PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT DISTINCT ?property ?propertyLabel ?place ?placeLabel WHERE {
  VALUES ?property {
    wdt:P19 wdt:P551 wdt:P69
  }
  wd:Q1744 ?property ?place .
  OPTIONAL {
    ?place rdfs:label ?placeLabel FILTER ( LANG( ?placeLabel ) = "en" )
  }
  BIND( IF( ?property = wdt:P19 , "place of birth" , IF( ?property = wdt:P551 , "residence" , "educated at" ) ) AS ?propertyLabel )
}

Got 3 rows and 4 columns:
| property                 | propertyLabel  | place                                                                 | placeLabel                                                   |
| ------------------------ | -------------- | --------------------------------------------------------------------- | ------------------------------------------------------------ |
| place of birth (wdt:P19) | place of birth | Bay City (wd:Q746820)                                                 | Bay City (en)                                                |
| educated at (wdt:P69)    | educated at    | Rochester Adams High School (wd:Q7353940)                             | Rochester Adams High School (en)                             |
| educated at (wdt:P69)    | educated at    | University of Michigan School of Music, Theatre & Dance (wd:Q7895775) | University of Michigan School of Music, Theatre & Dance (en) |

Madonna was born in Bay City. She grew up in the area where she attended Rochester Adams High School and later studied at the University of Michigan School of Music, Theatre & Dance.

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

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

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

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

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

[User] where did madonna grew up?

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

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

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

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

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

Example 2:
Question:
where did carmen electra grow up?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q185122 wdt:P19 ?x .
}

Using entities:
Carmen Electra, also known as Tara Patrick, Tara Leigh Patrick (wd:Q185122): American actress, model, and singer, Playboy Playmate, television actor, voice actor, film actor, dancer, singer, model, actor

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

Example 3:
Question:
where did neil gaiman grow up?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q210059 wdt:P19 ?x .
}

Using entities:
Neil Gaiman, also known as N. Gaiman, Neil Richard MacKinnon Gaiman, N. R. Gaiman, Gaiman, Neil Richard MacKinnon, Neil Richard Gaiman (wd:Q210059): English writer (born 1960), science fiction writer, television writer, film director, film producer, comics writer, screenwriter, journalist, beekeeper, novelist, blogger, writer, actor, poet

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

[Assistant] The similar examples suggest that the property "place of birth" (wdt:P19) is used to indicate where a person grew up or was born. To answer the question "where did Madonna grow up?" I will first search for the entity "Madonna" in Wikidata to get her identifier. Then I will query the place of birth for that entity.

[Tool]
Top 10 entity alternatives:
1. Madonna, also known as Madonna Ciccone, Madonna Louise Veronica Ciccone, Madonna Louise Ciccone, Madonna L. Ciccone (wd:Q1744): American singer, songwriter, and actress (born 1958), songwriter, singer, actor
2. Mary, also known as Mother of God, Mother of Jesus, Notre Dame, Our Lady, Queen of the Universe (wd:Q345): mother of Jesus
3. Madonna, also known as Madonna: The First Album (wd:Q177943): 1983 self-titled debut studio album by Madonna
4. Madonna (wd:Q1989780): painting composition by Edvard Munch, in different versions
5. Madonna, also known as Madonna in art, The Madonna in art, Virgin Mary in art (wd:Q926743): artistic representation of Mary, either alone or with her child Jesus
6. Madonna (wd:Q19794647): 2015 South Korean film directed by Shin Su-won
7. Madonna (wd:Q1147459): album by …And You Will Know Us by the Trail of Dead
8. Madonna (wd:Q486604): 2010 EP by Secret
9. Madonna, also known as Madonna, MD, Madonna, Maryland (wd:Q6728358): unincorporated community in Harford County, Maryland
10. Virgin and Child with an Angel (Madonna del Latte), also known as Madonna, Madonna with child and John the Baptist (wd:Q3842618): painting by Antonio da Correggio from 1520

[Assistant] The entity for Madonna the American singer is wd:Q1744. Now I will query the place of birth (wdt:P19) for this entity to find out where Madonna grew up.

