PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT DISTINCT ?government ?governmentLabel WHERE {
  wd:Q928 wdt:P122 ?government .
  OPTIONAL {
    ?government rdfs:label ?governmentLabel .
    FILTER ( LANG( ?governmentLabel ) = 'en' )
  }
}

Got 1 row and 2 columns:
| government          | governmentLabel |
| ------------------- | --------------- |
| republic (wd:Q7270) | republic (en)   |

The form of government in the Philippines is a republic.

[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 form of government do we have in the philippines?

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

[Tool]
Example 1:
Question:
what form of government does canada have?

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

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

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

Example 2:
Question:
what kind of system of government does the united states have?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q30 wdt:P122 ?x .
}

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

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

Example 3:
Question:
what type of government is the us government?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q30 wdt:P122 ?x .
}

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

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

[Assistant] Based on the examples, it seems like the property `wdt:P122` (basic form of government) is used to describe the form of government of a country. Let's first find the entity for the Philippines.

[Tool]
Top 10 entity alternatives:
1. Philippines, also known as ph, The Philippines, RP, Republic of the Philippines, Philippine Islands (wd:Q928): archipelagic country in Southeast Asia
2. Philippines (wd:Q70886687): scientific article published on 01 January 1966
3. Philippines (wd:Q116754458): scientific article published on 15 November 2001
4. Philippines (wd:Q47409215): scientific article published in August 1986
5. Philippines (wd:Q57715247): entry in Encyclopedia of Global Warming & Climate Change
6. Philippines. (wd:Q39611725): scientific article published on September 1983
7. Philippines (wd:L1259985-S1)
8. Philippines (wd:L476739-F2)
9. Philippines (wd:L254248-F1)
10. Philippines (wd:L254248)

[Assistant] The correct entity for the Philippines is `wd:Q928`. Now let's use the property `wdt:P122` to find the form of government in the Philippines.

[Tool]
Got 1 row and 1 column:
| government          |
| ------------------- |
| republic (wd:Q7270) |

[Assistant] The form of government in the Philippines is a republic. To provide a more complete answer, let's also include the label of the government form in the query.

[Tool]
Got 1 row and 2 columns:
| government          | governmentLabel |
| ------------------- | --------------- |
| republic (wd:Q7270) | republic (en)   |

[Assistant]
The form of government in the Philippines is a republic.

Now, I'll provide the final SPARQL query and answer.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT DISTINCT ?movie WHERE {
  ?movie wdt:P57 wd:Q103646 .
}

Got 44 rows and 1 column, showing the first 5 and last 5 rows below:
| movie                              |
| ---------------------------------- |
| Thirteen Lives (wd:Q105962844)     |
| Apollo 13 (wd:Q106428)             |
| Cocoon (wd:Q1105463)               |
| Splash (wd:Q1127184)               |
| Parenthood (wd:Q1137831)           |
| ...                                |
| Frost/Nixon (wd:Q691672)           |
| Ransom (wd:Q752362)                |
| Far and Away (wd:Q839341)          |
| Rebuilding Paradise (wd:Q96314873) |
| Night Shift (wd:Q997228)           |

The movies directed by Ron Howard include: Thirteen Lives (wd:Q105962844), Apollo 13 (wd:Q106428), Cocoon (wd:Q1105463), Splash (wd:Q1127184), Parenth... (wd:Q96314873), and Night Shift (wd:Q997228). There are many more movies in the list.

[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 movies did ron howard director?

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

[Tool]
Example 1:
Question:
what movies did ron howard do?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x wdt:P161 wd:Q103646 ; wdt:P31 / wdt:P279 * wd:Q11424 .
}

Using entities:
Ron Howard, also known as Ronald William Howard (wd:Q103646): American film director, producer, and actor, television producer, television director, television actor, film producer, film director, screenwriter, voice actor, film actor, director, actor
film, also known as cinematic work, moving picture, movie, motion pictures, motion picture (wd:Q11424): sequence of images that give the impression of movement, stored on film stock

Using properties:
cast member, also known as feat., starring (film/play), film starring, starring, actor (wd:P161 as wdt): actor in the subject production [use "character role" (P453) and...use "recorded participant" (P11108) for non-fiction productions], significant person, performer
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)

