PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT DISTINCT ?college WHERE {
  wd:Q7336 wdt:P69 ?college .
  ?college wdt:P31 / wdt:P279 * wd:Q38723 .
}

Otto Heinrich Frank went to Heidelberg 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] where did otto frank go to college?

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

[Tool]
Example 1:
Question:
where did president eisenhower go to college?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q9916 wdt:P69 ?x .
  ?x wdt:P31 / wdt:P279 * wd:Q38723 .
}

Using entities:
higher education institution, also known as HEI, Higher Education school, institution of higher education, Superior Institute (wd:Q38723): institution that provides higher education (e.g., universities, ...es, liberal arts colleges, institutes of technology, and others)
Dwight D. Eisenhower, also known as Ike, Eisenhower, Dwight Eisenhower, Dwight David Eisenhower, Ike Eisenhower (wd:Q9916): president of the United States from 1953 to 1961, military personnel, military officer, army officer, statesperson, politician, writer

Using properties:
subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as wdt): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
educated at, also known as graduated from, graduate of, place of education, school attended, schooled at (wd:P69 as wdt): educational institution attended by subject, affiliation

Example 2:
Question:
where did newt gingrich attend college?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q182788 wdt:P69 ?x .
  ?x wdt:P31 / wdt:P279 * wd:Q38723 .
}

Using entities:
Newt Gingrich, also known as Newton Leroy Gingrich, Newton Gingrich, Newton L. Ginrich, Newt L. Gingrich (wd:Q182788): American politician and author (born 1943), politician, historian, novelist, teacher, writer
higher education institution, also known as HEI, Higher Education school, institution of higher education, Superior Institute (wd:Q38723): institution that provides higher education (e.g., universities, ...es, liberal arts colleges, institutes of technology, and others)

Using properties:
subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as wdt): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
educated at, also known as graduated from, graduate of, place of education, school attended, schooled at (wd:P69 as wdt): educational institution attended by subject, affiliation

Example 3:
Question:
what college did james franco go to?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q306403 wdt:P69 ?x .
  ?x wdt:P31 / wdt:P279 * wd:Q38723 .
}

Using entities:
James Franco, also known as James Edward Franco (wd:Q306403): television presenter, television actor, American actor, film producer, film director, screenwriter, film editor, film actor, playwright, teacher, writer, actor, poet
higher education institution, also known as HEI, Higher Education school, institution of higher education, Superior Institute (wd:Q38723): institution that provides higher education (e.g., universities, ...es, liberal arts colleges, institutes of technology, and others)

Using properties:
subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as wdt): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
educated at, also known as graduated from, graduate of, place of education, school attended, schooled at (wd:P69 as wdt): educational institution attended by subject, affiliation

[Assistant] From the examples, the property "educated at" (wdt:P69) is used to find the college or higher education institution a person attended. The entity for higher education institution is wd:Q38723. Now I will search for the entity "Otto Frank" in Wikidata to get his identifier.

[Tool]
Top 10 entity alternatives:
1. Frank Otto (wd:Q1443909): German water polo player, water polo player
2. Otto Frank, also known as Otto Friedrich Frank, Friedrich Wilhelm Ferdinand Otto Frank (wd:Q89925): German physiologist (1865–1944), university teacher, cardiologist, physiologist, physician
3. Frank Otto (wd:Q1443902): German media entrepreneur, film director, geologist, director
4. Frank Otto (wd:Q16104521): American linguist (1936-2017), linguist
5. Frank Otto (wd:Q1443905): German historian of modern age, historian of Modern Age, writer
6. Otto Frank (wd:Q36977791): German FDP politician (1900-1963), politician
7. Otto Frank (wd:Q94791903): military officer, cartographer
8. Frank Otto (wd:Q96110480): researcher
9. Otto Frank (wd:Q94941069): engineer
10. Otto Frank (wd:Q116960730): Austrian architect, architect

[Assistant] There are multiple entities named Otto Frank. The most likely candidate for the Otto Frank related to the famous person (father of Anne Frank) is wd:Q89925 (Otto Frank, German physiologist). However, this might not be the correct Otto Frank as the famous Otto Frank was a businessman and not a physiologist. There is also wd:Q36977791 (Otto Frank, German FDP politician) which might not be the correct one either. I will check the description of wd:Q89925 to confirm if it matches the Otto Frank who is the father of Anne Frank. If not, I will try to find the correct Otto Frank by searching with more context.

