PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX xsd: <http://www.w3.org/2001/XMLSchema#>
SELECT ?person ?startDate ?endDate WHERE {
  ?person wdt:P2388 wd:Q79854 .
  ?person wdt:P571 ?startDate .
  ?person wdt:P570 ?endDate .
  FILTER ( ?startDate < "1964-01-01" ^^ xsd:date )
}

[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] How many General Secretaries of the CPSU were there before Leonid Brezhnev?

[Tool]
Top 10 entity alternatives:
1. Leonid Brezhnev, also known as Brezhnev, Leonid Ilyich Brezhnev (wd:Q765165): General Secretary of the Communist Party of the Soviet Union (1906–1982), military personnel, politician, engineer, surveyor
2. Admiral Kuznetsov, also known as Admiral Flota Sovetskovo Soyuza Kuznetsov, aircraft carrier Admiral Kuznetsov, Leonid Brezhnev, Riga, Tbilisi (wd:Q274924): 1985 Kuznetsov-class aircraft carrier
3. Starry Metropolis, also known as Neptune, Olivia, IMO 7359498, Kareliya, Leonid Brezhnev (wd:Q22968553): ship built in 1976
4. Leonid Brezhnev (wd:Q47510509): painting by Boris Chaliapin
5. Leonid Brezhnev, also known as Whiskey on the Rocks Leonid Brezhnev (wd:Q131583282): Leonid Brezhnev as depicted in television series Whiskey on the Rocks, politician
6. Leonid Brezhnev (wd:Q58345911): Scientific article (April 2014)
7. Leonid Brezhnev (wd:Q47511657): painting by Harvey Simpson
8. Leonid Brezhnev (wd:Q47510378): painting by Burton Philip Silverman
9. Leonid Brezhnev (wd:Q47509621): painting by Boris Artzybasheff
10. Yuri Brezhnev, also known as Yuri Leonidovich Brezhnev (wd:Q8061482): Soviet politician (1933-2013), politician

[Tool]
Top 10 entity alternatives:
1. Communist Party of the Soviet Union, also known as Bolshevik Party, CPSU, RCP(b), Russian Communist Party (Bolsheviks), All-Union Communist Party (Bolsheviks) (wd:Q79854): Marxist–Leninist founding and ruling party of the Soviet Union
2. Communist Party of the Soviet Union (wd:Q4229911): Political party founded in 2001
3. Communist Party of the Soviet Union (wd:Q3701765): Political party founded in 1992
4. Congress of the Communist Party of the Soviet Union (wd:Q2415599): supreme decision-making body of the Communist Party of the Soviet Union
5. The History of the Communist Party of the Soviet Union, also known as A Short History of the Communist Party of the Soviet Union (wd:Q2657367): history book commissioned by Joseph Stalin
6. ideology of the Communist Party of the Soviet Union (wd:Q13574353): soviet Union Communist Russian party government
7. Program of the Communist Party of the Soviet Union (wd:Q7248428)
8. Charter of the Communist Party of the Soviet Union (wd:Q4478159)
9. Organisation of the Communist Party of the Soviet Union (wd:Q11315556)
10. Purges of the Communist Party of the Soviet Union (wd:Q6591430): series of political events

[Tool]
Top 10 property alternatives:
1. position held by head of the organization, also known as position held by head of the organisation, secretary's position, president's position, position held by head of the organization, office held by head of the organisation (wd:P2388 as wdt/p): position of the head of this item
2. chairperson, also known as dean, headed by, leader, president, chairwoman (wd:P488 as wdt/p): presiding member of an organization, group or body, director / manager, significant person
3. official name, also known as long title, name, official title, registered name, full title (wd:P1448 as wdt/p): official name of the subject in its official language(s), name
4. house publication, also known as has mouthpiece, publishes, publication, organization publication, organisation publication (wd:P2813 as wdt/p): media that speaks for an organization or a movement, and that is usually edited by its members
5. headquarters location, also known as headquarters locality, seat, headquarters town, HQ, HQ location (wd:P159 as wdt/p): city or town where an organization's headquarters is or has been situated. Use P276 qualifier for specific building, significant place
6. logo image, also known as masthead, wordmark, trademark, trade mark, sign (wd:P154 as wdt/p): graphic mark or emblem commonly used by commercial enterprises, organizations and products, icon
7. authority, also known as executive authority, governed by, governing authority, governing body, has authority (wd:P797 as wdt/p): entity having executive power on given entity
8. has goal, also known as intention, mission, objective, objective of project or action, project of (wd:P3712 as wdt/p): desired result or outcome
9. founded by, also known as starter, co-founded by, started by, institutor, instituted by (wd:P112 as wdt/p): founder or co-founder of this organization, religion, place or entity, creator
10. significant event, also known as significant occurrence, significant incident, significant achievment, sign. event, outcome (wd:P793 as wdt/p): significant or notable events associated with the subject

No other items found

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?deathDate WHERE {
  wd:Q6711 wdt:P570 ?deathDate
}

Allen Ginsberg died on April 5, 1997.

[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] When did Allen Ginsberg die?

