PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?project ?projectLabel WHERE {
  ?project wdt:P161 wd:Q587156 .
  OPTIONAL {
    ?project rdfs:label ?projectLabel .
    FILTER ( LANG( ?projectLabel ) = "en" )
  }
}

Got 12 rows and 2 columns, showing the first 5 and last 5 rows below:
| ?project                                           | ?projectLabel                        |
| -------------------------------------------------- | ------------------------------------ |
| The Car (wd:Q1197355)                              | The Car                              |
| Escape to Witch Mountain (wd:Q1212511)             | Escape to Witch Mountain             |
| Return from Witch Mountain (wd:Q1925695)           | Return from Witch Mountain           |
| Raid on Entebbe (wd:Q2305094)                      | Raid on Entebbe                      |
| Tuff Turf (wd:Q2362823)                            | Tuff Turf                            |
| ...                                                | ...                                  |
| Black Snake Moan (wd:Q468660)                      | Black Snake Moan                     |
| Hello, Larry (wd:Q5708520)                         | Hello, Larry                         |
| No Deposit, No Return (wd:Q7044096)                | No Deposit, No Return                |
| The Real Housewives of Beverly Hills (wd:Q7759591) | The Real Housewives of Beverly Hills |
| Race to Witch Mountain (wd:Q922006)                | Race to Witch Mountain               |

Kim Richards has appeared in the following films and TV shows: The Car, Escape to Witch Mountain, Return from Witch Mountain, Raid on Entebbe, Tuff Turf, Black Snake Moan, Hello, Larry, No Deposit, No Return, The Real Housewives of Beverly Hills, and Race to Witch Mountain.

[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] To answer the question about what Kim Richards was in, we need to identify who Kim Richards is and then find out the projects, movies, or shows she was involved in. Let's start by searching for Kim Richards in the knowledge graph.

[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

No other items found

[Assistant]
From the search results, it appears that the most relevant entity for Kim Richards is the American actress and television personality (wd:Q587156). Now, let's find out the projects, movies, or shows she was involved in. We will look for properties that indicate her involvement in films, TV shows, or other media.

Let's list the triples where Kim Richards (wd:Q587156) is the subject to see what properties and objects are associated with her.

[Tool]
Got 297 rows and 3 columns, showing the first 10 rows below:
| subject                   | property                         | object                                                                                |
| ------------------------- | -------------------------------- | -------------------------------------------------------------------------------------------------------------- |
| Kim Richards (wd:Q587156) | instance of (wdt:P31)            | human (wd:Q5)                                                                                |
| Kim Richards (wd:Q587156) | occupation (wdt:P106)            | actor (wd:Q33999)                                                                                |
| Kim Richards (wd:Q587156) | sex or gender (wdt:P21)          | female (wd:Q6581072)                                                                                |
| Kim Richards (wd:Q587156) | given name (wdt:P735)            | Kim (wd:Q637123)                                                                                |
| Kim Richards (wd:Q587156) | date of birth (wdt:P569)         | 1964-09-19T00:00:00Z                                                                                |
| Kim Richards (wd:Q587156) | Commons category (wdt:P373)      | Kim Richards                                                                                |
| Kim Richards (wd:Q587156) | image (wdt:P18)                  | <http://commons.wikimedia.org/wiki/Special:FilePath/Nanny%20and%20the%20Professor%20Kim%20Richards%201970.jpg> |
| Kim Richards (wd:Q587156) | country of citizenship (wdt:P27) | United States (wd:Q30)                                                                                |
| Kim Richards (wd:Q587156) | family name (wdt:P734)           | Richards (wd:Q608991)                                                                                |
| Kim Richards (wd:Q587156) | place of birth (wdt:P19)         | Mineola (wd:Q2349502)                                                                                |
| ...                       | ...                              | ...                                                                                |

[Assistant]
From the list of triples, we can see that Kim Richards is indeed an actor, but we don't see any direct links to specific films or TV shows. To find out the projects she was involved in, we need to look for properties that link her to her roles in films or TV shows.

Common properties for actors include `P161` (cast member of), `P453` (role in), and `P181` (voice actor of). Let's search for these properties to see if they are used in relation to Kim Richards.

First, let's search for the property `P161` (cast member of) to see if it is used for Kim Richards.

[Tool] Got no rows and 3 columns

[Assistant] It seems that the property `P161` (cast member of) is not used for Kim Richards. Let's try another property, such as `P453` (role in), to see if it provides any information about the projects she was involved in.

