PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?school ?schoolLabel WHERE {
  wd:Q127417 wdt:P69 ?school .
  ?school wdt:P31 / wdt:P279 * wd:Q917182 .
  OPTIONAL {
    ?school rdfs:label ?schoolLabel FILTER ( LANG( ?schoolLabel ) = "en" )
  }
}

According to Wikidata, Douglas MacArthur attended the United States Military Academy, which is a military academy. Other schools listed without this classification were excluded for relevance.

[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-sebastian

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 school did douglas macarthur go to?

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

[Tool]
Example 1:
Question:
who played mulder in the x files?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q2744 p:P161 ?p .
  ?p ps:P161 ?x ; pq:P453 wd:Q2738 .
}

Using entities:
Fox Mulder, also known as FBI Special Agent Fox Mulder, Special Agent Fox Mulder, Mulder, Fox William Mulder (wd:Q2738): fictional character and protagonist of the television series The X-Files, special agent, FBI agent
The X-Files, also known as X-Files, The X Files, X Files (wd:Q2744): American science fiction-drama television series

Using properties:
cast member, also known as feat., starring (film/play), film starring, starring, actor (wd:P161 as p/ps): actor in the subject production [use "character role" (P453) and...use "recorded participant" (P11108) for non-fiction productions], significant person, performer
character role, also known as role, plays, performer of, as, acting role (wd:P453 as pq): specific role played or filled by subject -- use only as qualifier of "cast member" (P161), "voice actor" (P725)

Example 2:
Question:
what language does the country italy speak?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q38 wdt:P37 ?x .
}

Using entities:
Italy, also known as Italia, Republic of Italy, Repubblica Italiana, Italian Republic, ITA (wd:Q38): country in Southern Europe

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:
when does the world cup occur?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q19317 wdt:P2257 ?x .
}

Using entities:
FIFA World Cup, also known as World Cup, The World Cup, Soccer World Cup, FWC, FIFA World Cup of Football (wd:Q19317): international association football competition contested by the senior men's national teams

Using properties:
event interval, also known as event frequency, frequency of event, interval, period (wd:P2257 as wdt): standard nominal interval between scheduled or regularly recurri...1/(event frequency). Time period of periodically occurring event

[Assistant] I have seen examples of how to query for properties of an entity and how to query for values of a property for an entity. Now I will search for the entity "Douglas MacArthur" in Wikidata to find his identifier.

[Tool]
Top 10 entity alternatives:
1. Douglas MacArthur, also known as MacArthur, D. MacArthur, General MacArthur, General Douglas MacArthur (wd:Q127417): United States Army general in WWI, WWII and Korea (1880–1964), military officer, army officer
2. Douglas MacArthur (wd:Q47512806): painting by Howard Chandler Christy
3. Douglas MacArthur (wd:Q47509083): painting by Rudolphe Kiss
4. Douglas Macarthur (wd:Q110179636)
5. Douglas Allan Hamilton MacArthur, also known as Douglas MacArthur (wd:Q76272190): Peerage person ID=653481
6. Douglas MacArthur II (wd:Q269483): American diplomat (1909-1997), diplomat
7. General Douglas MacArthur (wd:Q5531839): artwork by Robert Dean
8. Douglas MacArthur Park (wd:Q49483971): park in Bexar County, Texas, United States of America
9. Douglas MacArthur Park (wd:Q49483969): park in Los Angeles County, California, United States of America
10. Douglas Hastings Macarthur (wd:Q5301578): New Zealand politician, politician

[Assistant] The entity for Douglas MacArthur, the United States Army general, is wd:Q127417. Now I will search for properties related to education or school for this entity.

[Tool]
Top 10 property alternatives:
1. educated at, also known as graduated from, graduate of, place of education, school attended, schooled at (wd:P69 as p/wdt): educational institution attended by subject, affiliation
2. Commons gallery, also known as gallery (wd:P935 as p/wdt): name of the Wikimedia Commons gallery page(s) related to this item (is suitable to allow multiple links to more gallery pages)
3. significant event, also known as significant occurrence, significant incident, significant achievment, sign. event, outcome (wd:P793 as p/wdt): significant or notable events associated with the subject
4. languages spoken, written or signed, also known as language of expression, language, wrote language, writes language, uses language (wd:P1412 as p/wdt): language(s) that a person or a people speaks, writes or signs, including the native language(s)
5. award received, also known as win, winner of, recognition title, received award, prize received (wd:P166 as p/wdt): award or recognition received by a person, organization or creative work
6. occupation, also known as job, work, vocation, profession, employment (wd:P106 as p/wdt): occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)
7. child, also known as has son, kids, mother of, kid, issue (wd:P40 as p/wdt): subject has object as child. Do not use for stepchildren—use "relative" (P1038), qualified with "type of kinship" (P1039), significant person, relative
8. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as p/wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
9. participant in, also known as participated in, present at, takes part, took part, took part in (wd:P1344 as p/wdt): event in which a person or organization was/is a participant; inverse of P710 or P1923, significant event, part of
10. mother, also known as mom, is child of, mommy, mum, mummy (wd:P25 as p/wdt): female parent of the subject. For stepmother, use "stepparent" (P3448), parent

No other items found

[Assistant] The property "educated at" (wdt:P69) is the relevant property for the school or educational institution attended by Douglas MacArthur. I will now write a SPARQL query to find the schools he attended.

[Tool]
Got 3 rows and 2 columns:
| school                                                             | schoolLabel                                               |
| ------------------------------------------------------------------ | --------------------------------------------------------- |
| United States Army Command and General Staff College (wd:Q1115050) | United States Army Command and General Staff College (en) |
| Milwaukee High School of the Arts (wd:Q6861744)                    | Milwaukee High School of the Arts (en)                    |
| United States Military Academy (wd:Q9219)                          | United States Military Academy (en)                       |

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The SPARQL query correctly retrieves the schools Douglas MacArthur attended using the property 'educated at' (wdt:P69). However, the result includes 'Milwaukee High School of the Arts', which is unlikely to be correct for Douglas MacArthur given his historical timeline and biography. This suggests that the data in Wikidata might have some inaccuracies or that the query is retrieving all educational institutions linked to him without filtering for relevance or time period. To improve, consider verifying the correctness of the schools or filtering the results based on the time period or type of institution (e.g., military academies). Also, the answer could be improved by clarifying that these are the schools listed in Wikidata and noting any potential discrepancies. Overall, the query is structurally correct but the answer needs refinement for accuracy and clarity.

[Assistant] Thank you for the feedback. To improve the accuracy, I will refine the query to retrieve only educational institutions that are military academies or higher military education institutions, as these are more likely to be relevant for Douglas MacArthur. I will filter the schools by their instance of (P31) property to include only military academies or similar institutions. I will first check the Wikidata item for "military academy" to use as a filter.

