PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT DISTINCT ?language WHERE {
  wd:Q225 wdt:P37 ?language .
}

Got 3 rows and 1 column:
| language            |
| ------------------- |
| Croatian (wd:Q6654) |
| Serbian (wd:Q9299)  |
| Bosnian (wd:Q9303)  |

The official languages of Bosnia and Herzegovina are Croatian, Serbian, and Bosnian.

[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 language do people from bosnia speak?

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

[Tool]
Example 1:
Question:
where is bosnia?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q225 wdt:P30 ?x .
}

Using entities:
Bosnia and Herzegovina, also known as Bosnia-Herzegovina, Bosnia & Herzegovina, Bosnia and Hercegovina, Bosnia, BIH (wd:Q225): country in Southeast Europe

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

Example 2:
Question:
what language do people speak in turkey?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q43 wdt:P37 ?x .
}

Using entities:
Turkey, also known as Republic of Turkey, Republic of Turkiye, Republic of Türkiye, TR, TUR (wd:Q43): country straddling Southeast Europe and West 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 do people from spain speak?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q29 wdt:P37 ?x .
}

Using entities:
Spain, also known as Kingdom of Spain (wd:Q29): country in southwestern Europe with territories in Africa

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 examples, it seems like we need to find the official language(s) of Bosnia and Herzegovina. Let's first identify the entity for Bosnia and Herzegovina.

[Tool]
Top 10 entity alternatives:
1. Bosnia and Herzegovina, also known as Bosnia-Herzegovina, Bosnia & Herzegovina, Bosnia and Hercegovina, Bosnia, BIH (wd:Q225): country in Southeast Europe
2. Constitution of Bosnia and Herzegovina, also known as Bosnia and Herzegovina (wd:Q1291601): The Constitution of Bosnia and Herzegovina
3. Bosnia and Herzegovina (wd:Q126844941): scholarly article
4. Bosnia and Herzegovina, also known as Star Trek Bosnia and Herzegovina (wd:Q99286256): the country of Bosnia and Herzegovina as depicted in Star Trek
5. Bosnia and Herzegovina (wd:L495446-S1)
6. Bosnia and Herzegovina (wd:L254133-F1)
7. Bosnia and Herzegovina (wd:L254133)
8. Bosnia and Herzegovina (wd:L655450-S1)
9. flag of Bosnia and Herzegovina, also known as Bosnia and Herzegovina flag, Bosnian flag (wd:Q162033): national flag of Bosnia and Herzegovina
10. Prijedor, also known as Prijedor (Bosnia and Herzegovina) (wd:Q323986): city in Bosnia and Herzegovina

[Assistant] The correct entity for Bosnia and Herzegovina is `wd:Q225`. Now let's look for the property that represents the official language or languages spoken in a country.

[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 `wd:P37` (official language) seems to be the most appropriate for our query. Let's construct a SPARQL query to find the official language(s) of Bosnia and Herzegovina.

```sparql
SELECT DISTINCT ?language WHERE {
  wd:Q225 wdt:P37 ?language .
}
```

Now, let's execute this query.

[Tool]
Got 3 rows and 1 column:
| language            |
| ------------------- |
| Croatian (wd:Q6654) |
| Serbian (wd:Q9299)  |
| Bosnian (wd:Q9303)  |

[Assistant]
The official languages of Bosnia and Herzegovina are Croatian, Serbian, and Bosnian.

Here is the final SPARQL query and answer:

```sparql
SELECT DISTINCT ?language WHERE {
  wd:Q225 wdt:P37 ?language .
}
```

Answer: The official languages of Bosnia and Herzegovina are Croatian, Serbian, and Bosnian.

[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 ?label WHERE {
  wd:Q403 wdt:P37 ?language .
  OPTIONAL {
    ?language rdfs:label ?label FILTER ( LANG( ?label ) = 'en' )
  }
}

The Serbian language is called Serbian.

[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 serbian language called?

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

[Tool]
Example 1:
Question:
what is the language called in turkey?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q43 wdt:P37 ?x .
}

Using entities:
Turkey, also known as Republic of Turkey, Republic of Turkiye, Republic of Türkiye, TR, TUR (wd:Q43): country straddling Southeast Europe and West 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 does fiji?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q712 wdt:P37 ?x .
}

Using entities:
Fiji, also known as FIJ, Fijī, Fijī Gaṇarājya, fj, Matanitu Tugalala o Viti (wd:Q712): island sovereign state in 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 language do russian people speak?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q159 wdt:P37 ?x .
}

Using entities:
Russia, also known as Russian Federation, RUS, RU, RF, ISO 3166-1:RU (wd:Q159): country in Eastern Europe and Northern 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 examples, it seems like we need to find the official language of Serbia. Let's first identify the entity for Serbia.

[Tool]
Top 10 entity alternatives:
1. Serbia, also known as RS, Srbija, SRB, Republika Srbija, Republic of Serbia (wd:Q403): country in Southeast Europe
2. Federal Republic of Yugoslavia, also known as FR Yugoslavia, Yugoslavia, Serbia, FRY (wd:Q838261): former Balkan republic (1992–2003)
3. Principality of Serbia, also known as Principality of Serbia (early medieval), Serbia (wd:Q13107370): medieval principality in Eastern Europe
4. Koča's Frontier, also known as Habsburg-occupied Serbia, Koča's frontier, Koča's uprising Serbia, Serbia (wd:Q2617606): Serbian rebels in the Sanjak of Smederevo (Ottoman Empire), during the Austro-Turkish War of 1788–1791
5. Sirmium, also known as Serbia (wd:Q1278936): Byzantine administrative unit (theme)
6. Serbia Prison, also known as Serbia (wd:Q3676018): in Warsaw
7. Serbia (wd:Q37438143): family name
8. 2024 UEFA European Championship Match 18, Slovenia - Serbia, also known as 2024 UEFA European Championship Match 18, Serbia (wd:Q123597099): association football match of UEFA Euro 2024
9. Serbia, also known as Star Trek Serbia (wd:Q99292310): the country of Serbia as depicted in Star Trek
10. Serbia (wd:Q55884152)

[Assistant] The correct entity for Serbia is `wd:Q403`. Now let's find out what the official language of Serbia is using the property `wdt:P37`.