[Tool]
Got 1 row and 2 columns:
| placeOfBirth          | placeOfBirthLabel |
| --------------------- | ----------------- |
| Bay City (wd:Q746820) | Bay City (en)     |

[Assistant] Madonna grew up in Bay City. Here is the final SPARQL query and the answer.

[Tool] Stopped generation process

[User]
Feedback (status=retry):
The question asks where Madonna grew up, but the SPARQL query retrieves her place of birth (wdt:P19). Place of birth is not necessarily the same as where someone grew up. To answer where Madonna grew up, the query should look for a property related to the place of upbringing or childhood residence, such as 'residence during childhood' or 'hometown' if available. Since Wikidata does not have a direct property for 'grew up in', a better approach might be to check for statements about her childhood residence or places associated with her early life. The current answer 'Madonna grew up in Bay City' is incorrect based on the query results, which only confirm her birthplace. Please revise the query to find the place where Madonna grew up, or clarify if such data is not available.

[Assistant] Thank you for the feedback. I understand that "place of birth" (wdt:P19) is not necessarily the same as "where someone grew up." I will now search for properties related to Madonna's childhood residence, upbringing, or hometown to find a more accurate answer. I will first search for properties of Madonna (wd:Q1744) that might be related to "grew up" or "childhood residence."

[Tool]
Top 10 property alternatives:
1. number of children, also known as children, children (number), how many children, issue, kids (wd:P1971 as wdt/p): number of children of the person, animal, or character
2. child, also known as has son, kids, mother of, kid, issue (wd:P40 as wdt/p): subject has object as child. Do not use for stepchildren—use "relative" (P1038), qualified with "type of kinship" (P1039), significant person, relative
3. mother, also known as mom, is child of, mommy, mum, mummy (wd:P25 as wdt/p): female parent of the subject. For stepmother, use "stepparent" (P3448), parent
4. father, also known as son of, child of, parent, is son of, is daughter of (wd:P22 as wdt/p): male parent of the subject. For stepfather, use "stepparent" (P3448), parent
5. relative, also known as relatives, grandparent, relation, non-binary parent, niece (wd:P1038 as wdt/p): family member (qualify with "kinship to subject", P1039; for direct family member please use specific property), significant person
6. sibling, also known as is sister of, is the brother of, is the sibling of, is the sister of, sib (wd:P3373 as wdt/p): the subject and the object have at least one common parent (brot...law, etc.) and step-siblings (step-brothers, step-sisters, etc.), relative
7. date of birth, also known as year of birth, birthdate, DOB, born on, born (wd:P569 as wdt/p): date on which the subject was born, inception
8. educated at, also known as graduated from, graduate of, place of education, school attended, schooled at (wd:P69 as wdt/p): educational institution attended by subject, affiliation
9. place of birth, also known as POB, location of birth, location born, born in, birthplace (wd:P19 as wdt/p): most specific known birth location of a person, animal or fictional character, location
10. sexual orientation, also known as sexuality (wd:P91 as wdt/p): the sexual orientation of the person relative to their declared ...r it has been widely agreed upon by historians after their death

No other items found

[Assistant] There are no direct properties related to childhood residence or where Madonna grew up in the property search for Madonna. I will now try a broader search for properties related to "grew up" or "upbringing" for Madonna to see if there is any relevant information.

[Tool]
Top 10 property alternatives:
1. place of birth, also known as POB, location of birth, location born, born in, birthplace (wd:P19 as wdt/p): most specific known birth location of a person, animal or fictional character, location
2. date of birth, also known as year of birth, birthdate, DOB, born on, born (wd:P569 as wdt/p): date on which the subject was born, inception
3. birth name, also known as née, name at birth, name before marriage, ne, né (wd:P1477 as wdt/p): full name of a person at birth, if different from their current, generally used name, name
4. educated at, also known as graduated from, graduate of, place of education, school attended, schooled at (wd:P69 as wdt/p): educational institution attended by subject, affiliation
5. child, also known as has son, kids, mother of, kid, issue (wd:P40 as wdt/p): subject has object as child. Do not use for stepchildren—use "relative" (P1038), qualified with "type of kinship" (P1039), significant person, relative
6. studied in, also known as is studied by, studied by, science, that studies, researched in, researched by (wd:P2579 as wdt/p): subject is studied by this science or domain, field of work
7. notable work, also known as artwork, wrote, writer of, works, work (wd:P800 as wdt/p): notable scientific, artistic or literary work, or other work of significance among subject's works
8. significant event, also known as significant occurrence, significant incident, significant achievment, sign. event, outcome (wd:P793 as wdt/p): significant or notable events associated with the subject
9. work period (start), also known as start working, flourished (start), start time for work, start date of activity, fl. (start) (wd:P2031 as wdt/p): start of period during which a person or group flourished (fl. = "floruit") in their professional activity, start time, floruit
10. mother, also known as mom, is child of, mommy, mum, mummy (wd:P25 as wdt/p): female parent of the subject. For stepmother, use "stepparent" (P3448), parent