[Tool] Got no rows and 3 columns

[Assistant] The property `P453` (role in) also does not provide any results for Kim Richards. Let's try one more property, `P181` (voice actor of), to see if it gives us any information about her voice acting roles.

[Tool] Got no rows and 3 columns

[Assistant]
It seems that none of the common properties for actors (`P161`, `P453`, `P181`) are used for Kim Richards in the knowledge graph. However, there might be other properties or ways to find the projects she was involved in.

Let's try a more general approach by looking for any properties that link Kim Richards to films or TV shows. We can use a SPARQL query to find any properties that might indicate her involvement in media projects.

Here is a SPARQL query to find any properties and objects related to Kim Richards that might indicate her involvement in films or TV shows:

```sparql
SELECT ?property ?object
WHERE {
  wd:Q587156 ?property ?object .
  FILTER(?property IN (wdt:P161, wdt:P453, wdt:P181, wdt:P800, wdt:P1431, wdt:P1441))
}
```

This query will look for properties like `P161` (cast member of), `P453` (role in), `P181` (voice actor of), `P800` (notable work), `P1431` (nominated for), and `P1441` (awarded) to see if they provide any relevant information.

[Tool] Got no rows and 2 columns

[Assistant]
It appears that none of the properties we checked (`P161`, `P453`, `P181`, `P800`, `P1431`, `P1441`) are used for Kim Richards in the knowledge graph. This suggests that the information about her involvement in films or TV shows might not be directly linked to her entity in the way we expected.

However, we can try a different approach by looking for statements where Kim Richards is mentioned as a cast member or performer in any media project. We can use a more flexible query to find any properties that might link her to media projects.

Let's try a broader query to find any properties and objects related to Kim Richards that might indicate her involvement in media projects:

```sparql
SELECT ?property ?object
WHERE {
  wd:Q587156 ?property ?object .
  FILTER(?property IN (wdt:P161, wdt:P453, wdt:P181, wdt:P800, wdt:P1431, wdt:P1441, wdt:P106, wdt:P31, wdt:P136, wdt:P144))
}
```

This query will look for a wider range of properties, including those related to her occupation, notable works, and genres, to see if they provide any relevant information.

[Tool]
Got 4 rows and 2 columns:
| ?property             | ?object                         |
| --------------------- | ------------------------------- |
| occupation (wdt:P106) | television actor (wd:Q10798782) |
| occupation (wdt:P106) | film actor (wd:Q10800557)       |
| occupation (wdt:P106) | actor (wd:Q33999)               |
| instance of (wdt:P31) | human (wd:Q5)                   |

[Assistant]
The query results show that Kim Richards is indeed an actor, both in television and film, but it doesn't provide specific projects she was involved in. Since the direct properties we tried didn't yield results, we need to explore other ways to find the media projects she was part of.

One approach is to look for statements where Kim Richards is mentioned as a cast member or performer in any media project. We can use the `P161` (cast member of) property in reverse, i.e., find media projects where Kim Richards is listed as a cast member.

Let's try the following SPARQL query to find media projects where Kim Richards is listed as a cast member:

```sparql
SELECT ?project ?projectLabel
WHERE {
  ?project wdt:P161 wd:Q587156 .
  OPTIONAL { ?project rdfs:label ?projectLabel . FILTER(LANG(?projectLabel) = "en") }
}
```

This query will find any media projects where Kim Richards is listed as a cast member and optionally retrieve their English labels for better readability.

[Tool]
Got 12 rows and 2 columns, showing the first 5 and last 5 rows below:
| ?project                                           | ?projectLabel                        |
| -------------------------------------------------- | ------------------------------------ |
| The Car (wd:Q1197355)                              | The Car                              |
| Escape to Witch Mountain (wd:Q1212511)             | Escape to Witch Mountain             |
| Return from Witch Mountain (wd:Q1925695)           | Return from Witch Mountain           |
| Raid on Entebbe (wd:Q2305094)                      | Raid on Entebbe                      |
| Tuff Turf (wd:Q2362823)                            | Tuff Turf                            |
| ...                                                | ...                                  |
| Black Snake Moan (wd:Q468660)                      | Black Snake Moan                     |
| Hello, Larry (wd:Q5708520)                         | Hello, Larry                         |
| No Deposit, No Return (wd:Q7044096)                | No Deposit, No Return                |
| The Real Housewives of Beverly Hills (wd:Q7759591) | The Real Housewives of Beverly Hills |
| Race to Witch Mountain (wd:Q922006)                | Race to Witch Mountain               |

