PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT DISTINCT ?occupation WHERE {
  wd:Q587156 wdt:P106 ?occupation .
  OPTIONAL {
    ?occupation rdfs:label ?occupationLabel .
    FILTER ( LANG( ?occupationLabel ) = "en" )
  }
}

Kim Richards was a television actor, film actor, and actor.

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

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

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

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

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

[User] what was kim richards in?

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

[Tool]
Example 1:
Question:
what is there to do in palm springs?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x wdt:P31 / wdt:P279 * wd:Q570116 ; wdt:P131 wd:Q488004 .
}

Using entities:
Palm Springs, also known as Palm City, Palm Springs, CA, Palm Springs, California (wd:Q488004): resort city in Riverside County, southern California, United States
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)

Example 2:
Question:
who was the president of the united states during ww2?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x p:P39 ?p .
  ?p ps:P39 wd:Q11696 ; pq:P580 ?y .
  wd:Q362 wdt:P580 ?w ; wdt:P582 ?v .
  FILTER ( ( ( ?y >= ?w ) && ( ?y <= ?v ) ) )
}

Using entities:
President of the United States, also known as US President, U.S. President, United States President, the president of the United States, President of the U.S. (wd:Q11696): head of state and head of government of the United States of America
World War II, also known as 2nd World War, WWII, WW II, WW2, WW 2 (wd:Q362): 1939–1945 global conflict

Using properties:
position held, also known as function, held position, holds position, job, office held (wd:P39 as p/ps): subject currently or formerly holds the object position or public office
start time, also known as start date, since, valid, join time, joined (wd:P580 as wdt/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 wdt): moment when an entity ceases to exist and a statement stops being entirely valid or no longer be true, point in time

Example 3:
Question:
who is jeremy sumpter?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q316964 wdt:P106 ?x .
}

Using entities:
Jeremy Sumpter, also known as Jeremy Robert Myron Sumpter (wd:Q316964): television actor, American actor, child actor, film actor, actor, model

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] Based on the examples, it seems like we need to find out what roles or occupations Kim Richards had. Let's first search for the entity "Kim Richards".

[Tool]
Top 10 entity alternatives:
1. Kim Richards, also known as Kimberley Richards, Kim Erica Richards (wd:Q587156): American actress and television personality (born 1964), television actor, film actor, actor
2. Kim Richards, also known as Kim Elizabeth Richards (wd:Q44115773): Australian politician, politician
3. Kim Richards, also known as NanoKim, NanoSounds (wd:Q123745576): content creator, Twitch streamer
4. Kim Richards (wd:Q76151754): Peerage person ID=566462
5. Kim Richardson, also known as Kimberly Ann Richardson (wd:Q19668126): Canadian actor and singer, jazz musician, actor
6. Kim Lahaie Richards, also known as Kim Lahaie (wd:Q26276511): American drag racer, crew chief, racing automobile driver
7. Kim Michele Richardson (wd:Q100598285): American writer, literary critic, writer
8. Sibel Kekilli, also known as Dilara, Sybel, Kim (wd:Q63682): German actress, actor
9. Kim, also known as Kim, CO (wd:Q2275070): Statutory Town in Las Animas County, Colorado, United States
10. Kim (wd:Q589868): picaresque novel by Rudyard Kipling

[Assistant]
The top result for "Kim Richards" is the American actress and television personality, which matches our context. We'll use this entity (wd:Q587156) to find out what roles or occupations she had.

Let's look at the properties of this entity to identify her roles or occupations.

[Tool]
Top 10 property alternatives:
1. occupation, also known as job, work, vocation, profession, employment (wd:P106 as wdt/p): occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)
2. country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as wdt/p): the object is a country that recognizes the subject as its citizen, country
3. 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
4. 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
5. 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
6. 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
7. 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)
8. 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)
9. languages spoken, written or signed, also known as language of expression, language, wrote language, writes language, uses language (wd:P1412 as wdt/p): language(s) that a person or a people speaks, writes or signs, including the native language(s)
10. given name, also known as name, proper name, personal name, middle name, forename (wd:P735 as wdt/p): first name or another given name of this person; values used with the property should not link disambiguations nor family names, name

No other items found

[Assistant]
The property "occupation" (wdt:P106) is the most relevant for finding out what roles or occupations Kim Richards had. Let's construct a SPARQL query to retrieve her occupations.

```sparql
SELECT DISTINCT ?occupation WHERE {
  wd:Q587156 wdt:P106 ?occupation .
  OPTIONAL { ?occupation rdfs:label ?occupationLabel . FILTER(LANG(?occupationLabel) = "en") }
}
```

This query will return the occupations of Kim Richards along with their English labels if available.

Let's execute this query.

[Tool]
Got 3 rows and 1 column:
| occupation                      |
| ------------------------------- |
| television actor (wd:Q10798782) |
| film actor (wd:Q10800557)       |
| actor (wd:Q33999)               |

[Assistant]
The SPARQL query has returned the occupations of Kim Richards:

- Television actor (wd:Q10798782)
- Film actor (wd:Q10800557)
- Actor (wd:Q33999)

These results indicate that Kim Richards was involved in acting, specifically in television and film.

Here is the final SPARQL query and the answer:

```sparql
SELECT DISTINCT ?occupation WHERE {
  wd:Q587156 wdt:P106 ?occupation .
  OPTIONAL { ?occupation rdfs:label ?occupationLabel . FILTER(LANG(?occupationLabel) = "en") }
}
```

Answer: Kim Richards was a television actor, film actor, and actor.

[Tool] Stopped generation process


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?writingSystem ?label WHERE {
  wd:Q8201 rdfs:label ?label .
  BIND( wd:Q8201 AS ?writingSystem )
}

Got 154 rows and 2 columns, showing the first 5 and last 5 rows below:
| writingSystem                 | label                 |
| ----------------------------- | --------------------- |
| Chinese characters (wd:Q8201) | aksara Cina (bjn)     |
| Chinese characters (wd:Q8201) | Aksara Cinten (jv)    |
| Chinese characters (wd:Q8201) | Aksara Tionghoa (su)  |
| Chinese characters (wd:Q8201) | Alfabet cinesc (lld)  |
| Chinese characters (wd:Q8201) | alfabeto cinezo (vec) |
| ...                           | ...                   |
| Chinese characters (wd:Q8201) | 漢字 (yue)              |
| Chinese characters (wd:Q8201) | 漢字 (zh-hant)          |
| Chinese characters (wd:Q8201) | 漢字 (zh-hk)            |
| Chinese characters (wd:Q8201) | 漢字 (zh-mo)            |
| Chinese characters (wd:Q8201) | 漢字 (zh-tw)            |

The Chinese writing system is called '漢字' (hanzi).