[Tool]
Got 218 rows and 3 columns, showing the first 10 rows below:
| subject                | property                         | object                              |
| ---------------------- | -------------------------------- | ----------------------------------- |
| Otto Frank (wd:Q89925) | instance of (wdt:P31)            | human (wd:Q5)                       |
| Otto Frank (wd:Q89925) | occupation (wdt:P106)            | physician (wd:Q39631)               |
| Otto Frank (wd:Q89925) | sex or gender (wdt:P21)          | male (wd:Q6581097)                  |
| Otto Frank (wd:Q89925) | given name (wdt:P735)            | Otto (wd:Q18029644)                 |
| Otto Frank (wd:Q89925) | date of birth (wdt:P569)         | 1865-06-21T00:00:00Z (xsd:dateTime) |
| Otto Frank (wd:Q89925) | Commons category (wdt:P373)      | Otto Frank (physiologist)           |
| Otto Frank (wd:Q89925) | country of citizenship (wdt:P27) | German Reich (wd:Q1206012)          |
| Otto Frank (wd:Q89925) | family name (wdt:P734)           | Frank (wd:Q13560458)                |
| Otto Frank (wd:Q89925) | place of birth (wdt:P19)         | Groß-Umstadt (wd:Q516474)           |
| Otto Frank (wd:Q89925) | date of death (wdt:P570)         | 1944-11-12T00:00:00Z (xsd:dateTime) |
| ...                    | ...                              | ...                                 |

[Assistant] The entity wd:Q89925 corresponds to Otto Frank the physiologist born in 1865 and died in 1944. This is not the Otto Frank who was the father of Anne Frank (the businessman). I will try to search for "Otto Frank Anne Frank" to find the correct entity.

[Tool]
Top 10 entity alternatives:
1. Anne Frank, also known as Anne M. Frank, Anna Frank, Anne Maries Frank, Annelies Marie Frank, Anna M Frank (wd:Q4583): German-born Dutch Jewish diarist and Holocaust victim (1929–1945), diarist, writer
2. Anne Frank, also known as Anne Maries Frank, Anne M. Frank, Annelies Marie Frank, Anna M Frank, Anna Frank (wd:Q4583): German-born Dutch Jewish diarist and Holocaust victim (1929–1945), diarist, writer
3. Frank Otto (wd:Q1443909): German water polo player, water polo player
4. Otto Frank, also known as Otto Friedrich Frank, Friedrich Wilhelm Ferdinand Otto Frank (wd:Q89925): German physiologist (1865–1944), university teacher, cardiologist, physiologist, physician
5. Frank Otto (wd:Q1443902): German media entrepreneur, film director, geologist, director
6. Frank Otto (wd:Q16104521): American linguist (1936-2017), linguist
7. Statue of Anne Frank, also known as Anne Frank (wd:Q27918477): public artwork by Pieter d'Hont in Utrecht, the Netherlands
8. Bust of Anne Frank, also known as Anne Frank (wd:Q41688543): sculpture by Doreen Kern
9. Aenne Pahl, also known as Anne Frank (wd:Q60540011): painter
10. Anne Frank (wd:Q128498127): opera by Shulamit Ran

[Assistant] The search did not return a distinct entity for Otto Frank, the father of Anne Frank. I will try a different approach and search for "Otto Frank businessman" to find the correct entity.

[Tool]
Top 10 entity alternatives:
1. Frank Otto (wd:Q1443909): German water polo player, water polo player
2. Otto Frank, also known as Otto Friedrich Frank, Friedrich Wilhelm Ferdinand Otto Frank (wd:Q89925): German physiologist (1865–1944), university teacher, cardiologist, physiologist, physician
3. Frank Otto (wd:Q1443902): German media entrepreneur, film director, geologist, director
4. Frank Otto (wd:Q16104521): American linguist (1936-2017), linguist
5. Frank Otto (wd:Q1443905): German historian of modern age, historian of Modern Age, writer
6. Otto Frank (wd:Q36977791): German FDP politician (1900-1963), politician
7. Otto Frank (wd:Q94791903): military officer, cartographer
8. Frank Otto (wd:Q96110480): researcher
9. Otto Frank (wd:Q94941069): engineer
10. Otto Frank (wd:Q116960730): Austrian architect, architect

[Assistant] The search still does not return a clear entity for Otto Frank the businessman (father of Anne Frank). I will try to find Otto Frank by searching for Anne Frank's family members to identify the correct Otto Frank entity.

[Tool]
Got 1 row and 3 columns:
| subject               | property         | object                         |
| --------------------- | ---------------- | ------------------------------ |
| Anne Frank (wd:Q4583) | father (wdt:P22) | Otto Heinrich Frank (wd:Q7336) |

[Assistant] The father of Anne Frank is Otto Heinrich Frank with the entity wd:Q7336. I will now query where Otto Heinrich Frank (wd:Q7336) went to college using the "educated at" property (wdt:P69) and filter for higher education institutions (wd:Q38723).

[Tool]
Got 1 row and 1 column:
| college                            |
| ---------------------------------- |
| Heidelberg University (wd:Q151510) |

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT DISTINCT ?education ?educationLabel WHERE {
  wd:Q52651 wdt:P69 ?education .
  OPTIONAL {
    ?education rdfs:label ?educationLabel FILTER ( LANG( ?educationLabel ) = "en" )
  }
}

Got 3 rows and 2 columns:
| education                                | educationLabel                  |
| ---------------------------------------- | ------------------------------- |
| Ohio State University (wd:Q309331)       | Ohio State University (en)      |
| East Technical High School (wd:Q5329490) | East Technical High School (en) |
| North Platte High School (wd:Q7056353)   | North Platte High School (en)   |

Jesse Owens was educated at Ohio State University, East Technical High School, and North Platte High School.

