PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?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 (wd:Q6654), Serbian (wd:Q9299), and Bosnian (wd:Q9303).

[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 examples.

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

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x wdt:P31 / wdt:P279 * wd:Q47461344 ; wdt:P50 wd:Q868 .
}

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
Aristotle, also known as the Stagirite (wd:Q868): 4th-century BCE Classical Greek philosopher and polymath, philosopher

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:
who plays hermione granger?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?p p:P161 ?y .
  ?y ps:P161 ?x ; pq:P453 wd:Q174009 .
}

Using entities:
Hermione Granger, also known as Hermione, Hermy, Hermione Jean Granger (wd:Q174009): fictional character from the Harry Potter stories, time traveller, politician, activist, student

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

Example 3:
Question:
where do most chinese live?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x wdt:P17 wd:Q148 ; wdt:P1082 ?y .
}
ORDER BY DESC ( ?y )
LIMIT 1

Using entities:
People's Republic of China, also known as Zhōngguó, The PRC, RPC, CHN, Red China (wd:Q148): country in East Asia

Using properties:
population, also known as inhabitants, human population (wd:P1082 as wdt): number of people inhabiting the place; number of people of subject
country, also known as sovereign state, state, land, host country (wd:P17 as wdt): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity

[Assistant] Based on the examples, we need to identify the entity for Bosnia and the property for language spoken. Let's first search for the entity representing Bosnia.

[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. Bosnia (wd:Q188736): region in Bosnia and Herzegovina
3. Bosnia (wd:Q4947317): live album by Grand Funk Railroad
4. Bosna, also known as Bosnia (song), Bosnia (wd:Q25502969): Croatian song
5. Bosnia (wd:Q10433448): 1996 live album by Ulf Lundell
6. Bosnia (wd:Q29021052): song by Argentine musician Luis Alberto Spinetta in the álbum Spinetta y los Socios del Desierto
7. Bosnia (wd:Q103894070): encyclopedia article
8. Bosnia (wd:Q119441173): painting by James Potter (active 1998–2000), Royal Military Police Museum
9. Bosnia (wd:Q74241437): scientific article published on January 10, 1998
10. Bosnia (wd:Q80218280): photograph by Ron Haviv

[Assistant] The top result is "Bosnia and Herzegovina" (wd:Q225), which seems to be the correct entity for the country. Next, let's search for the property that represents the language 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 pqv/pqn/prn/wdtn/wdt/pq/prv/p/psn/psv/ps/pr): language designated as official by this item, language used
2. languages spoken, written or signed, also known as language of expression, language, wrote language, writes language, uses language (wd:P1412 as pqv/pqn/prn/wdtn/wdt/pq/prv/p/psn/psv/ps/pr): language(s) that a person or a people speaks, writes or signs, including the native language(s)
3. number of speakers, writers, or signers, also known as signers of a language, speakers of language, writers of a language (wd:P1098 as pqv/pqn/prn/wdtn/wdt/pq/prv/p/psn/psv/ps/pr): number of people who use a language
4. language used, also known as languages used, medium of instruction, used language, uses language, working language (wd:P2936 as pqv/pqn/prn/wdtn/wdt/pq/prv/p/psn/psv/ps/pr): language widely used (spoken or written) in this place or at this event or organisation
5. 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 pqv/pqn/prn/wdtn/wdt/pq/prv/p/psn/psv/ps/pr): language associated with this creative work (such as books, show...guage" (P103) and "languages spoken, written or signed" (P1412))
6. programmed in, also known as language, programming language, written in (wd:P277 as pqv/pqn/prn/wdtn/wdt/pq/prv/p/psn/psv/ps/pr): the programming language(s) in which the software is developed
7. language style, also known as manner, term register, obsolete, register, sense register (wd:P6191 as pqv/pqn/prn/wdtn/wdt/pq/prv/p/psn/psv/ps/pr): to denote of the way a sense of a word is used, e.g., slang, vulgarism, babytalk, colloquialism, etc.
8. native language, also known as first language, L1 speaker of, language native, mother tongue (wd:P103 as pqv/pqn/prn/wdtn/wdt/pq/prv/p/psn/psv/ps/pr): language or languages a person has learned from early childhood, languages spoken, written or signed
9. Ethnologue language status, also known as EGIDS, language status (wd:P3823 as pqv/pqn/prn/wdtn/wdt/pq/prv/p/psn/psv/ps/pr): language status identifier by Ethnologue.com using EGIDS scale
10. population by native language, also known as native language population (wd:P12712 as pqv/pqn/prn/wdtn/wdt/pq/prv/p/psn/psv/ps/pr): native language population of a place, population

[Assistant]
The property "official language" (wd:P37) seems to be the most relevant for our purpose. Now, let's construct a simple SPARQL query to find the official language(s) of Bosnia and Herzegovina.

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

I will now execute this query to see the results.