[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 do you call the chinese writing system?

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

[Tool]
Example 1:
Question:
where do the broncos play?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q223507 wdt:P115 ?x .
}

Using entities:
Denver Broncos, also known as Broncos (wd:Q223507): National Football League franchise in Denver, Colorado

Using properties:
home venue, also known as home water, venue, stadium, home ground, home field (wd:P115 as wdt): home stadium or venue of a sports team or applicable performing arts organization, location

Example 2:
Question:
what is the san francisco giants mascot?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q308966 wdt:P822 ?x .
}

Using entities:
San Francisco Giants, also known as Giants, Gothams, New York Giants, New York Gothams, SFG (wd:Q308966): baseball team and Major League Baseball franchise in San Francisco, California, United States

Using properties:
mascot (wd:P822 as wdt): mascot of an organization, e.g. a sports team or university

Example 3:
Question:
where is washington d.c. at?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q61 wdt:P131 ?x .
}

Using entities:
Washington, D.C., also known as D.C. Washington, District of Columbia, The District, Washington, District of Columbia (wd:Q61): capital city of the United States of America

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

[Assistant] None of these examples directly relate to the Chinese writing system, but we can use them as a reference for structuring our query. Let's first search for the entity representing the Chinese writing system.

[Tool]
Top 10 entity alternatives:
1. Journal of Chinese Writing Systems (wd:Q58234452): journal
2. Letter-word Phrases and Chinese Writing System (wd:Q120662500): scholarly article in Journal of Xiamen University (Arts & Social Sciences) no. 6, 2010
3. Image-based anti-interference ro...Chinese character writing system (wd:Q129332745): scholarly article
4. Bibliography of the Chinese language and writing system (wd:Q125242720)
5. writing system, also known as wenzi, ven-tsee, script, graphematics (wd:Q8192): any conventional method of visually representing verbal or signed communication
6. Chinese system, also known as Chinese operating system (wd:Q118876973): program that hooks into an operating system to add the ability to display and input CJK characters
7. Conjectures on Creative Writing ...iplinary System of Chinese Style (wd:Q118678085)
8. Chinese-English biliteracy acqui...uage and writing system transfer (wd:Q52040278): scientific article published on 30 December 2004
9. Chinese writing (wd:Q125357998): Book about Chinese palaeography
10. The Chinese-based writing system of the Zhuang language (wd:Q56915490): article

[Assistant] From the search results, the most relevant entity seems to be "writing system" (wd:Q8192), which is described as "any conventional method of visually representing verbal or signed communication". However, this is a general term for writing systems. We need to find a specific entity for the Chinese writing system. Let's try searching again with a more specific query.

[Tool]
Top 10 entity alternatives:
1. Chinese characters, also known as wenzi, ven-tsee, traditional Vietnamese characters, traditional Korean characters, sinographs (wd:Q8201): logographic writing system with Han origin used in the Sinospher...r Chinese, Japanese, Korean and traditional Vietnamese languages
2. Chinese Script* (wd:Q119947963): painting by unknown artist, Division of Archaeology, University of Cambridge
3. simplified Chinese characters, also known as simplified Chinese script, 簡化字, 简化字, simplified Hanzi, simplified Han characters (wd:Q185614): standardized Chinese characters used in Mainland China, Malaysia and Singapore
4. Chinese cursive script, also known as cǎoshū, grass script, cursive script (wd:Q607543): handwriting, traditional calligraphic script style of East Asian orthography
5. Chinese script style, also known as Chinese script styles (wd:Q11059241): style of writing Chinese characters
6. Chinese script reform (wd:Q2894150)
7. Chinese family of scripts, also known as Chinese scripts (wd:Q117285848): family of writing systems descended from the Chinese oracle bone script
8. Design for writing-paper for Chinese script (wd:Q65574237): print in the National Gallery of Art (NGA 54223)
9. Sound and Script in Chinese Diaspora (wd:Q56455917): article
10. Chinese Buddhist Scriptures and Indian Philosophy (wd:Q119434134)

[Assistant]
The most relevant entity from the search results is "Chinese characters" (wd:Q8201), which is described as a logographic writing system with Han origin used in the Sinosphere. This seems to be the correct entity for the Chinese writing system.

Now, let's construct a simple SPARQL query to confirm this and retrieve the label for the Chinese writing system.

[Tool]
Got 154 rows and 2 columns, showing the first 5 and last 5 rows below:
| writingSystem                 | label                 |
| ----------------------------- | --------------------- |
| Chinese characters (wd:Q8201) | aksara Cina (bjn)     |
| Chinese characters (wd:Q8201) | Aksara Cinten (jv)    |
| Chinese characters (wd:Q8201) | Aksara Tionghoa (su)  |
| Chinese characters (wd:Q8201) | Alfabet cinesc (lld)  |
| Chinese characters (wd:Q8201) | alfabeto cinezo (vec) |
| ...                           | ...                   |
| Chinese characters (wd:Q8201) | 漢字 (yue)              |
| Chinese characters (wd:Q8201) | 漢字 (zh-hant)          |
| Chinese characters (wd:Q8201) | 漢字 (zh-hk)            |
| Chinese characters (wd:Q8201) | 漢字 (zh-mo)            |
| Chinese characters (wd:Q8201) | 漢字 (zh-tw)            |

[Assistant]
The query confirms that "Chinese characters" (wd:Q8201) is the correct entity for the Chinese writing system. The labels provided in various languages include "漢字" (hanzi) in Chinese, which is the term commonly used to refer to the Chinese writing system.

Therefore, the Chinese writing system is called "漢字" (hanzi).

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

[Tool] Stopped generation process


PREFIX pq: <http://www.wikidata.org/prop/qualifier/>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX p: <http://www.wikidata.org/prop/>
PREFIX ps: <http://www.wikidata.org/prop/statement/>
PREFIX xsd: <http://www.w3.org/2001/XMLSchema#>
SELECT ?coach WHERE {
  wd:Q330120 p:P286 ?stmt .
  ?stmt ps:P286 ?coach .
  ?stmt pq:P580 ?startTime .
  ?stmt pq:P582 ?endTime .
  FILTER ( ?startTime <= "2013-01-01T00:00:00Z" ^^ xsd:dateTime && "2013-01-01T00:00:00Z" ^^ xsd:dateTime <= ?endTime )
}

Ron Rivera

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

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

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

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

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

[User] who will coach carolina panthers in 2013?

