the best available information to answer the question. I will now provide the final answer.

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The system correctly identified Rihanna's place of birth as Saint Michael, which is indeed where she was born. However, the user's question specifically asks where Rihanna was raised, which may differ from her place of birth. The current query only retrieves the place of birth (wdt:P19) and does not check for a property indicating where she was raised. To improve, the query should attempt to find a property related to where Rihanna was raised or grew up, such as 'residence' (wdt:P551) or other relevant properties. If no explicit data about where she was raised is available, the answer should clarify that only the place of birth is known from Wikidata. This refinement would make the answer more precise and aligned with the user's question.

[Assistant] Thank you for the feedback. I will now refine the query to check for properties related to where Rihanna was raised, such as "residence" (wdt:P551) or other relevant properties that might indicate where she grew up or was raised. If no such data is found, I will clarify that only the place of birth is known from Wikidata.

[Tool]
Top 10 property alternatives:
1. occupation, also known as job, work, vocation, profession, employment (wd:P106 as wdt/p): occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)
2. country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as wdt/p): the object is a country that recognizes the subject as its citizen, country
3. owner of, also known as owns, owns property, shareholder of (wd:P1830 as wdt/p): entities owned by the subject
4. place of birth, also known as POB, location of birth, location born, born in, birthplace (wd:P19 as wdt/p): most specific known birth location of a person, animal or fictional character, location
5. unmarried partner, also known as romantic partner, partner of, partners, posslq, relationship (wd:P451 as wdt/p): someone with whom the person is in a relationship without being married. Use "spouse" (P26) for married couples, significant person
6. net worth, also known as declared patrimony, estimated net worth, net wealth, net worth estimate, personal assets (wd:P2218 as wdt/p): totality of wealth possessed by a person
7. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as wdt/p): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
8. date of birth, also known as year of birth, birthdate, DOB, born on, born (wd:P569 as wdt/p): date on which the subject was born, inception
9. Guardian topic ID, also known as Guardian, The Guardian topic, The Guardian topic ID (wd:P3106 as wdt/p): identifier for a topic at the Guardian newspaper website
10. official website, also known as site (official), home page, site official, URL, URL (official) (wd:P856 as wdt/p): URL of the official page of an item (current or former). Usage: ...but see the "Hijacked or dead websites" section of the Talk page, URL

No other items found

[Assistant] There is no direct property "residence" (wdt:P551) or similar for Rihanna in the properties related to her. I will now check if there are any statements about "residence" (wdt:P551) or "location of upbringing" or similar for Rihanna in the data.

[Tool] Got no rows and 3 columns

[Tool]
Top 10 property alternatives:
1. child, also known as has son, kids, mother of, kid, issue (wd:P40 as wdt/p): subject has object as child. Do not use for stepchildren—use "relative" (P1038), qualified with "type of kinship" (P1039), significant person, relative
2. place of birth, also known as POB, location of birth, location born, born in, birthplace (wd:P19 as wdt/p): most specific known birth location of a person, animal or fictional character, location
3. birth name, also known as née, name at birth, name before marriage, ne, né (wd:P1477 as wdt/p): full name of a person at birth, if different from their current, generally used name, name
4. date of birth, also known as year of birth, birthdate, DOB, born on, born (wd:P569 as wdt/p): date on which the subject was born, inception
5. influenced by, also known as favorite player, has influence, informed by, role model (wd:P737 as wdt/p): this person, idea, etc. is informed by that other person, idea, etc., e.g. “Heidegger was influenced by Aristotle”
6. occupation, also known as job, work, vocation, profession, employment (wd:P106 as wdt/p): occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)
7. country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as wdt/p): the object is a country that recognizes the subject as its citizen, country
8. wears, also known as wore, wearing, uniform, outfit, garment (wd:P3828 as wdt/p): clothing or accessory worn on subject's body, item operated
9. sex or gender, also known as gender or sex, sex, gender identity, gender expression, gender (wd:P21 as wdt/p): sex or gender identity of human or animal. For human: male, fema...m, female organism. Groups of same gender use subclass of (P279)
10. native language, also known as first language, L1 speaker of, language native, mother tongue (wd:P103 as wdt/p): language or languages a person has learned from early childhood, languages spoken, written or signed

No other items found

[Assistant]
There is no explicit property or statement in Wikidata about where Rihanna was raised or grew up. The only location information available is her place of birth, which is Saint Michael.

I will now provide the final answer clarifying this point.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The system correctly identified that Wikidata does not have explicit information about where Rihanna was raised. It appropriately queried for her place of birth as a proxy, which is Saint Michael. The SPARQL query is well-formed and returns the place of birth with its label. Since the question specifically asks where she was raised and that information is not available, the answer is complete and accurate given the data source.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX p: <http://www.wikidata.org/prop/>
PREFIX ps: <http://www.wikidata.org/prop/statement/>
PREFIX pq: <http://www.wikidata.org/prop/qualifier/>
SELECT ?start ?end WHERE {
  wd:Q91 p:P39 ?statement .
  ?statement ps:P39 wd:Q11696 ; pq:P580 ?start ; pq:P582 ?end .
}

Abraham Lincoln was president from March 4, 1861 to April 15, 1865.

[System]
You are a question answering assistant. Your job is to generate a SPARQL query to answer a given user question.