No other items found

[Assistant]
There are no direct properties related to "grew up" or "upbringing" for Madonna in Wikidata. Since Wikidata does not have a specific property for the place where someone grew up, and the place of birth is not necessarily the same, it seems that this information might not be explicitly available in Wikidata for Madonna.

I will now check if there are any statements or qualifiers related to early life or childhood residence for Madonna in Wikidata. I will list all properties and values for Madonna to see if any relevant information is present.

[Tool]
Got 2,173 rows and 3 columns, showing the first 10 rows below:
| subject            | property                         | object                                                                                |
| ------------------ | -------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------- |
| Madonna (wd:Q1744) | instance of (wdt:P31)            | human (wd:Q5)                                                                                |
| Madonna (wd:Q1744) | occupation (wdt:P106)            | actor (wd:Q33999)                                                                                |
| Madonna (wd:Q1744) | sex or gender (wdt:P21)          | female (wd:Q6581072)                                                                                |
| Madonna (wd:Q1744) | given name (wdt:P735)            | Louise (wd:Q3215140)                                                                                |
| Madonna (wd:Q1744) | date of birth (wdt:P569)         | 1958-08-16T00:00:00Z (xsd:dateTime)                                                                                |
| Madonna (wd:Q1744) | Commons category (wdt:P373)      | Madonna (entertainer)                                                                                |
| Madonna (wd:Q1744) | image (wdt:P18)                  | <http://commons.wikimedia.org/wiki/Special:FilePath/Madonna%20Rebel%20Heart%20Tour%202015%20-%20Stockholm%20%2823051472299%29%20%28cropped%29.jpg> |
| Madonna (wd:Q1744) | country of citizenship (wdt:P27) | United States (wd:Q30)                                                                                |
| Madonna (wd:Q1744) | family name (wdt:P734)           | Ciccone (wd:Q20830931)                                                                                |
| Madonna (wd:Q1744) | place of birth (wdt:P19)         | Bay City (wd:Q746820)                                                                                |
| ...                | ...                              | ...                                                                                |

[Assistant]
The list of properties for Madonna does not show any direct property related to where she grew up or her childhood residence. Since Wikidata does not have explicit data for where Madonna grew up, I conclude that this information is not available in the knowledge graph.

I will now provide a final answer stating that the information about where Madonna grew up is not explicitly available in Wikidata.

[Tool] Stopped generation process

[User]
Feedback (status=retry):
The system's approach to find where Madonna grew up by listing arbitrary properties of the entity wd:Q1744 is not effective. The query returns only descriptions in various languages, which do not answer the question. To answer where Madonna grew up, the query should specifically look for properties related to place of upbringing or childhood residence. Common properties to check include 'place of birth' (P19) or 'residence' (P551), but 'place of birth' is not necessarily where she grew up. Another approach is to check for 'educated at' (P69) or 'hometown' if available. Since Wikidata may not have a direct property for 'grew up in', a good approximation is to check 'place of birth' and 'residence' properties. The current query should be replaced with a targeted query that tries to find these properties and their values for Madonna. Also, the query should return the IRIs of the places, not just descriptions. Therefore, I recommend retrying with a refined query focusing on relevant properties to find where Madonna grew up.

