PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT DISTINCT ?work ?workLabel WHERE {
  ?work wdt:P161 wd:Q587156 ; wdt:P31 / wdt:P279 * wd:Q11424 .
  OPTIONAL {
    ?work rdfs:label ?workLabel FILTER ( LANG( ?workLabel ) = "en" )
  }
}

Got 9 rows and 2 columns:
| work                                     | workLabel                       |
| ---------------------------------------- | ------------------------------- |
| The Car (wd:Q1197355)                    | The Car (en)                    |
| Escape to Witch Mountain (wd:Q1212511)   | Escape to Witch Mountain (en)   |
| Return from Witch Mountain (wd:Q1925695) | Return from Witch Mountain (en) |
| Raid on Entebbe (wd:Q2305094)            | Raid on Entebbe (en)            |
| Tuff Turf (wd:Q2362823)                  | Tuff Turf (en)                  |
| Assault on Precinct 13 (wd:Q434718)      | Assault on Precinct 13 (en)     |
| Black Snake Moan (wd:Q468660)            | Black Snake Moan (en)           |
| No Deposit, No Return (wd:Q7044096)      | No Deposit, No Return (en)      |
| Race to Witch Mountain (wd:Q922006)      | Race to Witch Mountain (en)     |

Kim Richards was in the following films: The Car, Escape to Witch Mountain, Return from Witch Mountain, Raid on Entebbe, Tuff Turf, Assault on Precinct 13, Black Snake Moan, No Deposit, No Return, 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

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

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

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

[User] what was kim richards in?

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

[Tool]
Example 1:
Question:
what has lucy hale played in?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x wdt:P161 wd:Q229940 ; wdt:P31 / wdt:P279 * wd:Q11424 .
}

Using entities:
film, also known as cinematic work, moving picture, movie, motion pictures, motion picture (wd:Q11424): sequence of images that give the impression of movement, stored on film stock
Lucy Hale, also known as Lucy Kate Hale, Karen Lucille Hale (wd:Q229940): American actress and singer, television actor, songwriter, film actor, musician, designer, singer, actor, model

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

Example 2:
Question:
what did shawnee smith star in?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x wdt:P161 wd:Q233313 ; wdt:P31 / wdt:P279 * wd:Q11424 .
}

Using entities:
film, also known as cinematic work, moving picture, movie, motion pictures, motion picture (wd:Q11424): sequence of images that give the impression of movement, stored on film stock
Shawnee Smith, also known as Shawnee Rebecca Smith (wd:Q233313): singer-songwriter, television actor, American actress, stage actor, film actor, presenter, singer, actor

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

Example 3:
Question:
what does kat dennings star in?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x wdt:P161 wd:Q231751 ; wdt:P31 / wdt:P279 * wd:Q11424 .
}

Using entities:
film, also known as cinematic work, moving picture, movie, motion pictures, motion picture (wd:Q11424): sequence of images that give the impression of movement, stored on film stock
Kat Dennings, also known as Katherine Victoria Litwack (wd:Q231751): American actress (born 1986), television actor, voice actor, film actor, actor

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

[Assistant]
The examples show that to find what a person "was in" (such as films or TV shows), we can look for works where the person is a cast member (property wdt:P161) and the work is an instance or subclass of film or similar (wd:Q11424).

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

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

[Assistant]
The Kim Richards we are interested in is the American actress and television personality born in 1964 with the Wikidata ID wd:Q587156.

Now, I will construct a query to find the films or TV shows where Kim Richards (wd:Q587156) was a cast member. I will look for works that are instances or subclasses of film or television series (wd:Q11424).

[Tool]
Got 9 rows and 2 columns:
| work                                     | workLabel                       |
| ---------------------------------------- | ------------------------------- |
| The Car (wd:Q1197355)                    | The Car (en)                    |
| Escape to Witch Mountain (wd:Q1212511)   | Escape to Witch Mountain (en)   |
| Return from Witch Mountain (wd:Q1925695) | Return from Witch Mountain (en) |
| Raid on Entebbe (wd:Q2305094)            | Raid on Entebbe (en)            |
| Tuff Turf (wd:Q2362823)                  | Tuff Turf (en)                  |
| Assault on Precinct 13 (wd:Q434718)      | Assault on Precinct 13 (en)     |
| Black Snake Moan (wd:Q468660)            | Black Snake Moan (en)           |
| No Deposit, No Return (wd:Q7044096)      | No Deposit, No Return (en)      |
| Race to Witch Mountain (wd:Q922006)      | Race to Witch Mountain (en)     |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves films in which Kim Richards was a cast member by filtering works that are instances or subclasses of films. The answer lists the films found in the query result, which matches the execution result. The query uses appropriate properties and entities, and the answer is complete and accurate. No further refinement is necessary.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?writingSystem ?writingSystemLabel WHERE {
  wd:Q7850 wdt:P282 ?writingSystem .
  OPTIONAL {
    ?writingSystem rdfs:label ?writingSystemLabel FILTER ( LANG( ?writingSystemLabel ) = "en" )
  }
}