[Tool]
Top 10 entity alternatives:
1. military academy, also known as service academy, military university academy, military institute, military college (wd:Q917182): higher education institution operated by or for the military
2. Military Academy, also known as Akademi Militer, AKMIL, Indonesian Military Academy, Military Academy of the Indonesian National Army (wd:Q10862512): army education school in Central Java, Indonesia
3. Military Academy (wd:Q1228413): 2007 film by Granz Henman
4. Military Academy (wd:Q16253207): 1940 film by D. Ross Lederman
5. United States Military Academy, also known as Army, West Point Army, West Point, U.S. Military Academy at West Point, US Military Academy (wd:Q9219): federal service academy in West Point, New York, United States
6. Republic of China Military Academy, also known as Whampoa Military Academy, R.O.C. Military Academy, ROCMA, Kuomintang Army Officer Academy, CMA (wd:Q16242140): military academy of the Republic of China Army in Kaohsiung, Taiwan
7. Prussian Military Academy (wd:Q144242): school
8. Theresian Military Academy (wd:Q568705): Austrian military academy
9. Indian Military Academy (wd:Q3595639): officer training Academy of the Indian Army
10. Royal Military Academy, Woolwich, also known as RMA, RM Academy, Woolwich, RMA Woolwich, Royal Military Academy, The Royal Military Academy (wd:Q1573631): military academy in Woolwich, in south-east London

[Assistant] The entity for "military academy" is wd:Q917182. I will now refine the query to only include schools that are instances of military academy (wd:Q917182) or its subclasses.

[Tool]
Got 1 row and 2 columns:
| school                                    | schoolLabel                         |
| ----------------------------------------- | ----------------------------------- |
| United States Military Academy (wd:Q9219) | United States Military Academy (en) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the school Douglas MacArthur attended, filtering for institutions that are military academies. The answer is accurate and complete, providing the United States Military Academy as the school he attended. The query also includes English labels for readability. No further refinement is necessary.


PREFIX ps: <http://www.wikidata.org/prop/statement/>
PREFIX p: <http://www.wikidata.org/prop/>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX pq: <http://www.wikidata.org/prop/qualifier/>
SELECT ?actor ?actorLabel WHERE {
  wd:Q3577037 p:P161 ?castStatement .
  ?castStatement ps:P161 ?actor .
  ?castStatement pq:P453 wd:Q3036775 .
  OPTIONAL {
    ?actor rdfs:label ?actorLabel .
    FILTER ( LANG( ?actorLabel ) = "en" )
  }
}

The character Donna Moss on The West Wing was played by Janel Moloney.

[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-sebastian

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] who played donna on west wing?

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

[Tool]
Example 1:
Question:
what schools did barack obama attend?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q76 wdt:P69 ?x .
}

Using entities:
Barack Obama, also known as Honorable Barack Obama, BHO, Obama, Barry O Bomber, President Obama (wd:Q76): president of the United States from 2009 to 2017, community organizer, political writer, statesperson, politician, podcaster, memoirist, academic, lawyer, jurist

Using properties:
educated at, also known as graduated from, graduate of, place of education, school attended, schooled at (wd:P69 as wdt): educational institution attended by subject, affiliation

Example 2:
Question:
who is the prime minister of ethiopia?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q115 wdt:P6 ?x .
}

Using entities:
Ethiopia, also known as et, ETH, Federal Democratic Republic of Ethiopia (wd:Q115): country in the Horn of Africa

Using properties:
head of government, also known as head of national government, mayor, premier, president, prime minister (wd:P6 as wdt): head of the executive power of this town, city, municipality, state, country, or other governmental body, director / manager, chairperson

Example 3:
Question:
who does danneel harris play on one tree hill?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q203385 p:P161 ?p .
  ?p ps:P161 wd:Q230176 ; pq:P453 ?x .
}

Using entities:
One Tree Hill (wd:Q203385): 2003 American television drama series
Danneel Ackles, also known as Danneel Harris (wd:Q230176): American actress, television actor, film actor, actor, model

Using properties:
cast member, also known as feat., starring (film/play), film starring, starring, actor (wd:P161 as p/ps): actor in the subject production [use "character role" (P453) and...use "recorded participant" (P11108) for non-fiction productions], significant person, performer
character role, also known as role, plays, performer of, as, acting role (wd:P453 as pq): specific role played or filled by subject -- use only as qualifier of "cast member" (P161), "voice actor" (P725)

[Assistant]
From the examples, I see that to find who played a character in a TV show, we can use the property "cast member" (P161) with a qualifier "character role" (P453) to specify the character played.

Step 1: I will search for the entity "The West Wing" to get its Wikidata ID.

[Tool]
Top 10 entity alternatives:
1. The West Wing, also known as West Wing (wd:Q3577037): American political drama series created by Aaron Sorkin for NBC (1999–2006)
2. West Wing, also known as the West Wing, West Wing of the White House, White House West Wing (wd:Q1932621): west office section of the White House, Washington DC, USA
3. McGuffey Hall, also known as The West Wing (wd:Q123015331): building of Ohio University in Athens, Ohio, USA
4. The West Wing (wd:Q130511003): song by Akuma Kira
5. The West Wing (wd:Q130511005): instrumental track by Akuma Kira, Jarren Crist and Nolan Reese; 2015 studio recording
6. Pilot, also known as The West Wing pilot (wd:Q7194391): episode of The West Wing (S1 E1)
7. The West Wing Weekly (wd:Q28127811): American podcast
8. The West Wing Thing (wd:Q104867287): American podcast series
9. The West Wing, season 5 (wd:Q3730540): season of television series
10. The West Wing, season 4 (wd:Q3730539): season of television series

[Assistant] The West Wing TV series is identified as wd:Q3577037. Next, I will search for the property related to "cast member" or "actor" for this entity to find who played the character Donna.

[Tool]
Top 10 property alternatives:
1. cast member, also known as feat., starring (film/play), film starring, starring, actor (wd:P161 as p/wdt): actor in the subject production [use "character role" (P453) and...use "recorded participant" (P11108) for non-fiction productions], significant person, performer
2. director, also known as film director, movie director, game director, directed by (wd:P57 as p/wdt): director(s) of film, TV-series, stageplay, video game or similar, contributor to the creative work or subject, creator
3. screenwriter, also known as story by, teleplay by, video game writer, writer (of screenplays), writing credits (wd:P58 as p/wdt): person(s) who wrote the script for subject item, film crew member, author
4. producer, also known as music producer, record producer, produced by, film producer, creative producer (wd:P162 as p/wdt): person(s) who produced the film, musical work, theatrical produc...etc.) [for production company, use P272, video games - use P178]
5. filming location, also known as studio where filmed, shot in, shooting location, place where filmed, place of filming (wd:P915 as p/wdt): actual place where this scene/film was shot. For the setting, use "narrative location" (P840), recording location
6. genre, also known as genre of music, type of music, type of film, music genre, literary genre (wd:P136 as p/wdt): creative work's genre or an artist's field of work (P101). Use main subject (P921) to relate creative works to their topic
7. director of photography, also known as cinematographer, DOP (wd:P344 as p/wdt): person responsible for the framing, lighting, and filtration of the subject work, film crew member
8. original language of film or TV show, also known as media language, original language, language of the original work, created on language (wd:P364 as p/wdt): language in which a film or a performance work was originally cr... works and songs; use P407 ("language of work or name") instead., language of work or name
9. production company, also known as broadcasting company, theatrical troupe, theatre company, theater company, studio (wd:P272 as p/wdt): company that produced this film, audio or performing arts work
10. IMDb ID, also known as IMDb identifier, Internet Movie Database identifier (wd:P345 as p/wdt): identifier for the IMDb (with prefix 'tt', 'nm', 'co', 'ev', 'ch' or 'ni')

No other items found

[Assistant] The property "cast member" (wdt:P161) is the correct property to use to find actors in the TV series. Now I will search for the cast members of The West Wing who played a character named "Donna." I will look for cast members with the qualifier "character role" (P453) equal to "Donna." First, I need to find the entity for the character "Donna" in The West Wing. I will search for "Donna West Wing" to find the character entity.