[Assistant] Thank you for the feedback. I will refine the approach by specifically querying properties that might indicate where Madonna grew up or spent her childhood. These properties include place of birth (wdt:P19), residence (wdt:P551), and educated at (wdt:P69) as a proxy for places she spent significant time growing up. I will query these properties for Madonna (wd:Q1744) and return the IRIs and labels of the places.

[Tool]
Got 3 rows and 4 columns:
| property                 | propertyLabel  | place                                                                 | placeLabel                                                   |
| ------------------------ | -------------- | --------------------------------------------------------------------- | ------------------------------------------------------------ |
| place of birth (wdt:P19) | place of birth | Bay City (wd:Q746820)                                                 | Bay City (en)                                                |
| educated at (wdt:P69)    | educated at    | Rochester Adams High School (wd:Q7353940)                             | Rochester Adams High School (en)                             |
| educated at (wdt:P69)    | educated at    | University of Michigan School of Music, Theatre & Dance (wd:Q7895775) | University of Michigan School of Music, Theatre & Dance (en) |

[Assistant]
Madonna's place of birth is Bay City (wd:Q746820). She was educated at Rochester Adams High School (wd:Q7353940) and University of Michigan School of Music, Theatre & Dance (wd:Q7895775). Since there is no direct property for "grew up in," the place where she was educated can be a good proxy for where she grew up.

Here is the refined SPARQL query and the answer.

[Tool] Stopped generation process


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

Got 1 row and 2 columns:
| formOfGovernment    | formOfGovernmentLabel |
| ------------------- | --------------------- |
| 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

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] From the similar examples, the property "basic form of government" (wdt:P122) is used to find the form of government of a country. The entity for the Philippines is likely wd:Q928. I will now write a SPARQL query to get the form of government of the Philippines using this property.

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

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the form of government for the Philippines (wd:Q928) using the property wdt:P122. The query returns the identifier and the English label for the form of government, which is 'republic'. The answer provided is accurate and complete based on the query result. The query follows best practices by including an optional label retrieval with language filtering and returns the actual identifier as required. No further refinement is necessary.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT DISTINCT ?movie ?movieLabel WHERE {
  ?movie wdt:P57 wd:Q103646 ; wdt:P31 / wdt:P279 * wd:Q11424 .
  OPTIONAL {
    ?movie rdfs:label ?movieLabel FILTER ( LANG( ?movieLabel ) = "en" )
  }
}
LIMIT 50

Got 39 rows and 2 columns, showing the first 5 and last 5 rows below:
| movie                              | movieLabel               |
| ---------------------------------- | ------------------------ |
| Thirteen Lives (wd:Q105962844)     | Thirteen Lives (en)      |
| Apollo 13 (wd:Q106428)             | Apollo 13 (en)           |
| Cocoon (wd:Q1105463)               | Cocoon (en)              |
| Splash (wd:Q1127184)               | Splash (en)              |
| Parenthood (wd:Q1137831)           | Parenthood (en)          |
| ...                                | ...                      |
| Frost/Nixon (wd:Q691672)           | Frost/Nixon (en)         |
| Ransom (wd:Q752362)                | Ransom (en)              |
| Far and Away (wd:Q839341)          | Far and Away (en)        |
| Rebuilding Paradise (wd:Q96314873) | Rebuilding Paradise (en) |
| Night Shift (wd:Q997228)           | Night Shift (en)         |

Ron Howard directed the following movies: Thirteen Lives, Apollo 13, Cocoon, Splash, Parenthood, Frost/Nixon, Ransom, Far and Away, Rebuilding Paradise, Night Shift, among others.

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

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

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

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

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

[User] what 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] From the examples, we see that Ron Howard is identified as wd:Q103646 and the property for director is wdt:P57. Also, movies are instances or subclasses of wd:Q11424 (film). We can use this information to construct a query that finds movies directed by Ron Howard. I will now write a SPARQL query to get movies directed by Ron Howard.

