PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?county ?countyLabel WHERE {
  wd:Q486472 wdt:P131 ?county .
  ?county rdfs:label ?countyLabel
  FILTER ( LANG( ?countyLabel ) = "en" )
}

Using entities:
- Kansas City (wd:Q486472), also known as Kansas City, Kansas, Kansas City, KS, Kansas, Kansas, KCK: is instance of city in the United States / is instance of city of the United States / is instance of big city / is instance of consolidated city-county / is instance of county seat / city and county seat of Wyandotte County, State of Kansas, United States

Using properties:
- located in the administrative territorial entity (wd:P131 as wdt), also known as administrative territorial entity, administrative territory, city, happens in, in, etc.: is subproperty of location / is subproperty of part of / the item is located on the territory of the following administrative entity / the item is located on the territory of the following administrative entity / the item is located on the territory of the following ... the item falls only partially into the administrative entity. / the item is located on the territory of the following ... the item falls only partially into the administrative entity.

Answer: Kansas City, Kansas is in Wyandotte County.

Kansas City, Kansas is in Wyandotte County.

SPARQL query over wikidata:
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?county ?countyLabel WHERE {
  wd:Q486472 wdt:P131 ?county .
  ?county rdfs:label ?countyLabel
  FILTER ( LANG( ?countyLabel ) = "en" )
}

Using entities:
- Kansas City (wd:Q486472), also known as Kansas City, Kansas, Kansas City, KS, Kansas, Kansas, KCK: is instance of city in the United States / is instance of city of the United States / is instance of big city / is instance of consolidated city-county / is instance of county seat / city and county seat of Wyandotte County, State of Kansas, United States

Using properties:
- located in the administrative territorial entity (wd:P131 as wdt), also known as administrative territorial entity, administrative territory, city, happens in, in, etc.: is subproperty of location / is subproperty of part of / the item is located on the territory of the following administrative entity / the item is located on the territory of the following administrative entity / the item is located on the territory of the following ... the item falls only partially into the administrative entity. / the item is located on the territory of the following ... the item falls only partially into the administrative entity.

Execution result:
Got 1 row and 2 columns:
| county                        | countyLabel                |
| ----------------------------- | -------------------------- |
| Wyandotte County (wd:Q375652) | Wyandotte County (lang:en) |

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

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. Search for the 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. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