[Tool]
Got 1 row and 1 column:
| language           |
| ------------------ |
| Serbian (wd:Q9299) |

[Assistant] The official language of Serbia is Serbian. To provide a complete answer, I'll include the label of the language in the final SPARQL query.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?instrument WHERE {
  wd:Q191499 wdt:P1303 ?instrument .
}

Scott Joplin played the cornet, piano, guitar, and violin.

[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 did scott joplin play?

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

[Tool]
Example 1:
Question:
what type of music is scott joplin?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q191499 wdt:P136 ?x .
}

Using entities:
Scott Joplin, also known as The king of Ragtime (wd:Q191499): American composer, musician, and pianist, jazz musician, banjoist, composer, pianist

Using properties:
genre, also known as genre of music, type of music, type of film, music genre, literary genre (wd:P136 as wdt): creative work's genre or an artist's field of work (P101). Use main subject (P921) to relate creative works to their topic

Example 2:
Question:
what type of music was scott joplin noted for?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q191499 wdt:P136 ?x .
}

Using entities:
Scott Joplin, also known as The king of Ragtime (wd:Q191499): American composer, musician, and pianist, jazz musician, banjoist, composer, pianist

Using properties:
genre, also known as genre of music, type of music, type of film, music genre, literary genre (wd:P136 as wdt): creative work's genre or an artist's field of work (P101). Use main subject (P921) to relate creative works to their topic

Example 3:
Question:
what guitar did clapton play?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x wdt:P1535 wd:Q48187 ; wdt:P31 / wdt:P279 * wd:Q6607 .
}

Using entities:
Eric Clapton, also known as Slowhand, Eric Patrick Clapton (wd:Q48187): singer-songwriter, British musician, recording artist, jazz musician, guitarist, composer, singer
guitar (wd:Q6607): fretted string instrument

Using properties:
used by, also known as armiger, user, played by, of (wd:P1535 as wdt): item or concept that makes use of the subject (use sub-properties when appropriate)
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 out what Scott Joplin played. We can use the entity for Scott Joplin and look for properties related to instruments he played. Let's first confirm the entity for Scott Joplin.

[Tool]
Top 10 entity alternatives:
1. Scott Joplin, also known as The king of Ragtime (wd:Q191499): American composer, musician, and pianist, jazz musician, banjoist, composer, pianist
2. Scott Joplin (wd:Q12127336): 1977 film by Jeremy Kagan
3. Scott Joplin (wd:Q28730081): painting by Ellen Banks
4. Scott Joplinlaan (wd:Q19513256): street in Eindhoven, the Netherlands
5. Scott Joplinrode (wd:Q19513257): street in Zoetermeer, the Netherlands
6. Scott Joplin: Piano Rags (wd:Q7436590): album by Joshua Rifkin
7. Scott Joplin's foot (wd:Q30538526): scientific article published on July 1, 1998
8. Scott Joplin: Questions Remain (wd:Q113214829): scientific article published on 18 April 2006
9. Scott Joplin: Complete Piano Works, also known as The Collected Works of Scott Joplin (wd:Q28156183): book by Scott Joplin
10. Scott Joplin’s New Rag (wd:Q29003610): ragtime composition for piano by Scott Joplin

[Assistant] The correct entity for Scott Joplin is `wd:Q191499`. Now let's find the property that indicates what he played. We can search for properties related to playing instruments.

[Tool]
Top 10 property alternatives:
1. instrument, also known as uses this instrument, teaches instrument, instruments, plays this instrument, plays instrument (wd:P1303 as pr/psv/prv/wdtn/pqv/pq/pqn/wdt/psn/ps/prn/p): musical instrument that a person plays or teaches or used in a music occupation, uses
2. uses, also known as uses trope, used, using, wielded, wields (wd:P2283 as pr/psv/prv/wdtn/pqv/pq/pqn/wdt/psn/ps/prn/p): item or concept used by the subject or in the operation (see also instrument [P1303] and armament [P520])
3. instrumentation, also known as scoring, scored for, orchestration, instruments employed, orchestrated for (wd:P870 as pr/psv/prv/wdtn/pqv/pq/pqn/wdt/psn/ps/prn/p): combination of musical instruments employed in a composition or accompanying a (folk) dance
4. performer, also known as actor, sung by, singer, recording by, recorded by (wd:P175 as pr/psv/prv/wdtn/pqv/pq/pqn/wdt/psn/ps/prn/p): actor, musician, band or other performer associated with this role or musical work, contributor to the creative work or subject
5. sport, also known as play, plays, sport played, sports (wd:P641 as pr/psv/prv/wdtn/pqv/pq/pqn/wdt/psn/ps/prn/p): sport that the subject participates or participated in or is associated with
6. field of this occupation, also known as practice, works in, profession's field, practices, field of this profession (wd:P425 as pr/psv/prv/wdtn/pqv/pq/pqn/wdt/psn/ps/prn/p): field corresponding to this occupation or profession (use only f...fessions - for people use Property:P101, for companies use P452)
7. music created for, also known as music for, music for work, music made for, music made for work, music written for (wd:P9899 as pr/psv/prv/wdtn/pqv/pq/pqn/wdt/psn/ps/prn/p): a work, event, etc. for which a musical composition was created ... was written; a film for which motion picture music was created), created for
8. has melody, also known as uses tune, to the tune of, uses melody, TTTO, has tune (wd:P1625 as pr/psv/prv/wdtn/pqv/pq/pqn/wdt/psn/ps/prn/p): this work has the melody of the following work, references work, tradition or theory
9. produced sound, also known as call, makes call, makes sound, sound, sound emitted (wd:P4733 as pr/psv/prv/wdtn/pqv/pq/pqn/wdt/psn/ps/prn/p): item for the sound generated by the subject, for instance the cry of an animal
10. setlist, also known as set list, works performed, songs performed, performances, performance list (wd:P9793 as pr/psv/prv/wdtn/pqv/pq/pqn/wdt/psn/ps/prn/p): performances of songs or other music at an event; concert program, presented works