[Tool]
Top 10 entity alternatives:
1. Allen Ginsberg, also known as Irwin Allen Ginsberg (wd:Q6711): American poet and writer (1926–1997), autobiographer, photographer, screenwriter, playwright, musician, diarist, teacher, writer, poet
2. Allen Ginsberg (wd:Q102249265): Ph.D. Rutgers University, New Brunswick 1986
3. Allen Ginsberg Library (wd:Q117833470): this entity is a library in the state of colorado. it was identified and verified by the chr task force
4. Untitled (Allen Ginsberg) (wd:Q76558858): print in the National Gallery of Art (NGA 155538)
5. Allen Ginsberg no number (wd:Q64163104): photograph in the National Gallery of Art (NGA 88333)
6. Allen Ginsberg no number (wd:Q64163625): photograph in the National Gallery of Art (NGA 88331)
7. Allen Ginsberg no number (wd:Q64163102): photograph in the National Gallery of Art (NGA 88336)
8. Allen Ginsberg no number (wd:Q64163079): photograph in the National Gallery of Art (NGA 88334)
9. Allen Ginsberg no number (wd:Q64162725): photograph in the National Gallery of Art (NGA 88330)
10. Allen Ginsberg no number (wd:Q64162264): photograph in the National Gallery of Art (NGA 88332)

[Tool] Got no rows and 1 columns

[Tool]
Got 990 rows and 3 columns, showing the first 10 rows below:
| subject                   | property                         | object                                                                                |
| ------------------------- | -------------------------------- | ---------------------------------------------------------------------------------------------- |
| Allen Ginsberg (wd:Q6711) | instance of (wdt:P31)            | human (wd:Q5)                                                                                |
| Allen Ginsberg (wd:Q6711) | occupation (wdt:P106)            | writer (wd:Q36180)                                                                             |
| Allen Ginsberg (wd:Q6711) | sex or gender (wdt:P21)          | male (wd:Q6581097)                                                                             |
| Allen Ginsberg (wd:Q6711) | given name (wdt:P735)            | Irwin (wd:Q16277131)                                                                           |
| Allen Ginsberg (wd:Q6711) | date of birth (wdt:P569)         | 1926-06-03T00:00:00Z (xsd:dateTime)                                                            |
| Allen Ginsberg (wd:Q6711) | Commons category (wdt:P373)      | Allen Ginsberg                                                                                |
| Allen Ginsberg (wd:Q6711) | image (wdt:P18)                  | <http://commons.wikimedia.org/wiki/Special:FilePath/Allen%20Ginsberg%201979%20-%20cropped.jpg> |
| Allen Ginsberg (wd:Q6711) | country of citizenship (wdt:P27) | United States (wd:Q30)                                                                         |
| Allen Ginsberg (wd:Q6711) | family name (wdt:P734)           | Ginsberg (wd:Q21484848)                                                                        |
| Allen Ginsberg (wd:Q6711) | place of birth (wdt:P19)         | Newark (wd:Q25395)                                                                             |
| ...                       | ...                              | ...                                                                                |

[Tool]
Top 10 property alternatives:
1. date of death, also known as DOD, deathdate, died, died on, year of death (wd:P570 as psn/p/pr/wdt/pq/prn/pqn/ps/wdtn/psv/prv/pqv): dissolved, abolished or demolished date, date on which the subject died, end time
2. place of death, also known as POD, location of death, killed in, deathplace, died in (wd:P20 as psn/p/pr/wdt/pq/prn/pqn/ps/wdtn/psv/prv/pqv): most specific known (e.g. city instead of country, or hospital i... city) death location of a person, animal or fictional character, location
3. number of deaths, also known as dead, qty fatalities, qty deaths, number of fatalities, fatalities (wd:P1120 as psn/p/pr/wdt/pq/prn/pqn/ps/wdtn/psv/prv/pqv): total (cumulative) number of people who died since start as a direct result of an event or cause
4. manner of death, also known as type of death, nature of death, death manner, death type, circumstance of death (wd:P1196 as psn/p/pr/wdt/pq/prn/pqn/ps/wdtn/psv/prv/pqv): general circumstances of a person's death; e.g. natural causes, ...ysiological mechanism, e.g. heart attack, trauma, pneumonia etc.
5. cause of death, also known as death cause, murder method, method of murder, die of, die from (wd:P509 as psn/p/pr/wdt/pq/prn/pqn/ps/wdtn/psv/prv/pqv): underlying or immediate cause of death.  Underlying cause (e.g. ...adest category, e.g. natural causes, accident, homicide, suicide
6. killed by, also known as slaughtered by, slain by, shot dead by, murderer, murdered by (wd:P157 as psn/p/pr/wdt/pq/prn/pqn/ps/wdtn/psv/prv/pqv): person or organization who killed the subject, significant person
7. discontinued date, also known as EOL date, product discontinued, EOL, end-of-life date, end-of-life (wd:P2669 as psn/p/pr/wdt/pq/prn/pqn/ps/wdtn/psv/prv/pqv): date that the availability of a product or service was discontin...d "service retirement" (P730) for pieces or classes of equipment, end time
8. death rate, also known as mortality rate (wd:P10091 as psn/p/pr/wdt/pq/prn/pqn/ps/wdtn/psv/prv/pqv): the total number of persons dead per 1,000 population per year
9. number of victims of killer, also known as number of persons killed, number of killed persons, number of homicide victims, kills, kill count (wd:P1345 as psn/p/pr/wdt/pq/prn/pqn/ps/wdtn/psv/prv/pqv): people killed by the subject, both legal and illegal
10. posthumous name, also known as Honor Death (wd:P1786 as psn/p/pr/wdt/pq/prn/pqn/ps/wdtn/psv/prv/pqv): name given to a person after death (East Asia)