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

[Tool]
Example 1:
Question:
what sport does rebecca adlington compete in?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q49287 wdt:P641 ?x .
}

Using entities:
Rebecca Adlington, also known as Becky Adlington (wd:Q49287): British swimmer, Olympic gold medallist, swimmer

Using properties:
sport, also known as play, plays, sport played, sports (wd:P641 as wdt): sport that the subject participates or participated in or is associated with

Example 2:
Question:
who did stephenie meyer play in twilight?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q160071 p:P161 ?p .
  ?p ps:P161 wd:Q160219 ; pq:P453 ?x .
}

Using entities:
Twilight (wd:Q160071): 2008 American film directed by Catherine Hardwicke
Stephenie Meyer, also known as Stephenie Morgan Meyer (wd:Q160219): science fiction writer, film screenwriter, children's writer, American author, businessperson, film producer, screenwriter, entrepreneur, novelist, writer, actor

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

Example 3:
Question:
in what timezone is arizona?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q816 wdt:P421 ?x .
}

Using entities:
Arizona, also known as Ariz., US-AZ, The Grand Canyon State, State of Arizona, Grand Canyon State (wd:Q816): state of the United States of America

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

[Assistant] Based on the examples, we need to identify the entity for the Carolina Panthers and the property for the coach in 2013. Let's start by searching for the entity "Carolina Panthers".

[Tool]
Top 10 entity alternatives:
1. Carolina Panthers (wd:Q330120): American football team
2. history of the Carolina Panthers, also known as Carolina Panthers history, the Carolina Panthers history (wd:Q5869201): aspect of history
3. Carolina Panthers Cheerleaders (wd:Q130385213): cheerleading squad of the Carolina Panthers
4. 2021 Carolina Panthers season (wd:Q104869609): 27th season in franchise history
5. 2022 Carolina Panthers season (wd:Q110445399): 28th season in franchise history
6. 2020 Carolina Panthers season (wd:Q80995958): 26th season in franchise history
7. 2018 Carolina Panthers season (wd:Q48843395): 24th season in franchise history
8. 2015 Carolina Panthers season (wd:Q18701993): NFL team 21st season(lost Super Bowl)
9. 2019 Carolina Panthers season (wd:Q60525825): 25th season in franchise history
10. 2023 Carolina Panthers season (wd:Q116170055): 29th season in franchise history

[Assistant] The correct entity for the Carolina Panthers is `wd:Q330120`. Now, let's find the property that represents the coach of a team. We can search for the property "coach" to see if it exists and how it is used.

[Tool]
Top 10 property alternatives:
1. head coach, also known as team manager, trainer, senior coach, manager, coached by (wd:P286 as wdt/wdtn/prn/pq/pqv/pqn/p/ps/pr/psn/prv/psv): on-field manager or head coach of a sports club (not to be confu...eneral manager P505, which is not a coaching position) or person
2. coach of sports team, also known as trainer of sports team, club manager of sports team, trainer of, team manager of sports team, team manager of (wd:P6087 as wdt/wdtn/prn/pq/pqv/pqn/p/ps/pr/psn/prv/psv): sports club or team for which this person is or was on-field manager or coach
3. PlaymakerStats.com coach ID, also known as PlaymakerStats.com manager ID, TheFinalBall coach ID (wd:P6316 as wdt/wdtn/prn/pq/pqv/pqn/p/ps/pr/psn/prv/psv): identifier for an association football (soccer) coach at PlaymakerStats.com (formerly TheFinalBall.com)
4. LNB Coach id, also known as LNB Pro A coach ID (wd:P6743 as wdt/wdtn/prn/pq/pqv/pqn/p/ps/pr/psn/prv/psv): identifier for a coach in the French basketball championship
5. trained by, also known as personal trainer, trainer (wd:P10449 as wdt/wdtn/prn/pq/pqv/pqn/p/ps/pr/psn/prv/psv): personal trainer of the athlete, student of
6. LevskiSofia.info coach ID (wd:P6410 as wdt/wdtn/prn/pq/pqv/pqn/p/ps/pr/psn/prv/psv): identifier for a coach at the LevskiSofia.info
7. TuttoCalciatori.net coach ID (wd:P7035 as wdt/wdtn/prn/pq/pqv/pqn/p/ps/pr/psn/prv/psv): identifier of a football coach in the website TuttoCalciatori.net
8. Soccerdonna coach ID, also known as Soccerdonna trainer ID (wd:P8134 as wdt/wdtn/prn/pq/pqv/pqn/p/ps/pr/psn/prv/psv): identifier for a coach at the Soccerdonna
9. LegaBasket.it coach ID (wd:P5612 as wdt/wdtn/prn/pq/pqv/pqn/p/ps/pr/psn/prv/psv): identifier for a coach at legabasket.it
10. VBL people ID, also known as VBL coach ID, VBL player ID, VBL staff ID (wd:P4298 as wdt/wdtn/prn/pq/pqv/pqn/p/ps/pr/psn/prv/psv): identifier for a volleyball player on the website of the German Volleyball Federation

[Assistant] The property `wd:P286` (head coach) seems to be the most relevant for our query. Next, we need to check if this property is used for the Carolina Panthers (`wd:Q330120`) and if there is a way to filter by the year 2013. Let's list the triples for the Carolina Panthers to see if the head coach property is used and if there are any qualifiers for the year.

[Tool]
Got 1 row and 3 columns:
| subject                        | property              | object                      |
| ------------------------------ | --------------------- | --------------------------- |
| Carolina Panthers (wd:Q330120) | head coach (wdt:P286) | Dave Canales (wd:Q47456134) |

[Assistant] The result shows that the head coach of the Carolina Panthers is Dave Canales, but it doesn't specify the year. To get the coach for the year 2013, we need to look for a qualifier that specifies the year. Let's search for the property `wd:P286` with the qualifier `wdt:P580` (start time) or `wdt:P585` (point in time) to filter by the year 2013.

[Tool]
Top 10 property alternatives:
1. head coach, also known as team manager, trainer, senior coach, manager, coached by (wd:P286 as wdt/p): on-field manager or head coach of a sports club (not to be confu...eneral manager P505, which is not a coaching position) or person
2. sport, also known as play, plays, sport played, sports (wd:P641 as wdt/p): sport that the subject participates or participated in or is associated with
3. league or competition, also known as tournament, sports league, division, cup, competition (wd:P118 as wdt/p): league or competition in which team or player has played, or in which an event occurs, participant in
4. owned by, also known as belongs to, stockholders, stockholder, shareholders, shareholder (wd:P127 as wdt/p): owner of the subject
5. category for members of a team, also known as category for players, category for team members (wd:P6112 as wdt/p): Wikimedia category for players playing for a sports team, topic's main category
6. Flashscore.com team ID, also known as flashscore.com/team/, FlashScore.com team ID, https://www.flashscore.com/team/, www.flashscore.com/team/ (wd:P7876 as wdt/p): identifier for a sports team in the FlashScore.com database
7. country, also known as sovereign state, state, land, host country (wd:P17 as wdt/p): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
8. 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
9. official website, also known as site (official), home page, site official, URL, URL (official) (wd:P856 as wdt/p): 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
10. owner of, also known as owns, owns property, shareholder of (wd:P1830 as wdt/p): entities owned by the subject

No other items found

[Assistant] It seems that the search for the property "coach 2013" did not yield any specific results. However, we can try to construct a SPARQL query that includes the `wdt:P286` property and filters by the year 2013 using the `pq:P580` (start time) or `pq:P585` (point in time) qualifier. Let's try this approach.