[Tool]
Got 39 rows and 2 columns, showing the first 5 and last 5 rows below:
| movie                              | movieLabel               |
| ---------------------------------- | ------------------------ |
| Thirteen Lives (wd:Q105962844)     | Thirteen Lives (en)      |
| Apollo 13 (wd:Q106428)             | Apollo 13 (en)           |
| Cocoon (wd:Q1105463)               | Cocoon (en)              |
| Splash (wd:Q1127184)               | Splash (en)              |
| Parenthood (wd:Q1137831)           | Parenthood (en)          |
| ...                                | ...                      |
| Frost/Nixon (wd:Q691672)           | Frost/Nixon (en)         |
| Ransom (wd:Q752362)                | Ransom (en)              |
| Far and Away (wd:Q839341)          | Far and Away (en)        |
| Rebuilding Paradise (wd:Q96314873) | Rebuilding Paradise (en) |
| Night Shift (wd:Q997228)           | Night Shift (en)         |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves movies directed by Ron Howard by using the property wdt:P57 with the value wd:Q103646 (Ron Howard) and filtering for instances of movies (wd:Q11424). The query also optionally retrieves English labels for the movies, which is helpful for readability. The answer lists several movies that match the query results, and the execution result shows a reasonable number of movies directed by Ron Howard. The query and answer are appropriate and complete for the user's question.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT DISTINCT ?school ?schoolLabel WHERE {
  wd:Q19526 wdt:P69 ?school .
  ?school wdt:P31 / wdt:P279 * wd:Q9826 .
  OPTIONAL {
    ?school rdfs:label ?schoolLabel FILTER ( LANG( ?schoolLabel ) = "en" )
  }
}

Maya Angelou attended 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

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]
From the similar examples, it is clear that the property "educated at" (wdt:P69) is used to indicate the educational institutions a person attended. Also, to specifically find high schools, we can filter the results by checking if the institution is an instance of or subclass of "high school" (wd:Q9826).

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

[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 entity for Maya Angelou is wd:Q19526. Now I will query the educational institutions she attended using the property "educated at" (wdt:P69) and filter for high schools (wd:Q9826).

[Tool]
Got 1 row and 2 columns:
| school                                      | schoolLabel                        |
| ------------------------------------------- | ---------------------------------- |
| George Washington High School (wd:Q5545977) | George Washington High School (en) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the high school Maya Angelou attended by using the property 'educated at' (wdt:P69) and filtering for instances of high schools (wd:Q9826). The query returns the expected result, George Washington High School, with its identifier and English label. The answer is accurate and complete according to the data from Wikidata. No further refinement is necessary.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT DISTINCT ?college ?collegeLabel WHERE {
  wd:Q89925 wdt:P69 ?college .
  ?college wdt:P31 / wdt:P279 * wd:Q38723 .
  OPTIONAL {
    ?college rdfs:label ?collegeLabel FILTER ( LANG( ?collegeLabel ) = "en" )
  }
}

The Otto Frank entity related to a German physiologist (wd:Q89925) does not have any college or higher education institution listed in Wikidata. The Otto Frank related to Anne Frank's father could not be clearly identified in Wikidata, so I cannot provide the college he attended.

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

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

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

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

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

[User] where 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 need to find the entity for Otto Frank and then query where he went to college using the property wdt:P69.

[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 related to the famous Otto Frank (father of Anne Frank) is not clearly identified here. However, the Otto Frank who is a German physiologist (wd:Q89925) might not be the one we want. I will try to find Otto Frank related to Anne Frank to be more specific.

[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 entity Otto Frank (wd:Q89925) is a German physiologist and does not seem to be the Otto Frank related to Anne Frank. The Otto Frank we are interested in is Anne Frank's father. I will try to find Otto Frank by searching for "Otto Frank father of Anne Frank" to get a more precise entity.