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

[Assistant]
The query returned the official languages of Bosnia and Herzegovina: Croatian, Serbian, and Bosnian. To provide a more complete answer, we can also include the labels of these languages in the query. However, since the user did not explicitly request labels, we will keep the query simple and return the IRIs.

Here is the final SPARQL query:

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

And the answer to the question is:

- Croatian (wd:Q6654)
- Serbian (wd:Q9299)
- Bosnian (wd:Q9303)

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

[Tool] Stopped generation process

[User]
Feedback (status=done):
The output is correct and complete. The SPARQL query correctly identifies the official languages of Bosnia and Herzegovina, which are Croatian, Serbian, and Bosnian. The query is well-formed and follows all the rules for SPARQL queries.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?label WHERE {
  wd:Q9299 rdfs:label ?label .
  FILTER ( LANG( ?label ) = "en" )
}

Got 1 row and 1 column:
| label        |
| ------------ |
| Serbian (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 examples.

[Tool]
Example 1:
Question:
who played jacob black?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?p p:P161 ?y .
  ?y ps:P161 ?x ; pq:P453 wd:Q716835 .
}

Using entities:
Jacob Black (wd:Q716835): character from Twilight, vampire hunter, mechanic, student

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

Example 2:
Question:
where is the bank of america pavilion?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q4856037 wdt:P131 ?x .
}

Using entities:
Leader Bank Pavilion, also known as Blue Hills Bank Pavilion, Rockland Trust Bank Pavilion, Bank of America Pavilion (wd:Q4856037): outdoor theater in Boston, Massachusetts

Using properties:
located in the administrative territorial entity, also known as is in the settlement of, is in the voivodeship of, is in the shire of, is in the state of, is in the territory of (wd:P131 as wdt): the item is located on the territory of the following administra...if the item falls only partially into the administrative entity., location, part of

Example 3:
Question:
what currency do mexico use?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q96 wdt:P38 ?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:
currency, also known as base currency, used money (wd:P38 as wdt): currency used by item, uses

[Assistant] From the examples, we can see that to answer a question about what something is called, we need to look for the label or alternative names of the entity. In this case, we need to find the Serbian language entity and then check its labels or alternative names. Let's first search for the Serbian language entity.

[Tool]
Top 10 entity alternatives:
1. Serbian, also known as Srpski, Serbian language (wd:Q9299): standardized variety of Serbo-Croatian language used by Serbs
2. Sorbian, also known as Serbian language, Wendic language, Wendish (wd:Q25442): Lechitic language spoken by the Sorbs
3. Serbian language (wd:L616516-S1)
4. Serbian (language) (wd:L613158-S1)
5. History of Serbian, also known as Serbian language history (wd:Q31183797)
6. Serbian Sign Language (wd:Q113203025)
7. Serbian language in Croatia, also known as use of the Serbian language in Croatia (wd:Q20974148): overview about the use of the Serbian language in Croatia
8. Institute for Serbian Language (wd:Q16082649)
9. Serbian language in Montenegro (wd:Q65201055)
10. romanization of Serbian, also known as romanisation of Serbian, romanization of the Serbian language (wd:Q7362708): overview about the romanization of the Serbian language

[Assistant]
The top result is the entity for the Serbian language, which is `wd:Q9299`. Now, let's check the labels and alternative names for this entity.

We will use the `list` function to find the labels and alternative names associated with this entity.

[Tool]
Got 178 rows and 3 columns, showing the first 10 rows below:
| subject            | property   | object               |
| ------------------ | ---------- | -------------------- |
| Serbian (wd:Q9299) | rdfs:label | Afaan Sarbiyaa (om)  |
| Serbian (wd:Q9299) | rdfs:label | Amanung Serbyu (pam) |
| Serbian (wd:Q9299) | rdfs:label | an tSeirbis (ga)     |
| Serbian (wd:Q9299) | rdfs:label | Bahasa Serbia (kge)  |
| Serbian (wd:Q9299) | rdfs:label | Bahasa Serbia (ms)   |
| Serbian (wd:Q9299) | rdfs:label | Basa Serbia (jv)     |
| Serbian (wd:Q9299) | rdfs:label | Èdè Sérbíà (yo)      |
| Serbian (wd:Q9299) | rdfs:label | fiteny serba (mg)    |
| Serbian (wd:Q9299) | rdfs:label | Gagana Serbia (sm)   |
| Serbian (wd:Q9299) | rdfs:label | Idioma serbio (an)   |
| ...                | ...        | ...                  |

[Assistant]
The results show various labels for the Serbian language in different languages. However, the primary label in English is simply "Serbian". To confirm this, we can run a SPARQL query to retrieve the English label specifically.

Let's execute a SPARQL query to get the English label for the Serbian language.

```sparql
SELECT ?label
WHERE {
  wd:Q9299 rdfs:label ?label .
  FILTER(LANG(?label) = "en")
}
```

Executing this query:

[Tool]
Got 1 row and 1 column:
| label        |
| ------------ |
| Serbian (en) |

[Assistant]
The English label for the Serbian language is "Serbian".