[Assistant]
The SPARQL query has returned a list of media projects where Kim Richards is listed as a cast member. Here are the projects she was involved in:

1. **The Car** (wd:Q1197355)
2. **Escape to Witch Mountain** (wd:Q1212511)
3. **Return from Witch Mountain** (wd:Q1925695)
4. **Raid on Entebbe** (wd:Q2305094)
5. **Tuff Turf** (wd:Q2362823)
6. **Black Snake Moan** (wd:Q468660)
7. **Hello, Larry** (wd:Q5708520)
8. **No Deposit, No Return** (wd:Q7044096)
9. **The Real Housewives of Beverly Hills** (wd:Q7759591)
10. **Race to Witch Mountain** (wd:Q922006)

These are the films and TV shows in which Kim Richards has appeared.

Now, let's finalize the answer with the SPARQL query and the list of projects.

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?label WHERE {
  wd:Q8201 rdfs:label ?label .
  FILTER ( LANG( ?label ) = 'en' )
}

Got 1 row and 1 column:
| ?label             |
| ------------------ |
| Chinese characters |

Chinese characters

[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] To answer the question about what the Chinese writing system is called, I need to identify the entity representing the Chinese writing system and then retrieve its label or common name. Let's start by searching for the term "Chinese writing system" in the subject position.

[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

No other items found

[Assistant]
From the search results, the most relevant entity seems to be "writing system, also known as wenzi, ven-tsee, script, graphemics" (wd:Q8192). However, this is a general term for any writing system. We need to ensure that it specifically refers to the Chinese writing system. Let's check the properties and values associated with this entity to confirm.

I will list the triples where this entity is the subject to see if it has any specific connections to China or the Chinese language.

[Tool]
Got 773 rows and 3 columns, showing the first 10 rows below:
| subject                   | property                                       | object                                                                                |
| ------------------------- | ---------------------------------------------- | --------------------------------------------------------------------------------------------------------- |
| writing system (wd:Q8192) | instance of (wdt:P31)                          | type of system (wd:Q96116695)                                                                             |
| writing system (wd:Q8192) | Commons category (wdt:P373)                    | Writing systems                                                                                |
| writing system (wd:Q8192) | image (wdt:P18)                                | <http://commons.wikimedia.org/wiki/Special:FilePath/World%20alphabets%20%26%20writing%20systems%20ES.svg> |
| writing system (wd:Q8192) | part of (wdt:P361)                             | linguistic system (wd:Q6554068)                                                                           |
| writing system (wd:Q8192) | subclass of (wdt:P279)                         | notation (wd:Q2001982)                                                                                |
| writing system (wd:Q8192) | has part(s) (wdt:P527)                         | orthography (wd:Q43091)                                                                                |
| writing system (wd:Q8192) | described by source (wdt:P1343)                | Armenian Soviet Encyclopedia (wd:Q2657718)                                                                |
| writing system (wd:Q8192) | on focus list of Wikimedia project (wdt:P5008) | wd:Q5460604                                                                                |
| writing system (wd:Q8192) | different from (wdt:P1889)                     | handwriting style (wd:Q33260112)                                                                          |
| writing system (wd:Q8192) | topic's main category (wdt:P910)               | wd:Q6369308                                                                                |
| ...                       | ...                                            | ...                                                                                |

[Assistant]
The entity "writing system" (wd:Q8192) appears to be a general concept rather than specifically referring to the Chinese writing system. We need to find a more specific entity that represents the Chinese writing system.

Let's try another search, this time specifically looking for "Chinese writing system" or "Chinese script" in the subject position.

[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)

No other items found

[Assistant]
The search results provide several relevant entities:

1. **Chinese characters** (wd:Q8201): Logographic writing system with Han origin used in the Sinosphere.
2. **Simplified Chinese characters** (wd:Q185614): Standardized Chinese characters used in Mainland China, Malaysia, and Singapore.
3. **Chinese cursive script** (wd:Q607543): Traditional calligraphic script style of East Asian orthography.
4. **Chinese family of scripts** (wd:Q117285848): Family of writing systems descended from the Chinese oracle bone script.

The most comprehensive and general term for the Chinese writing system is "Chinese characters" (wd:Q8201). Let's retrieve the label for this entity to confirm its name.

I will execute a SPARQL query to get the label of the entity wd:Q8201.