Available knowledge graphs:
- wikidata at http://localhost:7001 with prefix index for entities and similarity index for properties, and notes:
  - P106 = occupation. Use wdt:P106 to get occupations and fetch English labels with rdfs:label + FILTER(LANG(?label)="en"). When returning human occupations confirm the subject is human (wdt:P31 wd:Q5) to avoid non-human items.
  - Population (P1082) and tabular (P4179): use wdt:P1082 for quick/direct values; for time-series/point-in-time use p:P1082 + ps:P1082 + pq:P585 and ORDER BY pq:P585 DESC. Inspect statement qualifiers (e.g., 'applies to part') and prov:wasDerivedFrom references (pr:P854 etc.) to detect city-proper vs metro/prefecture scopes before using values.
  - Common person properties: P31 (instance of human Q5), P106 (occupation), P569 (date of birth), P19 (place of birth), P27 (country of citizenship), P21 (sex/gender), P166 (award received). Use wdt: for direct values when possible.
  - P17 (country) can be incomplete/misleading for places (historical/overseas tags). To get modern cities in a country combine: instance-of city (P31=Q515) + wdt:P17 OR use wdt:P131* to find an admin parent whose wdt:P17 = the country. Also cross-check coordinates (P625) or admin hierarchy to spot outliers.
  - When filtering by date of birth (P569) use xsd:dateTime comparisons (e.g. >= "1900-01-01T00:00:00Z"^^xsd:dateTime). Be aware many items have year-only or imprecise dates and coverage is biased toward notable/public figures (sportspeople, politicians, artists).
  - To retrieve qualifiers (e.g., award year) use the statement/qualifier pattern: p:Pxxx / ps:Pxxx / pq:P585. Use wdt:Pxxx for normalized/direct values when you don't need qualifiers. Example: p:P166 + pq:P585 gives award year.
  - To get a person's occupations: use wdt:P106 for direct/normalized values and rdfs:label for human-readable names (FILTER(LANG(...))). Example: wd:Q... wdt:P106 ?occ . ?occ rdfs:label ?occLabel . FILTER(LANG(?occLabel)="en").
  - P166 = award received. Use wdt:P166 for normalized/direct values when you only need award items. To get award years or qualifiers use p:P166 / ps:P166 / pq:P585. Many statements lack pq:P585 — use OPTIONAL { ?stmt pq:P585 ?date } and ORDER BY DESC(?date). When listing award winners, filter ?person wdt:P31 wd:Q5 to ensure humans.
  - Population time-series pattern: wd:Q... p:P1082 ?stmt . ?stmt ps:P1082 ?pop . OPTIONAL { ?stmt pq:P585 ?date } . ORDER BY DESC(?date). pq:P585 is the point-in-time qualifier. IMPORTANT: time-series may mix scopes (city proper vs metro) — e.g., Tokyo has a 2016 entry ~38,140,000 likely metro vs smaller city figures. Inspect qualifiers/references for scope before use.
  - Use wdt:P131* to traverse the admin hierarchy and compare wdt:P17 on the place vs an admin parent to detect historical/colonial country assignments. When mismatches appear, inspect the admin parent's instance-of (P31), labels, qualifiers and references to interpret the historical scope.
  - wdt:P106 often yields multiple occupations for a person. Use GROUP_CONCAT(DISTINCT ?occLabel; separator=", ") or return multiple rows. Always fetch labels with rdfs:label + FILTER(LANG(?label)="en") to get readable occupation names.
  - When a search_entity returns multiple hits (person vs sculpture vs memorial), confirm you selected the human/statements by checking wdt:P31 (instance of) and relevant wdt: properties (e.g., wdt:P106). This avoids using a non-human QID by mistake.
  - search_autocomplete can be constrained with a SPARQL pattern containing ?search (e.g., SELECT * WHERE { ?search wdt:P31 wd:Q5 }). Use constraints to focus results (e.g., humans) and avoid ambiguous fallbacks; if it returns no results, fallback to search_entity and verify wdt:P31.
  - Use search_property_of_entity to find relevant properties for an entity (e.g., 'award' -> P166) and search_object_of_property to discover candidate objects (e.g., 'physicist' for P106). This reduces guessing P/Q ids and surfaces qualifiers.
  - Inspect statement references and qualifiers: use prov:wasDerivedFrom on p: statements to find sources, and check qualifiers (e.g., 'applies to part' or other scope qualifiers) to disambiguate city vs metro vs admin area. Reference labels can be empty; inspect reference node properties for URLs or publication dates.

Index types used for entities and properties:
- Prefix index: Retrieves items by overlap between query keywords and item words. The query keywords can match item words exactly or as prefixes.
- Similarity index: Retrieves items by cosine similarity between their embeddings and the query embedding.