Got 3 rows and 2 columns:
| writingSystem                               | writingSystemLabel                  |
| ------------------------------------------- | ----------------------------------- |
| traditional Chinese characters (wd:Q178528) | traditional Chinese characters (en) |
| simplified Chinese characters (wd:Q185614)  | simplified Chinese characters (en)  |
| Chinese characters (wd:Q8201)               | Chinese characters (en)             |

The Chinese writing system is called "Chinese characters," which includes both "traditional Chinese characters" and "simplified 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

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

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

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

[User] what do you call the chinese writing system?

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

[Tool]
Example 1:
Question:
what is the official language of china called?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q148 wdt:P37 ?x .
}

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

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

Example 2:
Question:
what language do chinese?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q148 wdt:P37 ?x .
}

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

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

Example 3:
Question:
what is the currency name of china?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q148 wdt:P38 ?x .
}

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

Using properties:
currency, also known as base currency, used money (wd:P38 as wdt): currency used by item, uses

[Assistant]
The question is about the name of the Chinese writing system. From the similar examples, we see that the entity for China is wd:Q148. However, the question is not about the language or currency but specifically about the writing system used in Chinese.

I will search for the entity "Chinese writing system" or "Chinese script" to find the relevant entity in Wikidata.

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

[Assistant]
The entity "writing system" (wd:Q8192) is a general term for any conventional method of visually representing verbal or signed communication. There is no direct entity named exactly "Chinese writing system," but we can use the general entity for writing system and specify it for Chinese.

Next, I will search for properties related to "Chinese writing system" or "Chinese script" to find how to link it to Chinese or to specify the Chinese writing system.

[Tool]
Top 10 property alternatives:
1. writing system, also known as script, writing script, written form (wd:P282 as prv/psv/pq/psn/pr/pqv/p/wdtn/ps/wdt/pqn/prn): alphabet, character set or other system of writing used by a language, word, or text, supported by a typeface
2. Han character in this lexeme, also known as contains kanji, kanji in this lexeme, hanzi in this lexeme, hanja in this lexeme, contains Hanzi (wd:P5425 as prv/psv/pq/psn/pr/pqv/p/wdtn/ps/wdt/pqn/prn): Han character(s) this lexeme consists of
3. CJKV variant character, also known as simplified character, traditional character, variant character, variant Chinese character, variant ideograph (wd:P5475 as prv/psv/pq/psn/pr/pqv/p/wdtn/ps/wdt/pqn/prn): equivalent form of this CJKV character used in different regions or writing systems over time
4. Hanyu Pinyin transliteration, also known as zh-Latn-pinyin, zh-Latn-TW-pinyin, zh-Latn-CN-pinyin, Pinyin, Hanyu Pinyin (wd:P1721 as prv/psv/pq/psn/pr/pqv/p/wdtn/ps/wdt/pqn/prn): hanyu pinyin transliteration of a Mandarin Chinese text (usually to be used as a qualifier), transliteration or transcription
5. sinogram reading pattern, also known as kanji reading pattern, reading pattern, reading pattern of CJKV ideograph, reading pattern of kanji, reading pattern of sinogram (wd:P5244 as prv/psv/pq/psn/pr/pqv/p/wdtn/ps/wdt/pqn/prn)
6. writing language, also known as languages of writings, languages written, language written, writing languages, language of works (wd:P6886 as prv/psv/pq/psn/pr/pqv/p/wdtn/ps/wdt/pqn/prn): language in which the writer has written their work, languages spoken, written or signed
7. has kanji reading, also known as kanji reading, reading as a kanji (wd:P13045 as prv/psv/pq/psn/pr/pqv/p/wdtn/ps/wdt/pqn/prn): phonetic reading or pronunciation of the kanji
8. Unicode character, also known as emoji, emote, pictograph, Unicode symbol (wd:P487 as prv/psv/pq/psn/pr/pqv/p/wdtn/ps/wdt/pqn/prn): Unicode character representing the item (only if this is not a c...acter or a compatiblity character: in that case, use only P4213)
9. languages spoken, written or signed, also known as language of expression, language, wrote language, writes language, uses language (wd:P1412 as prv/psv/pq/psn/pr/pqv/p/wdtn/ps/wdt/pqn/prn): language(s) that a person or a people speaks, writes or signs, including the native language(s)
10. typeface/font used, also known as is sample of, typeface used, typeface, lettering, font used (wd:P2739 as prv/psv/pq/psn/pr/pqv/p/wdtn/ps/wdt/pqn/prn): style of type used in a work