[Tool]
Got 1 row and 1 column:
| ?label             |
| ------------------ |
| Chinese characters |

[Assistant]
The label for the entity wd:Q8201 is "Chinese characters." Therefore, the Chinese writing system is commonly referred to as "Chinese characters."

Here is the final SPARQL query and answer:

```sparql
SELECT ?label WHERE {
  wd:Q8201 rdfs:label ?label .
  FILTER(LANG(?label) = 'en')
}
```

The answer to the question "What do you call the Chinese writing system?" is **Chinese characters**.

[Tool] Stopped generation process


PREFIX p: <http://www.wikidata.org/prop/>
PREFIX ps: <http://www.wikidata.org/prop/statement/>
PREFIX pq: <http://www.wikidata.org/prop/qualifier/>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX xsd: <http://www.w3.org/2001/XMLSchema#>
SELECT ?coach WHERE {
  wd:Q330120 p:P286 ?statement .
  ?statement ps:P286 ?coach .
  ?statement pq:P580 ?startTime .
  ?statement pq:P582 ?endTime .
  FILTER ( ?startTime <= '2013-01-01' ^^ xsd:dateTime && ?endTime >= '2013-12-31' ^^ xsd:dateTime )
}

Ron Rivera (wd:Q1991889)

[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]
To answer the question about who coached the Carolina Panthers in 2013, we need to identify the following:
1. The entity representing the Carolina Panthers.
2. The property that indicates the coach of a team.
3. The specific coach for the Carolina Panthers in 2013.

Let's start by searching for the Carolina Panthers in the knowledge graph.

[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

No other items found

[Assistant] The top result for "Carolina Panthers" is `wd:Q330120`, which represents the American football team. Next, we need to find the property that indicates the coach of a team. We can search for properties related to coaching.

[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 p/wdt): 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 p/wdt): Wikimedia category for players playing for a sports team, topic's main category
6. home venue, also known as home water, venue, stadium, home ground, home field (wd:P115 as p/wdt): home stadium or venue of a sports team or applicable performing arts organization, location
7. 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 p/wdt): identifier for a sports team in the FlashScore.com database
8. topic's main category, also known as article's main category, category, category for this topic, catmain, has category (wd:P910 as wdt/p): main Wikimedia category
9. owner of, also known as owns, owns property, shareholder of (wd:P1830 as p/wdt): entities owned by the subject
10. country, also known as sovereign state, state, land, host country (wd:P17 as p/wdt): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity

No other items found

[Assistant]
The top result for the property related to coaching is `wdt:P286`, which stands for "head coach." Now, we need to find out who the head coach of the Carolina Panthers was in 2013. We can use the `list` function to see if there are any specific statements about the coach in 2013.

Let's list the triples where the Carolina Panthers (`wd:Q330120`) are the subject and the property is `wdt:P286`.

[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. However, this seems incorrect because Dave Canales is not a well-known NFL coach. Let's verify this by checking the specific year 2013. We need to find the coach of the Carolina Panthers specifically in 2013.

We can use the `pq` (qualifier) property to check for the time period. The property `P580` (start time) and `P582` (end time) can be used to specify the time range.

Let's execute a SPARQL query to find the head coach of the Carolina Panthers in 2013.

[Tool] Got no rows and 1 columns

[Assistant]
It seems that the query did not return any results, which suggests that the data might not be structured in the way we expected. Let's try a different approach by looking for the coach of the Carolina Panthers in 2013 directly.

We can use the `pq` (qualifier) property to check for the time period more broadly. Let's try a simpler query to find the coach of the Carolina Panthers in 2013 by checking the statements with the `P580` (start time) qualifier.

[Tool] Got no rows and 1 columns

[Assistant]
It seems that the query still did not return any results. This suggests that the data might not have the specific qualifiers we are looking for, or the data might be structured differently.

Let's try a different approach by looking for the coach of the Carolina Panthers in 2013 by checking the statements with the `P585` (point in time) qualifier, which is often used to specify a specific year or date.

[Tool] Got no rows and 1 columns

[Assistant]
It seems that the query with the `P585` (point in time) qualifier also did not return any results. This suggests that the data might not have the specific qualifiers we are looking for, or the data might be structured differently.

Let's try a more general approach by looking for the coach of the Carolina Panthers and then checking the time period manually. We can list all the coaches of the Carolina Panthers and their associated time periods.

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

[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 time period includes the year 2013.

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

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

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
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]
To answer the question about who Nicolas Cage is married to, I need to first identify Nicolas Cage in the knowledge graph and then find out his spouse.