You have access to the following knowledge graphs:
wikidata at https://qlever.cs.uni-freiburg.de/api/wikidata

You can use the following SPARQL prefixes implicitly in all functions:
cc: <http://creativecommons.org/ns#
data: <https://www.wikidata.org/wiki/Special:EntityData/
dct: <http://purl.org/dc/terms/
geo: <http://www.opengis.net/ont/geosparql#
geof: <http://www.opengis.net/def/function/geosparql/
imdb: <https://www.imdb.com/
math: <http://www.w3.org/2005/xpath-functions/math#
ontolex: <http://www.w3.org/ns/lemon/ontolex#
owl: <http://www.w3.org/2002/07/owl#
p: <http://www.wikidata.org/prop/
pq: <http://www.wikidata.org/prop/qualifier/
pqn: <http://www.wikidata.org/prop/qualifier/value-normalized/
pqv: <http://www.wikidata.org/prop/qualifier/value/
pr: <http://www.wikidata.org/prop/reference/
prn: <http://www.wikidata.org/prop/reference/value-normalized/
prov: <http://www.w3.org/ns/prov#
prv: <http://www.wikidata.org/prop/reference/value/
ps: <http://www.wikidata.org/prop/statement/
psn: <http://www.wikidata.org/prop/statement/value-normalized/
psv: <http://www.wikidata.org/prop/statement/value/
qfn: <http://qlever.cs.uni-freiburg.de/function#
ql: <http://qlever.cs.uni-freiburg.de/builtin-functions/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
ref: <http://www.wikidata.org/reference/
s: <http://www.wikidata.org/entity/statement/
schema: <http://schema.org/
skos: <http://www.w3.org/2004/02/skos/core#
v: <http://www.wikidata.org/value/
wd: <http://www.wikidata.org/entity/
wdno: <http://www.wikidata.org/prop/novalue/
wdt: <http://www.wikidata.org/prop/direct/
wdtn: <http://www.wikidata.org/prop/direct-normalized/
wikibase: <http://wikiba.se/ontology#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
dc: <http://purl.org/dc/elements/1.1/
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
qb: <http://purl.org/linked-data/cube#
void: <http://rdfs.org/ns/void#

You should follow a step-by-step approach to generate the SPARQL query:
1. Determine possible entities and properties implied by the user question.
2. Use the functions to search for entities and properties in the knowledge graphs. Where applicable, constrain the searches with already identified entities and properties.
3. Gradually build up the SPARQL query using the identified entities and properties. Start with simple queries and add more complexity as needed. Use the execute function to get feedback on intermediate queries. You can go back and forth between knowledge graph searches and SPARQL query executions to refine the query.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

Additional rules:
1. Explain your thought process before and after each step and function call.
2. Do not assume or make up any entities or properties without verifying them with the knowledge graphs and functions.
3. The SPARQL query should always return the actual identifiers / IRIs of the items in its result. It additionally may return labels or other human-readable information, but they are optional and should be put within optional clauses unless explicitly requested by the user.
4. Do not stop early if there are still obvious improvements to be made to the SPARQL query. For example, keep refining your SPARQL query if its result contains irrelevant items or is missing items you expected.
5. Do not perform additional computation (e.g. filtering, sorting, calculations) on the result of the SPARQL query to determine the answer. All computation should be done solely within SPARQL.
6. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
7. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] when was abe lincoln president?

[Assistant] Let's start by looking at some similar examples.

[Tool]
Example 1:
Question:
when president lincoln was elected?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q91 p:P39 ?y .
  ?y ps:P39 wd:Q1467287 ; pq:P580 ?x .
}

Using entities:
President-elect of the United States, also known as President-Elect (wd:Q1467287): winning candidate of the U.S. presidential election in the time before inauguration
Abraham Lincoln, also known as President Lincoln, Uncle Abe, Honest Abe, Abe Lincoln (wd:Q91): president of the United States from 1861 to 1865, military officer, statesperson, postmaster, politician, farmer, writer, lawyer

Using properties:
position held, also known as function, held position, holds position, job, office held (wd:P39 as p/ps): subject currently or formerly holds the object position or public office
start time, also known as start date, since, valid, join time, joined (wd:P580 as pq): time an entity begins to exist or a statement starts being valid, point in time

Example 2:
Question:
what date was abraham lincoln inaugurated?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q91 p:P39 ?y .
  ?y ps:P39 wd:Q11696 ; pq:P580 ?x .
}

Using entities:
President of the United States, also known as US President, U.S. President, United States President, the president of the United States, President of the U.S. (wd:Q11696): head of state and head of government of the United States of America
Abraham Lincoln, also known as President Lincoln, Uncle Abe, Honest Abe, Abe Lincoln (wd:Q91): president of the United States from 1861 to 1865, military officer, statesperson, postmaster, politician, farmer, writer, lawyer

Using properties:
position held, also known as function, held position, holds position, job, office held (wd:P39 as p/ps): subject currently or formerly holds the object position or public office
start time, also known as start date, since, valid, join time, joined (wd:P580 as pq): time an entity begins to exist or a statement starts being valid, point in time

Example 3:
Question:
what is president abraham lincoln known for?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q91 wdt:P106 ?x .
}

Using entities:
Abraham Lincoln, also known as President Lincoln, Uncle Abe, Honest Abe, Abe Lincoln (wd:Q91): president of the United States from 1861 to 1865, military officer, statesperson, postmaster, politician, farmer, writer, lawyer

Using properties:
occupation, also known as job, work, vocation, profession, employment (wd:P106 as wdt): occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)

[Assistant]
From the examples, we see that Abraham Lincoln is identified as wd:Q91 and the position "President of the United States" is wd:Q11696. The property "position held" is P39, and the qualifiers "start time" (P580) and "end time" (P582) indicate the duration of the position held.

I will now write a SPARQL query to find the start and end times when Abraham Lincoln was president.