[Assistant]
The property "writing system" (wdt:P282) is described as alphabet, character set or other system of writing used by a language, word, or text. This seems to be the most relevant property to describe the writing system used by a language.

Next, I will search for the entity "Chinese language" to link it with the writing system property.

[Tool]
Top 10 entity alternatives:
1. Chinese, also known as Chinese language, Chinese languages, zh (wd:Q7850): language group of the Sinitic languages
2. Chinese, also known as Chinese language, Chinese languages, zh (wd:Q7850): language group of the Sinitic languages
3. Studies of the Chinese Language, also known as Chinese Language, Zhongguo Yuwen (wd:Q15762288): journal
4. Chinese Language (wd:Q110262537): Stack Exchange site for students, teachers, and linguists wanting to discuss the finer points of the Chinese language
5. Chinese language (wd:L1260101-S1)
6. Chinese language (wd:L727426-S1)
7. Sinitic, also known as Chinese languages, Sinitic languages (wd:Q33857): group of East Asian analytic languages and a major branch of the Sino-Tibetan language family
8. Tai Nüa, also known as Tai Le language, Tai Nüa language, Tai Na language, Tai Mau language, Tai Kong language (wd:Q36556): language
9. written Chinese language, also known as Chinese (wd:Q3110592): overview of writing varieties of Chinese, unified in Qin dynasty
10. Chinese Sign Language, also known as csl, CSL, ZGS (wd:Q1094190): sign language used in China and culturally related areas

[Assistant]
The entity "Chinese" (wd:Q7850) represents the Chinese language group. This is the appropriate entity to link with the writing system property.

Now I will construct a SPARQL query to find the writing system (wdt:P282) used by the Chinese language (wd:Q7850).

[Tool]
Got 3 rows and 2 columns:
| writingSystem                               | writingSystemLabel                  |
| ------------------------------------------- | ----------------------------------- |
| traditional Chinese characters (wd:Q178528) | traditional Chinese characters (en) |
| simplified Chinese characters (wd:Q185614)  | simplified Chinese characters (en)  |
| Chinese characters (wd:Q8201)               | Chinese characters (en)             |

[Assistant]
The Chinese writing system is called "Chinese characters," which includes both "traditional Chinese characters" and "simplified Chinese characters."

I will now provide the final answer with these details.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The answer correctly identifies the Chinese writing system as "Chinese characters," including both "traditional Chinese characters" and "simplified Chinese characters." The SPARQL query appropriately retrieves these writing systems related to the Chinese language (wd:Q7850) using the property for writing system (wdt:P282). The query returns the correct entities and their English labels, and the answer is clear and complete. No further refinement is necessary.


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX pq: <http://www.wikidata.org/prop/qualifier/>
PREFIX xsd: <http://www.w3.org/2001/XMLSchema#>
PREFIX p: <http://www.wikidata.org/prop/>
PREFIX ps: <http://www.wikidata.org/prop/statement/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?coach ?coachLabel WHERE {
  wd:Q330120 p:P286 ?statement .
  ?statement ps:P286 ?coach .
  ?statement pq:P580 ?start .
  ?statement pq:P582 ?end .
  FILTER ( ?start <= "2013-12-31T23:59:59Z" ^^ xsd:dateTime && ?end >= "2013-01-01T00:00:00Z" ^^ xsd:dateTime ) OPTIONAL {
    ?coach rdfs:label ?coachLabel FILTER ( LANG( ?coachLabel ) = "en" )
  }
}

The coach of the Carolina Panthers in 2013 was Ron Rivera.

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

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

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

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

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

[User] who will coach carolina panthers in 2013?