General notes across knowledge graphs:
- Use rdfs:label + FILTER(LANG(?label)="en") for labels; avoid SERVICE wikibase:label. Use wdt:Pxxx for normalized/direct values when qualifiers aren't needed. Use p:Pxxx / ps:Pxxx / pq:Pxxx to access statement qualifiers (e.g., award year via pq:P585). When dates matter, prefer xsd:dateTime and watch for year-only precision.
- Practical query patterns: use rdfs:label + FILTER(LANG(...)) for labels. Use wdt:Pxxx for direct/normalized values when qualifiers aren't needed. Use p:Pxxx / ps:Pxxx / pq:Pxxx to access qualifiers (dates via pq:P585). For dates use xsd:dateTime and expect year-only precision. For places: combine P17 with P131 or coordinate (P625) filters to avoid historical/overseas mismatches.
- Use OPTIONAL for pq: qualifiers (e.g., pq:P585), sort by qualifier (ORDER BY pq:P585 DESC) to prefer recent values. Use GROUP_CONCAT to combine multiple labels/values in one row. Watch for typed literals (xsd:dateTime, xsd:decimal) when filtering or sorting.
- Before querying, use search_entity to resolve human-friendly names to wd:Q identifiers and verify instance-of (e.g., check wdt:P31 = wd:Q5 for humans) to avoid ambiguous matches. Prefer the top match but programmatically confirm P31 before using its data.
- Use search_property to confirm property identifiers (e.g., "country" -> P17) before embedding them in queries. This prevents mistakes from assuming an ID and helps pick the best property if multiple choices exist.
- search_autocomplete can fall back to an unconstrained search or error when there are too many candidates. If this happens (e.g., "more than the maximum supported number of subject candidates"), retry with narrower constraints such as instance-of (wdt:P31), additional type filters, or short prefixes to reduce the candidate set; otherwise fallback to search_entity and verify wdt:P31.
- Use list(...) to inspect all triples on an entity for exploration, but expect large results for notable items. Prefer wdt: properties or targeted p:/ps:/pq: patterns in SPARQL when you need normalized values or qualifiers, respectively.
- Before embedding property or item IDs in SPARQL, use search_property, search_property_of_entity, and search_object_of_property to discover the appropriate P/PID or object QIDs. This reduces errors from guessing IDs and surfaces better property alternatives and qualifiers.
- search_constrained and search_autocomplete can return no results for constrained queries or when the index is large. If they fail, fallback to search_entity + verify P31 (or use search_property_of_entity). Constrain with instance-of (wdt:P31) or other properties in the SPARQL to improve matches.
- When selecting awards by year, prefer xsd:dateTime range filters (e.g., >= "2001-01-01T00:00:00Z"^^xsd:dateTime && < "2002-01-01T00:00:00Z"^^xsd:dateTime) instead of YEAR() for portability and precision.
- When selecting award winners via wdt:P166, filter ?person wdt:P31 wd:Q5 to ensure humans — fictional characters or non-humans may have award claims. If you need award years use p:P166 / ps:P166 / pq:P585 and OPTIONAL { ?stmt pq:P585 ?year } to retrieve qualifier years.
- Use wdt:P625 (coordinates) together with wdt:P131* and wdt:P17 checks to validate a place's modern country or to filter by geography. When country labels mismatch historically, inspect admin parents and coordinates to resolve whether the item refers to historical/colonial scope or current boundaries.
- Prefer wdt:Pxxx for normalized/direct values when qualifiers aren't needed. Use p:Pxxx / ps:Pxxx / pq:Pxxx to access qualifiers (e.g., pq:P585 for award year). Always fetch labels with rdfs:label + FILTER(LANG(?label) = "en").
- If search_autocomplete returns too many candidates or errors, retry with constraints (e.g., SELECT * WHERE { ?search wdt:P31 wd:Q5 }) or narrower query text. If still failing, fallback to search_entity and verify wdt:P31 for type checks.
- For award-year queries use p:P166 / ps:P166 / pq:P585 to access award statements and year qualifiers. Filter by xsd:dateTime ranges (e.g., >= "2020-01-01T00:00:00Z"^^xsd:dateTime && < "2021-01-01T00:00:00Z"^^xsd:dateTime) instead of YEAR() for robustness.
- Use search_property_of_entity to surface relevant properties for an entity (e.g., 'birth' -> P569/P19). list(...) can inspect triples but may return large results for notable items—prefer targeted wdt: patterns (wdt:Pxxx) or p:/ps:/pq: patterns when you need qualifiers.

SPARQL prefixes for use in function calls:
- bd: <http://www.bigdata.com/rdf#
- cc: <http://creativecommons.org/ns#
- data: <https://www.wikidata.org/wiki/Special:EntityData/
- dc: <http://purl.org/dc/elements/1.1/
- dct: <http://purl.org/dc/terms/
- foaf: <http://xmlns.com/foaf/0.1/
- geo: <http://www.opengis.net/ont/geosparql#
- geof: <http://www.opengis.net/def/function/geosparql/
- gn: <http://www.geonames.org/ontology#
- hint: <http://www.bigdata.com/queryHints#
- 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/
- qb: <http://purl.org/linked-data/cube#
- qfn: <http://qlever.cs.uni-freiburg.de/function#
- ql: <http://qlever.cs.uni-freiburg.de/builtin-functions/
- qlss: <https://qlever.cs.uni-freiburg.de/spatialSearch/
- 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/
- void: <http://rdfs.org/ns/void#
- 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#

Additional rules to follow:
- Explain your thought process before and after each step and function call.
- Do not just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
- Do not ask the user for clarifications without first attempting to complete the task. If the task input is incomplete or ambiguous, try to make reasonable assumptions and document them.
- 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.
- Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
- 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.
- 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.
- 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.
- For questions with a "True" or "False" answer the SPARQL query should be an ASK query.