Therefore, the Serbian language is called "Serbian".

Final SPARQL query and answer:

```sparql
SELECT ?label
WHERE {
  wd:Q9299 rdfs:label ?label .
  FILTER(LANG(?label) = "en")
}
```

Answer: The Serbian language is called "Serbian".

[Tool] Stopped generation process

[User]
Feedback (status=done):
The answer is correct and the SPARQL query is appropriate. It retrieves the English label for the Serbian language from Wikidata.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?instrument ?instrumentLabel WHERE {
  wd:Q191499 wdt:P1303 ?instrument .
  OPTIONAL {
    ?instrument rdfs:label ?instrumentLabel .
    FILTER ( LANG( ?instrumentLabel ) = "en" )
  }
}

Got 4 rows and 2 columns:
| instrument          | instrumentLabel |
| ------------------- | --------------- |
| cornet (wd:Q202027) | cornet (en)     |
| piano (wd:Q5994)    | piano (en)      |
| guitar (wd:Q6607)   | guitar (en)     |
| violin (wd:Q8355)   | violin (en)     |

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 examples.

[Tool]
Example 1:
Question:
what are the main languages spoken in spain?

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

Example 2:
Question:
where is tahiti bora bora?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q42000 wdt:P131 ?x .
}

Using entities:
Tahiti, also known as Otaheitee (wd:Q42000): island in the Southern Pacific Ocean

Using properties:
located in the administrative territorial entity, also known as is in the settlement of, is in the voivodeship of, is in the shire of, is in the state of, is in the territory of (wd:P131 as wdt): the item is located on the territory of the following administra...if the item falls only partially into the administrative entity., location, part of

Example 3:
Question:
what is there fun to do in san diego?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x wdt:P31 / wdt:P279 * wd:Q570116 ; wdt:P131 wd:Q16552 .
}

Using entities:
San Diego, also known as America's Finest City, Sandi, San Diego, CA, San Diego, Calif., San Diego, California (wd:Q16552): city in San Diego County, California, United States; second-largest city in California
tourist attraction, also known as attraction for tourists, POI for tourists, tourism attraction, touristic attraction, tourist place (wd:Q570116): place of interest where tourists visit

Using properties:
located in the administrative territorial entity, also known as is in the settlement of, is in the voivodeship of, is in the shire of, is in the state of, is in the territory of (wd:P131 as wdt): the item is located on the territory of the following administra...if the item falls only partially into the administrative entity., location, part of
subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as wdt): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)

[Assistant] From these examples, we can see how entities and properties are used in SPARQL queries. To answer the question "What did Scott Joplin play?", we need to identify the entity for Scott Joplin and the relevant property that indicates what he played. Let's start by searching for the entity "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 top result for "Scott Joplin" is the correct entity: Scott Joplin, also known as The King of Ragtime (wd:Q191499). Now, let's find out what properties are associated with this entity to determine what he played. We can search for properties related to "play" or "instrument" for this entity.

[Tool]
Top 10 property alternatives:
1. instrument, also known as uses this instrument, teaches instrument, instruments, plays this instrument, plays instrument (wd:P1303 as p/wdt): musical instrument that a person plays or teaches or used in a music occupation, uses
2. award received, also known as win, winner of, recognition title, received award, prize received (wd:P166 as p/wdt): award or recognition received by a person, organization or creative work
3. field of work, also known as scientific discipline, scientific area, responsible for, research on, research fields (wd:P101 as p/wdt): specialization of a person or organization; see P106 for the occupation, interested in
4. genre, also known as genre of music, type of music, type of film, music genre, literary genre (wd:P136 as p/wdt): creative work's genre or an artist's field of work (P101). Use main subject (P921) to relate creative works to their topic
5. sex or gender, also known as gender or sex, sex, gender identity, gender expression, gender (wd:P21 as p/wdt): sex or gender identity of human or animal. For human: male, fema...m, female organism. Groups of same gender use subclass of (P279)
6. notable work, also known as artwork, wrote, writer of, works, work (wd:P800 as p/wdt): notable scientific, artistic or literary work, or other work of significance among subject's works
7. occupation, also known as job, work, vocation, profession, employment (wd:P106 as p/wdt): occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)
8. pseudonym, also known as nom de plume, nom-de-plume, nome de guerre, pen name, ring name (wd:P742 as p/wdt): alias used by someone (for nickname use P1449), name
9. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as p/wdt): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
10. official website, also known as site (official), home page, site official, URL, URL (official) (wd:P856 as p/wdt): URL of the official page of an item (current or former). Usage: ...but see the "Hijacked or dead websites" section of the Talk page, URL

No other items found

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

Here is the initial SPARQL query:

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

Let's execute this query to see the results.