[Assistant]
The property `wd:P1303` (instrument) seems to be the most relevant for indicating what Scott Joplin played. Let's use this property in a SPARQL query to find out what instruments Scott Joplin played.

```sparql
SELECT ?instrument WHERE {
  wd:Q191499 wdt:P1303 ?instrument .
}
```

Let's execute this query.

[Tool]
Got 4 rows and 1 column:
| instrument          |
| ------------------- |
| cornet (wd:Q202027) |
| piano (wd:Q5994)    |
| guitar (wd:Q6607)   |
| violin (wd:Q8355)   |

[Assistant]
The SPARQL query returned the instruments that Scott Joplin played. According to the results, Scott Joplin played the cornet, piano, guitar, and violin.

Here is the final SPARQL query and the answer:

```sparql
SELECT ?instrument WHERE {
  wd:Q191499 wdt:P1303 ?instrument .
}
```

Answer: Scott Joplin played the cornet, piano, guitar, and violin.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT DISTINCT ?job WHERE {
  wd:Q81960 wdt:P106 ?job .
}

Robert Burns had the jobs of farmer, musicologist, writer, poet, and songwriter.

[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 jobs did robert burns have?

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

[Tool]
Example 1:
Question:
what books did robert burns wrote?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x wdt:P31 / wdt:P279 * wd:Q47461344 ; wdt:P50 wd:Q81960 .
}

Using entities:
written work, also known as creative written work, written delivery (wd:Q47461344): any work expressed in writing, such as inscriptions, manuscripts, documents or maps
Robert Burns, also known as Robbie Burns, Robden of Solway Firth, Scotland's favorite son, The Bard, Rabbie Burns (wd:Q81960): Scottish poet and lyricist (1759–1796), musicologist, songwriter, farmer, writer, poet

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)
author, also known as writer, written by, poet, playwright, maker (wd:P50 as wdt): main creator(s) of a written work (use on works, not humans); us...hor name string) when Wikidata item is unknown or does not exist, creator

Example 2:
Question:
what jobs did ben franklin do?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q34969 wdt:P106 ?x .
}

Using entities:
Benjamin Franklin, also known as The First American, Silence Dogood, Poor Richard, Ben Franklin, Franklin (wd:Q34969): American polymath and statesman (1706–1790), politician, polymath, diplomat, writer

Using properties:
occupation, also known as job, work, vocation, profession, employment (wd:P106 as wdt): occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)

Example 3:
Question:
what other jobs did benjamin franklin have?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q34969 wdt:P106 ?x .
}

Using entities:
Benjamin Franklin, also known as The First American, Silence Dogood, Poor Richard, Ben Franklin, Franklin (wd:Q34969): American polymath and statesman (1706–1790), politician, polymath, diplomat, writer

Using properties:
occupation, also known as job, work, vocation, profession, employment (wd:P106 as wdt): occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)

[Assistant] From the examples, we can see that the property `wdt:P106` is used to represent occupations or jobs. We need to identify Robert Burns first.

[Tool]
Top 10 entity alternatives:
1. Robert Burns, also known as Robbie Burns, Robden of Solway Firth, Scotland's favorite son, The Bard, Rabbie Burns (wd:Q81960): Scottish poet and lyricist (1759–1796), musicologist, songwriter, farmer, writer, poet
2. Robert Hunter, also known as Robert C. Christie Hunter, Robert Burns (wd:Q1375663): American lyricist, musician, singer-songwriter, translator, and poet, songwriter, translator, guitarist, lyricist, musician, writer, singer, poet
3. Bob Burns, also known as Robin Burn, Robin William Burn, Robert Burns, Robbie Burn (wd:Q887831): American musical comedian (1890–1956), radio personality, businessperson, film actor, comedian, musician
4. Robert Burns, also known as Robert Clayton Burns (wd:Q7342516): British artist (1869-1941), visual artist, art educator, designer, painter
5. Robert Burns (wd:Q27824730): Australian cyclist, sport cyclist
6. Robert Burns (wd:Q2156654): American politician (1792-1866), politician
7. Robert Burns, also known as William Robert Burns (wd:Q15997904): American attorney and politician in Oklahoma (1874-1950), politician, lawyer
8. Robert Burns (wd:Q3434685): Canadian politician (1936–2014), trade unionist, politician, lawyer, judge
9. Bob Burns III, also known as Bob Burns, Robert Burns, Kogar (wd:Q4931984): American film historian and actor, property designer, film historian, film actor
10. Robert H. Burns, also known as Robert Burns (wd:Q16066723): American politician in Wisconsin (1870-19__), politician

[Assistant]
The correct entity for Robert Burns is `wd:Q81960`. Now let's construct a SPARQL query to find his jobs using the property `wdt:P106`.

Here is the initial SPARQL query:

```sparql
SELECT DISTINCT ?job WHERE {
  wd:Q81960 wdt:P106 ?job .
}
```

I will now execute this query to get the results.