[Tool]
Got 1 row and 1 column:
| deathDate                           |
| ----------------------------------- |
| 1997-04-05T00:00:00Z (xsd:dateTime) |

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ( COUNT( ?award ) AS ?total ) WHERE {
  ?movie wdt:P101 wd:Q55400 .
  ?movie wdt:P168 ?award .
  ?award wdt:P31 wd:Q12136 .
}

Got 1 row and 1 column:
| total       |
| ----------- |
| 0 (xsd:int) |

[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] How many Oscars did all the movies directed by Hayao Miyazaki combined win?

[Tool]
Top 10 entity alternatives:
1. Hayao Miyazaki, also known as Miyazaki Hayao, Tsutomu Teruki (wd:Q55400): Japanese animator, film director, and mangaka (born 1941), mechanical designer, character designer, animation director, environmentalist, film producer, film director, comics artist, screenwriter, film editor, illustrator, animator, director, lyricist, mangaka
2. Hayao Miyazaki (wd:Q11454632): Japanese baseball player, baseball player
3. Hayao Miyazaki bibliography (wd:Q130265400)
4. Never-Ending Man: Hayao Miyazaki (wd:Q42859983): 2016 film
5. Hayao Miyazaki's Daydream Data Notes, also known as Miyazaki Hayao no Zassō Nōto (wd:Q888819): collection of manga and illustrated writings by Hayao Miyazaki
6. Hayao Miyazaki and the Heron (wd:Q130287351): 2024 documentary film
7. Miyazaki Prefecture, also known as Miyazaki (wd:Q130300): prefecture of Japan
8. Miyazaki (wd:Q204308): city in Miyazaki prefecture, Japan
9. 6905 Miyazaki, also known as Miyazaki (wd:Q717728): asteroid
10. Hayao (wd:Q60786238): Japanese male given name (はやお)

[Tool]
Got 1 row and 1 column:
| total       |
| ----------- |
| 0 (xsd:int) |

[Tool]
Got 1 row and 1 column:
| total       |
| ----------- |
| 0 (xsd:int) |


Failed to generate SPARQL query

[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] People of what age belong to the Silent Generation ?

[Tool]
Top 10 entity alternatives:
1. Silent Generation, also known as Lucky Few Generation (wd:Q3044693): cohort succeeding the Greatest Generation, born from 1928 to 1945
2. The Silent Generation (wd:Q7764217): album by The Dimes
3. The Silent Generation (wd:Q112669391): 2020 film
4. Silent zone generation (wd:Q124647370): US patent 11495205
5. Winter’s Children - The Silent Generation (wd:Q85671231): 2005 documentary film by Jens Schanze
6. China Witness, also known as China Witness: Voices from a Silent Generation. (wd:Q113681807): History of China in the 20th century
7. Comparison of Silent Navigator Waveform Generation Methods (wd:Q92381831): scientific article published on 30 May 2019
8. AI-assisted sound effect generation for silent video (wd:Q122763863): US patent 11381888
9. From the silent generation to the involved generation (wd:Q40372593): scientific article published on April 1, 1978
10. Retirement income decisions: the silent generation speaks. (wd:Q40344803): scientific article published on January 2005

[Assistant]
The Silent Generation refers to people born between 1928 and 1945. This cohort succeeded the Greatest Generation and is characterized by its formative years during the Great Depression and World War II.

**Answer:**
People born between 1928 and 1945 belong to the Silent Generation.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?founder WHERE {
  wd:Q479361 wdt:P112 ?founder
}

Got 3 rows and 1 column:
| founder                      |
| ---------------------------- |
| Fritz Mackensen (wd:Q448400) |
| Hans am Ende (wd:Q561091)    |
| Otto Modersohn (wd:Q71425)   |

The Worpswede artist colony was founded by Otto Modersohn.

[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 founded the Worpswede artist colony ?

[Tool]
Top 10 entity alternatives:
1. Worpswede artist colony, also known as Worpswede circle (wd:Q479361): Artist's colony founded in Worpswede in 1889
2. art colony, also known as artist colony, artists' colony (wd:Q1558054): place where artists live and interact with each other
3. Worpswede colony (wd:Q103974815): encyclopedia article
4. Nagybánya art colony, also known as Nagybanya art colony, Nagybánya artists' colony, Nagybanya School, Nagybánya School (wd:Q591229)
5. Önningeby artists colony, also known as Önningebykolonin (wd:Q2687905): Finnish artists colony
6. Ekensund Artists' Colony (wd:Q1669854)
7. Ein Hod artist colony, also known as Artists Village of Ein Hod, Ein Hod artists village (wd:Q124390656)
8. Nishimui Art Village, also known as Nishimui Art Colony, Nishimui Artists' Colony (wd:Q38277516)
9. New Rochelle artist colony (wd:Q19877130)
10. Kirkcudbright Artists' Colony (wd:Q20713695): artists' community