[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 following instruments that Scott Joplin played:
- Cornet (wd:Q202027)
- Piano (wd:Q5994)
- Guitar (wd:Q6607)
- Violin (wd:Q8355)

To provide a more complete answer, we can include the labels of these instruments in the query. Here is the updated SPARQL query:

```sparql
SELECT ?instrument ?instrumentLabel WHERE {
  wd:Q191499 wdt:P1303 ?instrument .
  OPTIONAL { ?instrument rdfs:label ?instrumentLabel . FILTER(LANG(?instrumentLabel) = "en") }
}
```

Let's execute this query to get the labels.

[Tool]
Got 4 rows and 2 columns:
| instrument          | instrumentLabel |
| ------------------- | --------------- |
| cornet (wd:Q202027) | cornet (en)     |
| piano (wd:Q5994)    | piano (en)      |
| guitar (wd:Q6607)   | guitar (en)     |
| violin (wd:Q8355)   | violin (en)     |

[Assistant]
The SPARQL query has successfully returned the instruments that Scott Joplin played along with their labels:

- Cornet (wd:Q202027)
- Piano (wd:Q5994)
- Guitar (wd:Q6607)
- Violin (wd:Q8355)

Based on this, we can provide the final answer to the user's question.

Here is the final SPARQL query and the answer:

```sparql
SELECT ?instrument ?instrumentLabel WHERE {
  wd:Q191499 wdt:P1303 ?instrument .
  OPTIONAL { ?instrument rdfs:label ?instrumentLabel . FILTER(LANG(?instrumentLabel) = "en") }
}
```

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

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query is well-formed and returns the correct instruments that Scott Joplin played. The query follows all the rules and the answer provided is accurate and complete.


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

Robert Burns had the following jobs: 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 examples.

[Tool]
Example 1:
Question:
which countries does russia border?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q159 wdt:P47 ?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:
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 2:
Question:
what form of government does brazil have?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q155 wdt:P122 ?x .
}

Using entities:
Brazil, also known as br, Brasil, Federative Republic of Brazil (wd:Q155): country in South America

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

Example 3:
Question:
what language does egyptians use?

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

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

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

[Assistant] Based on the examples, we need to identify the entity for Robert Burns and the property for jobs or occupations. Let's start by searching for Robert Burns.

[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`. Next, let's find the property for jobs or occupations. We can search for the property directly or look at the properties associated with Robert Burns.

I'll first try searching for the property.

[Tool]
Top 10 property alternatives:
1. occupation, also known as job, work, vocation, profession, employment (wd:P106 as pqv/pqn/prn/wdtn/wdt/pq/prv/p/psn/psv/ps/pr): occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)
2. field of this occupation, also known as practice, works in, profession's field, practices, field of this profession (wd:P425 as pqv/pqn/prn/wdtn/wdt/pq/prv/p/psn/psv/ps/pr): field corresponding to this occupation or profession (use only f...fessions - for people use Property:P101, for companies use P452)
3. members have occupation, also known as profession of members, organization of, organization for, organisation of, organisation for (wd:P3989 as pqv/pqn/prn/wdtn/wdt/pq/prv/p/psn/psv/ps/pr): some or all members of this group share the occupation
4. practiced by, also known as proponent, studied by, practitioners, practioner, occupation of this field (wd:P3095 as pqv/pqn/prn/wdtn/wdt/pq/prv/p/psn/psv/ps/pr): type of agents that study this subject or work in this field
5. position held, also known as function, held position, holds position, job, office held (wd:P39 as pqv/pqn/prn/wdtn/wdt/pq/prv/p/psn/psv/ps/pr): subject currently or formerly holds the object position or public office
6. employer, also known as working at, working for, working place, works at, works for (wd:P108 as pqv/pqn/prn/wdtn/wdt/pq/prv/p/psn/psv/ps/pr): person or organization for which the subject works or worked, affiliation
7. country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as pqv/pqn/prn/wdtn/wdt/pq/prv/p/psn/psv/ps/pr): the object is a country that recognizes the subject as its citizen, country
8. occupant, also known as tenant, resident, renter, occupiers, lessee (wd:P466 as pqv/pqn/prn/wdtn/wdt/pq/prv/p/psn/psv/ps/pr): person or organization occupying property, used by
9. field of work, also known as scientific discipline, scientific area, responsible for, research on, research fields (wd:P101 as pqv/pqn/prn/wdtn/wdt/pq/prv/p/psn/psv/ps/pr): specialization of a person or organization; see P106 for the occupation, interested in
10. work location, also known as work place, working from, working at, worked from, worked at (wd:P937 as pqv/pqn/prn/wdtn/wdt/pq/prv/p/psn/psv/ps/pr): location where persons or organisations were actively participating in employment, business or other work, significant place, location

[Assistant]
The property for occupation is `wdt:P106`. Now, let's construct a simple SPARQL query to find the jobs or occupations of Robert Burns.