[Tool]
Got 5 rows and 1 column:
| job                         |
| --------------------------- |
| farmer (wd:Q131512)         |
| musicologist (wd:Q14915627) |
| writer (wd:Q36180)          |
| poet (wd:Q49757)            |
| songwriter (wd:Q753110)     |

[Assistant]
The SPARQL query has successfully returned the jobs of Robert Burns. Here is the final answer:

Robert Burns had the following jobs:
- Farmer
- Musicologist
- Writer
- Poet
- Songwriter

Final SPARQL query:
```sparql
SELECT DISTINCT ?job WHERE {
  wd:Q81960 wdt:P106 ?job .
}
```

Answer:
Robert Burns had the jobs of farmer, musicologist, writer, poet, and songwriter.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?zipCode WHERE {
  wd:Q5083 wdt:P281 ?zipCode .
}

Got 1 row and 1 column:
| zipCode |
| ------- |
| 98101   |

The zip code for Seattle, Washington, according to the available data in Wikidata, is 98101.

[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 the zip code for seattle washington?

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

[Tool]
Example 1:
Question:
what is the zip code for minneapolis?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q36091 wdt:P281 ?x .
}

Using entities:
Minneapolis, also known as Minneapolis, Minnesota, Minneapolis, MN (wd:Q36091): city in and county seat of Hennepin County, Minnesota, United States

Using properties:
postal code, also known as pincode, PIN Code, postal index number, post code, postcode (wd:P281 as wdt): identifier assigned by postal authorities for the subject area or building

Example 2:
Question:
what is zip code for chicago illinois?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q1297 wdt:P281 ?x .
}

Using entities:
Chicago, also known as The Second City, The Queen of the West, The Windy City, City of Broad Shoulders, City by the Lake (wd:Q1297): city and county seat of Cook County, Illinois, United States of America

Using properties:
postal code, also known as pincode, PIN Code, postal index number, post code, postcode (wd:P281 as wdt): identifier assigned by postal authorities for the subject area or building

Example 3:
Question:
what zip code is chicago il?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q1297 wdt:P281 ?x .
}

Using entities:
Chicago, also known as The Second City, The Queen of the West, The Windy City, City of Broad Shoulders, City by the Lake (wd:Q1297): city and county seat of Cook County, Illinois, United States of America

Using properties:
postal code, also known as pincode, PIN Code, postal index number, post code, postcode (wd:P281 as wdt): identifier assigned by postal authorities for the subject area or building

[Assistant]
Based on the examples, we need to find the entity for Seattle, Washington and then use the property `postal code` (P281) to get the zip codes.

First, let's find the entity for Seattle, Washington.

[Tool]
Top 10 entity alternatives:
1. Seattle, also known as Seattle, WA, Seattle, Washington, Duwamps, New York Alki (wd:Q5083): city in and county seat of King County, State of Washington, United States
2. Seattle Washington Temple (wd:Q3844785): temple of the Church of Jesus Christ of Latter-day Saints in Bellevue, Washington
3. Washington Park, also known as Washington Park, Seattle (wd:Q7972093)
4. "Carole, Seattle, Washington" (wd:Q64144357): photograph in the National Gallery of Art (NGA 135163)
5. East Seattle, also known as East Seattle, WA, East Seattle, Washington (wd:Q122593560): populated place in King County, Washington, United States
6. Seattle, Washington Auditions (wd:Q114507485): episode of American Idol (S6 E2)
7. Seattleites, also known as Seattle, Washington, residents, Seattlites, Seattlers (wd:Q55779668): people from or residents of Seattle, Washington
8. Seattle Hill, also known as Seattle Hill, WA, Seattle Hill, Washington (wd:Q122540504): populated place in Snohomish County, Washington, United States
9. Seattle Heights, also known as Seattle Heights, WA, Seattle Heights, Washington (wd:Q122543838): neighborhood in Snohomish County, Washington, United States
10. University of Washington, also known as UW, washington.edu, UW-Seattle, U. of W., U of W (wd:Q219563): public research university in Seattle, Washington, United States

[Assistant]
The correct entity for Seattle, Washington is `wd:Q5083`.

Now, let's use the property `postal code` (P281) to get the zip codes for Seattle, Washington.

I'll construct the SPARQL query and execute it.

[Tool]
Got 1 row and 1 column:
| zipCode |
| ------- |
| 98101   |

[Assistant]
The SPARQL query returned a single zip code for Seattle, Washington. However, Seattle has multiple zip codes. Let's modify the query to ensure we get all the zip codes associated with Seattle.

I'll remove the `DISTINCT` keyword and see if that gives us more results.

[Tool]
Got 1 row and 1 column:
| zipCode |
| ------- |
| 98101   |

[Assistant]
It seems that even without the `DISTINCT` keyword, only one zip code is being returned. This suggests that the data in Wikidata might only list one zip code for Seattle, Washington.

However, to ensure we are not missing any other zip codes, let's check if there are any additional properties or qualifiers that might provide more zip codes.

I'll look for any additional properties or qualifiers related to the postal code for Seattle, Washington.

[Tool]
Got 1 row and 3 columns:
| subject            | property               | object |
| ------------------ | ---------------------- | ------ |
| Seattle (wd:Q5083) | postal code (wdt:P281) | 98101  |

[Assistant]
The list of triples confirms that only one zip code (98101) is directly associated with Seattle, Washington in Wikidata. This suggests that the data in Wikidata might be incomplete or limited to a single representative zip code.

Given this information, the best answer we can provide based on the available data is:

**The zip code for Seattle, Washington, according to the available data in Wikidata, is 98101.**

However, it's important to note that Seattle has multiple zip codes, and this result might not be comprehensive. For a more complete list, you might want to consult other sources such as the official postal service website.