### Step 1: Identify Nicolas Cage
I will start by searching for Nicolas Cage in the knowledge graph.

[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

No other items found

[Assistant]
The top result for Nicolas Cage is `wd:Q42869`, which matches the description of the American actor. I will use this identifier to find out who he is married to.

### Step 2: Find Nicolas Cage's Spouse
I will now search for the property that indicates marriage or spouse and then use it to find out who Nicolas Cage is married to.

First, let's find the property for "spouse" or "married to" in the knowledge graph.

[Tool]
Top 10 property alternatives:
1. spouse, also known as married partner, married to, marry, partner, spouses (wd:P26 as p/wdt): the subject has the object as their spouse (husband, wife, partn...etc.). Use "unmarried partner" (P451) for non-married companions, significant person, relative
2. unmarried partner, also known as romantic partner, partner of, partners, posslq, relationship (wd:P451 as p/wdt): someone with whom the person is in a relationship without being married. Use "spouse" (P26) for married couples, significant person
3. birth name, also known as née, name at birth, name before marriage, ne, né (wd:P1477 as p/wdt): full name of a person at birth, if different from their current, generally used name, name
4. 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)
5. 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
6. child, also known as has son, kids, mother of, kid, issue (wd:P40 as p/wdt): subject has object as child. Do not use for stepchildren—use "relative" (P1038), qualified with "type of kinship" (P1039), significant person, relative
7. father, also known as son of, child of, parent, is son of, is daughter of (wd:P22 as wdt/p): male parent of the subject. For stepfather, use "stepparent" (P3448), parent
8. ethnic group, also known as ethnic or cultural origin, tribal affiliation, race, people, ethnicity (wd:P172 as wdt/p): subject's ethnicity (consensus is that a VERY high standard of p...agreed on by scholars, or 3) is fictional and portrayed as such)
9. 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)
10. mother, also known as mom, is child of, mommy, mum, mummy (wd:P25 as p/wdt): female parent of the subject. For stepmother, use "stepparent" (P3448), parent

No other items found

[Assistant]
The property for "spouse" is `wd:P26`. I will now use this property to find out who Nicolas Cage is married to.

### Step 3: Execute the SPARQL Query
I will execute a SPARQL query to find the spouse of Nicolas Cage (`wd:Q42869`).

Here is the SPARQL query:

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

This query will return the IRI of the spouse and, optionally, the English label of the spouse.

Let's execute this query.

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

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

### Final Answer
Nicolas Cage is married to Riko Shibata.

Here is the final SPARQL query and 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.

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

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?placeOfBirth WHERE {
  wd:Q206939 wdt:P19 ?placeOfBirth .
}

Got 1 row and 1 column:
| ?placeOfBirth   |
| --------------- |
| London (wd:Q84) |

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]
To answer the question "Where was Elvis Costello born?", we need to identify the entity for Elvis Costello and the property for place of birth. Let's start by searching for Elvis Costello as a subject in the knowledge graph.

I will use the `search` function to find the entity 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

No other items found

[Assistant]
The top result for Elvis Costello is `wd:Q206939`, which represents the English singer-songwriter. Now, let's find the property for the place of birth. We can use the `search` function again to find the property for "place of birth".

I will use the `search` function to find 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 p/wdt/prn/ps/pq/psn/pqn/wdtn/pr/pqv/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 p/wdt/prn/ps/pq/psn/pqn/wdtn/pr/pqv/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 p/wdt/prn/ps/pq/psn/pqn/wdtn/pr/pqv/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 p/wdt/prn/ps/pq/psn/pqn/wdtn/pr/pqv/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 p/wdt/prn/ps/pq/psn/pqn/wdtn/pr/pqv/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 p/wdt/prn/ps/pq/psn/pqn/wdtn/pr/pqv/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 p/wdt/prn/ps/pq/psn/pqn/wdtn/pr/pqv/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 p/wdt/prn/ps/pq/psn/pqn/wdtn/pr/pqv/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 p/wdt/prn/ps/pq/psn/pqn/wdtn/pr/pqv/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 p/wdt/prn/ps/pq/psn/pqn/wdtn/pr/pqv/prv/psv): what the place, monument, memorial, or holiday, commemorates, main subject

No other items found

[Assistant]
The property for "place of birth" is `wdt:P19`. Now that we have both the entity for Elvis Costello (`wd:Q206939`) and the property for place of birth (`wdt:P19`), we can construct a SPARQL query to find where Elvis Costello was born.

Let's execute the SPARQL query to get the place of birth for Elvis Costello.