[Tool]
Top 10 entity alternatives:
1. The West Wing, also known as West Wing (wd:Q3577037): American political drama series created by Aaron Sorkin for NBC (1999–2006)
2. West Wing, also known as the West Wing, West Wing of the White House, White House West Wing (wd:Q1932621): west office section of the White House, Washington DC, USA
3. Donna West (wd:Q130267686): clinical assistant professor of nursing, clinical assistant professor
4. Donna E West, also known as Donna West (wd:Q85753634): researcher
5. West Wing (wd:Q26387306): building in Ringwood, New Forest, Hampshire, England, UK
6. First Assessment, also known as West Crow Wing, Minnesota, West Crow Wing (wd:Q5862254): unorganized territory of Crow Wing County, Minnesota, US
7. East Wing West Wing (wd:Q5329697): Hong Kong Drama Series
8. West Wing Week (wd:Q7987008): Weekly web-episode produced by The White House about the week's events concerning the President of the United States.
9. Buffalo West Wing (wd:Q30632637): 2011 novel by Julie Hyzy
10. McGuffey Hall, also known as The West Wing (wd:Q123015331): building of Ohio University in Athens, Ohio, USA

[Assistant] There is no direct entity for the character "Donna" from The West Wing. I will try a different approach: I will query the cast members of The West Wing and their character roles to find which one played "Donna."

[Tool] Got no rows and 3 columns

[Assistant] The query returned no results, possibly because the character role is not stored as a simple string or the character name "Donna" is not directly linked as a qualifier. I will try a simpler query to list all cast members and their character roles for The West Wing to manually check for "Donna."

[Tool]
Failed to call function execute:
failed to parse input: parse error at position 254 for token FILTER with content 'FILTER' (the input most likely does not follow the grammar)

[Assistant] The query failed because the endpoint does not support the SERVICE wikibase:label syntax and the FILTER function was incorrectly used. I will rewrite the query without SERVICE wikibase:label and use OPTIONAL with rdfs:label for actor labels.

[Tool]
Got 10 rows and 3 columns:
| actor                           | actorLabel             | characterRole                |
| ------------------------------- | ---------------------- | ---------------------------- |
| Stockard Channing (wd:Q1117390) | Stockard Channing (en) | Abbey Bartlet (wd:Q3603297)  |
| Janel Moloney (wd:Q114447)      | Janel Moloney (en)     | Donna Moss (wd:Q3036775)     |
| Martin Sheen (wd:Q184572)       | Martin Sheen (en)      | Josiah Bartlet (wd:Q2715593) |
| Allison Janney (wd:Q229487)     | Allison Janney (en)    | C. J. Cregg (wd:Q1080587)    |
| Rob Lowe (wd:Q296505)           | Rob Lowe (en)          | Sam Seaborn (wd:Q3946354)    |
| Bradley Whitford (wd:Q352180)   | Bradley Whitford (en)  | Josh Lyman (wd:Q5656906)     |
| John Spencer (wd:Q352748)       | John Spencer (en)      | Leo McGarry (wd:Q6524042)    |
| Richard Schiff (wd:Q355209)     | Richard Schiff (en)    | Toby Ziegler (wd:Q1345373)   |
| Dulé Hill (wd:Q458664)          | Dulé Hill (en)         | Charlie Young (wd:Q3666688)  |
| Joshua Malina (wd:Q60422)       | Joshua Malina (en)     | Will Bailey (wd:Q8002690)    |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly identifies the actor who played the character Donna Moss on The West Wing. It uses the property 'cast member' (P161) with the qualifier 'character role' (P453) to filter for the specific character Donna Moss (wd:Q3036775) in the TV series The West Wing (wd:Q3577037). The query returns the actor's identifier and English label, which matches the answer given: Janel Moloney. The query follows the rules by returning identifiers and labels optionally, and the answer is accurate and complete.


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?country ?countryLabel WHERE {
  ?country wdt:P31 wd:Q6256 ; wdt:P37 wd:Q188 .
  OPTIONAL {
    ?country rdfs:label ?countryLabel FILTER ( LANG( ?countryLabel ) = "en" )
  }
}

Got 6 rows and 2 columns:
| country                 | countryLabel       |
| ----------------------- | ------------------ |
| Germany (wd:Q183)       | Germany (en)       |
| Belgium (wd:Q31)        | Belgium (en)       |
| Luxembourg (wd:Q32)     | Luxembourg (en)    |
| Liechtenstein (wd:Q347) | Liechtenstein (en) |
| Switzerland (wd:Q39)    | Switzerland (en)   |
| Austria (wd:Q40)        | Austria (en)       |

The countries that speak German officially are Germany, Belgium, Luxembourg, Liechtenstein, Switzerland, and Austria.

[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-sebastian

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] which countries speak german officially?

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

[Tool]
Example 1:
Question:
what year did arizona cardinals go to superbowl?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?y wdt:P31 / wdt:P279 * wd:Q32096 ; wdt:P1923 wd:Q224164 ; wdt:P585 ?x .
}

Using entities:
Arizona Cardinals, also known as St. Louis Cardinals, Racine Cardinals, Morgan Athletic Club, Chicago Cardinals, Phoenix Cardinals (wd:Q224164): National Football League franchise in Glendale, Arizona
Super Bowl, also known as AFL–NFL World Championship Game (wd:Q32096): National Football League championship game

Using properties:
participating team, also known as teams (wd:P1923 as wdt): like 'Participant' (P710) but for teams. For an event like a cyc...member of sports team' (P54) as a qualifier for the individuals), participant
subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as wdt): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
point in time, also known as at time, as of, year, when, time of event (wd:P585 as wdt): date something took place, existed or a statement was true; for providing time use the "refine date" property (P4241)

Example 2:
Question:
what instruments does john williams use?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q370293 wdt:P1303 ?x .
}

Using entities:
John Williams (wd:Q370293): Australian classical guitarist, classical guitarist, performing artist, music educator, composer

Using properties:
instrument, also known as uses this instrument, teaches instrument, instruments, plays this instrument, plays instrument (wd:P1303 as wdt): musical instrument that a person plays or teaches or used in a music occupation, uses

Example 3:
Question:
what is the very first harry potter book?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x wdt:P179 wd:Q8337 ; wdt:P577 ?y .
}
ORDER BY ?y
LIMIT 1

Using entities:
Harry Potter, also known as Harry Potter series (wd:Q8337): 1997–2007 fantasy book series by J. K. Rowling

Using properties:
part of the series, also known as series, video game series, subseries, part of series, listed in (wd:P179 as wdt): series which contains the subject, part of
publication date, also known as launched, published, publication time, publication, pubdate (wd:P577 as wdt): date or point in time when a work was first published or released, point in time

[Assistant] The examples did not directly relate to countries speaking a language officially, so I will now search for the entity "German language" to find its Wikidata identifier. Then I will look for the property related to official language and find countries that have German as an official language.