Let's finalize the answer with the SPARQL query and the result.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?boyfriend WHERE {
  wd:Q575689 wdt:P451 ?boyfriend .
}

Kourtney Kardashian's boyfriends are Younes Bendjima and Scott Disick.

[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 kourtney kardashian boyfriends name?

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

[Tool]
Example 1:
Question:
what kourtney kardashian baby girls name?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q575689 wdt:P40 ?x .
}

Using entities:
Kourtney Kardashian, also known as Kourtney Kardashian Barker, Kourtney Mary Kardashian, Kourtney (wd:Q575689): American media personality, model and businesswoman (born 1979), media personality, fashion designer, television actor, businessperson, entrepreneur, socialite, celebrity, actor, model

Using properties:
child, also known as has son, kids, mother of, kid, issue (wd:P40 as wdt): subject has object as child. Do not use for stepchildren—use "relative" (P1038), qualified with "type of kinship" (P1039), significant person, relative

Example 2:
Question:
what kourtney kardashian name her daughter?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q575689 wdt:P40 ?x .
}

Using entities:
Kourtney Kardashian, also known as Kourtney Kardashian Barker, Kourtney Mary Kardashian, Kourtney (wd:Q575689): American media personality, model and businesswoman (born 1979), media personality, fashion designer, television actor, businessperson, entrepreneur, socialite, celebrity, actor, model

Using properties:
child, also known as has son, kids, mother of, kid, issue (wd:P40 as wdt): subject has object as child. Do not use for stepchildren—use "relative" (P1038), qualified with "type of kinship" (P1039), significant person, relative

Example 3:
Question:
what did kourtney kardashian go to college for?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q575689 p:P69 ?y .
  ?y pq:P812 ?x .
}

Using entities:
Kourtney Kardashian, also known as Kourtney Kardashian Barker, Kourtney Mary Kardashian, Kourtney (wd:Q575689): American media personality, model and businesswoman (born 1979), media personality, fashion designer, television actor, businessperson, entrepreneur, socialite, celebrity, actor, model

Using properties:
educated at, also known as graduated from, graduate of, place of education, school attended, schooled at (wd:P69 as p): educational institution attended by subject, affiliation
academic major, also known as academic subject, college major, field of study, major, studied (wd:P812 as pq): major someone studied at college/university

[Assistant] Based on the examples, we need to identify Kourtney Kardashian and then look for her relationships, specifically her boyfriends. Let's first confirm Kourtney Kardashian's entity.

[Tool]
Top 10 entity alternatives:
1. Kourtney Kardashian, also known as Kourtney Kardashian Barker, Kourtney Mary Kardashian, Kourtney (wd:Q575689): American media personality, model and businesswoman (born 1979), media personality, fashion designer, television actor, businessperson, entrepreneur, socialite, celebrity, actor, model
2. Kardashian (wd:Q56538884): family name
3. Kourtney (wd:Q101065644): unisex given name
4. Kanye West, also known as Ye, Kanye Omari West, Yeezy, Kanye Kardashian, Kanye (wd:Q15935): American rapper, record producer, singer and fashion designer (born 1977), fashion designer, record producer, businessperson, entrepreneur, songwriter, director, singer, rapper
5. Kim Kardashian, also known as Kim Kardashian West, Kim K, Kim K., Kimberly Noel Kardashian-West, Kim Kardashian-West (wd:Q186304): American media personality, businesswoman, model and actress (born 1980), erotic photography model, television producer, fashion designer, entrepreneur, voice actor, celebrity, socialite, blogger, actor, model
6. Khloé Kardashian, also known as Khloé Kardashian Odom, Khloé Kardashian-Odom, Khloe Kardashian Odom, Khloe Kardashian, Khloe Odom (wd:Q231270): American media personality,influencer, businesswoman (born 1984), radio personality, television actor, fashion designer, film producer, manufacturer, entrepreneur, film actor, socialite, celebrity, novelist, writer, actor, model
7. Kris Jenner, also known as Kristen Mary Jenner, Kristen Jenner, Kristen Mary Houghton, Kristen Mary "Kris" Jenner, Chris Jenner (wd:Q1138235): American media personality, socialite, and businesswoman, television presenter, television producer, flight attendant, celebrity, socialite, author, actor
8. Robert Kardashian, also known as Robert George Kardashian, Rob Kardashian, Robert G. Kardashian (wd:Q1816737): American attorney and businessman (1944–2003), entrepreneur, jurist, lawyer
9. Rob Kardashian, also known as Robert Arthur Kardashian (wd:Q26318): American television personality and businessman, television actor, businessperson, socialite, model
10. Kardashian-Jenner family, also known as Kardashian family, Kardashians (wd:Q95747857): American family prominent in entertainment, business, and fashion

[Assistant]
The correct entity for Kourtney Kardashian is `wd:Q575689`. Now, let's find the property that represents her relationships, particularly her boyfriends.

I will search for properties related to relationships for Kourtney Kardashian.

[Tool]
Top 10 property alternatives:
1. unmarried partner, also known as romantic partner, partner of, partners, posslq, relationship (wd:P451 as wdt/p): someone with whom the person is in a relationship without being married. Use "spouse" (P26) for married couples, significant person
2. spouse, also known as married partner, married to, marry, partner, spouses (wd:P26 as wdt/p): the subject has the object as their spouse (husband, wife, partn...etc.). Use "unmarried partner" (P451) for non-married companions, significant person, relative
3. 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
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. sex or gender, also known as gender or sex, sex, gender identity, gender expression, gender (wd:P21 as wdt/p): sex or gender identity of human or animal. For human: male, fema...m, female organism. Groups of same gender use subclass of (P279)
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. Instagram username, also known as IG username, www.instagram.com, urinsta, ufinsta, Insta ID (wd:P2003 as wdt/p): item's username on Instagram, website username or ID
8. stepparent, also known as step-parent, step parent, stepmother, step-mother, step mother (wd:P3448 as wdt/p): subject has the object as their stepparent, relative
9. 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
10. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as wdt/p): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)

No other items found

[Assistant]
The property `unmarried partner` (wd:P451) seems to be the most appropriate for finding Kourtney Kardashian's boyfriends. Let's construct a SPARQL query to find the boyfriends of Kourtney Kardashian.