Example 2:
Question:
what did ron howard direct?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x wdt:P57 wd:Q103646 .
}

Using entities:
Ron Howard, also known as Ronald William Howard (wd:Q103646): American film director, producer, and actor, television producer, television director, television actor, film producer, film director, screenwriter, voice actor, film actor, director, actor

Using properties:
director, also known as film director, movie director, game director, directed by (wd:P57 as wdt): director(s) of film, TV-series, stageplay, video game or similar, contributor to the creative work or subject, creator

Example 3:
Question:
what movies does leo howard play in?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x wdt:P161 wd:Q776957 ; wdt:P31 / wdt:P279 * wd:Q11424 .
}

Using entities:
film, also known as cinematic work, moving picture, movie, motion pictures, motion picture (wd:Q11424): sequence of images that give the impression of movement, stored on film stock
Leo Howard (wd:Q776957): television director, television actor, American actor, film actor, karateka, actor, model

Using properties:
cast member, also known as feat., starring (film/play), film starring, starring, actor (wd:P161 as wdt): actor in the subject production [use "character role" (P453) and...use "recorded participant" (P11108) for non-fiction productions], significant person, performer
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)

[Assistant] Based on the examples, it seems like we need to find movies where Ron Howard was the director. We can use the `wdt:P57` property which represents the director of a film. Let's construct a SPARQL query to list all the movies directed by Ron Howard.

[Tool]
Got 44 rows and 1 column, showing the first 5 and last 5 rows below:
| movie                              |
| ---------------------------------- |
| Thirteen Lives (wd:Q105962844)     |
| Apollo 13 (wd:Q106428)             |
| Cocoon (wd:Q1105463)               |
| Splash (wd:Q1127184)               |
| Parenthood (wd:Q1137831)           |
| ...                                |
| Frost/Nixon (wd:Q691672)           |
| Ransom (wd:Q752362)                |
| Far and Away (wd:Q839341)          |
| Rebuilding Paradise (wd:Q96314873) |
| Night Shift (wd:Q997228)           |

[Assistant]
The SPARQL query successfully returned the movies directed by Ron Howard. Here is the final SPARQL query and the list of movies:

```sparql
SELECT DISTINCT ?movie WHERE {
  ?movie wdt:P57 wd:Q103646 .
}
```

The movies directed by Ron Howard include:
- Thirteen Lives (wd:Q105962844)
- Apollo 13 (wd:Q106428)
- Cocoon (wd:Q1105463)
- Splash (wd:Q1127184)
- Parenthood (wd:Q1137831)
- Frost/Nixon (wd:Q691672)
- Ransom (wd:Q752362)
- Far and Away (wd:Q839341)
- Rebuilding Paradise (wd:Q96314873)
- Night Shift (wd:Q997228)

And many more.

Let's finalize the answer.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT DISTINCT ?highSchool WHERE {
  wd:Q19526 wdt:P69 ?highSchool .
  ?highSchool wdt:P31 / wdt:P279 * wd:Q9826 .
}

George Washington 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 high school did maya angelou go to?

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

[Tool]
Example 1:
Question:
where did lebron james go to highschool?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q36159 wdt:P69 ?x .
}

Using entities:
LeBron James, also known as LeBron Raymone James Sr., LeBron, The Chosen One, King James, LeBron Raymone James (wd:Q36159): American basketball player (born 1984), basketball player, television actor, screenwriter

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:
where did kobe bryant attend high school?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q25369 wdt:P69 ?x .
  ?x wdt:P31 / wdt:P279 * wd:Q9826 .
}

Using entities:
Kobe Bryant, also known as Kobe Bean Bryant, Kobe B. Bryant, Kobe, KB24, Black Mamba (wd:Q25369): American basketball player (1978–2020), professional athlete, basketball player, screenwriter
high school, also known as H.S., upper middle school, senior high school, HS (wd:Q9826): institution which provides all or part of secondary education

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 high school did president bill clinton attend?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q1124 wdt:P69 ?x .
  ?x wdt:P31 / wdt:P279 * wd:Q9826 .
}

Using entities:
Bill Clinton, also known as William Jefferson Blythe, William Jefferson Blythe III, William Jefferson "Bill" Clinton, William Jefferson Clinton, WJC (wd:Q1124): President of the United States from 1993 to 2001, autobiographer, statesperson, saxophonist, politician, governor, diplomat, teacher, jurist, lawyer, writer
high school, also known as H.S., upper middle school, senior high school, HS (wd:Q9826): institution which provides all or part of secondary education

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] Based on the examples, we can see that the property `educated at` (P69) is used to link individuals to their educational institutions. We need to find the entity for Maya Angelou and then use this property to find her high school.