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

I will execute this query to see 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 or occupations of Robert Burns. Here are the results:

- Farmer (wd:Q131512)
- Musicologist (wd:Q14915627)
- Writer (wd:Q36180)
- Poet (wd:Q49757)
- Songwriter (wd:Q753110)

Now, I will provide the final answer.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The output is correct and complete. The SPARQL query effectively retrieves all the occupations of Robert Burns from the Wikidata knowledge graph. The human-readable answer lists all the jobs found, which matches the execution result of the query.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT DISTINCT ?zipCode WHERE {
  ?partOfSeattle wdt:P131 wd:Q5083 .
  ?partOfSeattle wdt:P281 ?zipCode .
  FILTER ( REGEX( ?zipCode , "^[0-9]{5}$" ) )
}

Seattle, Washington has multiple standard 5-digit zip codes, including 98004, 98006, 98101, 98102, 98103, and many others.

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

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

[Tool]
Example 1:
Question:
where did queen isabella live?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q45859 wdt:P19 ?x .
}

Using entities:
Isabella I of Castile, also known as la Católica, Queen of Spain Isabel I, Queen Isabella, Queen Isabella of Spain, Queen of Castile and Leon Isabella, Queen of Castile and León Isabella (wd:Q45859): queen of the Crown of Castile, from 1474 to 1504; first queen of a dynastically-united Spain, from 1479 to 1504, ruler

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:
what country did james cook come from?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q7324 wdt:P27 ?x .
}

Using entities:
James Cook, also known as James Cooke, Cook, James, Captain James Cook, Captain Cook (wd:Q7324): British explorer, cartographer and naval officer (1728–1779), naval officer, cartographer, botanist, explorer, seafarer

Using properties:
country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as wdt): the object is a country that recognizes the subject as its citizen, country

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

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q5930 p:P725 ?p .
  ?p ps:P725 ?x ; pq:P453 wd:Q853073 .
}

Using entities:
Family Guy (wd:Q5930): American adult animated sitcom
Lois Griffin, also known as Lois Pewterschmidt Griffin, Lois Pewterschmidt, Lois Patrice Pewterschmidt, Lois Patrice Griffin (wd:Q853073): fictional character from the Family Guy franchise, housewife

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

[Assistant] To find the zip code for Seattle, Washington, we need to identify the entity for Seattle and then look for a property that represents the zip code.

[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 top result for "Seattle, Washington" is `wd:Q5083`. Now, let's find out if there is a property that represents the zip code for this entity.

I will search for properties related to "zip code" or "postal code" for the entity `wd:Q5083`.

[Tool]
Top 10 property alternatives:
1. postal code, also known as pincode, PIN Code, postal index number, post code, postcode (wd:P281 as p/wdt): identifier assigned by postal authorities for the subject area or building
2. local dialing code, also known as area code, dialling code, local calling code, local dialling code, STD code (wd:P473 as p/wdt): identifier dedicated to subject city by the area communication network
3. FIPS 55-3 (locations in the US), also known as fips code for US locations, Federal Information Processing Standard 55-3, FIPS 55-3 (wd:P774 as p/wdt): identifier for places in the United States per former Federal Information Processing Standard FIPS 55-3
4. social media followers, also known as number of subs, number of subscribers, sub count, sub number, subscriber number (wd:P8687 as p/wdt): number of subscribers on a particular social media website (use ... in time" and property for account. For Twitter, use numeric id.
5. autonomous system number, also known as ASN, AS number (wd:P3797 as p/wdt): unique identifier for a collection of connected Internet Protoco...ting prefixes under the control of one or more network operators
6. UN/LOCODE, also known as LOCCODE, LOCODE, UNECE location code, UNECE LOCODE, United Nations location code (wd:P1937 as p/wdt): geographic location code maintained by UNECE
7. coordinate location, also known as point on a map, gps coordinates, gps location, latitude, location (wd:P625 as p/wdt): geocoordinates of the subject. For Earth, please note that only WGS84 coordinating system is supported at the moment
8. area, also known as total area, surface area, surface, size, resolution (wd:P2046 as p/wdt): area occupied by an object
9. FactGrid item ID, also known as FG ID, FactGrid ID (wd:P8168 as wdtn/p/wdt): identifier for an item in FactGrid
10. located in time zone, also known as TZ, time zone, timezone (wd:P421 as p/wdt): time zone for this item

No other items found

[Assistant]
The property `wd:P281` (postal code) seems to be the most relevant for finding the zip code of Seattle, Washington. Let's construct a SPARQL query to retrieve the zip code for the entity `wd:Q5083`.

I will execute the following SPARQL query:

```sparql
SELECT ?zipCode WHERE {
  wd:Q5083 wdt:P281 ?zipCode .
}
```

This query will return the zip code(s) associated with Seattle, Washington.

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

[Assistant]
The zip code for Seattle, Washington is 98101. However, it's important to note that Seattle has multiple zip codes, and this query only returns one of them. To get a more comprehensive list, we can modify the query to return all zip codes associated with Seattle.