[User] what county is kansas city kansas?

[Assistant]
To determine the county in which Kansas City, Kansas is located, I need to find the administrative division (county) that contains this city.

### Step 1: Identify the entity for "Kansas City, Kansas"
I will first search for the entity representing "Kansas City, Kansas" in Wikidata.

Question: Kansas City Kansas

Top 10 entity alternatives:
1. Kansas City (wd:Q486472, matched via Kansas City, Kansas), also known as Kansas City, Kansas, Kansas City, KS, Kansas, Kansas, KCK: city and county seat of Wyandotte County, State of Kansas, United States / is instance of city in the United States / is instance of city of the United States / is instance of consolidated city-county / is instance of county seat / is instance of big city
2. Kansas City, Kansas (wd:Q20504965): painting by Henry Ossawa Tanner / painting by Henry Ossawa Tanner / is instance of painting
3. Kansas City, Kansas (wd:Q20504967): painting by Henry Ossawa Tanner (American Art, 1983.95.30) / painting by Henry Ossawa Tanner / is instance of painting
4. Kansas City, Kansas Mayors (wd:Q131927341): online exhibition from Kansas City Public Library (Kansas) / is instance of online exhibition
5. The Kansas City Kansas Republic (wd:Q100302325, matched via Kansas City Kansas Republic), also known as Kansas City Kansas Republic: newspaper published in Kansas City, Kansas / is instance of newspaper
6. The Kansas City Kansas News (wd:Q100302321, matched via Kansas City Kansas News), also known as Kansas City Kansas News: newspaper published in Kansas City, Kansas / is instance of newspaper
7. The Kansas City Kansas Globe (wd:Q100302319, matched via Kansas City Kansas Globe), also known as Kansas City Kansas Globe: newspaper published in Kansas City, Kansas / is instance of newspaper
8. Kansas City, Kansas Public Schools (wd:Q5856329), also known as KCKPS, U.S.D 500: school district in Kansas City, Kansas, United States / is instance of school district in the United States
9. Mayor of Kansas City, Kansas (wd:Q110633794), also known as Mayor of Kansas City: is subclass of mayor of a place in Kansas / political office in Kansas, United States / is instance of public office
10. Kansas City, Kansas Public Library (wd:Q30258034): archive organization in Kansas City, United States / is instance of cultural institution

[Assistant]
The top result, `wd:Q486472`, corresponds to "Kansas City, Kansas" as a city and county seat of Wyandotte County. This is the correct entity we are looking for.

### Step 2: Find the county (administrative division) of Kansas City, Kansas
The administrative division (county) of a city in the U.S. is typically represented by the property `wdt:P131` (located in the administrative territorial entity). I will query for the county using this property on `wd:Q486472`.

I will also retrieve the label of the county in English for clarity.

execute

SELECT ?county ?countyLabel WHERE { wd:Q486472 wdt:P131 ?county . ?county rdfs:label ?countyLabel FILTER(LANG(?countyLabel) = "en") }

[Assistant]
The query result shows that Kansas City, Kansas is located in **Wyandotte County**.

### Final Answer:
Kansas City, Kansas is in **Wyandotte County**.

I will now provide the final SPARQL query and answer.

answer

SELECT ?county ?countyLabel WHERE { wd:Q486472 wdt:P131 ?county . ?county rdfs:label ?countyLabel FILTER(LANG(?countyLabel) = "en") }

Answer: Kansas City, Kansas is in Wyandotte County.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?performer WHERE {
  wd:Q25097 wdt:P175 ?performer
}

Using entities:
- Chucky (wd:Q25097), also known as Charles Lee, Charles Lee Ray, Charles Ray, Chucky the murderdoll, Good Guy doll, etc.: has occupation serial killer / is instance of film character / is instance of fictional puppet / horror film villain

Using properties:
- performer (wd:P175 as wdt), also known as actor, actress, artist, dancer, musical artist, etc.: is subproperty of contributor to the creative work or subject / actor, musician, band or other performer associated with this role or musical work / actor, musician, music group or other performer associated with this work