[Tool]
Got 1 row and 2 columns:
| start                               | end                                 |
| ----------------------------------- | ----------------------------------- |
| 1861-03-04T00:00:00Z (xsd:dateTime) | 1865-04-15T00:00:00Z (xsd:dateTime) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the start and end dates of Abraham Lincoln's presidency from Wikidata. The answer provided is accurate and matches the query results. The query uses appropriate properties (P39 for position held, P580 for start time, and P582 for end time) and the correct entity for Abraham Lincoln (Q91) and the position of President of the United States (Q11696). No further refinement is necessary.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT DISTINCT ?language ?languageLabel WHERE {
  wd:Q79 wdt:P37 ?language .
  OPTIONAL {
    ?language rdfs:label ?languageLabel FILTER ( LANG( ?languageLabel ) = "en" )
  }
}

Got 1 row and 2 columns:
| language           | languageLabel |
| ------------------ | ------------- |
| Arabic (wd:Q13955) | Arabic (en)   |

Egypt speaks Arabic as its official language.

[System]
You are a question answering assistant. Your job is to generate a SPARQL query to answer a given user question.

You have access to the following knowledge graphs:
wikidata at https://qlever.cs.uni-freiburg.de/api/wikidata

You can use the following SPARQL prefixes implicitly in all functions:
cc: <http://creativecommons.org/ns#
data: <https://www.wikidata.org/wiki/Special:EntityData/
dct: <http://purl.org/dc/terms/
geo: <http://www.opengis.net/ont/geosparql#
geof: <http://www.opengis.net/def/function/geosparql/
imdb: <https://www.imdb.com/
math: <http://www.w3.org/2005/xpath-functions/math#
ontolex: <http://www.w3.org/ns/lemon/ontolex#
owl: <http://www.w3.org/2002/07/owl#
p: <http://www.wikidata.org/prop/
pq: <http://www.wikidata.org/prop/qualifier/
pqn: <http://www.wikidata.org/prop/qualifier/value-normalized/
pqv: <http://www.wikidata.org/prop/qualifier/value/
pr: <http://www.wikidata.org/prop/reference/
prn: <http://www.wikidata.org/prop/reference/value-normalized/
prov: <http://www.w3.org/ns/prov#
prv: <http://www.wikidata.org/prop/reference/value/
ps: <http://www.wikidata.org/prop/statement/
psn: <http://www.wikidata.org/prop/statement/value-normalized/
psv: <http://www.wikidata.org/prop/statement/value/
qfn: <http://qlever.cs.uni-freiburg.de/function#
ql: <http://qlever.cs.uni-freiburg.de/builtin-functions/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
ref: <http://www.wikidata.org/reference/
s: <http://www.wikidata.org/entity/statement/
schema: <http://schema.org/
skos: <http://www.w3.org/2004/02/skos/core#
v: <http://www.wikidata.org/value/
wd: <http://www.wikidata.org/entity/
wdno: <http://www.wikidata.org/prop/novalue/
wdt: <http://www.wikidata.org/prop/direct/
wdtn: <http://www.wikidata.org/prop/direct-normalized/
wikibase: <http://wikiba.se/ontology#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
dc: <http://purl.org/dc/elements/1.1/
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
qb: <http://purl.org/linked-data/cube#
void: <http://rdfs.org/ns/void#

You should follow a step-by-step approach to generate the SPARQL query:
1. Determine possible entities and properties implied by the user question.
2. Use the functions to search for entities and properties in the knowledge graphs. Where applicable, constrain the searches with already identified entities and properties.
3. Gradually build up the SPARQL query using the identified entities and properties. Start with simple queries and add more complexity as needed. Use the execute function to get feedback on intermediate queries. You can go back and forth between knowledge graph searches and SPARQL query executions to refine the query.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

Additional rules:
1. Explain your thought process before and after each step and function call.
2. Do not assume or make up any entities or properties without verifying them with the knowledge graphs and functions.
3. The SPARQL query should always return the actual identifiers / IRIs of the items in its result. It additionally may return labels or other human-readable information, but they are optional and should be put within optional clauses unless explicitly requested by the user.
4. Do not stop early if there are still obvious improvements to be made to the SPARQL query. For example, keep refining your SPARQL query if its result contains irrelevant items or is missing items you expected.
5. Do not perform additional computation (e.g. filtering, sorting, calculations) on the result of the SPARQL query to determine the answer. All computation should be done solely within SPARQL.
6. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
7. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] what kind of language does egypt speak?

[Assistant] Let's start by looking at some similar examples.

[Tool]
Example 1:
Question:
what language do they speak in egyptian?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q79 wdt:P37 ?x .
}

Using entities:
Egypt, also known as Republic of Egypt, Rep. Egypt, EGY, eg, Arab Republic of Egypt (wd:Q79): country in Northeast Africa and Southwest Asia

Using properties:
official language, also known as language spoken, spoken in, speaking, language official (wd:P37 as wdt): language designated as official by this item, language used

Example 2:
Question:
what languages do people speak in egypt?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q79 wdt:P37 ?x .
}

Using entities:
Egypt, also known as Republic of Egypt, Rep. Egypt, EGY, eg, Arab Republic of Egypt (wd:Q79): country in Northeast Africa and Southwest Asia

Using properties:
official language, also known as language spoken, spoken in, speaking, language official (wd:P37 as wdt): language designated as official by this item, language used

Example 3:
Question:
what language does egyptians use?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q79 wdt:P37 ?x .
}

Using entities:
Egypt, also known as Republic of Egypt, Rep. Egypt, EGY, eg, Arab Republic of Egypt (wd:Q79): country in Northeast Africa and Southwest Asia

Using properties:
official language, also known as language spoken, spoken in, speaking, language official (wd:P37 as wdt): language designated as official by this item, language used

[Assistant] The similar examples show that the property for the language spoken in a country is wdt:P37 (official language). The entity for Egypt is wd:Q79. I will now write a SPARQL query to get the languages spoken in Egypt using these.