Here is the initial SPARQL query:

```sparql
SELECT ?boyfriend WHERE {
  wd:Q575689 wdt:P451 ?boyfriend .
}
```

Let's execute this query to see the results.

[Tool]
Got 2 rows and 1 column:
| boyfriend                      |
| ------------------------------ |
| Younes Bendjima (wd:Q55200042) |
| Scott Disick (wd:Q7883337)     |

[Assistant]
The SPARQL query has returned the names of Kourtney Kardashian's boyfriends. The boyfriends are Younes Bendjima and Scott Disick.

Here is the final SPARQL query and the answer:

```sparql
SELECT ?boyfriend WHERE {
  wd:Q575689 wdt:P451 ?boyfriend .
}
```

Answer: Kourtney Kardashian's boyfriends are Younes Bendjima and Scott Disick.

Now, I will provide the final answer using the `answer` function.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?nationality WHERE {
  wd:Q192955 wdt:P27 ?nationality .
}

Got 2 rows and 1 column:
| nationality              |
| ------------------------ |
| United Kingdom (wd:Q145) |
| Canada (wd:Q16)          |

Steve Nash's nationalities are the United Kingdom and Canada.

[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 steve nash nationality?

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

[Tool]
Example 1:
Question:
who all has steve nash played for?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q192955 wdt:P54 ?x .
}

Using entities:
Steve Nash, also known as Stephen John Nash (wd:Q192955): Canadian basketball player and coach, basketball player, basketball coach, businessperson, film director

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

Example 2:
Question:
who is steve nash married to?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q192955 wdt:P26 ?x .
}

Using entities:
Steve Nash, also known as Stephen John Nash (wd:Q192955): Canadian basketball player and coach, basketball player, basketball coach, businessperson, film director

Using properties:
spouse, also known as married partner, married to, marry, partner, spouses (wd:P26 as wdt): the subject has the object as their spouse (husband, wife, partn...etc.). Use "unmarried partner" (P451) for non-married companions, significant person, relative

Example 3:
Question:
what year did steve nash play for the mavericks?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q192955 p:P54 ?p .
  ?p ps:P54 wd:Q132893 ; pq:P580 ?x ; pq:P582 ?y .
}

Using entities:
Dallas Mavericks, also known as Mavs (wd:Q132893): American professional basketball team, basketball player
Steve Nash, also known as Stephen John Nash (wd:Q192955): Canadian basketball player and coach, basketball player, basketball coach, businessperson, film director

Using properties:
member of sports team, also known as plays for, played for, sport team, team, team played for (wd:P54 as ps/p): sports teams or clubs that the subject represents or represented, member of
start time, also known as start date, since, valid, join time, joined (wd:P580 as pq): time an entity begins to exist or a statement starts being valid, point in time
end time, also known as ends, stop time, endtime, fall date, ineffective (wd:P582 as pq): moment when an entity ceases to exist and a statement stops being entirely valid or no longer be true, point in time

[Assistant] From the examples, we can see that Steve Nash is represented by the entity `wd:Q192955`. To find his nationality, we need to look for a property that indicates nationality. Let's search for such a property.

[Tool]
Top 10 property alternatives:
1. country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as pr/psv/prv/wdtn/pqv/pq/pqn/wdt/psn/ps/prn/p): the object is a country that recognizes the subject as its citizen, country
2. country for sport, also known as sports nationality, sports country, sport nationality, sporting nationality, sport country (wd:P1532 as pr/psv/prv/wdtn/pqv/pq/pqn/wdt/psn/ps/prn/p): country a person or a team represents when playing a sport, country
3. ethnic group, also known as ethnic or cultural origin, tribal affiliation, race, people, ethnicity (wd:P172 as pr/psv/prv/wdtn/pqv/pq/pqn/wdt/psn/ps/prn/p): subject's ethnicity (consensus is that a VERY high standard of p...agreed on by scholars, or 3) is fictional and portrayed as such)
4. place of birth, also known as POB, location of birth, location born, born in, birthplace (wd:P19 as pr/psv/prv/wdtn/pqv/pq/pqn/wdt/psn/ps/prn/p): most specific known birth location of a person, animal or fictional character, location
5. date of birth, also known as year of birth, birthdate, DOB, born on, born (wd:P569 as pr/psv/prv/wdtn/pqv/pq/pqn/wdt/psn/ps/prn/p): date on which the subject was born, inception
6. category for people born here, also known as category for place of birth, category of people born here (wd:P1464 as pr/psv/prv/wdtn/pqv/pq/pqn/wdt/psn/ps/prn/p): category item that groups people born in this place, related category
7. occupation, also known as job, work, vocation, profession, employment (wd:P106 as pr/psv/prv/wdtn/pqv/pq/pqn/wdt/psn/ps/prn/p): occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)
8. 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
9. birth name, also known as née, name at birth, name before marriage, ne, né (wd:P1477 as pr/psv/prv/wdtn/pqv/pq/pqn/wdt/psn/ps/prn/p): full name of a person at birth, if different from their current, generally used name, name
10. birthday, also known as b-day, bday, birth day (wd:P3150 as pr/psv/prv/wdtn/pqv/pq/pqn/wdt/psn/ps/prn/p): item for day and month on which the subject was born. Used when full "date of birth" (P569) isn't known., date of birth

[Assistant]
The property `country of citizenship` (wd:P27) seems to be the most appropriate for finding Steve Nash's nationality. Let's construct a SPARQL query to retrieve this information.