[Tool]
Top 10 entity alternatives:
1. Maya Angelou, also known as Marguerite Annie Johnson, Marguerite Ann Johnson, Marguerite Johnson, Marguerite Anne Johnson (wd:Q19526): American poet, author, and civil rights activist (1928–2014), human rights activist, television producer, television actor, autobiographer, film producer, film director, screenwriter, stage actor, playwright, journalist, politician, songwriter, professor, essayist, novelist, dancer, singer, writer
2. Maya Angelou, also known as Marguerite Ann Johnson, Marguerite Annie Johnson, Marguerite Johnson, Marguerite Anne Johnson (wd:Q19526): American poet, author, and civil rights activist (1928–2014), human rights activist, television producer, television actor, autobiographer, film director, film producer, screenwriter, stage actor, journalist, playwright, songwriter, politician, professor, essayist, novelist, writer, singer, dancer
3. Maya Angelou (wd:Q108467711): magazine article from 'American Funeral Director' published in 2014
4. Maya Angelou (wd:Q47513615): painting by Ross R. Rossin
5. Maya Angelou Academy (wd:Q14692192): American alternative school
6. Maya Angelou Birthplace, also known as Birthplace of Maya Angelou (wd:Q132261323): The house in St. Louis, Missouri where Maya Angelou was born
7. Maya Angelou, 1928-2014 (wd:Q116228315): journal article
8. Maya Angelou Library (wd:Q66364225): public library in Stockton, California, USA
9. Maya Angelou Northeast (wd:Q69781127): public library in Wichita, Kansas, USA
10. rue Maya Angelou (wd:Q125778051)

[Assistant]
The correct entity for Maya Angelou is `wd:Q19526`. Now, let's use the property `educated at` (P69) to find out which high school she attended.

I will run a SPARQL query to find the educational institutions Maya Angelou attended and filter for those that are high schools.

[Tool]
Got 1 row and 1 column:
| highSchool                                  |
| ------------------------------------------- |
| George Washington High School (wd:Q5545977) |

[Assistant]
The SPARQL query returned that Maya Angelou attended George Washington High School.

Here is the final SPARQL query and the answer:

```sparql
SELECT DISTINCT ?highSchool WHERE {
  wd:Q19526 wdt:P69 ?highSchool .
  ?highSchool wdt:P31 / wdt:P279* wd:Q9826 .
}
```

The high school that Maya Angelou attended is George Washington High School.

[Tool] Stopped generation process


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

Otto 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] Based on the examples, we need to identify the entity for Otto Frank and the property for 'educated at'. Let's first search for the entity 'Otto Frank'.

[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]
From the search results, the correct entity for Otto Frank is likely to be 'Otto Frank, also known as Otto Friedrich Frank, Friedrich Wilhelm Ferdinand Otto Frank (wd:Q89925)', who was a German physiologist. However, this does not seem to match the context of the question, as it refers to Anne Frank's father. Let's verify the correct entity for Anne Frank's father.

I will search for 'Anne Frank' and then look for her father.

[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. Statue of Anne Frank, also known as Anne Frank (wd:Q27918477): public artwork by Pieter d'Hont in Utrecht, the Netherlands
4. Bust of Anne Frank, also known as Anne Frank (wd:Q41688543): sculpture by Doreen Kern
5. Aenne Pahl, also known as Anne Frank (wd:Q60540011): painter
6. Anne Frank (wd:Q128498127): opera by Shulamit Ran
7. Anne Frank (wd:Q99711206): television executive
8. Anne Frank, also known as No Guilt (wd:Q123907483): 1990 single by Brainbombs
9. Anne Frank (wd:Q115618903): sculpture in Berlin, Germany
10. Anne Frank (wd:Q106898038): costume designer, theatre manager, textile worker, puppeteer, director

[Assistant]
The correct entity for Anne Frank is 'Anne Frank, also known as Anne M. Frank, Anna Frank, Anne Maries Frank, Annelies Marie Frank, Anna M Frank (wd:Q4583)'. Now, let's find the entity for her father, Otto Frank.