[Tool]
Got 109 rows and 3 columns, showing the first 10 rows below:
| subject                              | property                                                    | object                                                                                |
| ------------------------------------ | ----------------------------------------------------------- | ----------------------------------------------------------------------------------------- |
| Worpswede artist colony (wd:Q479361) | instance of (wdt:P31)                                       | art colony (wd:Q1558054)                                                                  |
| Worpswede artist colony (wd:Q479361) | country (wdt:P17)                                           | Germany (wd:Q183)                                                                         |
| Worpswede artist colony (wd:Q479361) | located in the administrative territorial entity (wdt:P131) | Worpswede (wd:Q269174)                                                                    |
| Worpswede artist colony (wd:Q479361) | coordinate location (wdt:P625)                              | POINT(8.932220 53.215600) (geo:wktLiteral)                                                |
| Worpswede artist colony (wd:Q479361) | Commons category (wdt:P373)                                 | Worpswede in art                                                                          |
| Worpswede artist colony (wd:Q479361) | image (wdt:P18)                                             | <http://commons.wikimedia.org/wiki/Special:FilePath/Heinrich%20Vogeler%20Sommerabend.jpg> |
| Worpswede artist colony (wd:Q479361) | inception (wdt:P571)                                        | 1989-01-01T00:00:00Z (xsd:dateTime)                                                       |
| Worpswede artist colony (wd:Q479361) | has part(s) (wdt:P527)                                      | Heinrich Vogeler (wd:Q213734)                                                             |
| Worpswede artist colony (wd:Q479361) | different from (wdt:P1889)                                  | Künstlerhäuser Worpswede (wd:Q1797150)                                                    |
| Worpswede artist colony (wd:Q479361) | founded by (wdt:P112)                                       | Otto Modersohn (wd:Q71425)                                                                |
| ...                                  | ...                                                         | ...                                                                                |

[Tool] Stopped generation process


SELECT ?university (COUNT(DISTINCT ?founder) AS ?count)
WHERE {
  wd:Q860580 wdt:P112 ?founder.
  ?founder wdt:P135 ?university.
  FILTER (wdt:P31 ?founder = wd:Q5)
}
GROUP BY ?university
HAVING (COUNT(DISTINCT ?founder) >= 2)

No, at least two of the founders of Tencent were not educated at the same university.

[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] Were at least two of the founders of tencent educated at the same university?

[Tool]
Top 10 entity alternatives:
1. Tencent, also known as Téngxùn Kònggǔ Yǒuxiàn Gōngsī, Teng xun (firma), Tencent Group, Téngxùn, Tengxun (wd:Q860580): Chinese multinational investment holding conglomerate
2. The Founders, also known as Founders (wd:Q24684532): 2016 film by Charlene Fisk, Carrie Schrader
3. Founders (wd:Q78219918): painting
4. FOUNDERS (wd:Q127051583): hymn tune
5. founders (wd:L34595-F2)
6. founders (wd:L34594-F2)
7. founded by, also known as starter, started by, institutor, co-founder, instituted by (wd:P112): founder or co-founder of this organization, religion, place or entity
8. Tencent QQ, also known as QQ, Qq, QICQ, OPEN-ICQ, OpenICQ (wd:Q857640): instant messaging software service
9. Tencent Video, also known as v.qq.com, TencentVideo, WeTV (wd:Q28136991): video streaming service from China
10. Tencent Pictures (wd:Q22080095): Chinese film production company

[Tool]
Top 10 property alternatives:
1. founded by, also known as starter, co-founded by, started by, institutor, instituted by (wd:P112 as psn/p/pr/wdt/pq/prn/pqn/ps/wdtn/psv/prv/pqv): founder or co-founder of this organization, religion, place or entity, creator
2. notable work, also known as artwork, wrote, writer of, works, work (wd:P800 as psn/p/pr/wdt/pq/prn/pqn/ps/wdtn/psv/prv/pqv): notable scientific, artistic or literary work, or other work of significance among subject's works
3. inception, also known as initial release date, founded in, founded on, founded on date, founding date (wd:P571 as psn/p/pr/wdt/pq/prn/pqn/ps/wdtn/psv/prv/pqv): time when an entity begins to exist; for date of official opening use P1619, start time
4. collection creator, also known as creator, archive creator, collector, archives of, archive of (wd:P6241 as psn/p/pr/wdt/pq/prn/pqn/ps/wdtn/psv/prv/pqv): entity (person, organization, etc.) that caused a record or collection to be produced or gathered
5. creator, also known as created by, visual artist, sculptor, sculpted by, realized by (wd:P170 as psn/p/pr/wdt/pq/prn/pqn/ps/wdtn/psv/prv/pqv): maker of this creative work or other object (where no more specific property exists)
6. author, also known as writer, written by, poet, playwright, maker (wd:P50 as psn/p/pr/wdt/pq/prn/pqn/ps/wdtn/psv/prv/pqv): main creator(s) of a written work (use on works, not humans); us...hor name string) when Wikidata item is unknown or does not exist, creator
7. location of formation, also known as place of incorporation, originates from, place of establishment, place of formation, place of foundation (wd:P740 as psn/p/pr/wdt/pq/prn/pqn/ps/wdtn/psv/prv/pqv): location where a group or organization was formed, location of creation
8. discoverer or inventor, also known as inventor or discoverer, inventor, invented by, invented, introduced by (wd:P61 as psn/p/pr/wdt/pq/prn/pqn/ps/wdtn/psv/prv/pqv): subject who discovered, first described, invented, or developed this discovery or invention or scientific hypothesis or theory
9. author name string, also known as short author name, writer named as, writer name, writer indicated as, songwriting credits string (wd:P2093 as psn/p/pr/wdt/pq/prn/pqn/ps/wdtn/psv/prv/pqv): stores unspecified author or editor name for publications; use i...or editor (P98) does not exist or is not known. Do not use both.
10. place of birth, also known as POB, location of birth, location born, born in, birthplace (wd:P19 as psn/p/pr/wdt/pq/prn/pqn/ps/wdtn/psv/prv/pqv): most specific known birth location of a person, animal or fictional character, location