Here is the SPARQL query:

```sparql
SELECT ?nationality WHERE {
  wd:Q192955 wdt:P27 ?nationality .
}
```

I will now execute this query.

[Tool]
Got 2 rows and 1 column:
| nationality              |
| ------------------------ |
| United Kingdom (wd:Q145) |
| Canada (wd:Q16)          |

[Assistant]
The SPARQL query returned two nationalities for Steve Nash: the United Kingdom (wd:Q145) and Canada (wd:Q16).

To provide a clear answer, I will include both nationalities in the response.

Here is the final SPARQL query and answer:

```sparql
SELECT ?nationality WHERE {
  wd:Q192955 wdt:P27 ?nationality .
}
```

Answer: Steve Nash's nationalities are the United Kingdom and Canada.

Now, I will provide the final answer using 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 ?country ?countryLabel WHERE {
  wd:Q181574 wdt:P1001 ?country .
  OPTIONAL {
    ?country rdfs:label ?countryLabel .
    FILTER ( LANG( ?countryLabel ) = "en" )
  }
}

Got 3 rows and 2 columns:
| country                | countryLabel                  |
| ---------------------- | ----------------------------- |
| Canada (wd:Q16)        | Canada (en)                   |
| United States (wd:Q30) | United States of America (en) |
| Mexico (wd:Q96)        | Mexico (en)                   |

The countries involved in the North American Free Trade Agreement (NAFTA) are: Canada, United States of America, and Mexico.

[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 countries are involved in the nafta?

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

[Tool]
Example 1:
Question:
what countries in north america continent?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q49 wdt:P527 ?x .
}

Using entities:
North America, also known as Turtle Island, Amérique du Nord, North and Central America, North America (region), North American Continent (wd:Q49): continent

Using properties:
has part(s), also known as has component, incorporates, has ingredient, has ingredients, has member (wd:P527 as wdt): part of this subject; inverse property of "part of" (P361). See also "has parts of the class" (P2670).

Example 2:
Question:
what 3 countries does mexico border?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q96 wdt:P47 ?x .
}
LIMIT 3

Using entities:
Mexico, also known as US of M, United Mexican States, MXN, MX, Mexican United States (wd:Q96): country in North America

Using properties:
shares border with, also known as shares borders with, next to, bordered by, border, borders clockwise (wd:P47 as wdt): countries or administrative subdivisions, of equal level, that t...rders, either by land or water. A single common point is enough.

Example 3:
Question:
what three countries does mexico border?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q96 wdt:P47 ?x .
}

Using entities:
Mexico, also known as US of M, United Mexican States, MXN, MX, Mexican United States (wd:Q96): country in North America

Using properties:
shares border with, also known as shares borders with, next to, bordered by, border, borders clockwise (wd:P47 as wdt): countries or administrative subdivisions, of equal level, that t...rders, either by land or water. A single common point is enough.

[Assistant] None of these examples directly mention NAFTA, but they provide useful information about countries and their relationships. Let's first find the entity for NAFTA.

[Tool]
Top 10 entity alternatives:
1. North American Free Trade Agreement, also known as NAFTA (wd:Q181574): trade bloc
2. Nafta, also known as Nefta (wd:Q1026298): Tunisian town
3. nafta (wd:Q1213853): chemical compound
4. Nafta (wd:Q11788993): 1961 film by Stanisław Lenartowicz
5. Nafta (wd:Q6958220): Soviet Union oil company operating abroad
6. Nafta, also known as IMO 8853946 (wd:Q52335786): bunkering tanker built in 1978
7. NAFTA, also known as NAFTA a.s. (wd:Q12772242): Slovak multinational company operating in the field of storage and extraction of hydrocarbons
8. Naftalan (wd:Q152825): city in Azerbaijan
9. Naphtali, also known as Naftali (wd:Q1771963): biblical figure and the sixth son of Jacob through his concubine Bilhah
10. United States–Mexico–Canada Agreement, also known as Canada–United States–Mexico Agreement, CUSMA, NAFTA 2.0, NAFTA Redux, New NAFTA (wd:Q56839716): North American trade bloc

[Assistant] The top result is the North American Free Trade Agreement (NAFTA), which is what we're looking for. Now let's look at the properties associated with this entity to see if we can find the countries involved.

[Tool]
Top 10 property alternatives:
1. applies to jurisdiction, also known as belongs to jurisdiction, applies to territorial jurisdiction, applies to region, applies to place, applies to geographic place (wd:P1001 as wdt/p): the item (institution, law, public office, public register...) o...a territorial jurisdiction: a country, state, municipality, ...), significant place, characteristic of, operating area
2. headquarters location, also known as headquarters locality, seat, headquarters town, HQ, HQ location (wd:P159 as wdt/p): city or town where an organization's headquarters is or has been situated. Use P276 qualifier for specific building, significant place
3. topic's main category, also known as article's main category, category, category for this topic, catmain, has category (wd:P910 as wdt/p): main Wikimedia category
4. official language, also known as language spoken, spoken in, speaking, language official (wd:P37 as wdt/p): language designated as official by this item, language used
5. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt/p): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
6. locator map image, also known as locator map, map image, map (wd:P242 as wdt/p): geographic map image which highlights the location of the subject within some larger entity, image
7. inception, also known as initial release date, founded in, founded on, founded on date, founding date (wd:P571 as wdt/p): time when an entity begins to exist; for date of official opening use P1619, start time
8. has characteristic, also known as has quality, inherent property, object has characteristic, parameter, quality (wd:P1552 as wdt/p): inherent or distinguishing quality or feature of the entity. Use a more specific property when possible
9. short name, also known as short title, shortname, abbreviation, shortened name, initialism (wd:P1813 as wdt/p): short name of a place, organisation, person, journal, wikidata property, etc. Used by some Wikipedia templates., name
10. logo image, also known as masthead, wordmark, trademark, trade mark, sign (wd:P154 as wdt/p): graphic mark or emblem commonly used by commercial enterprises, organizations and products, icon

No other items found

[Assistant]
The property `applies to jurisdiction` (P1001) seems to be the most relevant for finding the countries involved in NAFTA. Let's construct a SPARQL query to retrieve these countries.