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

[Assistant]
The SPARQL query returned that Elvis Costello was born in London, represented by the entity `wd:Q84`.

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

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?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)   |

David Carradine appeared in several movies, including Think Big, Death Race, The Misfit Brigade, Deathsport, Crank: High Voltage, Mean Streets, True Legend, Kill Bill: Volume 2, Big Stan, and Behind Enemy Lines.

[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] To answer the question about the movies David Carradine played in, we need to identify the entity for David Carradine and then find the movies he acted in. Let's start by searching for David Carradine in the knowledge graph.

[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

No other items found

[Assistant]
The top result for "David Carradine" is `wd:Q187038`, which matches the description of the American actor. Next, we need to find the movies he acted in. We will look for the property that indicates the movies an actor has appeared in. A common property for this is `P161` (cast member of).

Let's check if this property is used for David Carradine.

[Tool] Got no rows and 3 columns

[Assistant]
It seems that the property `P161` (cast member of) is not used for David Carradine. Let's try another property that might be used to indicate the movies he acted in. Another common property is `P453` (character role in creative work).

Let's check if this property is used for David Carradine.

[Tool] Got no rows and 3 columns

[Assistant]
It appears that the property `P453` (character role in creative work) is also not used for David Carradine. Let's try one more property, `P800` (notable work), which might list the notable works or movies he was involved in.

Let's check if this property is used for David Carradine.

[Tool] Got no rows and 3 columns

[Assistant]
It seems that the property `P800` (notable work) is also not used for David Carradine. Since these common properties are not yielding results, let's try a more general approach by listing all the properties associated with David Carradine to see if there are any other relevant properties.

Let's list all the properties for David Carradine.

[Tool]
Got 738 rows and 3 columns, showing the first 10 rows below:
| subject                      | property                         | object                                                                                |
| ---------------------------- | -------------------------------- | ---------------------------------------------------------------------------------------------------- |
| David Carradine (wd:Q187038) | instance of (wdt:P31)            | human (wd:Q5)                                                                                |
| David Carradine (wd:Q187038) | occupation (wdt:P106)            | actor (wd:Q33999)                                                                                |
| David Carradine (wd:Q187038) | sex or gender (wdt:P21)          | male (wd:Q6581097)                                                                                |
| David Carradine (wd:Q187038) | given name (wdt:P735)            | David (wd:Q18057751)                                                                                |
| David Carradine (wd:Q187038) | date of birth (wdt:P569)         | 1936-12-08T00:00:00Z                                                                                |
| David Carradine (wd:Q187038) | Commons category (wdt:P373)      | David Carradine                                                                                |
| David Carradine (wd:Q187038) | image (wdt:P18)                  | <http://commons.wikimedia.org/wiki/Special:FilePath/David%20Carradine%20Polanski%20Unauthorized.jpg> |
| David Carradine (wd:Q187038) | country of citizenship (wdt:P27) | United States (wd:Q30)                                                                               |
| David Carradine (wd:Q187038) | family name (wdt:P734)           | Carradine (wd:Q21482744)                                                                             |
| David Carradine (wd:Q187038) | place of birth (wdt:P19)         | Hollywood (wd:Q34006)                                                                                |
| ...                          | ...                              | ...                                                                                |

[Assistant]
From the list of properties, it appears that the property `P161` (cast member of) is not directly linked to David Carradine. However, we can try to find the movies he acted in by looking for statements where he is listed as a cast member.

Let's use a SPARQL query to find the movies where David Carradine is listed as a cast member (`P161`).

[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 where David Carradine is listed as a cast member. 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)

We can now provide the final answer to the user.

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?politicalSystem ?politicalSystemLabel WHERE {
  wd:Q155 wdt:P122 ?politicalSystem .
  OPTIONAL {
    ?politicalSystem rdfs:label ?politicalSystemLabel .
    FILTER ( LANG( ?politicalSystemLabel ) = "en" )
  }
}

Got 3 rows and 2 columns:
| ?politicalSystem                      | ?politicalSystemLabel    |
| ------------------------------------- | ------------------------ |
| representative democracy (wd:Q188759) | representative democracy |
| presidential system (wd:Q49892)       | presidential system      |
| federal republic (wd:Q512187)         | federal republic         |

Brazil has a representative democracy, a presidential system, and a federal republic structure.

[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] To answer the question about the type of political system in Brazil, I need to identify the entity for Brazil and then find the property that describes its political system. Let's start by searching for Brazil as a subject.