I will look for the property 'father' and then use it to find Otto Frank.

[Tool]
Top 10 property alternatives:
1. father, also known as son of, child of, parent, is son of, is daughter of (wd:P22 as pr/psv/prv/wdtn/pqv/pq/pqn/wdt/psn/ps/prn/p): male parent of the subject. For stepfather, use "stepparent" (P3448), parent
2. child, also known as has son, kids, mother of, kid, issue (wd:P40 as pr/psv/prv/wdtn/pqv/pq/pqn/wdt/psn/ps/prn/p): subject has object as child. Do not use for stepchildren—use "relative" (P1038), qualified with "type of kinship" (P1039), significant person, relative
3. parent, also known as guardian, parents (wd:P8810 as pr/psv/prv/wdtn/pqv/pq/pqn/wdt/psn/ps/prn/p): parent of the subject. Only use if neither father (P22) nor mother (P25) nor stepparent (P3448) is applicable., relative
4. mother, also known as mom, is child of, mommy, mum, mummy (wd:P25 as pr/psv/prv/wdtn/pqv/pq/pqn/wdt/psn/ps/prn/p): female parent of the subject. For stepmother, use "stepparent" (P3448), parent
5. relative, also known as relatives, grandparent, relation, non-binary parent, niece (wd:P1038 as pr/psv/prv/wdtn/pqv/pq/pqn/wdt/psn/ps/prn/p): family member (qualify with "kinship to subject", P1039; for direct family member please use specific property), significant person
6. Dictionary of Algorithms and Data Structures ID, also known as DADS ID (wd:P5106 as pr/psv/prv/wdtn/pqv/pq/pqn/wdt/psn/ps/prn/p): identifier for an entry in the Dictionary of Algorithms and Data Structures
7. stepparent, also known as step-parent, step parent, stepmother, step-mother, step mother (wd:P3448 as pr/psv/prv/wdtn/pqv/pq/pqn/wdt/psn/ps/prn/p): subject has the object as their stepparent, relative
8. godparent, also known as godfather, godmother (wd:P1290 as pr/psv/prv/wdtn/pqv/pq/pqn/wdt/psn/ps/prn/p): person who is the godparent of a given person, relative
9. family, also known as royal house, noble family, member of family, house, dynasty (wd:P53 as pr/psv/prv/wdtn/pqv/pq/pqn/wdt/psn/ps/prn/p): family, including dynasty and nobility houses. Not family name (use P734 for family name)., member of
10. spouse, also known as married partner, married to, marry, partner, spouses (wd:P26 as pr/psv/prv/wdtn/pqv/pq/pqn/wdt/psn/ps/prn/p): the subject has the object as their spouse (husband, wife, partn...etc.). Use "unmarried partner" (P451) for non-married companions, significant person, relative

[Assistant]
The correct property for 'father' is 'father, also known as son of, child of, parent, is son of, is daughter of (wd:P22)'.

Now, I will use this property to find Otto Frank, who is Anne Frank's father.

[Tool]
Got 1 row and 1 column:
| father                         |
| ------------------------------ |
| Otto Heinrich Frank (wd:Q7336) |

[Assistant] The entity for Otto Frank is 'Otto Heinrich Frank (wd:Q7336)'. Now, let's find out where he went to college by using the property 'educated at' (wdt:P69).

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

[Assistant]
Otto Frank went to Heidelberg University.

Here is the final SPARQL query and answer:

```sparql
SELECT ?college WHERE {
  wd:Q7336 wdt:P69 ?college .
}
```

Answer: Otto Frank went to Heidelberg University.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT DISTINCT ?education WHERE {
  wd:Q52651 wdt:P69 ?education .
}

Got 3 rows and 1 column:
| education                                |
| ---------------------------------------- |
| Ohio State University (wd:Q309331)       |
| East Technical High School (wd:Q5329490) |
| North Platte High School (wd:Q7056353)   |

Jesse Owens attended 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] Based on the examples, it seems that the property `P69` (educated at) is commonly used to represent the educational institutions attended by individuals. Let's first identify the entity for Jesse Owens.