[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 was jesse owens education?

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

[Tool]
Example 1:
Question:
what was eli whitney education?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q280930 wdt:P69 ?x .
}

Using entities:
Eli Whitney, also known as Eli Whitney Jr. (wd:Q280930): American inventor (1765-1825), tax collector, entrepreneur, politician, inventor, engineer

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

Example 2:
Question:
what kind of education did barack obama have?

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

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

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

Example 3:
Question:
what was jack london's education?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q45765 wdt:P69 ?x .
}

Using entities:
Jack London, also known as John Griffith "Jack" London, John Griffith "Jack London" Chaney, John Griffith Chaney London, John Griffith Chaney (wd:Q45765): American author, journalist and social activist (1876–1916), science fiction writer, children's writer, war correspondent, autobiographer, travel writer, screenwriter, prose writer, journalist, essayist, novelist, traveler, diarist, seaman, writer, poet

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

[Assistant] From the similar examples, the property "educated at" (wdt:P69) is used to find the educational institutions attended by a person. Now, I will search for the entity "Jesse Owens" to get his Wikidata identifier. Then I will use the property "educated at" to find his education.

[Tool]
Top 10 entity alternatives:
1. Jesse Owens, also known as James Cleveland "Jesse" Owens, James Cleveland Owens (wd:Q52651): American track and field athlete (1913–1980), athletics competitor, long jumper, sprinter
2. Jesse Owens (wd:Q6186721): 2012 film
3. Jesse Owens Award (wd:Q3540423): awards given out by USA Track and Field
4. Jesse Hickman, also known as Jesse Owens Hickman (wd:Q6186412): American baseball player, baseball player
5. The Jesse Owens Story, also known as Jesse Owens Story, Jessie Owens Story (wd:Q7743138): 1984 television film
6. Jesse Owens Park (wd:Q49507611): park in Pima County, Arizona, United States of America
7. Jesse Owens Park (wd:Q49507612): park in Los Angeles County, California, United States of America
8. Jesse Owens Plaza (wd:Q49507617): park in Franklin County, Ohio, United States of America
9. Jesse Owens Playground (wd:Q49507615): park in Kings County, New York, United States of America
10. Jesse Owens Park, also known as Stony Island Park (wd:Q49566705): park in the United States of America

[Assistant] The entity for Jesse Owens, the American track and field athlete, is wd:Q52651. Now I will query his education using the property "educated at" (wdt:P69).

[Tool]
Got 3 rows and 2 columns:
| education                                | educationLabel                  |
| ---------------------------------------- | ------------------------------- |
| Ohio State University (wd:Q309331)       | Ohio State University (en)      |
| East Technical High School (wd:Q5329490) | East Technical High School (en) |
| North Platte High School (wd:Q7056353)   | North Platte High School (en)   |

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT DISTINCT ?religion ?religionLabel WHERE {
  wd:Q252 wdt:P140 ?religion .
  ?religion rdfs:label ?religionLabel .
  FILTER ( LANG( ?religionLabel ) = "en" )
}

Got 6 rows and 2 columns:
| religion                  | religionLabel      |
| ------------------------- | ------------------ |
| Catholicism (wd:Q1841)    | Catholicism (en)   |
| Protestantism (wd:Q23540) | Protestantism (en) |
| Islam (wd:Q432)           | Islam (en)         |
| Buddhism (wd:Q748)        | Buddhism (en)      |
| Hinduism (wd:Q9089)       | Hinduism (en)      |
| Confucianism (wd:Q9581)   | Confucianism (en)  |

The religions practiced in Indonesia are Catholicism, Protestantism, Islam, Buddhism, Hinduism, and Confucianism.

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

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

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

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

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

[User] what are the religions practiced in indonesia?

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

[Tool]
Example 1:
Question:
what is the language used in indonesia?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q252 wdt:P37 ?x .
}

Using entities:
Indonesia, also known as id, ID, IDN, INA, Republic of Indonesia (wd:Q252): island country in Southeast Asia and Oceania

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

Example 2:
Question:
what language do they speak in indonesia?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q252 wdt:P37 ?x .
}

Using entities:
Indonesia, also known as id, ID, IDN, INA, Republic of Indonesia (wd:Q252): island country in Southeast Asia and Oceania

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

Example 3:
Question:
what are some of the religions in australia?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q408 wdt:P140 ?x .
}

Using entities:
Australia, also known as AU, The Commonwealth of Australia, Stria, Straya, Stralia (wd:Q408): country in Oceania

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

[Assistant] From the examples, we see that the entity for Indonesia is wd:Q252 and the property for religion is wdt:P140. We can use these to construct a query to find the religions practiced in Indonesia. I will now write and execute this query.