[Tool] Got no rows and 1 columns

[Assistant] It appears that there are no results when filtering by the start time (`pq:P580`). Let's try using the point in time (`pq:P585`) qualifier instead to see if we can get the coach for the year 2013.

[Tool] Got no rows and 1 columns

[Assistant]
It seems that using the point in time (`pq:P585`) qualifier also did not yield any results. This suggests that the data might not be structured in a way that includes the year as a qualifier for the head coach property.

Let's try a different approach. We can look for the specific seasons of the Carolina Panthers and see if the head coach is mentioned for the 2013 season. We can search for the entity "2013 Carolina Panthers season" and then check if the head coach is listed for that season.

First, let's search for the entity "2013 Carolina Panthers season".

[Tool]
Top 10 entity alternatives:
1. 2013 Carolina Panthers season (wd:Q2657368): NFL team season
2. 2021 Carolina Panthers season (wd:Q104869609): 27th season in franchise history
3. 2022 Carolina Panthers season (wd:Q110445399): 28th season in franchise history
4. 2020 Carolina Panthers season (wd:Q80995958): 26th season in franchise history
5. 2018 Carolina Panthers season (wd:Q48843395): 24th season in franchise history
6. 2015 Carolina Panthers season (wd:Q18701993): NFL team 21st season(lost Super Bowl)
7. 2019 Carolina Panthers season (wd:Q60525825): 25th season in franchise history
8. 2023 Carolina Panthers season (wd:Q116170055): 29th season in franchise history
9. 2024 Carolina Panthers season (wd:Q124167262): 30th season in franchise history
10. 2009 Carolina Panthers season (wd:Q4613485): NFL team season

[Assistant] The correct entity for the 2013 Carolina Panthers season is `wd:Q2657368`. Now, let's check if the head coach is listed for this specific season. We can use the `wdt:P286` property to find the head coach for the 2013 season.

[Tool] Got no rows and 1 columns

[Assistant]
It seems that the head coach is not directly linked to the 2013 Carolina Panthers season entity. Let's try another approach by looking at the statements for the 2013 season and see if there are any qualifiers or additional properties that might provide the head coach information.

We can list the triples for the 2013 Carolina Panthers season to see if there are any relevant properties or qualifiers.

[Tool]
Got 36 rows and 3 columns, showing the first 10 rows below:
| subject                                     | property                           | object                                       |
| ------------------------------------------- | ---------------------------------- | -------------------------------------------- |
| 2013 Carolina Panthers season (wd:Q2657368) | instance of (wdt:P31)              | American football team season (wd:Q26895936) |
| 2013 Carolina Panthers season (wd:Q2657368) | country (wdt:P17)                  | United States (wd:Q30)                       |
| 2013 Carolina Panthers season (wd:Q2657368) | Commons category (wdt:P373)        | 2013 Carolina Panthers season                |
| 2013 Carolina Panthers season (wd:Q2657368) | sport (wdt:P641)                   | American football (wd:Q41323)                |
| 2013 Carolina Panthers season (wd:Q2657368) | point in time (wdt:P585)           | 2013-01-01T00:00:00Z (xsd:dateTime)          |
| 2013 Carolina Panthers season (wd:Q2657368) | season of club or team (wdt:P5138) | Carolina Panthers (wd:Q330120)               |
| 2013 Carolina Panthers season (wd:Q2657368) | Freebase ID (wdt:P646)             | /m/0pb4fb4                                   |
| 2013 Carolina Panthers season (wd:Q2657368) | schema:description                 | NFL team season (en)                         |
| 2013 Carolina Panthers season (wd:Q2657368) | schema:name                        | 2013 Carolina Panthers season (en)           |
| 2013 Carolina Panthers season (wd:Q2657368) | rdf:type                           | wikibase:Item                                |
| ...                                         | ...                                | ...                                          |

[Assistant]
From the list of triples, we can see that the 2013 Carolina Panthers season is linked to the Carolina Panthers team via the `wdt:P5138` property (season of club or team). However, the head coach is not directly listed for this season.

Given this, let's try to find the head coach of the Carolina Panthers during the 2013 season by looking at the team's head coach and checking if there are any qualifiers that specify the year 2013. We can use the `wdt:P286` property and filter by the year 2013 using the `pq:P580` (start time) or `pq:P585` (point in time) qualifier.

Let's try the `pq:P585` (point in time) qualifier again, but this time for the Carolina Panthers team itself.

[Tool] Got no rows and 1 columns

[Assistant]
It seems that the head coach for the Carolina Panthers in 2013 is not directly linked with a point in time qualifier. Given this, we might need to look at the historical data for the team's head coaches and manually verify the year.

Let's list the head coaches of the Carolina Panthers and see if we can find the coach for 2013 by examining the start and end times of their tenure.

[Tool]
Got 8 rows and 3 columns:
| coach                       | startTime                           | endTime                             |
| --------------------------- | ----------------------------------- | ----------------------------------- |
| Ron Rivera (wd:Q1991889)    | 2011-01-01T00:00:00Z (xsd:dateTime) | 2019-01-01T00:00:00Z (xsd:dateTime) |
| Perry Fewell (wd:Q7169776)  | 2019-01-01T00:00:00Z (xsd:dateTime) | 2019-01-01T00:00:00Z (xsd:dateTime) |
| Chris Tabor (wd:Q57242442)  | 2023-01-01T00:00:00Z (xsd:dateTime) | 2023-01-01T00:00:00Z (xsd:dateTime) |
| Steven Wilks (wd:Q7615391)  | 2022-01-01T00:00:00Z (xsd:dateTime) | 2022-01-01T00:00:00Z (xsd:dateTime) |
| John Fox (wd:Q719030)       | 2002-01-01T00:00:00Z (xsd:dateTime) | 2010-01-01T00:00:00Z (xsd:dateTime) |
| Dave Canales (wd:Q47456134) | 2024-01-01T00:00:00Z (xsd:dateTime) |                                     |
| Matt Rhule (wd:Q14950994)   | 2020-01-01T00:00:00Z (xsd:dateTime) | 2022-01-01T00:00:00Z (xsd:dateTime) |
| Frank Reich (wd:Q5489177)   | 2023-01-01T00:00:00Z (xsd:dateTime) | 2023-01-01T00:00:00Z (xsd:dateTime) |

[Assistant]
From the results, we can see that Ron Rivera was the head coach of the Carolina Panthers from January 1, 2011, to January 1, 2019. This period includes the year 2013.