[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 correct entity for Jesse Owens is `wd:Q52651`. Now, let's use the property `P69` to find the educational institutions he attended.

[Tool]
Got 3 rows and 1 column:
| education                                |
| ---------------------------------------- |
| Ohio State University (wd:Q309331)       |
| East Technical High School (wd:Q5329490) |
| North Platte High School (wd:Q7056353)   |

[Assistant]
The educational institutions that Jesse Owens attended are:

- Ohio State University
- East Technical High School
- North Platte High School

Here is the final SPARQL query and answer:

```sparql
SELECT DISTINCT ?education WHERE {
  wd:Q52651 wdt:P69 ?education .
}
```

Answer: Jesse Owens attended Ohio State University, East Technical High School, and North Platte High School.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT DISTINCT ?religion WHERE {
  wd:Q252 wdt:P140 ?religion .
}

Got 6 rows and 1 column:
| religion                  |
| ------------------------- |
| Catholicism (wd:Q1841)    |
| Protestantism (wd:Q23540) |
| Islam (wd:Q432)           |
| Buddhism (wd:Q748)        |
| Hinduism (wd:Q9089)       |
| Confucianism (wd:Q9581)   |

The religions practiced in Indonesia include 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] Based on the examples, we can see that the property `P140` is used to denote the religion of a country. Let's use this property to find the religions practiced in Indonesia.

[Tool]
Got 6 rows and 1 column:
| religion                  |
| ------------------------- |
| Catholicism (wd:Q1841)    |
| Protestantism (wd:Q23540) |
| Islam (wd:Q432)           |
| Buddhism (wd:Q748)        |
| Hinduism (wd:Q9089)       |
| Confucianism (wd:Q9581)   |

[Assistant]
The query has successfully returned the religions practiced in Indonesia. Now, let's format the answer.

Here are the religions practiced in Indonesia:
- Catholicism
- Protestantism
- Islam
- Buddhism
- Hinduism
- Confucianism

I will now provide the final answer.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?location WHERE {
  wd:Q783 wdt:P625 ?location .
}

Honduras is located at the coordinates POINT(-86.816667 14.633333).

[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] Based on the examples, it seems like we need to find the coordinate location (P625) of Honduras to determine where it is in the world. Let's first identify the entity for Honduras.

[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 correct entity for Honduras is the first one, `wd:Q783`. Now let's check if this entity has a coordinate location (P625).

[Tool]
Got 1 row and 3 columns:
| subject            | property                       | object                                       |
| ------------------ | ------------------------------ | -------------------------------------------- |
| Honduras (wd:Q783) | coordinate location (wdt:P625) | POINT(-86.816667 14.633333) (geo:wktLiteral) |

[Assistant]
Honduras does indeed have a coordinate location. We can now construct a SPARQL query to retrieve this information.

### SPARQL Query
```sparql
SELECT ?location WHERE {
  wd:Q783 wdt:P625 ?location .
}
```

This query will return the coordinate location of Honduras. Let's execute it to confirm the result.

[Tool]
Got 1 row and 1 column:
| location                                     |
| -------------------------------------------- |
| POINT(-86.816667 14.633333) (geo:wktLiteral) |

[Assistant]
The SPARQL query successfully returned the coordinate location of Honduras. The coordinates are `POINT(-86.816667 14.633333)`.

### Final Answer
Honduras is located at the coordinates `POINT(-86.816667 14.633333)`.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT DISTINCT ?timeZone WHERE {
  wd:Q782 wdt:P421 ?timeZone .
}

The current time in Kauai, Hawaii, follows the Pacific/Honolulu time zone.

[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, we can see that the property `located in time zone` (wdt:P421) is used to find the time zone of a place. We need to find the entity for Kauai, Hawaii, and then use this property to find its time zone.

[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 most relevant entity for Kauai, Hawaii, is `Kauai County` (wd:Q111517). Now, let's check if this entity has a time zone associated with it using the property `located in time zone` (wdt:P421).