Let's execute the following SPARQL query:

```sparql
SELECT ?zipCode WHERE {
  wd:Q5083 wdt:P281 ?zipCode .
}
```

This query will return all zip codes associated with Seattle, Washington.

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

[Assistant]
It appears that the query only returned one zip code for Seattle, Washington, which is 98101. However, Seattle has multiple zip codes. This might be due to the way the data is structured in Wikidata.

To ensure we capture all zip codes, we can try a different approach by looking for all entities that are part of Seattle and then checking their zip codes. Let's try this approach:

1. Find entities that are part of Seattle.
2. Check if these entities have a zip code.

Here is the SPARQL query to achieve this:

```sparql
SELECT ?partOfSeattle ?zipCode WHERE {
  ?partOfSeattle wdt:P131 wd:Q5083 .
  ?partOfSeattle wdt:P281 ?zipCode .
}
```

This query will return all entities that are part of Seattle and their associated zip codes.

[Tool]
Got 257 rows and 2 columns, showing the first 5 and last 5 rows below:
| partOfSeattle                                                                      | zipCode    |
| ---------------------------------------------------------------------------------- | ---------- |
| University of Washington Southeast Asia Center (wd:Q100252662)                     | 98195-3650 |
| University of Washington Asian Law Center (wd:Q100709311)                          | 98195-3020 |
| University of Washington eScience Institute (wd:Q101097636)                        | 98195-1570 |
| Northwest Climate Adaptation Science Center (wd:Q101576883)                        | 98195-5674 |
| University of Washington Computational Neuroscience Center (wd:Q102047439)         | 98195      |
| ...                                                                                | ...        |
| University of Washington Center for Urban Horticulture (wd:Q99703417)              | 98105      |
| University of Washington Institute for Nano-Engineered Systems (wd:Q99705798)      | 98195      |
| Nano Engineering and Sciences Building (wd:Q99705827)                              | 98195      |
| University of Washington Latin A...an and Caribbean Studies Program (wd:Q99864848) | 98195-3650 |
| University of Washington South Asia Center (wd:Q99866754)                          | 98195-3650 |

[Assistant]
The query returned multiple zip codes for various parts of Seattle, Washington. Here are some of the zip codes:

- 98195-3650
- 98195-3020
- 98195-1570
- 98195-5674
- 98195
- 98105

These results indicate that Seattle has multiple zip codes, and the query successfully captured several of them.

To provide a concise answer, we can summarize the unique zip codes found. Let's execute a modified query to return only the unique zip codes:

```sparql
SELECT DISTINCT ?zipCode WHERE {
  ?partOfSeattle wdt:P131 wd:Q5083 .
  ?partOfSeattle wdt:P281 ?zipCode .
}
```

This query will return a list of distinct zip codes for Seattle, Washington.

[Tool]
Got 102 rows and 1 column, showing the first 5 and last 5 rows below:
| zipCode       |
| ------------- |
| 98004         |
| 98006         |
| 98101         |
| 98102         |
| 98103         |
| ...           |
| 98195-7735    |
| 98195-7920    |
| 98195-8280    |
| 98199         |
| WA 98195-4360 |

[Assistant]
The query returned a list of distinct zip codes for Seattle, Washington. Here are some of the unique zip codes:

- 98004
- 98006
- 98101
- 98102
- 98103
- ...
- 98195-7735
- 98195-7920
- 98195-8280
- 98199
- WA 98195-4360

These results show that Seattle has multiple zip codes, and the query successfully captured a comprehensive list of them.

To provide a final answer, I will use the SPARQL query that returns the distinct zip codes for Seattle, Washington.

Here is the final SPARQL query:

```sparql
SELECT DISTINCT ?zipCode WHERE {
  ?partOfSeattle wdt:P131 wd:Q5083 .
  ?partOfSeattle wdt:P281 ?zipCode .
}
```

And the answer to the question "What is the zip code for Seattle, Washington?" is that Seattle has multiple zip codes, including but not limited to those listed above.

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The SPARQL query is mostly correct, but the result includes some non-standard zip codes such as '98195-7735', '98195-7920', '98195-8280', '98199', and 'WA 98195-4360'. These are either extended zip codes (ZIP+4) or incorrectly formatted. To improve the query, consider filtering out these extended or incorrectly formatted zip codes to return only the standard 5-digit zip codes.

[Assistant]
Thank you for the feedback. To improve the query, we will filter out the extended or incorrectly formatted zip codes and return only the standard 5-digit zip codes. We can use a regex pattern to match only 5-digit zip codes.

Here is the updated SPARQL query:

```sparql
SELECT DISTINCT ?zipCode WHERE {
  ?partOfSeattle wdt:P131 wd:Q5083 .
  ?partOfSeattle wdt:P281 ?zipCode .
  FILTER (REGEX(?zipCode, "^[0-9]{5}$"))
}
```

This query will return only the standard 5-digit zip codes for Seattle, Washington.

Let's execute this updated query.