[Tool]
Top 10 entity alternatives:
1. German, also known as de, German language (wd:Q188): West Germanic language spoken mainly in Central Europe
2. German Language (wd:Q110262520): Stack Exchange site for speakers of German wanting to discuss the finer points of the language and translation
3. German (language) (wd:L4969-S1)
4. German (language) (wd:L612756-S1)
5. German language (wd:L1029357-S1)
6. German language (wd:L1121420-S2)
7. German language (wd:L1363537-S1)
8. Germanic, also known as Germanic family, Germanic language, Germanic language family, Germanic language group, Germanic languages (wd:Q21200): branch of the Indo-European language family
9. German Wikipedia, also known as dewiki, Wikipedia (de), wikipedia.de, German-language Wikipedia, German language Wikipedia (wd:Q48183): German-language edition of Wikipedia
10. Pennsylvania German, also known as Pennsylvanisch Deitsch, Pennsylvanisch, Pennsylvanian language, Pennsylvania German-language, Pennsylvania German language (wd:Q22711): variety of West Central German

[Assistant] The entity for the German language is wd:Q188. Now I will search for the property related to "official language" to find countries that have German as an official language.

[Tool]
Top 10 property alternatives:
1. official language, also known as language spoken, spoken in, speaking, language official (wd:P37 as ps/psv/wdtn/pr/p/wdt/pqv/prn/prv/pqn/pq/psn): language designated as official by this item, language used
2. native label, also known as official title, original label, original language label, original language name, original language title (wd:P1705 as ps/psv/wdtn/pr/p/wdt/pqv/prn/prv/pqn/pq/psn): label for the items in their official language  or their original language, name
3. Ethnologue language status, also known as EGIDS, language status (wd:P3823 as ps/psv/wdtn/pr/p/wdt/pqv/prn/prv/pqn/pq/psn): language status identifier by Ethnologue.com using EGIDS scale
4. language regulatory body, also known as language authority, regulatory body (wd:P1018 as ps/psv/wdtn/pr/p/wdt/pqv/prn/prv/pqn/pq/psn): regulatory body of a language
5. languages spoken, written or signed, also known as language of expression, language, wrote language, writes language, uses language (wd:P1412 as ps/psv/wdtn/pr/p/wdt/pqv/prn/prv/pqn/pq/psn): language(s) that a person or a people speaks, writes or signs, including the native language(s)
6. native language, also known as first language, L1 speaker of, language native, mother tongue (wd:P103 as ps/psv/wdtn/pr/p/wdt/pqv/prn/prv/pqn/pq/psn): language or languages a person has learned from early childhood, languages spoken, written or signed
7. language used, also known as languages used, medium of instruction, used language, uses language, working language (wd:P2936 as ps/psv/wdtn/pr/p/wdt/pqv/prn/prv/pqn/pq/psn): language widely used (spoken or written) in this place or at this event or organisation
8. language of work or name, also known as language of the reference, language of URL, language of website, language of work, named in language (wd:P407 as ps/psv/wdtn/pr/p/wdt/pqv/prn/prv/pqn/pq/psn): language associated with this creative work (such as books, show...guage" (P103) and "languages spoken, written or signed" (P1412))
9. programmed in, also known as language, programming language, written in (wd:P277 as ps/psv/wdtn/pr/p/wdt/pqv/prn/prv/pqn/pq/psn): the programming language(s) in which the software is developed
10. writing language, also known as languages of writings, languages written, language written, writing languages, language of works (wd:P6886 as ps/psv/wdtn/pr/p/wdt/pqv/prn/prv/pqn/pq/psn): language in which the writer has written their work, languages spoken, written or signed

[Assistant] The property for official language is wd:P37. Now I will write a SPARQL query to find countries (instances of country) that have German (wd:Q188) as an official language (wdt:P37). I will also include the country labels for readability.

[Tool]
Got 6 rows and 2 columns:
| country                 | countryLabel       |
| ----------------------- | ------------------ |
| Germany (wd:Q183)       | Germany (en)       |
| Belgium (wd:Q31)        | Belgium (en)       |
| Luxembourg (wd:Q32)     | Luxembourg (en)    |
| Liechtenstein (wd:Q347) | Liechtenstein (en) |
| Switzerland (wd:Q39)    | Switzerland (en)   |
| Austria (wd:Q40)        | Austria (en)       |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves countries where German is an official language by checking for instances of countries with the official language property set to German. The result includes the expected countries: Germany, Belgium, Luxembourg, Liechtenstein, Switzerland, and Austria. The query also optionally retrieves English labels for readability. The answer is accurate and complete based on the query results. No further refinement is necessary.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?dateOfBirth WHERE {
  wd:Q352 wdt:P569 ?dateOfBirth .
}

Adolf Hitler was born in the year 1889.

[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-sebastian

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 year was hitler was born?

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

[Tool]
Example 1:
Question:
where was dwight d. eisenhower from?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q9916 wdt:P19 ?x .
}

Using entities:
Dwight D. Eisenhower, also known as Ike, Eisenhower, Dwight Eisenhower, Dwight David Eisenhower, Ike Eisenhower (wd:Q9916): president of the United States from 1953 to 1961, military personnel, military officer, army officer, statesperson, politician, writer

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:
what did wagner compose?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x wdt:P86 wd:Q1511 .
}

Using entities:
Richard Wagner, also known as Wilhelm Richard Wagner, Wagner (wd:Q1511): German composer (1813–1883), theatrical director, autobiographer, music critic, librettist, conductor, essayist, composer, diarist, pianist, writer, poet

Using properties:
composer, also known as music by, written by, songwriter, musical score by, film score by (wd:P86 as wdt): person(s) who wrote the music [for lyricist, use "lyrics by" (P676)], creator

Example 3:
Question:
what state was texaco gas founded?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q775060 wdt:P740 ?p .
  ?p wdt:P131 + ?x .
  ?x wdt:P31 wd:Q107390 .
}

Using entities:
federated state, also known as state in a federation, state of a federation, state, federal state, constituent state (wd:Q107390): territorial and constitutional community forming part of a federal union
Texaco, also known as Texas Company, Texas Oil Company (wd:Q775060): oil subsidiary of Chevron Corporation

Using properties:
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 wdt): the item is located on the territory of the following administra...if the item falls only partially into the administrative entity., location, part of
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
location of formation, also known as place of incorporation, originates from, place of establishment, place of formation, place of foundation (wd:P740 as wdt): location where a group or organization was formed, location of creation

[Assistant]
The question is about the year Adolf Hitler was born. We need to find the entity for Adolf Hitler and then find the property that indicates the year of birth.