[Tool]
Got 6 rows and 2 columns:
| religion                  | religionLabel      |
| ------------------------- | ------------------ |
| Catholicism (wd:Q1841)    | Catholicism (en)   |
| Protestantism (wd:Q23540) | Protestantism (en) |
| Islam (wd:Q432)           | Islam (en)         |
| Buddhism (wd:Q748)        | Buddhism (en)      |
| Hinduism (wd:Q9089)       | Hinduism (en)      |
| Confucianism (wd:Q9581)   | Confucianism (en)  |

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT DISTINCT ?coordinate ?continent WHERE {
  wd:Q783 wdt:P625 ?coordinate .
  wd:Q783 wdt:P30 ?continent .
  OPTIONAL {
    ?continent rdfs:label ?continentLabel FILTER ( LANG( ?continentLabel ) = "en" )
  }
}

Honduras is a sovereign state in Central America. Its geographic coordinates are approximately longitude -86.82 and latitude 14.63. It is located on the continent of North America.

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

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

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

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

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

[User] where honduras in the world?

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

[Tool]
Example 1:
Question:
where are the netherlands on a world map?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q55 wdt:P625 ?x .
}

Using entities:
Netherlands, also known as 🇳🇱, the Netherlands, NL, nl, NED (wd:Q55): country in Northwestern Europe with territories in the Caribbean

Using properties:
coordinate location, also known as point on a map, gps coordinates, gps location, latitude, location (wd:P625 as wdt): geocoordinates of the subject. For Earth, please note that only WGS84 coordinating system is supported at the moment

Example 2:
Question:
where is singapore on a world map?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q334 wdt:P625 ?x .
}

Using entities:
Singapore, also known as SIN, S'pore, Singapore City, SGP, SG (wd:Q334): sovereign island country and city-state in maritime Southeast Asia

Using properties:
coordinate location, also known as point on a map, gps coordinates, gps location, latitude, location (wd:P625 as wdt): geocoordinates of the subject. For Earth, please note that only WGS84 coordinating system is supported at the moment

Example 3:
Question:
what continent is belize located in?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q242 wdt:P30 ?x .
}

Using entities:
Belize, also known as bz (wd:Q242): sovereign state in Central America

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

[Assistant]
From the examples, to answer "where is Honduras in the world?" we can either provide the geographic coordinates (property P625) or the continent (property P30) where Honduras is located.

First, I will search for the entity "Honduras" in Wikidata to get its identifier.

[Tool]
Top 10 entity alternatives:
1. Honduras, also known as hn, HN, HND, HON, Honduran Republic (wd:Q783): sovereign state in Central America
2. Hong Shengde, also known as Honduras (wd:Q9306612): Taiwanese actor, presenter, actor
3. Honduras, also known as Honduras, Barranquitas, Honduras Barrio, Honduras, Puerto Rico (wd:Q2879306): barrio in Barranquitas, Puerto Rico
4. Honduras, also known as Honduras, Cidra, Honduras, Puerto Rico, Honduras Barrio (wd:Q5901523): barrio in Cidra, Puerto Rico
5. Honduras, also known as Honduras, IN, Honduras, Indiana (wd:Q5893062): unincorporated community in Adams County, Indiana, United States
6. Honduras (wd:Q5901519): 1814 schooner
7. Honduras (wd:Q12891576)
8. Honduras (wd:Q12891575)
9. Honduras de la Sierra, also known as Honduras (wd:Q49978176): human settlement of Chiapas, Mexico
10. Honduras (wd:Q41377915): scientific article published on August 1985

[Assistant] The entity for the country Honduras is wd:Q783. Now I will check the geographic coordinates (property P625) and the continent (property P30) for Honduras.

[Tool]
Got 1 row and 2 columns:
| coordinate                                   | continent              |
| -------------------------------------------- | ---------------------- |
| POINT(-86.816667 14.633333) (geo:wktLiteral) | North America (wd:Q49) |

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT DISTINCT ?timeZoneLabel WHERE {
  wd:Q782 wdt:P421 wd:Q3241537 .
  wd:Q3241537 rdfs:label ?timeZoneLabel
  FILTER ( LANG( ?timeZoneLabel ) = "en" )
}

Got 1 row and 1 column:
| timeZoneLabel                  |
| ------------------------------ |
| Hawaii–Aleutian Time Zone (en) |

Kauai, Hawaii is in the Hawaii–Aleutian Time Zone. Wikidata does not provide the current time, but this is the time zone Kauai follows.

[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 current time in kauai hawaii?