[Tool]
Got 1 row and 2 columns:
| language           | languageLabel |
| ------------------ | ------------- |
| Arabic (wd:Q13955) | Arabic (en)   |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the official language of Egypt using the property for official language (wdt:P37). The query returns the language identifier and its English label, which is appropriate and answers the user's question accurately. The answer 'Egypt speaks Arabic as its official language' is correct and complete. No further refinement is needed.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT DISTINCT ?product ?productLabel WHERE {
  wd:Q81965 wdt:P1056 ?product .
  OPTIONAL {
    ?product rdfs:label ?productLabel FILTER ( LANG( ?productLabel ) = "en" )
  }
}

Got 1 row and 2 columns:
| product              | productLabel   |
| -------------------- | -------------- |
| motor car (wd:Q1420) | motor car (en) |

General Motors (GM) makes or produces motor cars.

[System]
You are a question answering assistant. Your job is to generate a SPARQL query to answer a given user question.

You have access to the following knowledge graphs:
wikidata at https://qlever.cs.uni-freiburg.de/api/wikidata

You can use the following SPARQL prefixes implicitly in all functions:
cc: <http://creativecommons.org/ns#
data: <https://www.wikidata.org/wiki/Special:EntityData/
dct: <http://purl.org/dc/terms/
geo: <http://www.opengis.net/ont/geosparql#
geof: <http://www.opengis.net/def/function/geosparql/
imdb: <https://www.imdb.com/
math: <http://www.w3.org/2005/xpath-functions/math#
ontolex: <http://www.w3.org/ns/lemon/ontolex#
owl: <http://www.w3.org/2002/07/owl#
p: <http://www.wikidata.org/prop/
pq: <http://www.wikidata.org/prop/qualifier/
pqn: <http://www.wikidata.org/prop/qualifier/value-normalized/
pqv: <http://www.wikidata.org/prop/qualifier/value/
pr: <http://www.wikidata.org/prop/reference/
prn: <http://www.wikidata.org/prop/reference/value-normalized/
prov: <http://www.w3.org/ns/prov#
prv: <http://www.wikidata.org/prop/reference/value/
ps: <http://www.wikidata.org/prop/statement/
psn: <http://www.wikidata.org/prop/statement/value-normalized/
psv: <http://www.wikidata.org/prop/statement/value/
qfn: <http://qlever.cs.uni-freiburg.de/function#
ql: <http://qlever.cs.uni-freiburg.de/builtin-functions/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
ref: <http://www.wikidata.org/reference/
s: <http://www.wikidata.org/entity/statement/
schema: <http://schema.org/
skos: <http://www.w3.org/2004/02/skos/core#
v: <http://www.wikidata.org/value/
wd: <http://www.wikidata.org/entity/
wdno: <http://www.wikidata.org/prop/novalue/
wdt: <http://www.wikidata.org/prop/direct/
wdtn: <http://www.wikidata.org/prop/direct-normalized/
wikibase: <http://wikiba.se/ontology#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
dc: <http://purl.org/dc/elements/1.1/
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
qb: <http://purl.org/linked-data/cube#
void: <http://rdfs.org/ns/void#

You should follow a step-by-step approach to generate the SPARQL query:
1. Determine possible entities and properties implied by the user question.
2. Use the functions to search for entities and properties in the knowledge graphs. Where applicable, constrain the searches with already identified entities and properties.
3. Gradually build up the SPARQL query using the identified entities and properties. Start with simple queries and add more complexity as needed. Use the execute function to get feedback on intermediate queries. You can go back and forth between knowledge graph searches and SPARQL query executions to refine the query.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

Additional rules:
1. Explain your thought process before and after each step and function call.
2. Do not assume or make up any entities or properties without verifying them with the knowledge graphs and functions.
3. The SPARQL query should always return the actual identifiers / IRIs of the items in its result. It additionally may return labels or other human-readable information, but they are optional and should be put within optional clauses unless explicitly requested by the user.
4. Do not stop early if there are still obvious improvements to be made to the SPARQL query. For example, keep refining your SPARQL query if its result contains irrelevant items or is missing items you expected.
5. Do not perform additional computation (e.g. filtering, sorting, calculations) on the result of the SPARQL query to determine the answer. All computation should be done solely within SPARQL.
6. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
7. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] what does gm make?

[Assistant] Let's start by looking at some similar examples.

[Tool]
Example 1:
Question:
what other cars does gm make?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q81965 wdt:P355 ?x .
}

Using entities:
General Motors, also known as GM, General Motors Corporation (wd:Q81965): automotive manufacturing corporation based in Detroit, Michigan, USA, American automotive manufacturing corporation

Using properties:
has subsidiary, also known as subordinate body, subsidiary body, subordinate unit, subsidiary, subsidiary company (wd:P355 as wdt): subsidiary of a company or organization; generally a fully owned...siness division" (P199). Opposite of parent organization (P749)., has part(s), owner of

Example 2:
Question:
what does pixar produce?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x wdt:P272 wd:Q127552 .
}

Using entities:
Pixar, also known as Graphics Group, Pixar Studios (wd:Q127552): American computer animation studio

Using properties:
production company, also known as broadcasting company, theatrical troupe, theatre company, theater company, studio (wd:P272 as wdt): company that produced this film, audio or performing arts work

Example 3:
Question:
what did george eastman make?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x wdt:P61 wd:Q189147 .
}

Using entities:
George Eastman, also known as geog. eastman, g. eastman, Geo. Eastman (wd:Q189147): American entrepreneur, inventor and photographer (1854–1932), patron of the arts, philanthropist, photographer, entrepreneur, inventor

Using properties:
discoverer or inventor, also known as inventor or discoverer, inventor, invented by, invented, introduced by (wd:P61 as wdt): subject who discovered, first described, invented, or developed this discovery or invention or scientific hypothesis or theory

[Assistant]
From the similar examples, we see two main approaches to interpret "what does gm make?":

1. If "gm" refers to General Motors (an automotive company), we can find what subsidiaries or products it makes using the property "has part" or "has subsidiary" (wdt:P355).
2. If "make" refers to inventions or creations, we can look for items invented or produced by "gm" using properties like "inventor" or "production company".