Therefore, the head coach of the Carolina Panthers in 2013 was Ron Rivera.

Here is the final SPARQL query and answer:

```sparql
SELECT ?coach WHERE {
  wd:Q330120 p:P286 ?stmt .
  ?stmt ps:P286 ?coach .
  ?stmt pq:P580 ?startTime .
  ?stmt pq:P582 ?endTime .
  FILTER(?startTime <= "2013-01-01T00:00:00Z"^^xsd:dateTime && "2013-01-01T00:00:00Z"^^xsd:dateTime <= ?endTime)
}
```

The answer is Ron Rivera.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?spouse ?spouseLabel WHERE {
  wd:Q42869 wdt:P26 ?spouse .
  OPTIONAL {
    ?spouse rdfs:label ?spouseLabel .
    FILTER ( LANG( ?spouseLabel ) = "en" )
  }
}

Nicolas Cage is married to Riko Shibata.

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

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

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

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

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

[User] who is nicolas cage married too?

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

[Tool]
Example 1:
Question:
what are the official languages 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:
who killed harvey milk?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q17141 wdt:P157 ?x .
}

Using entities:
Harvey Milk, also known as Harvey Bernard Milk (wd:Q17141): American gay rights activist (1930–1978), human rights activist, LGBTQ rights activist, naval officer, politician

Using properties:
killed by, also known as slaughtered by, slain by, shot dead by, murderer, murdered by (wd:P157 as wdt): person or organization who killed the subject, significant person

Example 3:
Question:
where was alice paul born?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q127328 wdt:P19 ?x .
}

Using entities:
Alice Paul, also known as Alice Stokes Paul (wd:Q127328): American suffragist, feminist, and activist (1885–1977), women's rights activist, suffragette, jurist

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, we can see that to answer the question "Who is Nicolas Cage married to?", we need to find the entity for Nicolas Cage and then use the property for spouse or partner. Let's first search for the entity representing Nicolas Cage.

[Tool]
Top 10 entity alternatives:
1. Nicolas Cage, also known as Nicolas Coppola, Nicolas Kim Coppola, Nic Cage (wd:Q42869): television presenter, television producer, executive producer, character actor, American actor, film director, film producer, screenwriter, voice actor, film actor, director, writer, actor
2. Nicolas Cage/Bobby Brown, also known as Saturday Night Live S18E1, Saturday Night Live, season 18 episode 1 (wd:Q110035758): episode of Saturday Night Live (S18 E1)
3. Weekend Update: Nicolas Cage (wd:Q110060114): sketch from Saturday Night Live
4. Cage's Kiss: The Nicolas Cage Podcast (wd:Q110580467): podcast
5. Cage Rage - A Nicolas Cage Podcast (wd:Q110575223): podcast
6. Weekend Update: Nicolas Cage and Bradley Cooper (wd:Q110060014): sketch from Saturday Night Live
7. cage (wd:Q129211): enclosure used to confine, contain or protect something or someone
8. China Zorrilla, also known as Nicolás (wd:Q458175): Uruguayan actress (1922–2014), stage actor, film actor, actor
9. Frida Kalho, also known as Nicolás (wd:Q458175): Uruguayan actress (1922–2014), stage actor, film actor, actor
10. The Cage, also known as Cage, Cage, The, Pilot: The Cage (wd:Q20909): 1986 episode of Star Trek: The Original Series directed by Robert Butler

[Assistant] The correct entity for Nicolas Cage is `wd:Q42869`. Now, let's find the property that represents marriage or spouse. We can use the `search_property` function to look for relevant properties.

[Tool]
Top 10 property alternatives:
1. spouse, also known as married partner, married to, marry, partner, spouses (wd:P26 as wdt/wdtn/prn/pq/pqv/pqn/p/ps/pr/psn/prv/psv): the subject has the object as their spouse (husband, wife, partn...etc.). Use "unmarried partner" (P451) for non-married companions, significant person, relative
2. relative, also known as relatives, grandparent, relation, non-binary parent, niece (wd:P1038 as wdt/wdtn/prn/pq/pqv/pqn/p/ps/pr/psn/prv/psv): family member (qualify with "kinship to subject", P1039; for direct family member please use specific property), significant person
3. unmarried partner, also known as romantic partner, partner of, partners, posslq, relationship (wd:P451 as wdt/wdtn/prn/pq/pqv/pqn/p/ps/pr/psn/prv/psv): someone with whom the person is in a relationship without being married. Use "spouse" (P26) for married couples, significant person
4. married name, also known as full name (married) (wd:P2562 as wdt/wdtn/prn/pq/pqv/pqn/p/ps/pr/psn/prv/psv): name or surname adopted by a person upon marriage, name
5. place of marriage, also known as marriage location, wedding location, wed at, married in, married at (wd:P2842 as wdt/wdtn/prn/pq/pqv/pqn/p/ps/pr/psn/prv/psv): location where the marriage was celebrated. Use as qualifier for property "spouse" (P26), significant place
6. birth name, also known as née, name at birth, name before marriage, ne, né (wd:P1477 as wdt/wdtn/prn/pq/pqv/pqn/p/ps/pr/psn/prv/psv): full name of a person at birth, if different from their current, generally used name, name
7. connects with, also known as contacts, couples with, intersects at grade, links to, mates with (wd:P2789 as wdt/wdtn/prn/pq/pqv/pqn/p/ps/pr/psn/prv/psv): item with which the item is physically connected, physically interacts with
8. companion of, also known as has astronomical companion, has companion, companion, astronomic companion of, astronomic companion (wd:P399 as wdt/wdtn/prn/pq/pqv/pqn/p/ps/pr/psn/prv/psv): two or more astronomic bodies of the same type relating to each other
9. end time, also known as ends, stop time, endtime, fall date, ineffective (wd:P582 as wdt/wdtn/prn/pq/pqv/pqn/p/ps/pr/psn/prv/psv): moment when an entity ceases to exist and a statement stops being entirely valid or no longer be true, point in time
10. relation (wd:P2309 as wdt/wdtn/prn/pq/pqv/pqn/p/ps/pr/psn/prv/psv): qualifier to define a property constraint in combination with P2...h the property "relative" is "type of kinship" (P1039), not this

[Assistant]
The correct property for spouse is `wd:P26`. Now, let's construct a simple SPARQL query to find out who Nicolas Cage is married to.

```sparql
SELECT ?spouse WHERE {
  wd:Q42869 wdt:P26 ?spouse .
}
```

I will execute this query to get the result.