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

[Tool]
Example 1:
Question:
what is the name of the pittsburgh steelers head coach?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q191477 wdt:P286 ?x .
}

Using entities:
Pittsburgh Steelers, also known as Pittsburgh Pirates, Rooneymen, Steelers (wd:Q191477): professional American football team based in Pittsburgh, Pennsylvania

Using properties:
head coach, also known as team manager, trainer, senior coach, manager, coached by (wd:P286 as wdt): 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

Example 2:
Question:
who is the head coach of the chicago blackhawks?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q209636 wdt:P286 ?x .
}

Using entities:
Chicago Blackhawks, also known as Chicago Black Hawks, Hawks, Chicago Stadium Corporation (wd:Q209636): hockey team of the National Hockey League

Using properties:
head coach, also known as team manager, trainer, senior coach, manager, coached by (wd:P286 as wdt): 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

Example 3:
Question:
who has coached the baltimore ravens?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q276539 wdt:P286 ?x .
}

Using entities:
Baltimore Ravens (wd:Q276539): National Football League franchise in Baltimore, Maryland

Using properties:
head coach, also known as team manager, trainer, senior coach, manager, coached by (wd:P286 as wdt): 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

[Assistant]
From the examples, the property for head coach or coach of a sports team is wdt:P286. The Carolina Panthers is a professional American football team, so we need to find the entity for Carolina Panthers and then query for the head coach in the year 2013.

Next, I will search for the entity "Carolina Panthers" in Wikidata.

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

[Assistant]
The entity for the Carolina Panthers American football team is wd:Q330120. The property for head coach is wdt:P286. Since the question asks for the coach in 2013, we need to find the coach of the Carolina Panthers specifically for the year 2013.

I will now search for the property related to the time or date qualifier for the head coach property to filter the coach by the year 2013.

[Tool]
Top 10 property alternatives:
1. head coach, also known as team manager, trainer, senior coach, manager, coached by (wd:P286 as wdt/p): on-field manager or head coach of a sports club (not to be confu...eneral manager P505, which is not a coaching position) or person
2. sport, also known as play, plays, sport played, sports (wd:P641 as wdt/p): sport that the subject participates or participated in or is associated with
3. league or competition, also known as tournament, sports league, division, cup, competition (wd:P118 as wdt/p): league or competition in which team or player has played, or in which an event occurs, participant in
4. owned by, also known as belongs to, stockholders, stockholder, shareholders, shareholder (wd:P127 as wdt/p): owner of the subject
5. category for members of a team, also known as category for players, category for team members (wd:P6112 as wdt/p): Wikimedia category for players playing for a sports team, topic's main category
6. home venue, also known as home water, venue, stadium, home ground, home field (wd:P115 as wdt/p): 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 wdt/p): 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 wdt/p): entities owned by the subject
10. 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

No other items found

[Assistant] The property for head coach is confirmed as wdt:P286. To find the coach specifically for the year 2013, we need to check the statements for the head coach property with a qualifier for the time or start/end date. I will now list the statements for the Carolina Panthers (wd:Q330120) with the property head coach (wdt:P286) to see if there are qualifiers for the coaching periods.

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

[Assistant]
The current direct property wdt:P286 shows the head coach as Dave Canales, but this is likely the current coach and does not specify the year 2013.

To get the coach for a specific year, we need to look at the statement level (not the direct property) to check for qualifiers such as start time or end time. I will now query the statement for the head coach (P286) of Carolina Panthers (Q330120) with qualifiers for start time or end time to find the coach for 2013.

[Tool]
SPARQL execution failed:
Error while executing a SERVICE request to <http://wikiba.se:80/ontology#label>: SERVICE responded with HTTP status code: 301, Moved Permanently. First 100 bytes of the response: '<html>
<head><title>301 Moved Permanently</title></head>
<body>
<center><h1>301 Moved Permanently'

[Assistant] The query failed because the SERVICE wikibase:label is not supported by the endpoint. I will rewrite the query without using SERVICE wikibase:label and instead use optional rdfs:label to get the coach's name.