Since "gm" commonly refers to General Motors, an automotive company, the most relevant interpretation is to find what General Motors makes or produces. We can query for the subsidiaries or products of General Motors.

Next, I will search for the entity "gm" to confirm it refers to General Motors and then find the appropriate property to get what it makes.

[Tool] No entity items found

[Assistant] The search for "gm" did not return any entity directly. I will try searching for "General Motors" explicitly to find the entity for GM.

[Tool]
Top 10 entity alternatives:
1. General Motors, also known as GM, General Motors Corporation (wd:Q81965): automotive manufacturing corporation based in Detroit, Michigan, USA, American automotive manufacturing corporation
2. General Motors railway station, also known as General Motors station, General Motors (wd:Q5532064): closed railway station in Dandenong South, Victoria, Australia
3. General Motors (wd:Q16891615): former Rochester Industrial and Rapid Transit Railway station and streetcar carhouse in Rochester, New York
4. General Motors (wd:Q84480751): scientific article published on 01 November 1983
5. General Motors, also known as General Motors (Poland) (wd:Q30338742): Polish subsidary of General Motors
6. General motors (wd:Q84481962): scientific article published on 01 February 1983
7. Grumman TBF Avenger, also known as TBM Avenger, TBM, Grumman Torpedo Bomber Design 1, Grumman TBM, Grumman Tarpon (wd:Q734103): 1941 torpedo bomber aircraft model by Grumman
8. Rogers Arena, also known as GM Place, General Motors Place (wd:Q517318): sports arena in Vancouver, British Columbia, Canada
9. GM Korea, also known as General Motors Korea, GM Daewoo, 한국GM (wd:Q497193): South Korean subsidiary of General Motors
10. General Motors EV1, also known as EV1 (wd:Q152013): electric compact car model

[Assistant]
The entity "General Motors" is wd:Q81965. This is the automotive manufacturing corporation commonly known as GM.

Next, I will search for properties of General Motors that relate to what it makes or produces. I will search for properties related to "make" or "produce" for this entity.

[Tool]
Top 10 property alternatives:
1. product, material, or service produced or provided, also known as products, product or service provided, product, material, or service produced or provided, product, output (wd:P1056 as wdt/p): material or product produced or sold by an organization, industry, facility, or process, material or product produced by an organization, industry, facility, or process, immediate cause of
2. inception, also known as initial release date, founded in, founded on, founded on date, founding date (wd:P571 as wdt/p): time when an entity begins to exist; for date of official opening use P1619, start time
3. founded by, also known as starter, co-founded by, started by, institutor, instituted by (wd:P112 as wdt/p): founder or co-founder of this organization, religion, place or entity, creator
4. official shop URL, also known as online store, shop, shop URL, store, store URL (wd:P10225 as wdt/p): official URL where the agent sells products/merchandise, official website
5. award received, also known as win, winner of, recognition title, received award, prize received (wd:P166 as wdt/p): award or recognition received by a person, organization or creative work
6. official name, also known as long title, name, official title, registered name, full title (wd:P1448 as wdt/p): official name of the subject in its official language(s), name
7. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt/p): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
8. topic's main category, also known as article's main category, category, category for this topic, catmain, has category (wd:P910 as wdt/p): main Wikimedia category
9. location of formation, also known as place of incorporation, originates from, place of establishment, place of formation, place of foundation (wd:P740 as wdt/p): location where a group or organization was formed, location of creation
10. country of origin, also known as origin country, place of origin, originates from, country, CoO (wd:P495 as wdt/p): country of origin of this item (creative work, food, phrase, product, etc.), significant place, country

No other items found

[Assistant]
The property "product, material, or service produced or provided" (wdt:P1056) is the most relevant property for what General Motors makes or produces.

I will now write a SPARQL query to get the products or materials produced or provided by General Motors (wd:Q81965) using the property wdt:P1056.

[Tool]
Got 1 row and 2 columns:
| product              | productLabel   |
| -------------------- | -------------- |
| motor car (wd:Q1420) | motor car (en) |

[Assistant] General Motors (GM) makes or produces motor cars. I will now provide the final answer with the SPARQL query.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the products made by General Motors (GM) using the property 'product, material, or service produced or provided' (wdt:P1056). The result shows that GM makes motor cars, which directly answers the user's question. The query also includes English labels for readability. The answer is accurate and complete based on the data from Wikidata.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?city ?cityLabel ?population WHERE {
  ?city wdt:P31 / wdt:P279 * wd:Q515 .
  ?city wdt:P17 wd:Q29 .
  ?city wdt:P1082 ?population .
  OPTIONAL {
    ?city rdfs:label ?cityLabel FILTER ( LANG( ?cityLabel ) = "en" )
  }
}
ORDER BY DESC ( ?population )
LIMIT 1

The largest city in Spain by population is Madrid (wd:Q2807) with a population of 3,416,771.

[System]
You are a question answering assistant. Your job is to generate a SPARQL query to answer a given user question.