[Tool]
Got 1 row and 1 column:
| spouse                       |
| ---------------------------- |
| Riko Shibata (wd:Q109355504) |

[Assistant]
The SPARQL query returned that Nicolas Cage is married to Riko Shibata. To provide a more complete answer, let's include the label of Riko Shibata in the query.

```sparql
SELECT ?spouse ?spouseLabel WHERE {
  wd:Q42869 wdt:P26 ?spouse .
  OPTIONAL { ?spouse rdfs:label ?spouseLabel . FILTER(LANG(?spouseLabel) = "en") }
}
```

I will execute this updated query to get the label.

[Tool]
Got 1 row and 2 columns:
| spouse                       | spouseLabel       |
| ---------------------------- | ----------------- |
| Riko Shibata (wd:Q109355504) | Riko Shibata (en) |

[Assistant]
The SPARQL query confirms that Nicolas Cage is married to Riko Shibata.

Here is the final SPARQL query and the answer:

```sparql
SELECT ?spouse ?spouseLabel WHERE {
  wd:Q42869 wdt:P26 ?spouse .
  OPTIONAL { ?spouse rdfs:label ?spouseLabel . FILTER(LANG(?spouseLabel) = "en") }
}
```

Answer: Nicolas Cage is married to Riko Shibata.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?birthPlace ?birthPlaceLabel WHERE {
  wd:Q206939 wdt:P19 ?birthPlace .
  OPTIONAL {
    ?birthPlace rdfs:label ?birthPlaceLabel .
    FILTER ( LANG( ?birthPlaceLabel ) = 'en' )
  }
}

Got 1 row and 2 columns:
| birthPlace      | birthPlaceLabel |
| --------------- | --------------- |
| London (wd:Q84) | London (en)     |

Elvis Costello was born in London.

[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 was elvis costello born?

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

[Tool]
Example 1:
Question:
who did kat graham play in parent trap?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q729782 p:P161 ?p .
  ?p ps:P161 wd:Q151118 ; pq:P453 ?x .
}

Using entities:
Kat Graham, also known as Katerina Graham, Katerina Alexandre Hartford Graham (wd:Q151118): American actress and singer (born 1989), executive producer, singer-songwriter, television actor, record producer, philanthropist, voice actor, film actor, dancer
The Parent Trap, also known as Parent Trap (wd:Q729782): 1998 romantic comedy film directed by Nancy Meyers

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

Example 2:
Question:
what kind government does canada have?

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

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

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

Example 3:
Question:
where is the sistine chapel by michelangelo?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q2943 wdt:P131 ?x .
}

Using entities:
Sistine Chapel (wd:Q2943): chapel in the Apostolic Palace, Vatican City

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

[Assistant] Based on the examples, we need to identify the entity for Elvis Costello and the property for place of birth. Let's start by searching for Elvis Costello.

[Tool]
Top 10 entity alternatives:
1. Elvis Costello, also known as Declan MacManus, Declan Patrick MacManus (wd:Q206939): English singer-songwriter (born 1954), record producer, songwriter, guitarist, singer
2. Elvis Costello (wd:Q107119978): lithograph at the Museum of Modern Art; unknown designer
3. Elvis Costello (wd:Q125462686): written work by Eduardo Margaretto Kohrmann
4. Elvis Costello (wd:Q125462696): 1993 edition of written work by Eduardo Margaretto Kohrmann
5. Elvis Costello (wd:Q28052324): painting by Adam Birtwistle
6. Spectacle: Elvis Costello with... (wd:Q7575075): television series
7. Elvis Costello Band concert (wd:Q99322922): Elvis Costello Band concert performed during Montreux Jazz Festival the 1989-07-11
8. Elvis Costello Solo concert (wd:Q99429372): Elvis Costello Solo concert performed during Montreux Jazz Festival the 1989-07-11
9. Elvis Costello & the Attractions, also known as Elvis Costello and the Attractions, Nick Lowe And His Sound (wd:Q7714866): UK musical group
10. Elvis Costello with Steve Nieve (wd:Q105091759): print by Jenny Gill

[Assistant] The first result is the correct entity for Elvis Costello. Now let's search for the property for place of birth.

[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/wdtn/prn/pq/pqv/pqn/p/ps/pr/psn/prv/psv): 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/wdtn/prn/pq/pqv/pqn/p/ps/pr/psn/prv/psv): date on which the subject was born, inception
3. country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as wdt/wdtn/prn/pq/pqv/pqn/p/ps/pr/psn/prv/psv): the object is a country that recognizes the subject as its citizen, country
4. birthday, also known as b-day, bday, birth day (wd:P3150 as wdt/wdtn/prn/pq/pqv/pqn/p/ps/pr/psn/prv/psv): item for day and month on which the subject was born. Used when full "date of birth" (P569) isn't known., date of birth
5. birth name, also known as née, name at birth, name before marriage, ne, né (wd:P1477 as wdt/wdtn/prn/pq/pqv/pqn/p/ps/pr/psn/prv/psv): full name of a person at birth, if different from their current, generally used name, name
6. category for people born here, also known as category for place of birth, category of people born here (wd:P1464 as wdt/wdtn/prn/pq/pqv/pqn/p/ps/pr/psn/prv/psv): category item that groups people born in this place, related category
7. valid in place, also known as applies to country, applies to location, applies to place, country, true in (wd:P3005 as wdt/wdtn/prn/pq/pqv/pqn/p/ps/pr/psn/prv/psv): place where a statement is valid, applies to part
8. country of origin, also known as origin country, place of origin, originates from, country, CoO (wd:P495 as wdt/wdtn/prn/pq/pqv/pqn/p/ps/pr/psn/prv/psv): country of origin of this item (creative work, food, phrase, product, etc.), significant place, country
9. country, also known as sovereign state, state, land, host country (wd:P17 as wdt/wdtn/prn/pq/pqv/pqn/p/ps/pr/psn/prv/psv): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
10. commemorates, also known as monument to, memorial to, memorializes, marks, in memory of (wd:P547 as wdt/wdtn/prn/pq/pqv/pqn/p/ps/pr/psn/prv/psv): what the place, monument, memorial, or holiday, commemorates, main subject

[Assistant] The first result is the correct property for place of birth. Now we can construct a simple SPARQL query to find out where Elvis Costello was born.