### Step 1: Simple Query to Retrieve Countries
We'll start with a simple query to retrieve the countries that NAFTA applies to.

```sparql
SELECT ?country WHERE {
  wd:Q181574 wdt:P1001 ?country .
}
```

Let's execute this query and see the results.

[Tool]
Got 3 rows and 1 column:
| country                |
| ---------------------- |
| Canada (wd:Q16)        |
| United States (wd:Q30) |
| Mexico (wd:Q96)        |

[Assistant]
The query successfully retrieved the countries involved in NAFTA: Canada, the United States, and Mexico.

To provide a more complete answer, we can include the labels of these countries in the result. However, since the labels are optional, we will use an `OPTIONAL` clause to fetch them.

### Step 2: Include Country Labels
Let's modify the query to include the labels of the countries.

```sparql
SELECT ?country ?countryLabel WHERE {
  wd:Q181574 wdt:P1001 ?country .
  OPTIONAL { ?country rdfs:label ?countryLabel . }
}
```

Let's execute this updated query.

[Tool]
Got 1,085 rows and 2 columns, showing the first 5 and last 5 rows below:
| country         | countryLabel     |
| --------------- | ---------------- |
| Canada (wd:Q16) | Cænada (ang)     |
| Canada (wd:Q16) | Canada (ami)     |
| Canada (wd:Q16) | Canada (cbk-zam) |
| Canada (wd:Q16) | Canada (ceb)     |
| Canada (wd:Q16) | Canada (ch)      |
| ...             | ...              |
| Mexico (wd:Q96) | 墨西哥 (zh-hk)      |
| Mexico (wd:Q96) | 墨西哥 (zh-mo)      |
| Mexico (wd:Q96) | 墨西哥 (zh-my)      |
| Mexico (wd:Q96) | 墨西哥 (zh-sg)      |
| Mexico (wd:Q96) | 墨西哥 (zh-tw)      |

[Assistant]
The query returned multiple labels for each country in different languages. To simplify the result, we can limit the labels to a specific language, such as English.

### Step 3: Limit Labels to English
Let's modify the query to only include the English labels.

```sparql
SELECT ?country ?countryLabel WHERE {
  wd:Q181574 wdt:P1001 ?country .
  OPTIONAL { ?country rdfs:label ?countryLabel . FILTER(LANG(?countryLabel) = "en") }
}
```

Let's execute this updated query.

[Tool]
Got 3 rows and 2 columns:
| country                | countryLabel                  |
| ---------------------- | ----------------------------- |
| Canada (wd:Q16)        | Canada (en)                   |
| United States (wd:Q30) | United States of America (en) |
| Mexico (wd:Q96)        | Mexico (en)                   |

[Assistant]
The query now returns the countries involved in NAFTA along with their English labels. The countries are:

- Canada
- United States of America
- Mexico

We can now provide the final answer.

### Final Answer
The countries involved in the North American Free Trade Agreement (NAFTA) are:

- Canada
- United States of America
- Mexico

Here is the final SPARQL query:

```sparql
SELECT ?country ?countryLabel WHERE {
  wd:Q181574 wdt:P1001 ?country .
  OPTIONAL { ?country rdfs:label ?countryLabel . FILTER(LANG(?countryLabel) = "en") }
}
```

Let's finalize the answer.

[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 ?placeOfBirth ?placeOfBirthLabel WHERE {
  wd:Q1744 wdt:P19 ?placeOfBirth .
  OPTIONAL {
    ?placeOfBirth rdfs:label ?placeOfBirthLabel .
    FILTER ( LANG( ?placeOfBirthLabel ) = 'en' )
  }
}

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

Madonna grew up in Bay City, Michigan.

[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 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] Based on the examples, it seems like the place of birth (P19) is often used to indicate where someone grew up. However, this might not always be accurate, as people can move around during their childhood. Let's first identify Madonna as an entity in the knowledge graph.

[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 correct entity for Madonna, the American singer and actress, is `wd:Q1744`. Now let's check if we can find information about where she grew up using the place of birth property (P19).

[Tool]
Got 1 row and 1 column:
| placeOfBirth          |
| --------------------- |
| Bay City (wd:Q746820) |

[Assistant]
The place of birth for Madonna is Bay City, Michigan (`wd:Q746820`). While this indicates where she was born, it doesn't necessarily mean she grew up there. To be thorough, let's check if there are any other properties that might provide more specific information about where she grew up.

I'll search for properties related to "grew up" or "childhood" for Madonna.

[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]
The search for properties related to "grew up" or "childhood" for Madonna did not yield any additional relevant properties beyond the place of birth (P19). Given this, the most accurate information we have is that Madonna was born in Bay City, Michigan, and it is reasonable to infer that she likely grew up there, although this is not explicitly stated.

To finalize the answer, I will construct a SPARQL query that returns the place of birth and include an optional clause to fetch the label for better readability.

[Tool] Stopped generation process