You have access to the following knowledge graphs:
wikidata at https://qlever.cs.uni-freiburg.de/api/wikidata

You can use the following SPARQL prefixes implicitly in all functions:
cc: <http://creativecommons.org/ns#
data: <https://www.wikidata.org/wiki/Special:EntityData/
dct: <http://purl.org/dc/terms/
geo: <http://www.opengis.net/ont/geosparql#
geof: <http://www.opengis.net/def/function/geosparql/
imdb: <https://www.imdb.com/
math: <http://www.w3.org/2005/xpath-functions/math#
ontolex: <http://www.w3.org/ns/lemon/ontolex#
owl: <http://www.w3.org/2002/07/owl#
p: <http://www.wikidata.org/prop/
pq: <http://www.wikidata.org/prop/qualifier/
pqn: <http://www.wikidata.org/prop/qualifier/value-normalized/
pqv: <http://www.wikidata.org/prop/qualifier/value/
pr: <http://www.wikidata.org/prop/reference/
prn: <http://www.wikidata.org/prop/reference/value-normalized/
prov: <http://www.w3.org/ns/prov#
prv: <http://www.wikidata.org/prop/reference/value/
ps: <http://www.wikidata.org/prop/statement/
psn: <http://www.wikidata.org/prop/statement/value-normalized/
psv: <http://www.wikidata.org/prop/statement/value/
qfn: <http://qlever.cs.uni-freiburg.de/function#
ql: <http://qlever.cs.uni-freiburg.de/builtin-functions/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
ref: <http://www.wikidata.org/reference/
s: <http://www.wikidata.org/entity/statement/
schema: <http://schema.org/
skos: <http://www.w3.org/2004/02/skos/core#
v: <http://www.wikidata.org/value/
wd: <http://www.wikidata.org/entity/
wdno: <http://www.wikidata.org/prop/novalue/
wdt: <http://www.wikidata.org/prop/direct/
wdtn: <http://www.wikidata.org/prop/direct-normalized/
wikibase: <http://wikiba.se/ontology#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
dc: <http://purl.org/dc/elements/1.1/
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
qb: <http://purl.org/linked-data/cube#
void: <http://rdfs.org/ns/void#

You should follow a step-by-step approach to generate the SPARQL query:
1. Determine possible entities and properties implied by the user question.
2. Use the functions to search for entities and properties in the knowledge graphs. Where applicable, constrain the searches with already identified entities and properties.
3. Gradually build up the SPARQL query using the identified entities and properties. Start with simple queries and add more complexity as needed. Use the execute function to get feedback on intermediate queries. You can go back and forth between knowledge graph searches and SPARQL query executions to refine the query.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

Additional rules:
1. Explain your thought process before and after each step and function call.
2. Do not assume or make up any entities or properties without verifying them with the knowledge graphs and functions.
3. The SPARQL query should always return the actual identifiers / IRIs of the items in its result. It additionally may return labels or other human-readable information, but they are optional and should be put within optional clauses unless explicitly requested by the user.
4. Do not stop early if there are still obvious improvements to be made to the SPARQL query. For example, keep refining your SPARQL query if its result contains irrelevant items or is missing items you expected.
5. Do not perform additional computation (e.g. filtering, sorting, calculations) on the result of the SPARQL query to determine the answer. All computation should be done solely within SPARQL.
6. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
7. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] what the largest city in spain?

[Assistant] Let's start by looking at some similar examples.

[Tool]
Example 1:
Question:
what is the name of the capital of spain?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q29 wdt:P36 ?x .
}

Using entities:
Spain, also known as Kingdom of Spain (wd:Q29): country in southwestern Europe with territories in Africa

Using properties:
capital, also known as administrative seat, seat of government, seat, principal place, location of capital (wd:P36 as wdt): seat of government of a country, province, state or other type of administrative territorial entity

Example 2:
Question:
what are the main languages spoken in spain?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q29 wdt:P37 ?x .
}

Using entities:
Spain, also known as Kingdom of Spain (wd:Q29): country in southwestern Europe with territories in Africa

Using properties:
official language, also known as language spoken, spoken in, speaking, language official (wd:P37 as wdt): language designated as official by this item, language used

Example 3:
Question:
what are the official languages in spain?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q29 wdt:P37 ?x .
}

Using entities:
Spain, also known as Kingdom of Spain (wd:Q29): country in southwestern Europe with territories in Africa

Using properties:
official language, also known as language spoken, spoken in, speaking, language official (wd:P37 as wdt): language designated as official by this item, language used

[Assistant] From the examples, I see that Spain is represented by wd:Q29 in Wikidata. To find the largest city in Spain, I need to find cities located in Spain and then determine which one is the largest by population. I will first search for the property related to "largest city" or "population" to help me build the query.