[Tool]
Failed to call function execute:
failed to parse input: parse error at position 147 for token VAR1 with content '?founder' (the input most likely does not follow the grammar)

[Tool]
Failed to call function execute:
failed to parse input: parse error at position 147 for token VAR1 with content '?founder' (the input most likely does not follow the grammar)

[Tool] Got no rows and 2 columns

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ( COUNT( ?airport ) AS ?count ) WHERE {
  ?airport wdt:P131 wd:Q1055 .
  ?airport wdt:P31 wd:Q1291 .
}

Got 1 row and 1 column:
| count       |
| ----------- |
| 0 (xsd:int) |

[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] How many international airports are located within the city of Hamburg ?

[Tool]
Top 10 entity alternatives:
1. Hamburg, also known as Free and Hanseatic City of Hamburg, Hamburg, Germany, Hamburg, Freie und Hansestadt (wd:Q1055): city and state in the North of Germany
2. Hamburger SV, also known as Hamburg SV, HSV, H.S.V., Hamburg Sport Club, HamburgerSV (wd:Q51974): German sports club based in Hamburg, with its largest branch being its football department
3. Hamburg, also known as Hamburg, IA, Hamburg, Iowa (wd:Q998718): city in Fremont County, Iowa, United States
4. Hamburg, also known as Hamburg, AR, Hamburg, Arkansas (wd:Q79657): city in Ashley County, Arkansas, United States
5. Hamburg, also known as Hamburg, Minnesota, Hamburg, MN (wd:Q1005682): city in Carver County, Minnesota, United States
6. Hamburg, also known as Hamburg, New Jersey, Hamburg, NJ (wd:Q1082931): borough in Sussex County, New Jersey, United States
7. Hamburg, also known as Hamburg, New York, Hamburg, NY (wd:Q742785): town in Erie County, New York, United States
8. Hamburg, also known as Hamburg, IL (wd:Q2672139): village in Calhoun County, Illinois, United States
9. Hamburg, also known as Hamburg, PA, Hamburg, Pennsylvania (wd:Q1181264): borough in Berks County, Pennsylvania, United States
10. Hamburg, also known as Hamburgh (wd:Q939795): breed of chicken developed in Germany and Holland prior to 1700

[Tool]
Got 1 row and 3 columns:
| subject            | property                                                    | object            |
| ------------------ | ----------------------------------------------------------- | ----------------- |
| Hamburg (wd:Q1055) | located in the administrative territorial entity (wdt:P131) | Germany (wd:Q183) |

[Tool]
Got 1 row and 1 column:
| count       |
| ----------- |
| 0 (xsd:int) |

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?date WHERE {
  wd:Q15787 wdt:P575 ?date
}

HIV was first identified in 1983.

[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] When was HIV first identified?

[Tool]
Top 10 entity alternatives:
1. HIV, also known as AIDS virus, human immunodeficiency virus (wd:Q15787): human retrovirus, cause of AIDS
2. Hiv (wd:Q5959052): village in Iran
3. .hiv (wd:Q20573587): top level domain
4. human immunodeficiency virus infectious disease, also known as HIV+, HIV infection, HIV infections, HIV-positive (wd:Q18556697): disease affecting the human immune system
5. HIV/AIDS in Ethiopia, also known as HIV (wd:Q65409016): Ethiopia faces an epidemic among sub-populations and geographic areas
6. HyperChem Input File, also known as HIV, .hin, HyperChem molecule file format, HIV molecule file format (wd:Q28530466): file format
7. HIV (wd:Q87558374): scientific article published on 01 August 2014
8. HIV (wd:Q93531156)
9. HIV. (wd:Q43247940): scientific article published in February 1998
10. HIV. (wd:Q45982420): scientific article published in February 2001