[Tool]
Got 1 row and 1 column:
| birthPlace      |
| --------------- |
| London (wd:Q84) |

[Assistant] Elvis Costello was born in London. To provide a more complete answer, let's include the label of the birthplace in the query.

[Tool]
Got 1 row and 2 columns:
| birthPlace      | birthPlaceLabel |
| --------------- | --------------- |
| London (wd:Q84) | London (en)     |

[Assistant]
The SPARQL query has successfully returned the birthplace of Elvis Costello along with its label. We can now finalize the answer.

Elvis Costello was born in London.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT DISTINCT ?movie WHERE {
  ?movie wdt:P161 wd:Q187038 .
}

Got 118 rows and 1 column, showing the first 5 and last 5 rows below:
| movie                             |
| --------------------------------- |
| Think Big (wd:Q1031705)           |
| Death Race (wd:Q1033191)          |
| The Misfit Brigade (wd:Q10478647) |
| Deathsport (wd:Q1134750)          |
| Crank: High Voltage (wd:Q1138916) |
| ...                               |
| Mean Streets (wd:Q841335)         |
| True Legend (wd:Q910896)          |
| Kill Bill: Volume 2 (wd:Q928019)  |
| Big Stan (wd:Q939728)             |
| Behind Enemy Lines (wd:Q946863)   |

The movies in which David Carradine played a role include: Think Big, Death Race, The Misfit Brigade, Deathsport, Crank: High Voltage, Mean Streets, True Legend, Kill Bill: Volume 2, Big Stan, Behind Enemy Lines, 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 movies did david carradine play in?

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

[Tool]
Example 1:
Question:
what films have johnny depp been in?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x wdt:P161 wd:Q37175 ; wdt:P31 / wdt:P279 * wd:Q11424 .
}

Using entities:
film, also known as cinematic work, moving picture, movie, motion pictures, motion picture (wd:Q11424): sequence of images that give the impression of movement, stored on film stock
Johnny Depp, also known as John Christopher "Johnny" Depp II, John Christopher Depp, John Christopher Depp II, John Depp, John C. Depp II (wd:Q37175): American actor (born 1963), television actor, nightclub owner, film director, film producer, screenwriter, voice actor, film actor, guitarist, musician, actor

Using properties:
cast member, also known as feat., starring (film/play), film starring, starring, actor (wd:P161 as wdt): actor in the subject production [use "character role" (P453) and...use "recorded participant" (P11108) for non-fiction productions], significant person, performer
subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as wdt): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain
instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)

Example 2:
Question:
where's wayne state?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q7976637 wdt:P131 ?x .
}

Using entities:
Wayne State College, also known as Nebraska State Teachers College at Wayne, wsc.edu, WSC (wd:Q7976637): public college in Wayne, Nebraska, United States

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 team did deion sanders play for in baseball?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q954184 wdt:P54 ?x .
}

Using entities:
Deion Sanders, also known as Deion Luwynn Sanders Sr., Prime Time, Neon Deion (wd:Q954184): American football and baseball player and football coach, American football player, American football coach, baseball player

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

[Assistant] From the examples, we can see that the first example is quite relevant to our question. We need to find the movies that David Carradine played in. Let's start by searching for the entity "David Carradine".

[Tool]
Top 10 entity alternatives:
1. David Carradine, also known as John Arthur Carradine (wd:Q187038): American actor (1936–2009), television producer, television actor, character actor, film director, film producer, screenwriter, voice actor, film actor, director, actor
2. David Carradine, also known as David M. Carradine, D. Carradine (wd:Q123597734): structural engineer at BRANZ in New Zealand, structural engineer
3. David Carradine, Actor, Is Dead at 72 (wd:Q123708760): The New York Times article (June 5, 2009)
4. David, also known as David, King of Israel, King David, Dawud re d'Israele, Nabi Dawud King of Israel, sweet singer of Israel (wd:Q41370): king of Israel and Judah, instrumentalist, monarch, warlord, herder, ruler, poet
5. Jacques-Louis David, also known as J.-L. David, Louis David, L. David, J.L. David, J. L. David (wd:Q83155): architectural draftsperson, French painter (1748–1825), politician, painter
6. David, also known as David by Michelangelo, Michelangelo's David, David of Michelangelo, Michaelangelo's David (wd:Q179900): sculpture by Michelangelo
7. Saint David, also known as St. David, St David, David of Wales, Dewi, David (wd:Q331697): patron saint of Wales, Catholic bishop, Catholic priest
8. David, also known as David, Chiriquí, San José de David (wd:Q279009): capital of the province of Chiriquí, Panama
9. Gerard David, also known as Gheeraert Davidt, Gheeraedt David, Gheeraert David, Gheeraedt Davit, Gheeraedt Davidt (wd:Q333380): Early Netherlandish painter, (c. 1460–1523), draftsperson, illuminator, painter, artist
10. Armand David, also known as Pere David, Jean-Pierre-Armand David, David, Père David, Jean Pierre Armand David (wd:Q346939): French Catholic priest, zoologist, and botanist (1826–1900), Catholic priest, ornithologist, missionary, zoologist, botanist, explorer

[Assistant] The correct entity for David Carradine is `wd:Q187038`. Now, let's identify the property that links actors to the movies they have acted in. Based on the example, it seems like `wdt:P161` (cast member) is the appropriate property. We will verify this by listing some triples where `wd:Q187038` is the subject and `wdt:P161` is the property.

[Tool] Got no rows and 3 columns

[Assistant]
It appears that there are no direct triples linking David Carradine (`wd:Q187038`) to movies using the `wdt:P161` property. This might be because the property is used in the reverse direction, where the movie is the subject and the actor is the object. Let's try a different approach by searching for movies where David Carradine is listed as a cast member.

We will use the property `wdt:P161` to find movies where David Carradine is a cast member.

[Tool]
Got 118 rows and 1 column, showing the first 5 and last 5 rows below:
| movie                             |
| --------------------------------- |
| Think Big (wd:Q1031705)           |
| Death Race (wd:Q1033191)          |
| The Misfit Brigade (wd:Q10478647) |
| Deathsport (wd:Q1134750)          |
| Crank: High Voltage (wd:Q1138916) |
| ...                               |
| Mean Streets (wd:Q841335)         |
| True Legend (wd:Q910896)          |
| Kill Bill: Volume 2 (wd:Q928019)  |
| Big Stan (wd:Q939728)             |
| Behind Enemy Lines (wd:Q946863)   |

[Assistant]
The SPARQL query successfully returned a list of movies in which David Carradine played a role. Here are some of the movies:

- Think Big (wd:Q1031705)
- Death Race (wd:Q1033191)
- The Misfit Brigade (wd:Q10478647)
- Deathsport (wd:Q1134750)
- Crank: High Voltage (wd:Q1138916)
- Mean Streets (wd:Q841335)
- True Legend (wd:Q910896)
- Kill Bill: Volume 2 (wd:Q928019)
- Big Stan (wd:Q939728)
- Behind Enemy Lines (wd:Q946863)

I will now provide the final SPARQL query and the answer to the user's question.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?politicalSystem WHERE {
  wd:Q155 wdt:P122 ?politicalSystem .
}

Got 3 rows and 1 column:
| politicalSystem                       |
| ------------------------------------- |
| representative democracy (wd:Q188759) |
| presidential system (wd:Q49892)       |
| federal republic (wd:Q512187)         |

Brazil has a political system that includes representative democracy, a presidential system, and a federal republic.