[Tool]
Got 8 rows and 4 columns:
| coach                       | coachLabel        | start                               | end                                 |
| --------------------------- | ----------------- | ----------------------------------- | ----------------------------------- |
| Matt Rhule (wd:Q14950994)   | Matt Rhule (en)   | 2020-01-01T00:00:00Z (xsd:dateTime) | 2022-01-01T00:00:00Z (xsd:dateTime) |
| Ron Rivera (wd:Q1991889)    | Ron Rivera (en)   | 2011-01-01T00:00:00Z (xsd:dateTime) | 2019-01-01T00:00:00Z (xsd:dateTime) |
| Dave Canales (wd:Q47456134) | Dave Canales (en) | 2024-01-01T00:00:00Z (xsd:dateTime) |                                     |
| Frank Reich (wd:Q5489177)   | Frank Reich (en)  | 2023-01-01T00:00:00Z (xsd:dateTime) | 2023-01-01T00:00:00Z (xsd:dateTime) |
| Chris Tabor (wd:Q57242442)  | Chris Tabor (en)  | 2023-01-01T00:00:00Z (xsd:dateTime) | 2023-01-01T00:00:00Z (xsd:dateTime) |
| Perry Fewell (wd:Q7169776)  | Perry Fewell (en) | 2019-01-01T00:00:00Z (xsd:dateTime) | 2019-01-01T00:00:00Z (xsd:dateTime) |
| John Fox (wd:Q719030)       | John Fox (en)     | 2002-01-01T00:00:00Z (xsd:dateTime) | 2010-01-01T00:00:00Z (xsd:dateTime) |
| Steven Wilks (wd:Q7615391)  | Steven Wilks (en) | 2022-01-01T00:00:00Z (xsd:dateTime) | 2022-01-01T00:00:00Z (xsd:dateTime) |

[Assistant]
The coach of the Carolina Panthers in 2013 was Ron Rivera. His coaching period started in 2011 and ended in 2019, which includes the year 2013.

I will now provide the final answer with the SPARQL query.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the head coach of the Carolina Panthers during the year 2013 by filtering the coaching statements with start and end times that cover the entire year. The query returns the coach's identifier and label, and the answer 'Ron Rivera' is accurate according to the data. The query follows the rules by returning identifiers and labels optionally, and it does not perform any post-processing outside SPARQL. No improvements are necessary.


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

Got 5 rows and 2 columns:
| spouse                          | spouseLabel             |
| ------------------------------- | ----------------------- |
| Erika Koike (wd:Q109355321)     | Erika Koike (en)        |
| Riko Shibata (wd:Q109355504)    | Riko Shibata (en)       |
| Alice Kim Cage (wd:Q12606061)   | Alice Kim Cage (en)     |
| Patricia Arquette (wd:Q215976)  | Patricia Arquette (en)  |
| Lisa Marie Presley (wd:Q237324) | Lisa Marie Presley (en) |

Nicolas Cage has been married to Erika Koike, Riko Shibata, Alice Kim Cage, Patricia Arquette, and Lisa Marie Presley.

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

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

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

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

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

[User] who is nicolas cage married too?

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

[Tool]
Example 1:
Question:
who did corey feldman married?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q375419 wdt:P26 ?x .
}

Using entities:
Corey Feldman (wd:Q375419): American actor and musician, television producer, television actor, film producer, film director, voice actor, stage actor, film actor, composer, singer, actor

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

Example 2:
Question:
who tom cruise been married to?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q37079 wdt:P26 ?x .
}

Using entities:
Tom Cruise, also known as Thomas Cruise Mapother IV (wd:Q37079): American actor and producer (born 1962), stunt performer, aircraft pilot, film producer, film director, screenwriter, film actor, producer, director, writer, actor

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

Example 3:
Question:
who did scarlett johansson married?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q34436 wdt:P26 ?x .
}

Using entities:
Scarlett Johansson, also known as Scarlett Ingrid Johansson (wd:Q34436): American actress (born 1984), recording artist, film director, stage actor, voice actor, film actor, singer, model, actor

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

[Assistant] From the examples, the property for spouse or married partner is wdt:P26. Now I will search for the entity "Nicolas Cage" to get his Wikidata ID.

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

[Assistant] The entity for Nicolas Cage is wd:Q42869. Now I will query for his spouse using the property wdt:P26.

[Tool]
Got 5 rows and 2 columns:
| spouse                          | spouseLabel             |
| ------------------------------- | ----------------------- |
| Erika Koike (wd:Q109355321)     | Erika Koike (en)        |
| Riko Shibata (wd:Q109355504)    | Riko Shibata (en)       |
| Alice Kim Cage (wd:Q12606061)   | Alice Kim Cage (en)     |
| Patricia Arquette (wd:Q215976)  | Patricia Arquette (en)  |
| Lisa Marie Presley (wd:Q237324) | Lisa Marie Presley (en) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves all spouses of Nicolas Cage using the property wdt:P26. The answer lists all the spouses found in the query result, which matches the known information about Nicolas Cage's marriages. The query also optionally retrieves English labels for the spouses, which is helpful for readability. The output is complete, accurate, and follows the rules for SPARQL queries. No further refinement is necessary.