[Tool] Got no rows and 1 columns

[Tool]
Top 10 property alternatives:
1. time of discovery or invention, also known as invented in, time of invention, time of discovery, invention time, invented on (wd:P575 as wdt/p): date or point in time when the item was discovered or invented
2. described by source, also known as mentioned in, source of item, reviewed in, mentioned in news article, talked about in (wd:P1343 as wdt/p): work where this item is described, attested in
3. has part(s), also known as has component, incorporates, has ingredient, has ingredients, has member (wd:P527 as wdt/p): part of this subject; inverse property of "part of" (P361). See also "has parts of the class" (P2670).
4. has effect, also known as has symptom, implies, leads to, led to, outcome (wd:P1542 as wdt/p): effect of this item, followed by
5. ScienceDirect topic ID, also known as Science Direct topic ID, Science Direct topic identifier, ScienceDirect topic identifier (wd:P10376 as wdt/p): identifier for a topic on the research publication website ScienceDirect
6. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt/p): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
7. external data available at URL, also known as data, external data URL, URL with external data (wd:P1325 as wdt/p): URL where external data on this item can be found
8. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as wdt/p): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
9. pronunciation audio, also known as listen, audio pronunciation (wd:P443 as wdt/p): audio file with pronunciation, audio
10. prevalence (wd:P1193 as wdt/p): portion in percent of a population with a given disease or disorder

No other items found

[Tool]
Got 1 row and 1 column:
| date                                |
| ----------------------------------- |
| 1983-01-01T00:00:00Z (xsd:dateTime) |

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?developer WHERE {
  wd:Q533822 wdt:P19 ?developer
}

Princeton University

[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 developed WordNet?

[Tool]
Top 10 entity alternatives:
1. WordNet, also known as Princeton WordNet (wd:Q533822): Princeton University's computational lexicon of English, a seman...nodes connected by hypernymy, hyponymy, holonymy, meronymy, etc.
2. word net, also known as wordnet (wd:Q2594143): network of words connected by semantic relationships (synonyms, antonyms, hypernyms, hyponyms, meronyms, holonyms)
3. WordNet (wd:Q125949755)
4. WordNet (wd:Q98000414): chapter in book from 2010
5. WordNet: An Electronic Lexical Database, also known as WordNet, WordNet.  An  Electronic Lexical Database (wd:Q35839029): book edition published in 1998 with Fellbaum as editor
6. Arabic WordNet, also known as AWN (wd:Q28136431)
7. Estonian Wordnet (wd:Q31277898)
8. Malayalam WordNet (wd:Q25112033): WordNet for Malayalam language by CUSAT
9. Chinese WordNet, also known as CWN (wd:Q65924663): Huang et al. wordnet in Chinese
10. GF WordNet (wd:Q112258758): a lexical resource which combines WordNet resources from many languages and makes them compatible within GF

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?mountain WHERE {
  ?mountain wdt:P31 wd:Q13592 .
  ?mountain wdt:P131 wd:Q20 .
}

The highest point of Norway is Galdhøpiggen, a mountain located in Lom, Oppland, Norway.

[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 is the highest point of Norway?

[Tool]
Top 10 entity alternatives:
1. highest point of Paris (wd:Q1440664)
2. highest point of Loir-et-Cher (wd:Q26885408): highest point of the Loir-et-Cher department in France
3. highest point, also known as elevation of highest point, extreme point highest, highest peak, pinnacle, summit (wd:P610): point with highest elevation in a region or path
4. Evolution of highest point of France (wd:Q3592878)
5. highest point of the Netherlands (wd:Q93077339): the continental highest point of the Netherlands (Europe)
6. highest point of Engure parish (wd:Q112612917)
7. highest point of Lapmežciems parish (wd:Q112648516)
8. highest point of the head (wd:L1017737-S1)
9. highest point of Háldi mountain (wd:L636172-S1)
10. highest point of the Homiel Region, also known as highest point of the Gomel Region (wd:Q28110432): hill in Belarus

[Tool]
Top 10 entity alternatives:
1. Norway, also known as Kingdom of Norway (wd:Q20): country in Northern Europe
2. Norway, also known as Norway, Iowa, Norway, IA (wd:Q1913264): city in Iowa, United States
3. Norway, also known as Norway, MI, Norway, Michigan (wd:Q2480177): city in Dickinson County, Michigan, United States
4. Norway, also known as Norway, SC, Norway, South Carolina (wd:Q3243583): town in South Carolina
5. Kingdom of Norway, also known as Norway, Norwegian Empire (wd:Q2196956): former Kingdom from 872 to 1397
6. Norway, also known as Norway, Maine, Norway, ME (wd:Q2734330): town in Maine, USA
7. Norway, also known as Norway, IN, Norway, Indiana (wd:Q2118814): census-designated place in Indiana
8. Kingdom of Norway, also known as Norway, Norwegian Kingdom (wd:Q2597352): short-lived monarchy in Northern Europe (1814)
9. Norway, also known as Norway, New York, Norway, NY (wd:Q944765): town in New York, USA
10. Norway, also known as Norway, WI (wd:Q3046928): town in Wisconsin, USA

[Tool] Got no rows and 1 columns

[Tool] Got no rows and 1 columns

[Tool] Got no rows and 1 columns

[Tool]
Top 10 entity alternatives:
1. Galdhøpiggen (wd:Q203942): mountain in Lom, Oppland, Norway
2. Galdhøpiggen (wd:Q31730783): hill summit in Porsgrunn, Telemark, Norway
3. Vesle Galdhøpiggen (wd:Q3044956): mountain in Norway
4. Berge Galdhopiggen, also known as IMO 9753284 (wd:Q83651173): bulk carrier built in 2017
5. Galdhøpiggen Summer Ski Centre (wd:Q20553374): ski resort in Galdhøpiggen, Norway
6. Tree line shifts, changing veget...orway) over the past ~4400 years (wd:Q114136288): scientific article published in 2021

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?date WHERE {
  wd:Q41304 wdt:P571 ?date
}

The Weimar Republic started on 9 November 1918.