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

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

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

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

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

[User] what type of political system is brazil?

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

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

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

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

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

Example 2:
Question:
what disease did helen keller?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q38203 wdt:P1050 ?x .
}

Using entities:
Helen Keller, also known as Helen Adams Keller (wd:Q38203): American author and activist (1880–1968), political activist, autobiographer, peace activist, trade unionist, suffragette, essayist, linguist, writer, orator

Using properties:
medical condition, also known as disability, suffers from, suffer from, sickness, paralympic disability (wd:P1050 as wdt): any state relevant to the health of an organism, including diseases and positive conditions

Example 3:
Question:
what are the names of michael jackson children?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q2831 wdt:P40 ?x .
}

Using entities:
Michael Jackson, also known as M.J., MJ, M. J., The King of Pop, King of Pop (wd:Q2831): American singer, songwriter, and dancer (1958–2009), singer-songwriter, recording artist, record producer, businessperson, philanthropist, music arranger, autobiographer, film director, choreographer, art collector, entrepreneur, screenwriter, voice actor, songwriter, film actor, composer, dancer, singer, actor, model, poet

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

[Assistant] Based on the examples, we need to identify the entity for Brazil and the property that describes its political system. Let's start by searching for the entity Brazil.

[Tool]
Top 10 entity alternatives:
1. Brazil, also known as Federative Republic of Brazil, Brasil, br (wd:Q155): country in South America
2. Brazil, also known as br, Brasil, Federative Republic of Brazil (wd:Q155): country in South America
3. Brazil (wd:Q25057): 1985 dystopian film by Terry Gilliam
4. Brazil, also known as Brazil, Indiana, Brazil, IN (wd:Q1998364): city in Clay County, Indiana, United States
5. State of Brazil, also known as Brazil, Colonial Brazil, Portuguese Brazil (wd:Q11876909): state of the Portuguese Empire
6. Brazil, also known as Stars and Guitars (wd:Q4958616): 1944 film by Joseph Santley
7. Brazil, also known as Brazil, IA (wd:Q17511873): human settlement in Appanoose County, Iowa, United States
8. Viceroyalty of Brazil, also known as Brasil, Brazil (wd:Q2920081): Portuguese viceroyalty in Brazil 1763-1815
9. Brazil (wd:Q13581616): 1991 song by Bebi Dol
10. Brazil (wd:Q4095706): 1994 novel by John Updike

[Assistant] The correct entity for Brazil is `wd:Q155`. Now, let's search for properties that might describe the political system of a country.

[Tool]
Top 10 property alternatives:
1. voting system, also known as electoral system, voting system, type of election (wd:P8196 as wdt/wdtn/prn/pq/pqv/pqn/p/ps/pr/psn/prv/psv): system used for this election or vote
2. basic form of government, also known as form of government, government, type of government (wd:P122 as wdt/wdtn/prn/pq/pqv/pqn/p/ps/pr/psn/prv/psv): subject's government
3. diplomatic relation, also known as political relation, political relations, foreign relations, foreign relation, diplomatic relations (wd:P530 as wdt/wdtn/prn/pq/pqv/pqn/p/ps/pr/psn/prv/psv): diplomatic relations of the country
4. member of political party, also known as political party member, political party, party membership, party, member of party (wd:P102 as wdt/wdtn/prn/pq/pqv/pqn/p/ps/pr/psn/prv/psv): the political party of which a person is or has been a member or otherwise affiliated, member of
5. position held, also known as function, held position, holds position, job, office held (wd:P39 as wdt/wdtn/prn/pq/pqv/pqn/p/ps/pr/psn/prv/psv): subject currently or formerly holds the object position or public office
6. political alignment, also known as political position, alignment (wd:P1387 as wdt/wdtn/prn/pq/pqv/pqn/p/ps/pr/psn/prv/psv): political position within the left–right political spectrum
7. political coalition, also known as electoral block, political bloc, political alliance, electoral list, electoral alliance (wd:P5832 as wdt/wdtn/prn/pq/pqv/pqn/p/ps/pr/psn/prv/psv): agreement for cooperation between different political parties, member of
8. political ideology, also known as editorial viewpoint, has political ideology, ideology, official ideology, official political ideology (wd:P1142 as wdt/wdtn/prn/pq/pqv/pqn/p/ps/pr/psn/prv/psv): political ideology of an organization or person or of a work (such as a newspaper)
9. authority, also known as executive authority, governed by, governing authority, governing body, has authority (wd:P797 as wdt/wdtn/prn/pq/pqv/pqn/p/ps/pr/psn/prv/psv): entity having executive power on given entity
10. parliamentary group, also known as faction, party organization, party (wd:P4100 as wdt/wdtn/prn/pq/pqv/pqn/p/ps/pr/psn/prv/psv): parliamentary group to which a member of a parliament belongs, member of

[Assistant]
The property `wd:P122` (basic form of government) seems to be the most relevant for describing the political system of a country. Let's use this property to construct a SPARQL query to find out the political system of Brazil.

Here is the SPARQL query:

```sparql
SELECT ?politicalSystem WHERE {
  wd:Q155 wdt:P122 ?politicalSystem .
}
```

Let's execute this query.

[Tool]
Got 3 rows and 1 column:
| politicalSystem                       |
| ------------------------------------- |
| representative democracy (wd:Q188759) |
| presidential system (wd:Q49892)       |
| federal republic (wd:Q512187)         |

[Assistant]
The political system of Brazil includes the following types:
- Representative democracy (wd:Q188759)
- Presidential system (wd:Q49892)
- Federal republic (wd:Q512187)

To provide a clear and concise answer, we can combine these into a single statement.

Here is the final SPARQL query and answer:

```sparql
SELECT ?politicalSystem WHERE {
  wd:Q155 wdt:P122 ?politicalSystem .
}
```

Answer: Brazil has a political system that includes representative democracy, a presidential system, and a federal republic.

Now, let's finalize the answer.

[Tool] Stopped generation process