Step 1: Search for the entity "Adolf Hitler" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Adolf Hitler, also known as Bohemian Corporal (wd:Q352): dictator of Germany from 1933 to 1945, politician
2. Adolph, also known as Adolf Hitler (wd:Q12626556): computer virus
3. Adolf Hitler, also known as TMNT Adventures Adolf Hitler (wd:Q100345867): Adolf Hitler as depicted in the Teenage Mutant Ninja Turtles Adventures comics
4. Adolf Hitler, also known as Family Guy Adolf Hitler (wd:Q120332530): Adolf Hitler as depicted in animated television series Family Guy, politician
5. Adolf Hitler (wd:Q78526535): edition; published in 1997
6. Adolf Hitler (wd:Q47510643): painting by Jerry Farnsworth
7. Adolf Hitler (wd:Q20463000): painting by Andrea Badami
8. Adolf Hitler (wd:Q112253120): painting by 1935 H. Knirr
9. Adolf Hitler (wd:Q112243291): painting by F. Heß
10. Adolf Hitler (wd:Q112235833): painting by R.G. Zill

[Assistant] The entity for Adolf Hitler is wd:Q352. Now, let's find the property that indicates the year of birth for this entity. Usually, the property for date of birth is P569. Let's confirm this by searching for properties related to birth for Adolf Hitler.

[Tool]
Top 10 property alternatives:
1. date of baptism, also known as christened, time of christening, time of baptism, date of christening, date of baptism in early childhood (wd:P1636 as p/wdt): date when a person was baptized. For times when only baptism rec...were available, this can be a good substitute for date of birth., start time
2. place of birth, also known as POB, location of birth, location born, born in, birthplace (wd:P19 as p/wdt): 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 p/wdt): date on which the subject was born, inception
4. work period (start), also known as start working, flourished (start), start time for work, start date of activity, fl. (start) (wd:P2031 as p/wdt): start of period during which a person or group flourished (fl. = "floruit") in their professional activity, start time, floruit
5. sex or gender, also known as gender or sex, sex, gender identity, gender expression, gender (wd:P21 as p/wdt): sex or gender identity of human or animal. For human: male, fema...m, female organism. Groups of same gender use subclass of (P279)
6. military branch, also known as unit branch, service branch, formation, branch (wd:P241 as p/wdt): branch to which this military unit, award, office, or person belongs, e.g. Royal Navy, part of
7. country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as p/wdt): the object is a country that recognizes the subject as its citizen, country
8. described by source, also known as mentioned in, source of item, reviewed in, mentioned in news article, talked about in (wd:P1343 as p/wdt): work where this item is described, attested in
9. mother, also known as mom, is child of, mommy, mum, mummy (wd:P25 as p/wdt): female parent of the subject. For stepmother, use "stepparent" (P3448), parent
10. date of death, also known as DOD, deathdate, died, died on, year of death (wd:P570 as p/wdt): dissolved, abolished or demolished date, date on which the subject died, end time

No other items found

[Assistant] The property for the date of birth is P569. Now, I will write a SPARQL query to get the year Adolf Hitler was born using the entity wd:Q352 and property wdt:P569.

[Tool]
Got 1 row and 1 column:
| dateOfBirth                         |
| ----------------------------------- |
| 1889-04-20T00:00:00Z (xsd:dateTime) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the date of birth of Adolf Hitler using the appropriate entity (wd:Q352) and property (wdt:P569). The answer provided, 1889, is accurate and matches the query result. The query follows the rules by returning the actual identifier and the date value. No further refinement is necessary.


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT DISTINCT ?song ?songLabel WHERE {
  {
    ?song wdt:P86 wd:Q34086 .
  } UNION {
    ?song wdt:P676 wd:Q34086 .
  }
  OPTIONAL {
    ?song rdfs:label ?songLabel FILTER ( LANG( ?songLabel ) = "en" )
  }
}

Justin Bieber wrote 37 songs according to Wikidata. The query returns the Wikidata identifiers and English labels of these songs.

[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-sebastian

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 are all the songs justin bieber wrote?

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

[Tool]
Example 1:
Question:
what did john quincy adams died of?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q11816 wdt:P509 ?x .
}

Using entities:
John Quincy Adams, also known as President Adams, JQA, J. Q. Adams, J. Adams, John Q. Adams (wd:Q11816): President of the United States from 1825 to 1829, statesperson, politician, diplomat, diarist, writer, lawyer

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 kind government does canada have?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q16 wdt:P122 ?x .
}

Using entities:
Canada, also known as CA, CAN, Dominion of Canada, ISO 3166-1:CA (wd:Q16): country in North America

Using properties:
basic form of government, also known as form of government, government, type of government (wd:P122 as wdt): subject's government

Example 3:
Question:
who has tom brady played for?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q313381 wdt:P54 ?x .
}

Using entities:
Tom Brady, also known as Thomas Edward Patrick Brady, Jr., Thomas Edward Brady, Jr., Thomas Edward Patrick Brady Jr., Thomas Edward Patrick Brady, Thomas Brady (wd:Q313381): American football player (born 1977), American football player

Using properties:
member of sports team, also known as plays for, played for, sport team, team, team played for (wd:P54 as wdt): sports teams or clubs that the subject represents or represented, member of

[Assistant]
The examples show how to query for properties of an entity. In this case, we want to find all songs that Justin Bieber wrote. We need to identify the entity for Justin Bieber and the property that relates a songwriter to the songs they wrote.

Step 1: Search for the entity "Justin Bieber" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Justin Bieber, also known as Justin Drew Bieber (wd:Q34086): Canadian singer (born 1994), musician
2. Lili Elbe, also known as Einar Mogens Andreas Wegener, Einar Wegener, Justin Bieber, Lili Ilse Elvenes (wd:Q1140735): Danish painter and transgender woman (1882–1931), painter
3. Justin Bieber (wd:Q127000216): Is It A Good Idea To Microwave This? experiment 296
4. Justin Bieber, also known as Saturday Night Live S38E13, Saturday Night Live, season 38 episode 13 (wd:Q110037270): episode of Saturday Night Live (S38 E13)
5. Justin Bieber: Seasons (wd:Q84078716): docu-series
6. Kristian Marolt, also known as Croatian Justin Bieber (wd:Q49272382): Croatian singer-songwriter, singer-songwriter
7. Promo: Justin Bieber (wd:Q110056122): sketch from Saturday Night Live
8. Justin Bieber's Believe (wd:Q15285106): 2013 American biographical concert film directed by Jon M. Chu
9. Asim Azhar, also known as Justin Bieber of Pakistan, The Justin Bieber of Pakistan (wd:Q66771659): Pakistani singer-songwriter, singer-songwriter
10. Justin Bieber: Our World (wd:Q108704270): 2021 film directed by Michael D. Ratner

[Assistant] The entity for the Canadian singer Justin Bieber is wd:Q34086. Next, we need to find the property that relates a songwriter to the songs they wrote. Let's search for properties related to "written by" or "composer" for the entity Justin Bieber.