[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] When did the Weimar Republic start?

[Tool]
Top 10 entity alternatives:
1. Weimar Republic, also known as German Republic, Weimar Germany, Republic of Germany, Germany, German Reich (wd:Q41304): Germany in the years 1918/1919–1933
2. flag of the Weimar Republic, also known as the Weimar Republic flag, Weimar Republic flag (wd:Q4485721): flag
3. Landtag (Weimar Republic) (wd:Q1453030): federated state parliament in German Weimar Republic (1919—1934)
4. history of the Weimar Republic, also known as the Weimar Republic history, Weimar Republic history (wd:Q104731094): aspect of German history
5. historian of the Weimar Republic, also known as historian of Weimar Republic, Weimar Republic historian (wd:Q104730830): historian specializing in history of the Weimar Republic
6. hyperinflation in the Weimar Republic (wd:Q695052): occurrence of hyperinflation in early 20th century Germany
7. states of the Weimar Republic (wd:Q3712151): federated states of the Weimar Republic
8. States of the Weimar Republic (wd:Q3712151): federated states of the Weimar Republic
9. Reichsadler of the Weimar Republic, also known as coat of arms of the Weimar Republic (wd:Q25401250)
10. Landtag of Bavaria (Weimar Republic) (wd:Q812353): Parliament of the Free State of Bavaria during the period of the Weimar Republic

[Tool] Got no rows and 1 columns

[Tool]
Got 855 rows and 3 columns, showing the first 10 rows below:
| subject                     | property                                       | object                                                              |
| --------------------------- | ---------------------------------------------- | ------------------------------------------------------------------- |
| Weimar Republic (wd:Q41304) | instance of (wdt:P31)                          | historical period (wd:Q11514315)                                    |
| Weimar Republic (wd:Q41304) | country (wdt:P17)                              | German Reich (wd:Q1206012)                                          |
| Weimar Republic (wd:Q41304) | coordinate location (wdt:P625)                 | POINT(13.375000 52.520000) (geo:wktLiteral)                         |
| Weimar Republic (wd:Q41304) | Commons category (wdt:P373)                    | Weimar Republic                                                     |
| Weimar Republic (wd:Q41304) | population (wdt:P1082)                         | 62411000 (xsd:decimal)                                              |
| Weimar Republic (wd:Q41304) | inception (wdt:P571)                           | 1918-11-09T00:00:00Z (xsd:dateTime)                                 |
| Weimar Republic (wd:Q41304) | described at URL (wdt:P973)                    | <https://stadtlexikon.karlsruhe.de/index.php/De:Lexikon:ereig-0212> |
| Weimar Republic (wd:Q41304) | described by source (wdt:P1343)                | Armenian Soviet Encyclopedia (wd:Q2657718)                          |
| Weimar Republic (wd:Q41304) | official name (wdt:P1448)                      | Deutsches Reich (de)                                                |
| Weimar Republic (wd:Q41304) | on focus list of Wikimedia project (wdt:P5008) | wd:Q6173448                                                         |
| ...                         | ...                                            | ...                                                                 |

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?employeeCount WHERE {
  wd:Q1027807 wdt:P1128 ?employeeCount
}

Got 1 row and 1 column:
| employeeCount        |
| -------------------- |
| 385000 (xsd:decimal) |

The Port of Rotterdam employs 385,000 people.

[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] How many perople do the Port of Rotterdam employ?

[Tool]
Top 10 entity alternatives:
1. Port of Rotterdam (wd:Q1027807): largest port in Europe, located in the city of Rotterdam, Netherlands
2. Port of Rotterdam Authority, also known as Directie bedrijfsvoering Havenbedrijf   etc. (wd:Q2187039): manager of Rotterdam's port and industrial area in the Netherlands
3. The Port of Rotterdam (wd:Q59543911): painting by Eugène Boudin
4. Portrait of Erasmus of Rotterdam (wd:Q107122548)
5. Portrait of Erasmus of Rotterdam (wd:Q110572054): painting by Hans Holbein the Younger and workshop (David Owsley Museum)
6. Portrait of Erasmus of Rotterdam (wd:Q116966868): painting by Workshop Lucas Cranach the Elder (Landesmuseum für Kunst und Kulturgeschichte Oldenburg)
7. Portrait of Erasmus of Rotterdam (wd:Q116968152): painting by Copy after Lucas Cranach the Elder or Workshop Lucas Cranach the Elder (Sammlung Würth)
8. Portrait of Erasmus of Rotterdam (wd:Q20809158): painting by Hans Holbein the Younger
9. Portrait of Erasmus of Rotterdam (wd:Q110571788): painting by Hans Holbein the Younger and workshop
10. Portrait of Erasmus of Rotterdam writing (wd:Q105684225): painting by Hans Holbein