[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

No other items found

[Assistant] The top result for Brazil is the country in South America, which is what we are looking for. The IRI for Brazil is `wd:Q155`. Next, I will search for properties related to the political system of Brazil.

[Tool]
Top 10 property alternatives:
1. basic form of government, also known as form of government, government, type of government (wd:P122 as wdt/p): subject's government
2. diplomatic relation, also known as political relation, political relations, foreign relations, foreign relation, diplomatic relations (wd:P530 as p/wdt): diplomatic relations of the country
3. head of government, also known as head of national government, mayor, premier, president, prime minister (wd:P6 as wdt/p): head of the executive power of this town, city, municipality, state, country, or other governmental body, director / manager, chairperson
4. office held by head of government, also known as title of head of government, position of head of government, office of head of government, head of government's office, position held by head of government (wd:P1313 as wdt/p): political office that is fulfilled by the head of the government of this item
5. office held by head of state, also known as head of state, position held by head of state, state headed by (wd:P1906 as wdt/p): political office that is fulfilled by the head of state of this item
6. capital, also known as administrative seat, seat of government, seat, principal place, location of capital (wd:P36 as wdt/p): seat of government of a country, province, state or other type of administrative territorial entity
7. part of, also known as of, within, system of, subsystem of, subgroup of (wd:P361 as p/wdt): object of which the subject is a part (if this subject is alread... of "has part" (P527, see also "has parts of the class" (P2670))
8. 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
9. legislative body, also known as aboriginal council, Zila, Tehsil, rural council, representative body (wd:P194 as wdt/p): legislative body governing this entity; political institution wi...ted representatives, such as a parliament/legislature or council
10. head of state, also known as leader, state headed by, monarch, president, queen (wd:P35 as wdt/p): official with the highest formal authority in a country/state, director / manager, chairperson

No other items found

[Assistant]
The top result for the property related to the political system is `basic form of government` (P122). This property seems to describe the type of government or political system of a country. Now, let's construct a SPARQL query to find the value of this property for Brazil.

Here is the SPARQL query:

```sparql
SELECT ?politicalSystem ?politicalSystemLabel
WHERE {
  wd:Q155 wdt:P122 ?politicalSystem.
  OPTIONAL { ?politicalSystem rdfs:label ?politicalSystemLabel . FILTER(LANG(?politicalSystemLabel) = "en") }
}
```

I will execute this query to get the result.

[Tool]
Got 3 rows and 2 columns:
| ?politicalSystem                      | ?politicalSystemLabel    |
| ------------------------------------- | ------------------------ |
| representative democracy (wd:Q188759) | representative democracy |
| presidential system (wd:Q49892)       | presidential system      |
| federal republic (wd:Q512187)         | federal republic         |

[Assistant]
The SPARQL query returned three types of political systems for Brazil:
- Representative democracy (wd:Q188759)
- Presidential system (wd:Q49892)
- Federal republic (wd:Q512187)

These results indicate that Brazil has a representative democracy, a presidential system, and is a federal republic.

Therefore, the type of political system in Brazil is a **representative democracy** with a **presidential system** and a **federal republic** structure.

Here is the final SPARQL query and answer:

```sparql
SELECT ?politicalSystem ?politicalSystemLabel
WHERE {
  wd:Q155 wdt:P122 ?politicalSystem.
  OPTIONAL { ?politicalSystem rdfs:label ?politicalSystemLabel . FILTER(LANG(?politicalSystemLabel) = "en") }
}
```

Answer: Brazil has a representative democracy, a presidential system, and a federal republic structure.

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?date WHERE {
  wd:Q211386 wdt:P585 ?date .
}

April 18, 1906

[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] when did the big earthquake hit san francisco?

[Assistant] To answer the question about when the big earthquake hit San Francisco, I need to identify the specific earthquake event and then find its date. Let's start by searching for the entity representing the major San Francisco earthquake.