[Tool]
Top 10 property alternatives:
1. described by source, also known as mentioned in, source of item, reviewed in, mentioned in news article, talked about in (wd:P1343 as p/wdt): work where this item is described, attested in
2. languages spoken, written or signed, also known as language of expression, language, wrote language, writes language, uses language (wd:P1412 as p/wdt): language(s) that a person or a people speaks, writes or signs, including the native language(s)
3. religion or worldview, also known as believes, worldview, religious affiliation, religion or world view, religion (wd:P140 as p/wdt): religion of a person, organization or religious building, or associated with this subject
4. signature, also known as signature image, image of signature, facsimiles, autograph (wd:P109 as p/wdt): image of a person's signature, image
5. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as p/wdt): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
6. place of birth, also known as POB, location of birth, location born, born in, birthplace (wd:P19 as p/wdt): most specific known birth location of a person, animal or fictional character, location
7. date of birth, also known as year of birth, birthdate, DOB, born on, born (wd:P569 as p/wdt): date on which the subject was born, inception
8. participant in, also known as participated in, present at, takes part, took part, took part in (wd:P1344 as p/wdt): event in which a person or organization was/is a participant; inverse of P710 or P1923, significant event, part of
9. educated at, also known as graduated from, graduate of, place of education, school attended, schooled at (wd:P69 as p/wdt): educational institution attended by subject, affiliation
10. short name, also known as short title, shortname, abbreviation, shortened name, initialism (wd:P1813 as p/wdt): short name of a place, organisation, person, journal, wikidata property, etc. Used by some Wikipedia templates., name

No other items found

[Assistant] The search for properties related to "written" for Justin Bieber did not return a direct property for songs he wrote. Let's try searching for properties related to "composer" or "author" in general.

[Tool]
Top 10 property alternatives:
1. composer, also known as music by, written by, songwriter, musical score by, film score by (wd:P86 as ps/psv/wdtn/pr/p/wdt/pqv/prn/prv/pqn/pq/psn): person(s) who wrote the music [for lyricist, use "lyrics by" (P676)], creator
2. inception, also known as initial release date, founded in, founded on, founded on date, founding date (wd:P571 as ps/psv/wdtn/pr/p/wdt/pqv/prn/prv/pqn/pq/psn): time when an entity begins to exist; for date of official opening use P1619, start time
3. lyricist, also known as text poet, writer (of song lyrics), words by, text writer, text by (wd:P676 as ps/psv/wdtn/pr/p/wdt/pqv/prn/prv/pqn/pq/psn): author of song lyrics, author
4. composers.am person ID (wd:P9628 as ps/psv/wdtn/pr/p/wdt/pqv/prn/prv/pqn/pq/psn): identifier for a person in the  site of Composers Union of Armenia
5. music created for, also known as music for, music for work, music made for, music made for work, music written for (wd:P9899 as ps/psv/wdtn/pr/p/wdt/pqv/prn/prv/pqn/pq/psn): a work, event, etc. for which a musical composition was created ... was written; a film for which motion picture music was created), created for
6. location of creation, also known as manufactured in, manufacturing location, mint, minted at, photographed at (wd:P1071 as ps/psv/wdtn/pr/p/wdt/pqv/prn/prv/pqn/pq/psn): place where the item was conceived or made; where applicable, location of final assembly, significant place
7. Musicsperlacobla composer ID (wd:P11203 as ps/psv/wdtn/pr/p/wdt/pqv/prn/prv/pqn/pq/psn): composer identifier used by musicsperlacobla archive
8. orchestrator, also known as arranged for orchestra by, orchestral arrangement by, orchestral arranger, orchestration by, orchestrations by (wd:P10806 as ps/psv/wdtn/pr/p/wdt/pqv/prn/prv/pqn/pq/psn): person or body responsible for arranging a musical composition for orchestra, adapted by
9. Musicalics composer ID (wd:P6925 as ps/psv/wdtn/pr/p/wdt/pqv/prn/prv/pqn/pq/psn): identifier for a composer in the Musicalics database
10. CompositionToday composer ID, also known as Composition Today composer ID (wd:P8688 as ps/psv/wdtn/pr/p/wdt/pqv/prn/prv/pqn/pq/psn): composer ID on the website CompositionToday

[Assistant]
The property "composer" (wdt:P86) is used for the person(s) who wrote the music. There is also "lyricist" (wdt:P676) for the author of song lyrics. Since the question is about songs Justin Bieber wrote, we should consider both properties.

Step 2: Construct a SPARQL query to find all songs where Justin Bieber (wd:Q34086) is listed as composer (wdt:P86) or lyricist (wdt:P676).

[Tool]
Got 37 rows and 2 columns, showing the first 5 and last 5 rows below:
| song                                       | songLabel                        |
| ------------------------------------------ | -------------------------------- |
| Monster (wd:Q102104614)                    | Monster (en)                     |
| Anyone (wd:Q104612841)                     | Anyone (en)                      |
| Hold On (wd:Q105763560)                    | Hold On (en)                     |
| Peaches (wd:Q106070690)                    | Peaches (en)                     |
| Stay (wd:Q107439752)                       | Stay (en)                        |
| ...                                        | ...                              |
| Yummy (wd:Q79646941)                       | Yummy (en)                       |
| Get Me (wd:Q83975347)                      | Get Me (en)                      |
| Intentions (wd:Q84491474)                  | Intentions (en)                  |
| Yummy (Summer Walker Remix) (wd:Q84925511) | Yummy (Summer Walker Remix) (en) |
| Holy (wd:Q99441275)                        | Holy (en)                        |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves all songs that Justin Bieber wrote, considering both the lyricist (P676) and composer (P86) properties. It returns the Wikidata identifiers and English labels of these songs, which matches the user's question. The query uses a UNION to cover both properties, ensuring completeness. The answer states the number of songs found and provides a sample of results, which is informative and clear. No further refinement is necessary.


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT DISTINCT ?place ?placeLabel WHERE {
  {
    wd:Q34479 wdt:P551 ?place .
  } UNION {
    wd:Q34479 wdt:P263 ?place .
  } UNION {
    wd:Q34479 wdt:P19 ?place .
  } UNION {
    wd:Q34479 wdt:P20 ?place .
  }
  ?place rdfs:label ?placeLabel FILTER ( LANG( ?placeLabel ) = "en" )
}

Got 2 rows and 2 columns:
| place                         | placeLabel          |
| ----------------------------- | ------------------- |
| Fukiage Gyoen (wd:Q11288366)  | Fukiage Gyoen (en)  |
| Akasaka Estate (wd:Q11635414) | Akasaka Estate (en) |

According to Wikidata, the known places where Emperor Hirohito lived include Akasaka Estate (his place of birth) and Fukiage Gyoen (his place of death). There are no additional residences or official residences listed for him in Wikidata, so these are the main known locations associated with where he lived.

[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-sebastian

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 did emperor hirohito live?