Answer: Brad Dourif

Brad Dourif

SPARQL query over wikidata:
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?performer WHERE {
  wd:Q25097 wdt:P175 ?performer
}

Using entities:
- Chucky (wd:Q25097), also known as Charles Lee, Charles Lee Ray, Charles Ray, Chucky the murderdoll, Good Guy doll, etc.: has occupation serial killer / is instance of film character / is instance of fictional puppet / horror film villain

Using properties:
- performer (wd:P175 as wdt), also known as actor, actress, artist, dancer, musical artist, etc.: is subproperty of contributor to the creative work or subject / actor, musician, band or other performer associated with this role or musical work / actor, musician, music group or other performer associated with this work

Execution result:
Got 1 row and 1 column:
| performer                |
| ------------------------ |
| Brad Dourif (wd:Q329734) |

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

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. Search for the 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. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

Available knowledge graphs:
- wikidata at http://localhost:7001 with prefix index for entities and similarity index for properties, and notes:
  - P106 = occupation. Use wdt:P106 to get occupations and fetch English labels with rdfs:label + FILTER(LANG(?label)="en"). When returning human occupations confirm the subject is human (wdt:P31 wd:Q5) to avoid non-human items.
  - Population (P1082) and tabular (P4179): use wdt:P1082 for quick/direct values; for time-series/point-in-time use p:P1082 + ps:P1082 + pq:P585 and ORDER BY pq:P585 DESC. Inspect statement qualifiers (e.g., 'applies to part') and prov:wasDerivedFrom references (pr:P854 etc.) to detect city-proper vs metro/prefecture scopes before using values.
  - Common person properties: P31 (instance of human Q5), P106 (occupation), P569 (date of birth), P19 (place of birth), P27 (country of citizenship), P21 (sex/gender), P166 (award received). Use wdt: for direct values when possible.
  - P17 (country) can be incomplete/misleading for places (historical/overseas tags). To get modern cities in a country combine: instance-of city (P31=Q515) + wdt:P17 OR use wdt:P131* to find an admin parent whose wdt:P17 = the country. Also cross-check coordinates (P625) or admin hierarchy to spot outliers.
  - When filtering by date of birth (P569) use xsd:dateTime comparisons (e.g. >= "1900-01-01T00:00:00Z"^^xsd:dateTime). Be aware many items have year-only or imprecise dates and coverage is biased toward notable/public figures (sportspeople, politicians, artists).
  - To retrieve qualifiers (e.g., award year) use the statement/qualifier pattern: p:Pxxx / ps:Pxxx / pq:P585. Use wdt:Pxxx for normalized/direct values when you don't need qualifiers. Example: p:P166 + pq:P585 gives award year.
  - To get a person's occupations: use wdt:P106 for direct/normalized values and rdfs:label for human-readable names (FILTER(LANG(...))). Example: wd:Q... wdt:P106 ?occ . ?occ rdfs:label ?occLabel . FILTER(LANG(?occLabel)="en").
  - P166 = award received. Use wdt:P166 for normalized/direct values when you only need award items. To get award years or qualifiers use p:P166 / ps:P166 / pq:P585. Many statements lack pq:P585 — use OPTIONAL { ?stmt pq:P585 ?date } and ORDER BY DESC(?date). When listing award winners, filter ?person wdt:P31 wd:Q5 to ensure humans.
  - Population time-series pattern: wd:Q... p:P1082 ?stmt . ?stmt ps:P1082 ?pop . OPTIONAL { ?stmt pq:P585 ?date } . ORDER BY DESC(?date). pq:P585 is the point-in-time qualifier. IMPORTANT: time-series may mix scopes (city proper vs metro) — e.g., Tokyo has a 2016 entry ~38,140,000 likely metro vs smaller city figures. Inspect qualifiers/references for scope before use.
  - Use wdt:P131* to traverse the admin hierarchy and compare wdt:P17 on the place vs an admin parent to detect historical/colonial country assignments. When mismatches appear, inspect the admin parent's instance-of (P31), labels, qualifiers and references to interpret the historical scope.
  - wdt:P106 often yields multiple occupations for a person. Use GROUP_CONCAT(DISTINCT ?occLabel; separator=", ") or return multiple rows. Always fetch labels with rdfs:label + FILTER(LANG(?label)="en") to get readable occupation names.
  - When a search_entity returns multiple hits (person vs sculpture vs memorial), confirm you selected the human/statements by checking wdt:P31 (instance of) and relevant wdt: properties (e.g., wdt:P106). This avoids using a non-human QID by mistake.
  - search_autocomplete can be constrained with a SPARQL pattern containing ?search (e.g., SELECT * WHERE { ?search wdt:P31 wd:Q5 }). Use constraints to focus results (e.g., humans) and avoid ambiguous fallbacks; if it returns no results, fallback to search_entity and verify wdt:P31.
  - Use search_property_of_entity to find relevant properties for an entity (e.g., 'award' -> P166) and search_object_of_property to discover candidate objects (e.g., 'physicist' for P106). This reduces guessing P/Q ids and surfaces qualifiers.
  - Inspect statement references and qualifiers: use prov:wasDerivedFrom on p: statements to find sources, and check qualifiers (e.g., 'applies to part' or other scope qualifiers) to disambiguate city vs metro vs admin area. Reference labels can be empty; inspect reference node properties for URLs or publication dates.