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

[Tool]
Example 1:
Question:
what is time zone in hawaii?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q782 wdt:P421 ?x .
}

Using entities:
Hawaii, also known as Hawaii State, Hawaii, United States, Kaimana Hila, The Aloha State, State of Hawaii (wd:Q782): state of the United States of America

Using properties:
located in time zone, also known as TZ, time zone, timezone (wd:P421 as wdt): time zone for this item

Example 2:
Question:
what is the hawaii time zone?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q782 wdt:P421 ?x .
}

Using entities:
Hawaii, also known as Hawaii State, Hawaii, United States, Kaimana Hila, The Aloha State, State of Hawaii (wd:Q782): state of the United States of America

Using properties:
located in time zone, also known as TZ, time zone, timezone (wd:P421 as wdt): time zone for this item

Example 3:
Question:
what is the actual current local time now in uk?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q145 wdt:P421 ?x .
}

Using entities:
United Kingdom, also known as U.K., UK, U. K., U K, United Kingdom of Great Britain and Northern Ireland (wd:Q145): country in north-west Europe

Using properties:
located in time zone, also known as TZ, time zone, timezone (wd:P421 as wdt): time zone for this item

[Assistant] From the examples, I see that the property "located in time zone" (wdt:P421) is used to find the time zone of a location. First, I will find the entity for Kauai, Hawaii, and then I will query its time zone using the property wdt:P421.

[Tool]
Top 10 entity alternatives:
1. Kauai County, also known as Kauai County, Hawaii, Kauai County, HI (wd:Q111517): county in Hawaii, United States
2. Kauaians, also known as Kauai, Hawaii, residents, Kauai inhabitants, Kauai residents (wd:Q114840257): natives or inhabitants of Kauai
3. Hāʻena, also known as Hāʻena, Kauai County, Hawaii, Hāʻena, HI (wd:Q24191782): human settlement in Kauai County, Hawaii, United States of America
4. Mayor of Kauai, also known as Mayor of Kauai County, Hawaii, Mayor of Kauaʻi (wd:Q6797729): political office in the United States
5. 2020 COVID-19 pandemic in Kauai County, Hawaii, also known as 2020 coronavirus outbreak in Kauai County, Hawaii, 2020 COVID pandemic in Kauai County, Hawaii, 2020 Kauai County, Hawaii COVID-19 pandemic, COVID-19 pandemic in Kauai County, Hawaii, Kauai County, Hawaii COVID-19 pandemic (wd:Q94286649): pandemic in Kauai County, Hawaii
6. Scabies epidemiology, Kauai, Hawaii, 1981-1985 (wd:Q68688381): scientific article published on 01 November 1987
7. Communitywide pregnancy reporting in Kauai, Hawaii (wd:Q35948571): scientific article
8. Kauai, Hawaii Tracking Station (NAID 81438948) (wd:Q71193969): item in the National Archives and Records Administration's holdings
9. Keratoacanthoma in Japanese Hawaiians in Kauai, Hawaii (wd:Q71119443): scientific article published on 01 December 1995
10. Marines Assault Kauai, Hawaii (NAID 102045278) (wd:Q67462028): item in the National Archives and Records Administration's holdings

[Assistant] The best matching entity for Kauai, Hawaii is "Kauai County" with the entity ID wd:Q111517. Now I will query the time zone of Kauai County using the property "located in time zone" (wdt:P421).

[Tool] Got no rows and 2 columns

[Assistant] The query did not return any time zone for Kauai County (wd:Q111517). Since Kauai is part of Hawaii, I will try to get the time zone for the state of Hawaii (wd:Q782) instead.

[Tool]
Got 2 rows and 2 columns:
| timeZone                                | timeZoneLabel                  |
| --------------------------------------- | ------------------------------ |
| Pacific/Honolulu (wd:Q28149311)         | Pacific/Honolulu (en)          |
| Hawaii–Aleutian Time Zone (wd:Q3241537) | Hawaii–Aleutian Time Zone (en) |

[Assistant]
The state of Hawaii (wd:Q782) has two time zones listed: "Pacific/Honolulu" (wd:Q28149311) and "Hawaii–Aleutian Time Zone" (wd:Q3241537). Kauai, Hawaii is in the Hawaii–Aleutian Time Zone. Now, I will find the current time in the Hawaii–Aleutian Time Zone. However, Wikidata does not provide real-time data such as the current time. I can only provide the time zone information.

I will finalize the answer with the time zone information for Kauai, Hawaii.

[Tool] Stopped generation process


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

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

Egyptians speak Arabic as their language.

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

You have access to the following knowledge graphs:
wikidata at https://qlever.cs.uni-freiburg.de/api/wikidata-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 kind of language do egyptian speak?

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

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

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

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

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

Example 2:
Question:
what language do egyptians use?

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

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

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

Example 3:
Question:
what language does egyptians use?

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

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

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

[Assistant] The similar examples indicate that the entity for Egypt is wd:Q79 and the property for the language spoken or official language is wdt:P37. We can use these to construct a SPARQL query to find the languages spoken by Egyptians (which is related to the country Egypt). I will now write and execute this query.