[Tool]
Top 10 entity alternatives:
1. Diary of Anne Frank, also known as The Secret Annex, The Diary of a Young Girl, The Diary of Ann Frank, The Diary of Anne Frank, Diary of a Young Girl (wd:Q6911): famous diary of a 13-year old Dutch Jewish girl hiding from the Nazis to escape the Holocaust
2. The Diary of Anne Frank, also known as Diary of Anne Frank (wd:Q707986): 1959 film directed by George Stevens
3. Mi Ricordo Anna Frank, also known as Mi ricordo Anna Frank, Memories of Anne Frank (wd:Q3855957): 2010 Italian television film about Anne Frank, directed by Alberto Negrin
4. The Diary of Anne Frank, also known as Diary of Anne Frank (wd:Q821121): 1980 film directed by Boris Sagal
5. betrayal of Anne Frank (wd:Q3257209)
6. Statue of Anne Frank, also known as Anne Frank (wd:Q27918477): public artwork by Pieter d'Hont in Utrecht, the Netherlands
7. statue of Anne Frank (wd:Q28873418): statue of Anne Frank on the Westermarkt in Amsterdam, Netherlands
8. sculpture of Anne Frank (wd:Q27929393): sculpture of Anne Frank at Merwedeplein, Amsterdam, Netherlands
9. The Diary of Anne Frank, also known as Diary of Anne Frank (wd:Q1170501): 1987 British television miniseries directed by Gareth Davies
10. Bust of Anne Frank, also known as Anne Frank (wd:Q41688543): sculpture by Doreen Kern

[Assistant] I did not find a direct entity for Otto Frank as the father of Anne Frank in the search results. I will try to find Otto Frank by searching for "Otto Frank Anne Frank father" to see if I can get a more relevant 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 still returns the German physiologist Otto Frank (wd:Q89925) as the closest match. Since the Otto Frank related to Anne Frank might not have a distinct Wikidata entity or is not easily found by search, I will try to query the property "educated at" (wdt:P69) for this Otto Frank (wd:Q89925) to see if there is any college information available.

[Tool] Got no rows and 2 columns

[Assistant] The entity Otto Frank (wd:Q89925) does not have any college or higher education institution listed under the property "educated at" (wdt:P69). Since I could not find a more relevant Otto Frank entity related to Anne Frank, and the searched entity does not have college information, I am unable to provide the college Otto Frank attended. I will now finalize my answer.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The system correctly identified that the Otto Frank entity it found (wd:Q89925) is a German physiologist and not Anne Frank's father. It also correctly noted that the Otto Frank related to Anne Frank's father could not be clearly identified in Wikidata, so it cannot provide the college he attended. The SPARQL query is appropriate for the identified entity, and the lack of results is consistent with the data available. Therefore, the answer is correct and complete given the current knowledge graph data.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT DISTINCT ?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

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 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" in Wikidata to get his identifier.

[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. Based on the examples, the property for education is "educated at" (wdt:P69). I will now query the educational institutions Jesse Owens attended using this property.

[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

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the educational institutions attended by Jesse Owens using the property wdt:P69. The query returns the identifiers and English labels of the institutions, which are Ohio State University, East Technical High School, and North Platte High School. The answer is accurate and complete based on the data retrieved from Wikidata. No further refinement is necessary.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT DISTINCT ?religion ?religionLabel WHERE {
  wd:Q252 wdt:P140 ?religion .
  OPTIONAL {
    ?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

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. Let's 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

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the religions practiced in Indonesia by using the property P140 (religion or worldview) for the entity Indonesia (wd:Q252). The query returns the expected religions: Catholicism, Protestantism, Islam, Buddhism, Hinduism, and Confucianism, along with their English labels. The query follows the rules by returning the identifiers and labels in an optional clause. The answer is complete and accurate based on the data from Wikidata.


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

Honduras is located at the coordinates POINT(-86.816667 14.633333) on the world map. It is situated in 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

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 coordinates of Honduras or the continent it is located in.

Step 1: Let's find the Wikidata 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 entity for the country Honduras is wd:Q783. Now, let's find the coordinates of Honduras using the property for coordinate location (wdt:P625).

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

[Assistant] Honduras is located at the coordinates POINT(-86.816667 14.633333) on the world map. To provide additional context, let's also find the continent where Honduras is located.

[Tool]
Got 1 row and 2 columns:
| continent              | continentLabel     |
| ---------------------- | ------------------ |
| North America (wd:Q49) | North America (en) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the coordinates and continent of Honduras from Wikidata. The answer provides the coordinates in a standard format and correctly identifies Honduras as being located in North America, which is accurate. The query follows best practices by including labels optionally and returns the actual identifiers. No further refinement is necessary.