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

Got 1 row and 2 columns:
| placeOfBirth    | placeOfBirthLabel |
| --------------- | ----------------- |
| London (wd:Q84) | London (en)       |

Elvis Costello was born in London.

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

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

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

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

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

[User] where was elvis costello born?

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

[Tool]
Example 1:
Question:
what city did elvis presley grew up in?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q303 wdt:P19 ?x .
}

Using entities:
Elvis Presley, also known as The King of Rock'n'Roll, Elvis A. Presley, King of Rock'n'Roll, Elvis, Elvis Aaron Presley (wd:Q303): American singer and actor (1935–1977), military personnel, military officer, philanthropist, film actor, composer, activist, singer, actor

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

Example 2:
Question:
where did elvis presley started his career?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q303 wdt:P19 ?x .
}

Using entities:
Elvis Presley, also known as The King of Rock'n'Roll, Elvis A. Presley, King of Rock'n'Roll, Elvis, Elvis Aaron Presley (wd:Q303): American singer and actor (1935–1977), military personnel, military officer, philanthropist, film actor, composer, activist, singer, actor

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

Example 3:
Question:
where was tommy emmanuel born?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q310298 wdt:P19 ?x .
}

Using entities:
Tommy Emmanuel, also known as William Thomas Emmanuel (wd:Q310298): Australian guitarist, jazz guitarist, percussionist, jazz musician, songwriter, guitarist, composer, lecturer, singer

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

[Assistant] From the examples, we see that the property for place of birth is wdt:P19 and the entity for Elvis Costello needs to be identified. Next, I will search for the entity "Elvis Costello" in Wikidata.

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

[Assistant] The entity for Elvis Costello as the English singer-songwriter is wd:Q206939. Now I will query the place of birth (wdt:P19) for this entity.

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

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the place of birth for Elvis Costello using the property P19 (place of birth). The query returns the identifier and the English label for the place, which is London (wd:Q84). The answer provided is accurate and complete. The query follows the rules by returning the identifier and optionally the label, and the answer matches the query result. No further refinement is necessary.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT DISTINCT ?movie ?movieLabel WHERE {
  ?movie wdt:P161 wd:Q187038 ; wdt:P31 / wdt:P279 * wd:Q11424 .
  OPTIONAL {
    ?movie rdfs:label ?movieLabel FILTER ( LANG( ?movieLabel ) = "en" )
  }
}

Got 111 rows and 2 columns, showing the first 5 and last 5 rows below:
| movie                             | movieLabel               |
| --------------------------------- | ------------------------ |
| Think Big (wd:Q1031705)           | Think Big (en)           |
| Death Race (wd:Q1033191)          | Death Race (en)          |
| The Misfit Brigade (wd:Q10478647) | The Misfit Brigade (en)  |
| Deathsport (wd:Q1134750)          | Deathsport (en)          |
| Crank: High Voltage (wd:Q1138916) | Crank: High Voltage (en) |
| ...                               | ...                      |
| Mean Streets (wd:Q841335)         | Mean Streets (en)        |
| True Legend (wd:Q910896)          | True Legend (en)         |
| Kill Bill: Volume 2 (wd:Q928019)  | Kill Bill: Volume 2 (en) |
| Big Stan (wd:Q939728)             | Big Stan (en)            |
| Behind Enemy Lines (wd:Q946863)   | Behind Enemy Lines (en)  |

David Carradine played in 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 among others. There are 111 movies in total found in the knowledge graph.

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

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

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

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

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

[User] what movies did david carradine play in?