[Tool]
Top 10 property alternatives:
1. headquarters location, also known as headquarters locality, seat, headquarters town, HQ, HQ location (wd:P159 as prv/psv/pq/psn/pr/pqv/p/wdtn/ps/wdt/pqn/prn): city or town where an organization's headquarters is or has been situated. Use P276 qualifier for specific building, significant place
2. location, also known as neighbourhood, whereabouts, vilage, venue, town (wd:P276 as prv/psv/pq/psn/pr/pqv/p/wdtn/ps/wdt/pqn/prn): location of the object, structure or event. In the case of an ad...ity use P706. Use P7153 for locations associated with the object
3. located in the administrative territorial entity, also known as is in the settlement of, is in the voivodeship of, is in the shire of, is in the state of, is in the territory of (wd:P131 as prv/psv/pq/psn/pr/pqv/p/wdtn/ps/wdt/pqn/prn): the item is located on the territory of the following administra...if the item falls only partially into the administrative entity., location, part of
4. contains the administrative territorial entity, also known as has shires, has rural cities, has regions, has municipalities, has members (wd:P150 as prv/psv/pq/psn/pr/pqv/p/wdtn/ps/wdt/pqn/prn): (list of) direct subdivisions of an administrative territorial entity, has part(s)
5. capital, also known as administrative seat, seat of government, seat, principal place, location of capital (wd:P36 as prv/psv/pq/psn/pr/pqv/p/wdtn/ps/wdt/pqn/prn): seat of government of a country, province, state or other type of administrative territorial entity
6. place served by transport hub, also known as serves city, train station serves, served by transport hub, city served, area served by transport hub (wd:P931 as prv/psv/pq/psn/pr/pqv/p/wdtn/ps/wdt/pqn/prn): territorial entity or entities served by this transport hub (airport, train station, etc.), significant place
7. operating area, also known as province served, serves jurisdiction, serves geographic region, serves geographic area, serves area (wd:P2541 as prv/psv/pq/psn/pr/pqv/p/wdtn/ps/wdt/pqn/prn): geographic area or jurisdiction an organisation or industry operates in, serves, or has responsibility for, location
8. capital of, also known as national capital of, parish seat of, provincial capital of, seat of, state capital (wd:P1376 as prv/psv/pq/psn/pr/pqv/p/wdtn/ps/wdt/pqn/prn): country, state, department, canton or other administrative division of which the municipality is the governmental seat, located in the administrative territorial entity
9. urban population (wd:P6343 as prv/psv/pq/psn/pr/pqv/p/wdtn/ps/wdt/pqn/prn): number of people living within the territorial entity who live in its urban parts, population
10. residence, also known as living in, place of residence, resided at, resided in, resident in (wd:P551 as prv/psv/pq/psn/pr/pqv/p/wdtn/ps/wdt/pqn/prn): the place where the person is or has been, resident, location

[Assistant] The property "located in the administrative territorial entity" (wdt:P131) can be used to find cities located in Spain. The property "population" (wdt:P1082) is commonly used to indicate the population of a city. I will now build a query to find cities located in Spain (wd:Q29) and order them by population to get the largest city.

[Tool]
Got 1 row and 3 columns:
| city               | cityLabel    | population          |
| ------------------ | ------------ | ------------------- |
| Melilla (wd:Q5831) | Melilla (en) | 85811 (xsd:decimal) |

[Assistant] The query returned Melilla as the largest city in Spain by population, which seems incorrect because Madrid is known as the largest city in Spain. Melilla is an autonomous city but not the largest city by population. I will refine the query to consider only cities that are part of the country Spain (wd:Q29) directly, excluding autonomous cities or territories. I will also check for the property "country" (wdt:P17) to ensure the city belongs to Spain.

[Tool]
Got 1 row and 3 columns:
| city              | cityLabel   | population            |
| ----------------- | ----------- | --------------------- |
| Madrid (wd:Q2807) | Madrid (en) | 3416771 (xsd:decimal) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly identifies the largest city in Spain by population. It filters for instances of cities located in Spain and orders them by population in descending order, limiting the result to the top one. The answer, Madrid, is accurate and matches the query result. The query also optionally retrieves the English label of the city, which is helpful for readability. Overall, the output is correct and complete.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT DISTINCT ?causeOfDeath ?causeOfDeathLabel WHERE {
  wd:Q40933 wdt:P509 ?causeOfDeath .
  OPTIONAL {
    ?causeOfDeath rdfs:label ?causeOfDeathLabel FILTER ( LANG( ?causeOfDeathLabel ) = "en" )
  }
}

Got 1 row and 2 columns:
| causeOfDeath                       | causeOfDeathLabel          |
| ---------------------------------- | -------------------------- |
| cervix uterine cancer (wd:Q160105) | cervix uterine cancer (en) |

Eva Peron had cervix uterine cancer.

[System]
You are a question answering assistant. Your job is to generate a SPARQL query to answer a given user question.

You have access to the following knowledge graphs:
wikidata at https://qlever.cs.uni-freiburg.de/api/wikidata

You can use the following SPARQL prefixes implicitly in all functions:
cc: <http://creativecommons.org/ns#
data: <https://www.wikidata.org/wiki/Special:EntityData/
dct: <http://purl.org/dc/terms/
geo: <http://www.opengis.net/ont/geosparql#
geof: <http://www.opengis.net/def/function/geosparql/
imdb: <https://www.imdb.com/
math: <http://www.w3.org/2005/xpath-functions/math#
ontolex: <http://www.w3.org/ns/lemon/ontolex#
owl: <http://www.w3.org/2002/07/owl#
p: <http://www.wikidata.org/prop/
pq: <http://www.wikidata.org/prop/qualifier/
pqn: <http://www.wikidata.org/prop/qualifier/value-normalized/
pqv: <http://www.wikidata.org/prop/qualifier/value/
pr: <http://www.wikidata.org/prop/reference/
prn: <http://www.wikidata.org/prop/reference/value-normalized/
prov: <http://www.w3.org/ns/prov#
prv: <http://www.wikidata.org/prop/reference/value/
ps: <http://www.wikidata.org/prop/statement/
psn: <http://www.wikidata.org/prop/statement/value-normalized/
psv: <http://www.wikidata.org/prop/statement/value/
qfn: <http://qlever.cs.uni-freiburg.de/function#
ql: <http://qlever.cs.uni-freiburg.de/builtin-functions/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
ref: <http://www.wikidata.org/reference/
s: <http://www.wikidata.org/entity/statement/
schema: <http://schema.org/
skos: <http://www.w3.org/2004/02/skos/core#
v: <http://www.wikidata.org/value/
wd: <http://www.wikidata.org/entity/
wdno: <http://www.wikidata.org/prop/novalue/
wdt: <http://www.wikidata.org/prop/direct/
wdtn: <http://www.wikidata.org/prop/direct-normalized/
wikibase: <http://wikiba.se/ontology#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
dc: <http://purl.org/dc/elements/1.1/
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
qb: <http://purl.org/linked-data/cube#
void: <http://rdfs.org/ns/void#