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

[Tool] Stopped generation process


PREFIX pq: <http://www.wikidata.org/prop/qualifier/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX xsd: <http://www.w3.org/2001/XMLSchema#>
PREFIX p: <http://www.wikidata.org/prop/>
PREFIX ps: <http://www.wikidata.org/prop/statement/>
SELECT DISTINCT ?senator WHERE {
  ?senator p:P39 ?statement .
  ?statement ps:P39 wd:Q4416090 ; pq:P768 ?district ; pq:P580 ?start ; pq:P582 ?end .
  ?district wdt:P131 wd:Q1370 .
  FILTER ( ?start < "2014-01-01T00:00:00Z" ^^ xsd:dateTime && ?end >= "2013-01-01T00:00:00Z" ^^ xsd:dateTime )
}

The Virginia senators in 2013 were Tim Kaine, Mark Warner, and Jim Webb.

[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 are the virginia senators 2013?

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

[Tool]
Example 1:
Question:
who are the senators of kansas 2013?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x p:P39 ?p .
  ?p ps:P39 wd:Q4416090 ; pq:P768 ?w ; pq:P580 ?y ; pq:P582 ?z .
  ?w wdt:P131 wd:Q1558 .
  FILTER ( ( ?y < "2014-01-01T00:00:00Z" ^^ xsd:dateTime ) && ( ?z >= "2013-01-01T00:00:00Z" ^^ xsd:dateTime ) )
}

Using entities:
Kansas, also known as Kan., Kans., Kansas, United States of America, US-KS, KS (wd:Q1558): state of the United States of America
United States senator, also known as U.S. senator, US senator (wd:Q4416090): member of the United States Senate

Using properties:
located in the administrative territorial entity, also known as is in the settlement of, is in the voivodeship of, is in the shire of, is in the state of, is in the territory of (wd:P131 as wdt): the item is located on the territory of the following administra...if the item falls only partially into the administrative entity., location, part of
position held, also known as function, held position, holds position, job, office held (wd:P39 as p/ps): subject currently or formerly holds the object position or public office
start time, also known as start date, since, valid, join time, joined (wd:P580 as pq): time an entity begins to exist or a statement starts being valid, point in time
end time, also known as ends, stop time, endtime, fall date, ineffective (wd:P582 as pq): moment when an entity ceases to exist and a statement stops being entirely valid or no longer be true, point in time
electoral district, also known as riding, seat, ward, electoral area, electorate (wd:P768 as pq): electoral district this person is representing, or of the office... or "office contested" (P541) or "candidacy in election" (P3602)

Example 2:
Question:
who are the current maryland senators?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x p:P39 ?p .
  ?p ps:P39 wd:Q4416090 .
  ?p pq:P768 ?y .
  ?y wdt:P131 wd:Q1391 .
  FILTER NOT EXISTS {
    ?p pq:P582 ?z .
  }
}

Using entities:
Maryland, also known as Maryland, United States, Md., MD, US-MD, Old Line State (wd:Q1391): state of the United States of America
United States senator, also known as U.S. senator, US senator (wd:Q4416090): member of the United States Senate

Using properties:
located in the administrative territorial entity, also known as is in the settlement of, is in the voivodeship of, is in the shire of, is in the state of, is in the territory of (wd:P131 as wdt): the item is located on the territory of the following administra...if the item falls only partially into the administrative entity., location, part of
position held, also known as function, held position, holds position, job, office held (wd:P39 as p/ps): subject currently or formerly holds the object position or public office
end time, also known as ends, stop time, endtime, fall date, ineffective (wd:P582 as pq): moment when an entity ceases to exist and a statement stops being entirely valid or no longer be true, point in time
electoral district, also known as riding, seat, ward, electoral area, electorate (wd:P768 as pq): electoral district this person is representing, or of the office... or "office contested" (P541) or "candidacy in election" (P3602)

Example 3:
Question:
who is the senator of the state of texas?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x p:P39 ?p .
  ?p ps:P39 wd:Q4416090 .
  ?p pq:P768 ?y .
  ?y wdt:P131 wd:Q1439 .
  FILTER NOT EXISTS {
    ?p pq:P582 ?z .
  }
}

Using entities:
Texas, also known as Lone Star State, US-TX, TX, Texas, United States, Tex. (wd:Q1439): state of the United States of America
United States senator, also known as U.S. senator, US senator (wd:Q4416090): member of the United States Senate

Using properties:
located in the administrative territorial entity, also known as is in the settlement of, is in the voivodeship of, is in the shire of, is in the state of, is in the territory of (wd:P131 as wdt): the item is located on the territory of the following administra...if the item falls only partially into the administrative entity., location, part of
position held, also known as function, held position, holds position, job, office held (wd:P39 as p/ps): subject currently or formerly holds the object position or public office
end time, also known as ends, stop time, endtime, fall date, ineffective (wd:P582 as pq): moment when an entity ceases to exist and a statement stops being entirely valid or no longer be true, point in time
electoral district, also known as riding, seat, ward, electoral area, electorate (wd:P768 as pq): electoral district this person is representing, or of the office... or "office contested" (P541) or "candidacy in election" (P3602)

[Assistant]
From the examples, we see that the query to find senators of a state in a specific year involves:
- Position held (P39) = United States senator (Q4416090)
- Electoral district (P768) located in the state (P131)
- Start time (P580) and end time (P582) qualifiers to filter for the year 2013

We need to find the entity for Virginia and then find persons who held the position of United States senator representing Virginia in 2013.