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

[Tool]
Example 1:
Question:
what movies did quentin tarantino star in?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x wdt:P161 wd:Q3772 ; wdt:P31 / wdt:P279 * wd:Q11424 .
}

Using entities:
film, also known as cinematic work, moving picture, movie, motion pictures, motion picture (wd:Q11424): sequence of images that give the impression of movement, stored on film stock
Quentin Tarantino, also known as Quentin Jerome Tarantino, Tarantino (wd:Q3772): American filmmaker, television actor, film director, film producer, screenwriter, film editor, film actor, producer, director, author, writer, actor

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

Example 2:
Question:
what did shawnee smith star in?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x wdt:P161 wd:Q233313 ; wdt:P31 / wdt:P279 * wd:Q11424 .
}

Using entities:
film, also known as cinematic work, moving picture, movie, motion pictures, motion picture (wd:Q11424): sequence of images that give the impression of movement, stored on film stock
Shawnee Smith, also known as Shawnee Rebecca Smith (wd:Q233313): singer-songwriter, television actor, American actress, stage actor, film actor, presenter, singer, actor

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

Example 3:
Question:
what films did patrick swayze star in?

SPARQL:
SELECT DISTINCT ?x WHERE {
  ?x wdt:P161 wd:Q49004 ; wdt:P31 / wdt:P279 * wd:Q11424 .
}

Using entities:
film, also known as cinematic work, moving picture, movie, motion pictures, motion picture (wd:Q11424): sequence of images that give the impression of movement, stored on film stock
Patrick Swayze, also known as Patrick Wayne Swayze (wd:Q49004): American actor, singer and dancer (1952–2009), singer-songwriter, television actor, film producer, choreographer, voice actor, film actor, aikidoka, dancer, singer, actor

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

[Assistant]
From the examples, it is clear that to find movies an actor played in, we can use the property "cast member" (wdt:P161) with the actor's entity and filter for instances of films (wd:Q11424).

Next, I will search for the entity of David Carradine in Wikidata to get his identifier.

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

[Assistant] The entity for David Carradine as an American actor is wd:Q187038. Now I will construct a SPARQL query to find movies (films) where David Carradine was a cast member.

[Tool]
Got 111 rows and 2 columns, showing the first 5 and last 5 rows below:
| movie                             | movieLabel               |
| --------------------------------- | ------------------------ |
| Think Big (wd:Q1031705)           | Think Big (en)           |
| Death Race (wd:Q1033191)          | Death Race (en)          |
| The Misfit Brigade (wd:Q10478647) | The Misfit Brigade (en)  |
| Deathsport (wd:Q1134750)          | Deathsport (en)          |
| Crank: High Voltage (wd:Q1138916) | Crank: High Voltage (en) |
| ...                               | ...                      |
| Mean Streets (wd:Q841335)         | Mean Streets (en)        |
| True Legend (wd:Q910896)          | True Legend (en)         |
| Kill Bill: Volume 2 (wd:Q928019)  | Kill Bill: Volume 2 (en) |
| Big Stan (wd:Q939728)             | Big Stan (en)            |
| Behind Enemy Lines (wd:Q946863)   | Behind Enemy Lines (en)  |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves movies in which David Carradine played by using the property 'cast member' (wdt:P161) and filtering for instances of films (wd:Q11424). The query also optionally retrieves English labels for the movies, which is helpful for readability. The answer provides a representative sample of movies along with the total count, which is informative and complete. The query and answer follow the rules and provide a correct and comprehensive response to the user's question.


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

Got 3 rows and 2 columns:
| formOfGovernment                      | formOfGovernmentLabel         |
| ------------------------------------- | ----------------------------- |
| representative democracy (wd:Q188759) | representative democracy (en) |
| presidential system (wd:Q49892)       | presidential system (en)      |
| federal republic (wd:Q512187)         | federal republic (en)         |

Brazil's political system is a representative democracy, a presidential system, and a federal republic.

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

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

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

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

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

[User] what type of political system is brazil?

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

[Tool]
Example 1:
Question:
what form of government does brazil have?

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

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

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

Example 2:
Question:
what sort of government does brazil have?

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

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

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

Example 3:
Question:
what is the president of brazil?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q155 wdt:P6 ?x .
}

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

Using properties:
head of government, also known as head of national government, mayor, premier, president, prime minister (wd:P6 as wdt): head of the executive power of this town, city, municipality, state, country, or other governmental body, director / manager, chairperson

[Assistant]
From the similar examples, we see that the property "basic form of government" (wdt:P122) is used to describe the type of political system a country has. Brazil is identified as wd:Q155 in Wikidata.

I will now write a SPARQL query to get the basic form of government for Brazil using this property.

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

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the types of political systems associated with Brazil using the property 'basic form of government' (wdt:P122). The results include 'representative democracy', 'presidential system', and 'federal republic', which accurately reflect Brazil's political system. The query also properly fetches English labels for readability. The answer is complete and correctly addresses the user's question.