You should follow a step-by-step approach to generate the SPARQL query:
1. Determine possible entities and properties implied by the user question.
2. Use the functions to search for entities and properties in the knowledge graphs. Where applicable, constrain the searches with already identified entities and properties.
3. Gradually build up the SPARQL query using the identified entities and properties. Start with simple queries and add more complexity as needed. Use the execute function to get feedback on intermediate queries. You can go back and forth between knowledge graph searches and SPARQL query executions to refine the query.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

Additional rules:
1. Explain your thought process before and after each step and function call.
2. Do not assume or make up any entities or properties without verifying them with the knowledge graphs and functions.
3. The SPARQL query should always return the actual identifiers / IRIs of the items in its result. It additionally may return labels or other human-readable information, but they are optional and should be put within optional clauses unless explicitly requested by the user.
4. Do not stop early if there are still obvious improvements to be made to the SPARQL query. For example, keep refining your SPARQL query if its result contains irrelevant items or is missing items you expected.
5. Do not perform additional computation (e.g. filtering, sorting, calculations) on the result of the SPARQL query to determine the answer. All computation should be done solely within SPARQL.
6. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
7. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] what type of cancer did eva peron have?

[Assistant] Let's start by looking at some similar examples.

[Tool]
Example 1:
Question:
what type of cancer did donna summer died from?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q908933 wdt:P509 ?x .
}

Using entities:
Donna Summer, also known as Donna Sommer, LaDonna Gaines (wd:Q908933): American singer (1948–2012), recording artist, songwriter, musician, composer, singer, actor

Using properties:
cause of death, also known as death cause, murder method, method of murder, die of, die from (wd:P509 as wdt): underlying or immediate cause of death.  Underlying cause (e.g. ...adest category, e.g. natural causes, accident, homicide, suicide

Example 2:
Question:
what cancer did audrey hepburn died of?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q42786 wdt:P509 ?x .
}

Using entities:
Audrey Hepburn, also known as Edda Kathleen Ruston, Audrey Kathleen Ruston, Edda van Heemstra, Audrey Kathleen Hepburn-Ruston (wd:Q42786): British actress (1929–1993), philanthropist, ballet dancer, humanitarian, stage actor, film actor, dancer, actor, model

Using properties:
cause of death, also known as death cause, murder method, method of murder, die of, die from (wd:P509 as wdt): underlying or immediate cause of death.  Underlying cause (e.g. ...adest category, e.g. natural causes, accident, homicide, suicide

Example 3:
Question:
what disease did helen keller?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q38203 wdt:P1050 ?x .
}

Using entities:
Helen Keller, also known as Helen Adams Keller (wd:Q38203): American author and activist (1880–1968), political activist, autobiographer, peace activist, trade unionist, suffragette, essayist, linguist, writer, orator

Using properties:
medical condition, also known as disability, suffers from, suffer from, sickness, paralympic disability (wd:P1050 as wdt): any state relevant to the health of an organism, including diseases and positive conditions

[Assistant]
From the examples, it appears that the property "cause of death" (wdt:P509) is commonly used to find the type of cancer or disease a person had that caused their death. Another property that might be relevant is "medical condition" (wdt:P1050).

Next, I will search for the entity "Eva Peron" in Wikidata to get her identifier.

[Tool]
Top 10 entity alternatives:
1. Eva Perón, also known as Evita Perón, Maria Eva Duarte de Peron, Evita, María Eva Duarte de Perón, Maria Eva Duarte Peron (wd:Q40933): Argentine actress and politician (1919–1952), women's rights activist, trade unionist, stage actor, suffragist, politician, film actor
2. Eva Perón: The True Story, also known as Eva Peron, Eva Perón (wd:Q953441): 1996 film by Juan Carlos Desanzo
3. Fray Luis Beltrán, also known as Eva Perón, Eva Perón tanker, Fray Luis Beltrán tanker (wd:Q113059537): tanker
4. Eva Perón (wd:Q113030601): tanker
5. Hospital Lagomarsino, also known as Eva Perón (wd:Q5902632): hospital in Merlo, Buenos Aires
6. Uruguay, also known as Eva Perón (wd:Q113330807): 1951 passenger ship
7. Eva Perón (wd:Q47512378): painting by Boris Chaliapin
8. Estadio Eva Perón, also known as Estadio Eva Peron (wd:Q5400194): football stadium in Junín, Argentina
9. Puerto Eva Perón (wd:Q972928): ciudad en la provincia de Chaco, Argentina
10. Eva Perón Foundation (wd:Q2004004): former Argentine foundation

[Assistant] The entity for Eva Peron is wd:Q40933. Now I will check the property "cause of death" (wdt:P509) for Eva Peron to see if the type of cancer she had is recorded there.

[Tool]
Got 1 row and 2 columns:
| causeOfDeath                       | causeOfDeathLabel          |
| ---------------------------------- | -------------------------- |
| cervix uterine cancer (wd:Q160105) | cervix uterine cancer (en) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the cause of death for Eva Peron using the property 'cause of death' (wdt:P509). The query returns the identifier and English label for the cause of death, which is 'cervix uterine cancer' (wd:Q160105). The answer is accurate and complete based on the data from Wikidata. The query follows the rules by returning the actual identifier and an optional label. No further refinement is necessary.