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

[Tool]
Example 1:
Question:
who will michael schumacher drive for in 2013?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q9671 p:P54 ?p .
  ?p ps:P54 ?x ; pq:P580 ?y ; pq:P582 ?z .
  FILTER ( ( ?y < "2014-01-01T00:00:00Z" ^^ xsd:dateTime ) && ( ?z >= "2013-01-01T00:00:00Z" ^^ xsd:dateTime ) )
}

Using entities:
Michael Schumacher, also known as Schuey, Schumi (wd:Q9671): German racing driver, Formula One driver, motorcycle racer

Using properties:
member of sports team, also known as plays for, played for, sport team, team, team played for (wd:P54 as p/ps): sports teams or clubs that the subject represents or represented, member of
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
end time, also known as ends, stop time, endtime, fall date, ineffective (wd:P582 as pq): moment when an entity ceases to exist and a statement stops being entirely valid or no longer be true, point in time

Example 2:
Question:
what character does ellen play in finding nemo?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q132863 p:P725 ?p .
  ?p pq:P453 ?x .
  ?p ps:P725 wd:Q483325 .
}

Using entities:
Finding Nemo, also known as Nemo (wd:Q132863): 2003 American animated film
Ellen DeGeneres, also known as Ellen Lee DeGeneres (wd:Q483325): American comedian, television host, actress, and writer (born 1958), LGBTQ rights activist, television presenter, television producer, television actor, talk show host, screenwriter, voice actor, film actor, presenter, comedian, writer, actor

Using properties:
character role, also known as role, plays, performer of, as, acting role (wd:P453 as pq): specific role played or filled by subject -- use only as qualifier of "cast member" (P161), "voice actor" (P725)
voice actor, also known as voice actors, voice dubber, voice actress, voice actresses, voiced by (wd:P725 as p/ps): performer of a spoken role in a creative work such as animation,... (P453) as qualifier] [use "cast member" (P161) for live acting], film crew member, cast member

Example 3:
Question:
what are major religions in the united states?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q30 wdt:P140 ?x .
}

Using entities:
United States, also known as the U.S. of A, United States of America, the US of America, United States of North America, U. S. (wd:Q30): country primarily located in North America

Using properties:
religion or worldview, also known as believes, worldview, religious affiliation, religion or world view, religion (wd:P140 as wdt): religion of a person, organization or religious building, or associated with this subject

[Assistant] I have seen examples of how to query for places related to a person. Now I will search for the entity "Emperor Hirohito" in Wikidata to get his identifier. Then I will look for properties related to where he lived.

[Tool]
Top 10 entity alternatives:
1. Hirohito, also known as Prince Michi, Emperor Shōwa, Showa, Shōwa, Emperor Hirohito (wd:Q34479): Emperor of Japan from 1926 to 1989, military personnel, marine biologist, aristocrat, zoologist, diplomat, monarch
2. Annals of Emperor Showa, also known as Annals of Emperor Shōwa, Annals of Emperor Hirohito (wd:Q86339815)
3. Portrait of Emperor Hirohito (wd:Q120122666): photograph by Vincenzo Laviosa
4. Emperor Hirohito and Empress Nagako (wd:Q63195683)
5. 250 Shillings (Emperor Hirohito) [Num29821] (wd:Q132003665): Non-circulating coins - Milled - Somalia
6. 25 Shillings (Emperor Hirohito) [Num84930] (wd:Q132003361): Non-circulating coins - Milled - Somalia
7. emperor, also known as empress, imperator (wd:Q39018): type of monarch
8. monarch, also known as emperor, empress regnant, king, queen regnant (wd:Q116): person at the head of a monarchy
9. Emperor dragonfly, also known as Anax imperator, Blue Emperor, Emperor, Emperor Dragonfly (wd:Q527496): species of insect
10. Emperor of China, also known as Huang-ti, Huang Ti, Son of Heaven, thearch, Ti (wd:Q268218): sovereign of Imperial China

[Assistant] The entity for Emperor Hirohito is wd:Q34479. Now I will search for properties related to where he lived. I will search for properties of this entity with the query "residence" or "lived".

[Tool]
Top 10 property alternatives:
1. family, also known as royal house, noble family, member of family, house, dynasty (wd:P53 as p/wdt): family, including dynasty and nobility houses. Not family name (use P734 for family name)., member of
2. occupation, also known as job, work, vocation, profession, employment (wd:P106 as p/wdt): occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)
3. country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as p/wdt): the object is a country that recognizes the subject as its citizen, country
4. part of, also known as of, within, system of, subsystem of, subgroup of (wd:P361 as p/wdt): object of which the subject is a part (if this subject is alread... of "has part" (P527, see also "has parts of the class" (P2670))
5. place of birth, also known as POB, location of birth, location born, born in, birthplace (wd:P19 as p/wdt): most specific known birth location of a person, animal or fictional character, location
6. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as p/wdt): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
7. date of birth, also known as year of birth, birthdate, DOB, born on, born (wd:P569 as p/wdt): date on which the subject was born, inception
8. spouse, also known as married partner, married to, marry, partner, spouses (wd:P26 as p/wdt): the subject has the object as their spouse (husband, wife, partn...etc.). Use "unmarried partner" (P451) for non-married companions, significant person, relative
9. described by source, also known as mentioned in, source of item, reviewed in, mentioned in news article, talked about in (wd:P1343 as p/wdt): work where this item is described, attested in
10. signature, also known as signature image, image of signature, facsimiles, autograph (wd:P109 as p/wdt): image of a person's signature, image

No other items found

[Assistant] The property "residence" or "place lived" does not appear directly in the top property results for Emperor Hirohito. I will try searching for the property "residence" in Wikidata to see if there is a specific property for the place where a person lived.

[Tool]
Top 10 property alternatives:
1. residence, also known as living in, place of residence, resided at, resided in, resident in (wd:P551 as ps/psv/wdtn/pr/p/wdt/pqv/prn/prv/pqn/pq/psn): the place where the person is or has been, resident, location
2. occupant, also known as tenant, resident, renter, occupiers, lessee (wd:P466 as ps/psv/wdtn/pr/p/wdt/pqv/prn/prv/pqn/pq/psn): person or organization occupying property, used by
3. work location, also known as work place, working from, working at, worked from, worked at (wd:P937 as ps/psv/wdtn/pr/p/wdt/pqv/prn/prv/pqn/pq/psn): location where persons or organisations were actively participating in employment, business or other work, significant place, location
4. capital, also known as administrative seat, seat of government, seat, principal place, location of capital (wd:P36 as ps/psv/wdtn/pr/p/wdt/pqv/prn/prv/pqn/pq/psn): seat of government of a country, province, state or other type of administrative territorial entity
5. official residence, also known as resides at, lives in, palace, presidential mansion, presidential palace (wd:P263 as ps/psv/wdtn/pr/p/wdt/pqv/prn/prv/pqn/pq/psn): the residence at which heads of government and other senior figures officially reside, residence
6. number of households, also known as dwellings, households (wd:P1538 as ps/psv/wdtn/pr/p/wdt/pqv/prn/prv/pqn/pq/psn): total number of households in this place, includes dwellings of all types
7. number of housing units, also known as dwelling-places, housing units, number of dwelling-places (wd:P10814 as ps/psv/wdtn/pr/p/wdt/pqv/prn/prv/pqn/pq/psn): number of housing units (dwellings) in a specific place (such as city, county, state, country etc.)
8. family, also known as royal house, noble family, member of family, house, dynasty (wd:P53 as ps/psv/wdtn/pr/p/wdt/pqv/prn/prv/pqn/pq/psn): family, including dynasty and nobility houses. Not family name (use P734 for family name)., member of
9. property, also known as allowed qualifier (wd:P2306 as ps/psv/wdtn/pr/p/wdt/pqv/prn/prv/pqn/pq/psn): qualifier to define a property constraint in combination with P2...traint), or to limit the scope of Q44292881 (wikidata statement)
10. Wikidata property, also known as main property, property for this item, property, has property (wd:P1687 as ps/psv/wdtn/pr/p/wdt/pqv/prn/prv/pqn/pq/psn): main Wikidata property for this item