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

The big earthquake that hit San Francisco, known as the 1906 San Francisco earthquake, occurred on 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

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

[Tool]
Example 1:
Question:
what year was the great san francisco fire?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q211386 wdt:P585 ?x .
}

Using entities:
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

Using properties:
point in time, also known as at time, as of, year, when, time of event (wd:P585 as wdt): date something took place, existed or a statement was true; for providing time use the "refine date" property (P4241)

Example 2:
Question:
when did the christchurch quake happened?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q151850 wdt:P585 ?x .
}

Using entities:
February 2011 Christchurch earthquake, also known as Christchurch 2011 earthquake, Christchurch earthquake (wd:Q151850): February 2011 earthquake in New Zealand

Using properties:
point in time, also known as at time, as of, year, when, time of event (wd:P585 as wdt): date something took place, existed or a statement was true; for providing time use the "refine date" property (P4241)

Example 3:
Question:
where did the loma prieta earthquake occur?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q1053476 wdt:P131 ?x .
}

Using entities:
1989 Loma Prieta earthquake, also known as 1989 San Francisco earthquake, Loma Prieta earthquake (wd:Q1053476): major earthquake in northern California

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

[Assistant] From the examples, I see that the 1906 San Francisco earthquake is represented by the entity wd:Q211386 and the property for the date or time of the event is wdt:P585 (point in time). I will now query the date when the 1906 San Francisco earthquake happened.

[Tool]
Got 1 row and 1 column:
| date                                |
| ----------------------------------- |
| 1906-04-18T00:00:00Z (xsd:dateTime) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the point in time (P585) for the 1906 San Francisco earthquake (Q211386), which is the date the earthquake occurred. The answer provided, April 18, 1906, matches the query result and is accurate. The query follows the rules by returning the actual identifier and the date. No further refinement is necessary.


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

Laos is located at the coordinates POINT(104.100000 18.200000) on the world map.

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

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

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

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

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

[User] where is laos in world map?

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

[Tool]
Example 1:
Question:
where is singapore on a world map?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q334 wdt:P625 ?x .
}

Using entities:
Singapore, also known as SIN, S'pore, Singapore City, SGP, SG (wd:Q334): sovereign island country and city-state in maritime Southeast Asia

Using properties:
coordinate location, also known as point on a map, gps coordinates, gps location, latitude, location (wd:P625 as wdt): geocoordinates of the subject. For Earth, please note that only WGS84 coordinating system is supported at the moment

Example 2:
Question:
where are the netherlands on a world map?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q55 wdt:P625 ?x .
}

Using entities:
Netherlands, also known as 🇳🇱, the Netherlands, NL, nl, NED (wd:Q55): country in Northwestern Europe with territories in the Caribbean

Using properties:
coordinate location, also known as point on a map, gps coordinates, gps location, latitude, location (wd:P625 as wdt): geocoordinates of the subject. For Earth, please note that only WGS84 coordinating system is supported at the moment

Example 3:
Question:
where great britain on the world map?

SPARQL:
SELECT DISTINCT ?x WHERE {
  wd:Q23666 wdt:P625 ?x .
}

Using entities:
Great Britain, also known as Gt. Brit, mainland Britain, GBR, GB, Britannia (wd:Q23666): island in the North Atlantic Ocean off the northwest coast of continental Europe

Using properties:
coordinate location, also known as point on a map, gps coordinates, gps location, latitude, location (wd:P625 as wdt): geocoordinates of the subject. For Earth, please note that only WGS84 coordinating system is supported at the moment

[Assistant]
From the similar examples, it is clear that to find the location of a country like Laos on the world map, we need to get the coordinate location (property P625) of Laos (entity Q819).

Next, I will search for the entity Laos in Wikidata to confirm its identifier.

[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

[Assistant] The entity for the country Laos is wd:Q819. Now I will write a SPARQL query to get the coordinate location (property P625) of Laos.

[Tool]
Got 1 row and 1 column:
| coordinate                                   |
| -------------------------------------------- |
| POINT(104.100000 18.200000) (geo:wktLiteral) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the geocoordinate location of Laos (wd:Q819) using the property P625. The answer provides the coordinates in the expected WGS84 format as a POINT with longitude and latitude. The query is simple, direct, and returns the correct information to answer the user's question about where Laos is on the world map. No further refinement is necessary.