[Tool]
Got 269 rows and 3 columns, showing the first 10 rows below:
| subject                         | property                                                    | object                                                                                |
| ------------------------------- | ----------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------- |
| Port of Rotterdam (wd:Q1027807) | instance of (wdt:P31)                                       | organization (wd:Q43229)                                                                                |
| Port of Rotterdam (wd:Q1027807) | country (wdt:P17)                                           | Netherlands (wd:Q55)                                                                                |
| Port of Rotterdam (wd:Q1027807) | located in the administrative territorial entity (wdt:P131) | Rotterdam (wd:Q2680952)                                                                                |
| Port of Rotterdam (wd:Q1027807) | coordinate location (wdt:P625)                              | POINT(4.286700 51.885000) (geo:wktLiteral)                                                                            |
| Port of Rotterdam (wd:Q1027807) | Commons category (wdt:P373)                                 | Port of Rotterdam                                                                                |
| Port of Rotterdam (wd:Q1027807) | image (wdt:P18)                                             | <http://commons.wikimedia.org/wiki/Special:FilePath/Port%20of%20Rotterdam%20Landsat%208%20Photo%208%20May%202016.jpg> |
| Port of Rotterdam (wd:Q1027807) | has part(s) (wdt:P527)                                      | Europoort (wd:Q1336552)                                                                                |
| Port of Rotterdam (wd:Q1027807) | described by source (wdt:P1343)                             | Canon of Dutch History (wd:Q907660)                                                                                |
| Port of Rotterdam (wd:Q1027807) | official website (wdt:P856)                                 | <http://www.portofrotterdam.com/>                                                                                |
| Port of Rotterdam (wd:Q1027807) | native label (wdt:P1705)                                    | Haven van Rotterdam (nl)                                                                                |
| ...                             | ...                                                         | ...                                                                                |

[Tool]
Top 10 property alternatives:
1. employees, also known as workers, staff, personnel, number of employees, employee count (wd:P1128 as wdt/p): total number of employees of a company at a given "point in time...not deprecated rank). Add data for recent years, don't overwrite
2. operator, also known as offered by, operated by, provided by, run by, service operator (wd:P137 as wdt/p): person, profession, organization or entity that operates the equipment, facility, or service, used by
3. coordinate location, also known as point on a map, gps coordinates, gps location, latitude, location (wd:P625 as wdt/p): geocoordinates of the subject. For Earth, please note that only WGS84 coordinating system is supported at the moment
4. has part(s), also known as has component, incorporates, has ingredient, has ingredients, has member (wd:P527 as wdt/p): part of this subject; inverse property of "part of" (P361). See also "has parts of the class" (P2670).
5. 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/p): the item is located on the territory of the following administra...if the item falls only partially into the administrative entity., location, part of
6. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt/p): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
7. country, also known as sovereign state, state, land, host country (wd:P17 as wdt/p): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
8. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as wdt/p): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
9. has facility, also known as has amenity, has feature, features, amenity, facility (wd:P912 as wdt/p): the subject item has this type of facility, e.g. toilet, car park, has part(s) of the class
10. official website, also known as site (official), home page, site official, URL, URL (official) (wd:P856 as wdt/p): URL of the official page of an item (current or former). Usage: ...but see the "Hijacked or dead websites" section of the Talk page, URL

No other items found

[Tool]
Got 1 row and 1 column:
| employeeCount        |
| -------------------- |
| 385000 (xsd:decimal) |

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ( COUNT( ?film ) AS ?count ) WHERE {
  ?film wdt:P139 wd:Q135100 .
  ?film wdt:P577 ?date .
  FILTER ( YEAR( ?date ) = 1978 ) FILTER ( ?film != wd:Q267721 )
}

[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] How many other musical films were launched the same year as Grease?

[Tool]
Top 10 entity alternatives:
1. fat, also known as grease, fats and oils, fat or oil, dietary fats, dietary fat (wd:Q127980): esters of three fatty acid chains and the alcohol glycerol, one of the three main macronutrients, also known as triglycerides
2. Grease (wd:Q267721): 1978 film by Randal Kleiser
3. grease, also known as lubricating grease, grease lubricant (wd:Q629823): semi-solid, oily lubricant
4. Grease (wd:Q611626): 1972 musical
5. Grease (wd:Q728791): original song written and composed by Barry Gibb; from the 1978 film "Grease", performed by Frankie Valli
6. Grease (wd:Q3776108): 2010 video game
7. Grease (wd:Q104861673): American media franchise
8. Grease (wd:Q114518793): episode of Cheers (S9 E6)
9. Grease (wd:Q116013684): sardana by Martí de Joan
10. Grease (wd:Q126836847): vocal track by Mina; 1986 studio recording; cover version

[Tool]
Failed to call function execute:
failed to parse input: parse error at position 144 for token MINUS with content 'MINUS' (the input most likely does not follow the grammar)

[Tool]
Got 1 row and 1 column:
| count       |
| ----------- |
| 0 (xsd:int) |

[Tool] Stopped generation process