[Tool] Got no rows and 1 columns

[Assistant] It seems that `Kauai County` does not have a direct time zone property. However, since Kauai is part of Hawaii, we can use the time zone of Hawaii instead. Let's find the time zone for Hawaii (wd:Q782).

[Tool]
Got 2 rows and 1 column:
| timeZone                                |
| --------------------------------------- |
| Pacific/Honolulu (wd:Q28149311)         |
| Hawaii–Aleutian Time Zone (wd:Q3241537) |

[Assistant]
The time zones for Hawaii are `Pacific/Honolulu` (wd:Q28149311) and `Hawaii–Aleutian Time Zone` (wd:Q3241537). Since Kauai is part of Hawaii, it follows the same time zone.

To get the current time in Kauai, we need to use the `Pacific/Honolulu` time zone, as it is the standard time zone for the state of Hawaii.

However, the current time is not directly available in the knowledge graph. We can provide the time zone and suggest that the user can use this information to find the current time.

Here is the SPARQL query to get the time zone:

```sparql
SELECT DISTINCT ?timeZone WHERE {
  wd:Q782 wdt:P421 ?timeZone .
}
```

And the answer is that the current time in Kauai, Hawaii, follows the `Pacific/Honolulu` time zone.

Let's finalize this with the answer function.

[Tool] Stopped generation process


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

The official language of Egypt is Arabic.

[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] Based on the similar examples, it seems that the property `wdt:P37` (official language) is used to find the language spoken in a country. Let's confirm this by checking the property details.

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

[Assistant] The property `wdt:P37` (official language) is indeed the correct property to use for finding the language spoken in a country. Now, let's identify the entity for Egypt.

[Tool]
Top 10 entity alternatives:
1. Egypt, also known as Republic of Egypt, Rep. Egypt, EGY, eg, Arab Republic of Egypt (wd:Q79): country in Northeast Africa and Southwest Asia
2. Khedivate of Egypt, also known as Egypt, Egyptian Khedivate (wd:Q127861): 1867-1914 monarchy in Northeastern Africa
3. Egypt Eyalet, also known as QASR of Egypt, Pashalik of Egypt, Egypt, Mısır Eyalet, Beylerbeyilik of Egypt (wd:Q491507): Egyptian State (1517–1867)
4. Egypt, also known as Egypt, AK, Egypt, AR (wd:Q2083973): town in Arkansas
5. Egypt, also known as Egypt, Etowah County, Alabama, Egypt, AL (wd:Q5348296): census-designated place in Etowah County, Alabama
6. Egypt, also known as Egypt, Pennsylvania (wd:Q5348306): human settlement in Pennsylvania, United States
7. Egypt 1156 B.C., also known as Egypt, Egypt 1156 B.C.: Tomb of the Pharaoh (wd:Q3586212): 1999 video game
8. Egypt, also known as Egypt, WV (wd:Q5348310): unincorporated community in Jefferson County, West Virginia
9. Egypt (wd:Q5348317): 2004 album by Youssou N'Dour
10. Egypt, also known as Egypt, IN, Egypt, Indiana (wd:Q5348297): unincorporated community in Jasper County, Minnesota

[Assistant]
The entity for Egypt is `wd:Q79`. Now we can construct the SPARQL query to find the official language of Egypt using the property `wdt:P37`.

Let's execute the query:

```sparql
SELECT DISTINCT ?language WHERE {
  wd:Q79 wdt:P37 ?language .
  OPTIONAL { ?language rdfs:label ?label . FILTER(LANG(?label) = "en") }
}
```

This query will return the official language of Egypt and optionally its English label.

[Tool]
Got 1 row and 1 column:
| language           |
| ------------------ |
| Arabic (wd:Q13955) |

[Assistant]
The official language of Egypt is Arabic.

Here is the final SPARQL query and answer:

```sparql
SELECT DISTINCT ?language WHERE {
  wd:Q79 wdt:P37 ?language .
  OPTIONAL { ?language rdfs:label ?label . FILTER(LANG(?label) = "en") }
}
```

Answer: The official language of Egypt is Arabic.

[Tool] Stopped generation process