I will now search for the entity "Virginia" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Virginia, also known as State of Virginia, Old Dominion, US-VA, Va., Commonwealth of Virginia (wd:Q1370): state of the United States of America
2. Virginia, also known as VA, Virginia, United States, Va., US-VA, Old Dominion (wd:Q1370): state of the United States of America
3. 50 Virginia, also known as (50) Virginia, Virginia (wd:Q154933): main-belt asteroid
4. Virginia, also known as Virginia, Minnesota, Virginia, MN (wd:Q986681): city in St. Louis County, Minnesota, United States
5. Virginia, also known as Virginia, Illinois, Virginia, IL (wd:Q579625): city in Illinois, USA
6. Virginia, also known as Virginia, Nebraska, Virginia, NE (wd:Q2207776): village in Gage County, Nebraska, United States
7. Virgínia, also known as Virginia (wd:Q1787215): town and municipality in the state of Minas Gerais, Brazil
8. Verginia, also known as Virginia (wd:Q1278485): 5th-century BC Roman heroine
9. Virginia, also known as Virginia, County Cavan (wd:Q255427): town in County Cavan, Ireland
10. Virginia (wd:Q290763): genus of reptiles

[Assistant]
The entity for the state of Virginia in the United States is wd:Q1370.

Next, I will write a SPARQL query to find the senators of Virginia in 2013 using the approach from the examples:
- Position held (P39) = United States senator (Q4416090)
- Electoral district (P768) located in Virginia (Q1370)
- Start time (P580) and end time (P582) qualifiers to filter for the year 2013

[Tool]
Got 3 rows and 1 column:
| senator                  |
| ------------------------ |
| Tim Kaine (wd:Q359888)   |
| Mark Warner (wd:Q453893) |
| Jim Webb (wd:Q532279)    |

[Assistant]
The query returned three senators for Virginia in 2013: Tim Kaine (wd:Q359888), Mark Warner (wd:Q453893), and Jim Webb (wd:Q532279).

I will now finalize the answer with these results.

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT DISTINCT ?governor WHERE {
  wd:Q812 wdt:P6 ?governor .
}

The state governor of Florida is Ron DeSantis.

[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 is the state governor of florida?

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

[Tool]
Example 1:
Question:
who is the new governor of florida 2011?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q20198851 wdt:P1308 ?x .
}

Using entities:
Governor of Florida, also known as Florida Governor (wd:Q20198851): head of state and of government of the U.S. state of Florida

Using properties:
position holder, also known as incumbent, noble title holder, office holder, position held by (wd:P1308 as wdt): persons who hold and/or held the position

Example 2:
Question:
who is the current governor of georgia?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q739 wdt:P6 ?x .
}

Using entities:
Colombia, also known as The Republic of Colombia, Republic of Colombia, ISO 3166-1:CO, Colombiá, COL (wd:Q739): sovereign state in South America

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

Example 3:
Question:
who is the elected governor of california?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q99 wdt:P6 ?x .
}

Using entities:
California, also known as US-CA, State of California, The Golden State, Calif., Cali. (wd:Q99): state of the United States of America

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

[Assistant]
From the examples, it seems that the property "head of government" (wdt:P6) is used to indicate the governor or equivalent position for a state entity. Also, the entity for Florida is likely wd:Q812.

I will now write a SPARQL query to find the current governor of Florida using this property and entity.

[Tool]
Got 1 row and 1 column:
| governor                   |
| -------------------------- |
| Ron DeSantis (wd:Q3105215) |

[Tool] Stopped generation process


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

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

Douglas MacArthur attended the United States Army Command and General Staff College, Milwaukee High School of the Arts, and the United States Military Academy.

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

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

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

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

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

[User] what school did douglas macarthur go to?

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

[Tool]
Example 1:
Question:
where did douglas macarthur die?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q127417 wdt:P20 ?x .
}

Using entities:
Douglas MacArthur, also known as MacArthur, D. MacArthur, General MacArthur, General Douglas MacArthur (wd:Q127417): United States Army general in WWI, WWII and Korea (1880–1964), military officer, army officer

Using properties:
place of death, also known as POD, location of death, killed in, deathplace, died in (wd:P20 as wdt): most specific known (e.g. city instead of country, or hospital i... city) death location of a person, animal or fictional character, location

Example 2:
Question:
where did eleanor roosevelt go to school?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q83396 wdt:P69 ?x .
}

Using entities:
Eleanor Roosevelt, also known as Eleanor Roosevelt Roosevelt, Elaenore Roosevelt, Anna Eleanor Roosevelt Roosevelt, First Lady of the world, Anna Roosevelt (wd:Q83396): First Lady of the United States from 1933 to 1945, women's rights activist, human rights activist, peace activist, autobiographer, journalist, politician, columnist, diplomat, writer

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

Example 3:
Question:
where did barack obama went to school?