[Tool]
Got 26 rows and 1 column, showing the first 5 and last 5 rows below:
| zipCode |
| ------- |
| 98004   |
| 98006   |
| 98101   |
| 98102   |
| 98103   |
| ...     |
| 98144   |
| 98164   |
| 98174   |
| 98195   |
| 98199   |

[Assistant]
The updated query has successfully filtered out the extended or incorrectly formatted zip codes and returned only the standard 5-digit zip codes for Seattle, Washington. Here are the standard 5-digit zip codes:

- 98004
- 98006
- 98101
- 98102
- 98103
- ...
- 98144
- 98164
- 98174
- 98195
- 98199

To provide a final answer, I will use the updated SPARQL query that returns the distinct 5-digit zip codes for Seattle, Washington.

Here is the final SPARQL query:

```sparql
SELECT DISTINCT ?zipCode WHERE {
  ?partOfSeattle wdt:P131 wd:Q5083 .
  ?partOfSeattle wdt:P281 ?zipCode .
  FILTER (REGEX(?zipCode, "^[0-9]{5}$"))
}
```

And the answer to the question "What is the zip code for Seattle, Washington?" is that Seattle has multiple standard 5-digit zip codes, including 98004, 98006, 98101, 98102, 98103, and many others.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query is well-formed and returns the correct 5-digit zip codes for Seattle, Washington. The answer provided is accurate and comprehensive, listing several of the zip codes found in the execution result. No further refinement is necessary.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?boyfriend WHERE {
  {
    wd:Q575689 wdt:P26 ?boyfriend
  } UNION {
    wd:Q575689 wdt:P451 ?boyfriend
  }
}

Kourtney Kardashian's boyfriends are Travis Barker, 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 examples.

[Tool]
Example 1:
Question:
what religion are people in russia?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q159 wdt:P3075 ?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 religion, also known as established religion, state religion (wd:P3075 as wdt): official religion in this administrative entity

Example 2:
Question:
what country was theodor schwann born in?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q76745 wdt:P19 ?x .
}

Using entities:
Theodor Schwann, also known as F. T. Schwann, Schwann (wd:Q76745): German physiologist (1810–1882), university teacher, physiologist, biologist, physician, botanist

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:
who does david beckham play for in 2012?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q10520 p:P54 ?p .
  ?p ps:P54 ?x ; pq:P580 ?y ; pq:P582 ?z .
  FILTER ( ( ?y < "2013-01-01T00:00:00Z" ^^ xsd:dateTime ) && ( ?z >= "2012-01-01T00:00:00Z" ^^ xsd:dateTime ) )
}

Using entities:
David Beckham, also known as Becks, Beckham (wd:Q10520): English association football player, association football player, sports executive, businessperson, entrepreneur, blogger, actor, model

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] Based on the examples, we need to identify Kourtney Kardashian and then look for her relationships or partners. Let's first find 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 out about her relationships or boyfriends. We will use the property "spouse" (`P26`) and "partner" (`P451`) to check for her significant others.

First, let's try the "spouse" property:

[Tool]
Got 1 row and 1 column:
| boyfriend                  |
| -------------------------- |
| Travis Barker (wd:Q220140) |

[Assistant]
It appears that Kourtney Kardashian's spouse is Travis Barker. However, to ensure we have a complete picture, let's also check if she has any other partners listed under the "partner" property (`P451`).

Let's run another query for the "partner" property:

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

[Assistant]
Kourtney Kardashian has had multiple partners. According to the data:

- Her current spouse is **Travis Barker**.
- She has also been in relationships with **Younes Bendjima** and **Scott Disick**.

To provide a comprehensive answer, we can combine both sets of results. Here is the final SPARQL query:

```sparql
SELECT ?boyfriend WHERE {
  { wd:Q575689 wdt:P26 ?boyfriend }
  UNION
  { wd:Q575689 wdt:P451 ?boyfriend }
}
```

This query will return all of Kourtney Kardashian's significant others, including her spouse and partners.

Let's execute this final query:

[Tool]
Got 3 rows and 1 column:
| boyfriend                      |
| ------------------------------ |
| Travis Barker (wd:Q220140)     |
| Younes Bendjima (wd:Q55200042) |
| Scott Disick (wd:Q7883337)     |

[Assistant]
The final SPARQL query has successfully returned all of Kourtney Kardashian's significant others, including her spouse and partners. Here is the final answer:

Kourtney Kardashian's boyfriends include:
- **Travis Barker** (current spouse)
- **Younes Bendjima**
- **Scott Disick**

Here is the final SPARQL query:

```sparql
SELECT ?boyfriend WHERE {
  { wd:Q575689 wdt:P26 ?boyfriend }
  UNION
  { wd:Q575689 wdt:P451 ?boyfriend }
}
```

And the answer to the user's question:

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

[Tool] Stopped generation process

[User]
Feedback (status=done):
The output is correct and complete. The SPARQL query successfully retrieves all of Kourtney Kardashian's boyfriends from the knowledge graph, and the human-readable answer lists them accurately.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
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 (wd:Q145) and Canada (wd:Q16).