Index types used for entities and properties:
- Prefix index: Retrieves items by overlap between query keywords and item words. The query keywords can match item words exactly or as prefixes.
- Similarity index: Retrieves items by cosine similarity between their embeddings and the query embedding.

General notes across knowledge graphs:
- Use rdfs:label + FILTER(LANG(?label)="en") for labels; avoid SERVICE wikibase:label. Use wdt:Pxxx for normalized/direct values when qualifiers aren't needed. Use p:Pxxx / ps:Pxxx / pq:Pxxx to access statement qualifiers (e.g., award year via pq:P585). When dates matter, prefer xsd:dateTime and watch for year-only precision.
- Practical query patterns: use rdfs:label + FILTER(LANG(...)) for labels. Use wdt:Pxxx for direct/normalized values when qualifiers aren't needed. Use p:Pxxx / ps:Pxxx / pq:Pxxx to access qualifiers (dates via pq:P585). For dates use xsd:dateTime and expect year-only precision. For places: combine P17 with P131 or coordinate (P625) filters to avoid historical/overseas mismatches.
- Use OPTIONAL for pq: qualifiers (e.g., pq:P585), sort by qualifier (ORDER BY pq:P585 DESC) to prefer recent values. Use GROUP_CONCAT to combine multiple labels/values in one row. Watch for typed literals (xsd:dateTime, xsd:decimal) when filtering or sorting.
- Before querying, use search_entity to resolve human-friendly names to wd:Q identifiers and verify instance-of (e.g., check wdt:P31 = wd:Q5 for humans) to avoid ambiguous matches. Prefer the top match but programmatically confirm P31 before using its data.
- Use search_property to confirm property identifiers (e.g., "country" -> P17) before embedding them in queries. This prevents mistakes from assuming an ID and helps pick the best property if multiple choices exist.
- search_autocomplete can fall back to an unconstrained search or error when there are too many candidates. If this happens (e.g., "more than the maximum supported number of subject candidates"), retry with narrower constraints such as instance-of (wdt:P31), additional type filters, or short prefixes to reduce the candidate set; otherwise fallback to search_entity and verify wdt:P31.
- Use list(...) to inspect all triples on an entity for exploration, but expect large results for notable items. Prefer wdt: properties or targeted p:/ps:/pq: patterns in SPARQL when you need normalized values or qualifiers, respectively.
- Before embedding property or item IDs in SPARQL, use search_property, search_property_of_entity, and search_object_of_property to discover the appropriate P/PID or object QIDs. This reduces errors from guessing IDs and surfaces better property alternatives and qualifiers.
- search_constrained and search_autocomplete can return no results for constrained queries or when the index is large. If they fail, fallback to search_entity + verify P31 (or use search_property_of_entity). Constrain with instance-of (wdt:P31) or other properties in the SPARQL to improve matches.
- When selecting awards by year, prefer xsd:dateTime range filters (e.g., >= "2001-01-01T00:00:00Z"^^xsd:dateTime && < "2002-01-01T00:00:00Z"^^xsd:dateTime) instead of YEAR() for portability and precision.
- When selecting award winners via wdt:P166, filter ?person wdt:P31 wd:Q5 to ensure humans — fictional characters or non-humans may have award claims. If you need award years use p:P166 / ps:P166 / pq:P585 and OPTIONAL { ?stmt pq:P585 ?year } to retrieve qualifier years.
- Use wdt:P625 (coordinates) together with wdt:P131* and wdt:P17 checks to validate a place's modern country or to filter by geography. When country labels mismatch historically, inspect admin parents and coordinates to resolve whether the item refers to historical/colonial scope or current boundaries.
- Prefer wdt:Pxxx for normalized/direct values when qualifiers aren't needed. Use p:Pxxx / ps:Pxxx / pq:Pxxx to access qualifiers (e.g., pq:P585 for award year). Always fetch labels with rdfs:label + FILTER(LANG(?label) = "en").
- If search_autocomplete returns too many candidates or errors, retry with constraints (e.g., SELECT * WHERE { ?search wdt:P31 wd:Q5 }) or narrower query text. If still failing, fallback to search_entity and verify wdt:P31 for type checks.
- For award-year queries use p:P166 / ps:P166 / pq:P585 to access award statements and year qualifiers. Filter by xsd:dateTime ranges (e.g., >= "2020-01-01T00:00:00Z"^^xsd:dateTime && < "2021-01-01T00:00:00Z"^^xsd:dateTime) instead of YEAR() for robustness.
- Use search_property_of_entity to surface relevant properties for an entity (e.g., 'birth' -> P569/P19). list(...) can inspect triples but may return large results for notable items—prefer targeted wdt: patterns (wdt:Pxxx) or p:/ps:/pq: patterns when you need qualifiers.