[Assistant] The property "residence" (wdt:P551) is the place where the person is or has been resident. There is also "official residence" (wdt:P263) which is the residence at which heads of government and other senior figures officially reside. I will query for the residence and official residence of Emperor Hirohito (wd:Q34479).

[Tool]
Got 1 row and 4 columns:
| residence | residenceLabel | officialResidence | officialResidenceLabel |
| --------- | -------------- | ----------------- | ---------------------- |

[Assistant] The query for residence and official residence of Emperor Hirohito returned no results. I will try to find the place of birth and place of death as additional information about where he lived.

[Tool]
Got 1 row and 4 columns:
| placeOfBirth                  | placeOfBirthLabel   | placeOfDeath                 | placeOfDeathLabel  |
| ----------------------------- | ------------------- | ---------------------------- | ------------------ |
| Akasaka Estate (wd:Q11635414) | Akasaka Estate (en) | Fukiage Gyoen (wd:Q11288366) | Fukiage Gyoen (en) |

[Assistant] Emperor Hirohito was born at Akasaka Estate and died at Fukiage Gyoen. These are places where he lived at least at the beginning and end of his life. Since there was no direct residence information, these places are relevant to where he lived. I will provide these as the answer.

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The SPARQL query correctly retrieves Emperor Hirohito's place of birth and place of death, which are Akasaka Estate and Fukiage Gyoen respectively. However, the user's question asks where Emperor Hirohito lived, which is broader than just birth and death locations. The query should be refined to also include other known residences or places where he lived during his lifetime, if such data is available in Wikidata. This could involve querying properties related to residence or official residence. Additionally, the answer should clarify that the current data only covers birth and death places and may not fully answer the question about all places he lived.

[Assistant] Thank you for the feedback. I will refine the query to include the properties "residence" (wdt:P551) and "official residence" (wdt:P263) along with place of birth and place of death to cover all known places where Emperor Hirohito lived. I will also clarify in the answer that these are the known places from Wikidata and may not cover all places he lived.

[Tool]
Got 2 rows and 2 columns:
| place                         | placeLabel          |
| ----------------------------- | ------------------- |
| Fukiage Gyoen (wd:Q11288366)  | Fukiage Gyoen (en)  |
| Akasaka Estate (wd:Q11635414) | Akasaka Estate (en) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves places associated with Emperor Hirohito's residence, including place of birth, place of death, official residence, and residence. The answer accurately reflects the query results, mentioning Akasaka Estate and Fukiage Gyoen as known places where he lived. The query uses appropriate properties and returns the identifiers and labels as required. No further refinement is necessary.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?coordinate WHERE {
  wd:Q3572 wdt:P625 ?coordinate .
}

Tunis (wd:Q3572) is located at the geographical coordinates POINT(10.180000 36.800833). This represents its location on a map.

[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-sebastian

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 is tunis on a map?

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

[Tool]
Example 1:
Question:
who won london mayoral elections 2012?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q38931 p:P1308 ?p .
  ?p ps:P1308 ?x ; pq:P580 ?y ; pq:P582 ?z .
  FILTER ( ( ?y < "2013-01-01T00:00:00Z" ^^ xsd:dateTime ) && ( ?z >= "2012-01-01T00:00:00Z" ^^ xsd:dateTime ) )
}

Using entities:
Mayor of London (wd:Q38931): head of the government of Greater London

Using properties:
position holder, also known as incumbent, noble title holder, office holder, position held by (wd:P1308 as p/ps): persons who hold and/or held the position
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
end time, also known as ends, stop time, endtime, fall date, ineffective (wd:P582 as pq): moment when an entity ceases to exist and a statement stops being entirely valid or no longer be true, point in time

Example 2:
Question:
where are the atlanta falcons located?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q272059 wdt:P159 ?x .
}

Using entities:
Atlanta Falcons, also known as Falcons (wd:Q272059): American football team

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:
on what continent is canada found?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q16 wdt:P30 ?x .
}

Using entities:
Canada, also known as CA, CAN, Dominion of Canada, ISO 3166-1:CA (wd:Q16): country in North America

Using properties:
continent (wd:P30 as wdt): continent of which the subject is a part, located in/on physical feature

[Assistant]
The question "where is Tunis on a map?" is asking for the location of Tunis. Tunis is a city, so we want to find its geographical location. Typically, the property for location coordinates in Wikidata is "coordinate location" (wdt:P625).

Step 1: Search for the entity "Tunis" in Wikidata to get its identifier.

[Tool]
Top 10 entity alternatives:
1. Tunis (wd:Q3572): capital of Tunisia
2. French protectorate of Tunisia, also known as Protectorat français de Tunisie, Tunis, Tunisia (wd:Q2017684): 1881-1956 monarchy in Northern Africa
3. Tunis, also known as American Tunis (wd:Q7853119): sheep breed
4. Tunis (wd:Q14222206): village in the Egyptian depression of el-Faiyum
5. Tunis (wd:Q12203526): village in Sohag Governorate, Egypt
6. Tunis (wd:Q96411338): census Designated Place in Texas, United States
7. TUNIS (wd:Q7672034): UNIX-like operating system developed at the University of Toronto
8. Tunis (wd:Q26199309): human settlement in Oman
9. Tunis (wd:Q47457038): given name
10. Tunis (wd:Q16902089): human settlement in Unorganized North Cochrane District, Ontario, Canada

[Assistant]
The entity "Tunis" with the identifier wd:Q3572 is the capital of Tunisia, which is the most relevant entity for the question.

Step 2: We want to find the geographical location of Tunis. The property "coordinate location" (wdt:P625) is typically used for this. I will now write a SPARQL query to get the coordinate location of Tunis (wd:Q3572).

[Tool]
Got 1 row and 1 column:
| coordinate                                  |
| ------------------------------------------- |
| POINT(10.180000 36.800833) (geo:wktLiteral) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the geographical coordinates (P625) of Tunis (Q3572) from Wikidata. The answer provides the coordinates in a standard POINT format, which accurately represents Tunis's location on a map. The query is simple, direct, and returns the expected result. No further refinement is necessary.