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

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

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

[Assistant] From the examples, the property "educated at" (wdt:P69) is used to find the school or educational institution a person attended. Douglas MacArthur is identified as wd:Q127417. I will now write a query to find the schools Douglas MacArthur attended using this property.

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

[Tool] Stopped generation process


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

The actor who played Donna Moss on The West Wing is Janel Moloney.

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

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

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

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

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

[User] who played donna on west wing?

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

[Tool]
Example 1:
Question:
who plays claudia joy on army wives?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q2308037 p:P161 ?p .
  ?p ps:P161 ?x ; pq:P453 wd:Q5129199 .
}

Using entities:
Army Wives (wd:Q2308037): American television series
Claudia Joy Holden (wd:Q5129199): fictional character

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

Example 2:
Question:
who plays moira on the l word?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q216792 p:P161 ?p .
  ?p ps:P161 ?x ; pq:P453 wd:Q3319244 .
}

Using entities:
The L Word (wd:Q216792): American-Canadian television series
Max Sweeney, also known as Moira Sweeney (wd:Q3319244): fictional character from the television series The L Word

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

Example 3:
Question:
who plays meg in family guy?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q5930 p:P725 ?p .
  ?p ps:P725 ?x ; pq:P453 wd:Q908772 .
}

Using entities:
Family Guy (wd:Q5930): American adult animated sitcom
Meg Griffin, also known as Megan Griffin, Megatron "Meg" Harvey Oswald Griffin, Megatron Harvey Oswald Griffin, Megan "Meg" Griffin (wd:Q908772): fictional character from the Family Guy franchise, high school student

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

[Assistant]
From the examples, the pattern to find who played a character in a TV show is to use the property "cast member" (P161) with a qualifier "character role" (P453) for the specific character.

Next, I will search for the entity representing the TV show "The West Wing" to use it in the query.

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

[Assistant]
The entity for the TV show "The West Wing" is wd:Q3577037.

Now I will search for the character "Donna" related to "The West Wing" to find the corresponding entity.

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

[Assistant] I did not find a direct entity for the character "Donna" from "The West Wing" in the search results. I will try to find the cast members of "The West Wing" and check if there is a character named Donna among them. This can be done by looking at the cast members (P161) of the TV show and their character roles (P453).

[Tool]
SPARQL execution failed:
Error while executing a SERVICE request to <http://wikiba.se:80/ontology#label>: SERVICE responded with HTTP status code: 301, Moved Permanently. First 100 bytes of the response: '<html>
<head><title>301 Moved Permanently</title></head>
<body>
<center><h1>301 Moved Permanently'

[Assistant] The query failed because the SERVICE wikibase:label is not supported by the endpoint. I will rewrite the query without using SERVICE wikibase:label and instead use rdfs:label with OPTIONAL clauses to get the labels.

[Tool]
Got 10 rows and 4 columns:
| actor                           | actorLabel             | character                    | characterLabel      |
| ------------------------------- | ---------------------- | ---------------------------- | ------------------- |
| Stockard Channing (wd:Q1117390) | Stockard Channing (en) | Abbey Bartlet (wd:Q3603297)  | Abbey Bartlet (en)  |
| Janel Moloney (wd:Q114447)      | Janel Moloney (en)     | Donna Moss (wd:Q3036775)     | Donna Moss (en)     |
| Martin Sheen (wd:Q184572)       | Martin Sheen (en)      | Josiah Bartlet (wd:Q2715593) | Josiah Bartlet (en) |
| Allison Janney (wd:Q229487)     | Allison Janney (en)    | C. J. Cregg (wd:Q1080587)    | C. J. Cregg (en)    |
| Rob Lowe (wd:Q296505)           | Rob Lowe (en)          | Sam Seaborn (wd:Q3946354)    | Sam Seaborn (en)    |
| Bradley Whitford (wd:Q352180)   | Bradley Whitford (en)  | Josh Lyman (wd:Q5656906)     | Josh Lyman (en)     |
| John Spencer (wd:Q352748)       | John Spencer (en)      | Leo McGarry (wd:Q6524042)    | Leo McGarry (en)    |
| Richard Schiff (wd:Q355209)     | Richard Schiff (en)    | Toby Ziegler (wd:Q1345373)   | Toby Ziegler (en)   |
| Dulé Hill (wd:Q458664)          | Dulé Hill (en)         | Charlie Young (wd:Q3666688)  | Charlie Young (en)  |
| Joshua Malina (wd:Q60422)       | Joshua Malina (en)     | Will Bailey (wd:Q8002690)    | Will Bailey (en)    |

[Assistant]
The character "Donna Moss" (wd:Q3036775) is played by the actor Janel Moloney (wd:Q114447) in the TV show "The West Wing" (wd:Q3577037).

I will now provide the final answer with a SPARQL query that retrieves the actor who played Donna Moss on The West Wing.

[Tool] Stopped generation process