[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 examples.

[Tool]
Example 1:
Question:
where did dolly parton grew up?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q180453 wdt:P19 ?x .
}

Using entities:
Dolly Parton, also known as Dolly Rebecca Parton, Dolly Parton Dean (wd:Q180453): American singer, songwriter and actress, multi-instrumentalist, singer-songwriter, television actor, recording artist, country musician, record producer, autobiographer, businessperson, country singer, film producer, screenwriter, voice actor, songwriter, film actor, guitarist, composer, banjoist, 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 2:
Question:
who are the judges of the supreme court?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x wdt:P39 ?y .
  ?y wdt:P279 wd:Q20706330 .
}

Using entities:
United States Supreme Court justice, also known as Justice of the Supreme Court of the United States, Justices of the Supreme Court of the United States, Justices of the United States Supreme Court (wd:Q20706330): Chief Justice and associate justice of the Supreme Court of the United States

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
position held, also known as function, held position, holds position, job, office held (wd:P39 as wdt): subject currently or formerly holds the object position or public office

Example 3:
Question:
who does dominic monaghan play in lord of the rings?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q127367 p:P161 ?p .
  ?p ps:P161 wd:Q152165 ; pq:P453 ?x .
}

Using entities:
The Lord of the Rings: The Fellowship of the Ring, also known as Lord of the Rings: The Fellowship of the Ring, The Fellowship of the Ring (wd:Q127367): 2001 film by Peter Jackson
Dominic Monaghan (wd:Q152165): German-born British actor, television actor, screenwriter, stage actor, film actor, actor

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

[Assistant] Based on the examples, we need to identify the entity for Steve Nash and the property for nationality. Let's start by searching for the entity "Steve Nash".

[Tool]
Top 10 entity alternatives:
1. Steve Nash, also known as Stephen John Nash (wd:Q192955): Canadian basketball player and coach, basketball player, basketball coach, businessperson, film director
2. Steve Nash (wd:Q16137022): English rugby league footballer and coach, rugby league player
3. Steve Nash (wd:Q48851147): disc jockey
4. Steve Nash (wd:Q42316961): actor
5. Steven Jackson, also known as Steven Nash Jackson (wd:Q3499240): American baseball player, baseball player
6. Steven G. Nash (wd:Q98756087): American politician, businessperson, politician
7. Steven Roy Nash, also known as Dr. Steven Roy Nash (wd:Q76187877): Peerage person ID=590989
8. Edward Mungo Steven Nash, also known as Edward Nash (wd:Q76187880): (born 1990)
9. Nash, also known as Nash, Texas, Nash, TX (wd:Q978847): city in Bowie County, Texas, United States
10. Nash, also known as Nash, OK, Nash, Oklahoma (wd:Q2321969): town in Grant County, Oklahoma, United States

[Assistant] The top result for "Steve Nash" is the Canadian basketball player and coach, which matches our context. We will use `wd:Q192955` as the entity for Steve Nash. Next, let's search for the property "nationality".

[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 pqv/pqn/prn/wdtn/wdt/pq/prv/p/psn/psv/ps/pr): 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 pqv/pqn/prn/wdtn/wdt/pq/prv/p/psn/psv/ps/pr): 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 pqv/pqn/prn/wdtn/wdt/pq/prv/p/psn/psv/ps/pr): 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 pqv/pqn/prn/wdtn/wdt/pq/prv/p/psn/psv/ps/pr): 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 pqv/pqn/prn/wdtn/wdt/pq/prv/p/psn/psv/ps/pr): 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 pqv/pqn/prn/wdtn/wdt/pq/prv/p/psn/psv/ps/pr): category item that groups people born in this place, related category
7. occupation, also known as job, work, vocation, profession, employment (wd:P106 as pqv/pqn/prn/wdtn/wdt/pq/prv/p/psn/psv/ps/pr): 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 pqv/pqn/prn/wdtn/wdt/pq/prv/p/psn/psv/ps/pr): 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 pqv/pqn/prn/wdtn/wdt/pq/prv/p/psn/psv/ps/pr): 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 pqv/pqn/prn/wdtn/wdt/pq/prv/p/psn/psv/ps/pr): 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 top result for "nationality" is `wd:P27`, which stands for "country of citizenship". This seems to be the correct property to use. Now, let's construct a simple SPARQL query to find Steve Nash's nationality.

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

I will now execute this query to get the result.

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

[Assistant]
The query returned two nationalities for Steve Nash: the United Kingdom and Canada. To provide a clear answer, I will include both in the response.

Here is the final SPARQL query and the answer:

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

Steve Nash's nationalities are the United Kingdom (wd:Q145) and Canada (wd:Q16).

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

[Tool] Stopped generation process

[User]
Feedback (status=done):
The output is correct and complete. The SPARQL query returns the correct nationalities of Steve Nash, which are the United Kingdom and Canada.