SPARQL prefixes for use in function calls:
- bd: <http://www.bigdata.com/rdf#
- cc: <http://creativecommons.org/ns#
- data: <https://www.wikidata.org/wiki/Special:EntityData/
- dc: <http://purl.org/dc/elements/1.1/
- dct: <http://purl.org/dc/terms/
- foaf: <http://xmlns.com/foaf/0.1/
- geo: <http://www.opengis.net/ont/geosparql#
- geof: <http://www.opengis.net/def/function/geosparql/
- gn: <http://www.geonames.org/ontology#
- hint: <http://www.bigdata.com/queryHints#
- 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/
- qb: <http://purl.org/linked-data/cube#
- qfn: <http://qlever.cs.uni-freiburg.de/function#
- ql: <http://qlever.cs.uni-freiburg.de/builtin-functions/
- qlss: <https://qlever.cs.uni-freiburg.de/spatialSearch/
- 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/
- void: <http://rdfs.org/ns/void#
- 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#

Additional rules to follow:
- Explain your thought process before and after each step and function call.
- Do not just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
- Do not ask the user for clarifications without first attempting to complete the task. If the task input is incomplete or ambiguous, try to make reasonable assumptions and document them.
- 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.
- Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
- 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.
- 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.
- 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.
- For questions with a "True" or "False" answer the SPARQL query should be an ASK query.

[User] who does the voice for chucky in child's play?

[Assistant]
To find out who does the voice for Chucky in Child's Play, I need to identify the relevant entity for Chucky and then find the voice actor associated with it.

Step 1: Search for the entity "Chucky" in Wikidata to identify the correct item.

Question: Chucky

Top 10 entity alternatives:
1. Hirving Lozano (wd:Q17633812, matched via Chucky), also known as Chucky, Chucky Lozano, Hirving Lozano Bahena, Hirving Rodrigo Lozano Bahena: has occupation association football player / Mexican association football player / has occupation soccer player / is instance of human / Mexican footballer / Mexican footballer
2. Chucky (wd:Q25097), also known as Charles Lee, Charles Lee Ray, Charles Ray, Chucky the murderdoll, Good Guy doll, etc.: is instance of fictional puppet / is instance of film character / has occupation serial killer / horror film villain
3. Chucky (wd:Q106824359): American horror television series / is instance of television series / is instance of serial
4. Chucky (wd:Q85752306): is instance of male given name
5. Matías Real (wd:Q126939089, matched via CHucky), also known as Bochi, chucker, CHucky: has occupation association football player / has occupation soccer player / is instance of human / futbolista argentino
6. Chucky (wd:Q130921788): scientific article published on 12 November 2013 / is instance of scholarly article / is instance of academic article
7. Chucky (wd:Q122300786): is instance of video game / 2019 video game
8. Chucky (wd:Q110058876): is instance of Saturday Night Live sketch / sketch from Saturday Night Live
9. Earth-Mover (wd:Q3046465, matched via Chucky), also known as Chuck Moss, Chucky, Jeanne Chretien: is instance of comics character / Marvel comics character
10. Chucky Atkins (wd:Q935693), also known as Kenneth Lavon Atkins, Kenneth Lavon "Chucky" Atkins: has occupation basketball player / American basketball player / is instance of human