[Tool]
Top 10 entity alternatives:
1. 1906 San Francisco earthquake, also known as Great San Francisco Earthquake and Fire, San Francisco earthquake of 1906, San Francisco earthquake and fire, 1906, Great 1906 San Francisco Earthquake, earthquake of 1906 (wd:Q211386): major earthquake that struck San Francisco and the coast of Northern California
2. 1906 San Francisco earthquake, also known as 1906 San Francisco earthquake and fire, earthquake of 1906, San Francisco earthquake of 1906, Great 1906 San Francisco Earthquake, Great San Francisco Earthquake and Fire (wd:Q211386): major earthquake that struck San Francisco and the coast of Northern California
3. 1989 Loma Prieta earthquake, also known as 1989 San Francisco earthquake, Loma Prieta earthquake (wd:Q1053476): major earthquake in northern California
4. 1957 San Francisco earthquake (wd:Q20312370)
5. Earthquake waves at San Francisco (wd:Q80986050): scientific article published on 01 February 1884
6. The Great San Francisco Earthquake (wd:Q125816606): scientific article published in 1988
7. The San Francisco earthquake of 1906 (wd:Q58176314): scholarly article by Dennis R. Dean published November 1993 in Annals of Science
8. Saints and the San Francisco earthquake (wd:Q57138167): scientific article published on 01 January 1983
9. The Big Picture: San Francisco Earthquake (wd:Q110056932): sketch from Saturday Night Live
10. Psychic Effects of the San Francisco Earthquake (wd:Q57143755): scholarly article published 4 August 1906 in The Hospital

No other items found

[Assistant]
The top result is the 1906 San Francisco earthquake, which is commonly referred to as the "Great San Francisco Earthquake." Now, let's find the date of this earthquake.

I will execute a SPARQL query to retrieve the date of the 1906 San Francisco earthquake.

[Tool]
Got 1 row and 1 column:
| ?date                |
| -------------------- |
| 1906-04-18T00:00:00Z |

[Assistant]
The 1906 San Francisco earthquake occurred on April 18, 1906.

Here is the final SPARQL query and answer:

```sparql
SELECT ?date WHERE {
  wd:Q211386 wdt:P585 ?date .
}
```

The big earthquake hit San Francisco on April 18, 1906.

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?coordinates WHERE {
  wd:Q819 wdt:P625 ?coordinates .
}

Laos is located at the coordinates 104.100000, 18.200000.

[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 is laos in world map?

[Assistant]
To answer the question "Where is Laos in the world map?", we need to find the geographical location of Laos. Specifically, we should look for the coordinates or the country's position on the map.

Let's start by finding the entity for Laos and then look for its geographical information.

[Tool]
Top 10 entity alternatives:
1. Laos, also known as LAO, Lao PDR, Lao People's Democratic Republic, la (wd:Q819): country in Southeast Asia
2. Tai peoples, also known as Laos, Shans (wd:Q703353): ethnic group
3. Laotians, also known as Lao, Laos (wd:Q11346642): citizens or residents of Laos
4. Laos (wd:Q28322504): family name
5. Laos (wd:Q3217694): German hard rock band
6. Laos (wd:Q103947900): encyclopedia article
7. Laos. (wd:Q47411910): scientific article published in May 1986
8. Laos (wd:Q59597671): Congressional Research Service report
9. Laos (wd:Q58675659): scholarly article
10. Laos (wd:Q130900075): scientific article published in January 2003

No other items found

[Assistant]
The top result for "Laos" is `wd:Q819`, which represents the country Laos (Lao People's Democratic Republic). Now, let's find the geographical coordinates of Laos.

We will look for the property that provides the coordinates of a country. The property `P625` (coordinate location) is commonly used for this purpose.

Let's check if Laos has a coordinate location.

[Tool]
Got 1 row and 3 columns:
| subject        | property                       | object                      |
| -------------- | ------------------------------ | --------------------------- |
| Laos (wd:Q819) | coordinate location (wdt:P625) | POINT(104.100000 18.200000) |

[Assistant]
Laos has a coordinate location of `POINT(104.100000 18.200000)`. These coordinates represent the geographical position of Laos on the world map.

Now, let's construct a SPARQL query to retrieve these coordinates.

```sparql
SELECT ?coordinates
WHERE {
  wd:Q819 wdt:P625 ?coordinates .
}
```

This query will return the coordinates of Laos.

Let's execute this query to confirm the result.

[Tool]
Got 1 row and 1 column:
| ?coordinates                |
| --------------------------- |
| POINT(104.100000 18.200000) |

[Assistant]
The SPARQL query successfully returned the coordinates of Laos, which are `POINT(104.100000 18.200000)`.

Therefore, the answer to the question "Where is Laos in the world map?" is:

Laos is located at the coordinates `104.100000, 18.200000`.

Here is the final SPARQL query:

```sparql
SELECT ?coordinates
WHERE {
  wd:Q819 wdt:P625 ?coordinates .
}
```

And the answer:

Laos is located at the coordinates `104.100000, 18.200000`.

[Tool] Stopped generation process