[Assistant]
The correct entity for Chucky, the fictional character from Child's Play, is wd:Q25097, which is described as a fictional puppet and horror film villain. Now, I need to find the voice actor for this character.

Step 2: Investigate the properties of Chucky (wd:Q25097) to find the voice actor property.

Question: voice actor

Top 10 property alternatives:
1. present in work (wd:P1441 as p/wdt, matched via character in), also known as appeared in, appears in, appears in work, character in, featured in work, etc.: this (fictional or fictionalized) entity, place, or person ... P1343 for entities described in non-fictional accounts) / work in which this fictional entity (Q14897293) or historical ... P1343 for entities described in non-fictional accounts)
2. performer (wd:P175 as p/wdt, matched via actor), also known as actor, actress, artist, dancer, musical artist, etc.: actor, musician, band or other performer associated with this role or musical work / actor, musician, music group or other performer associated with this work / is subproperty of contributor to the creative work or subject
3. child (wd:P40 as p/wdt, matched via sons), also known as children, daughter, daughters, descendants, father of, etc.: subject has object as child. Do not use for stepchildren—use "relative" (P1038), qualified with "type of kinship" (P1039) / subject has the object in their family as their offspring son or daughter (independently of their age) / subject has object as biological, foster, and/or adoptive child / is subproperty of significant person / is subproperty of relative
4. enemy (wd:P7047 as p/wdt, matched via archvillain), also known as arch-enemy, archenemy, archfoe, archnemesis, archrival, etc.: opponent character or group of this fictive character or group / opponent character or group of this character or group / is subproperty of significant person
5. creator (wd:P170 as p/wdt, matched via artist (non-musical)), also known as art by, artist (non-musical), art work by, artwork by, by, etc.: maker of this creative work or other object (where no more specific property exists) / maker of this creative work or other object (where no more specific property exists) / maker of a creative work or other object (where no more specific property exists)
6. nickname (wd:P1449 as p/wdt, matched via fan-name), also known as aka, also known as, epithet, fan-name, fanname, etc.: informal name (for a pseudonym use P742) / is subproperty of name
7. given name (wd:P735 as p/wdt, matched via name), also known as Christian name, first name, forename, middle name, name, etc.: first name or another given name of this person; values used with the property should not link disambiguations nor family names / first name or another given name of this person; values used with the property shouldn't link disambiguations nor family names / first name or another given name of this person; values used with the property shouldn't link disambiguations nor family names / is subproperty of name
8. occupation (wd:P106 as p/wdt, matched via vocation), also known as avocation, career, craft, employ, employment, etc.: occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39) / occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39) / occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)
9. instance of (wd:P31 as p/wdt, matched via is a), also known as example of, has type, is a, is an, is of type, etc.: type to which this subject corresponds/belongs. Different ... and the volcano is a type (instance) of volcanic landform / that class of which this subject is a particular example and ... a subclass of mountain (and an instance of volcanic landform)
10. country of citizenship (wd:P27 as p/wdt, matched via citizen of), also known as citizen of, citizenship, country, (legal) nationality, nation, etc.: the object is a country that recognizes the subject as its citizen / the object is a country that recognizes the subject as its citizen / is subproperty of country

No other items found

[Assistant]
The property "performer" (wdt:P175) is the most relevant here, as it links a character to the actor or performer who portrayed or voiced them. I will now check the performer property for Chucky (wd:Q25097) to find the voice actor.

Step 3: Query the performer property for Chucky (wd:Q25097).

execute

SELECT ?performer WHERE { wd:Q25097 wdt:P175 ?performer }

[Assistant]
The voice actor for Chucky in Child's Play is Brad Dourif (wd:Q329734). I will now confirm this by retrieving the label for Brad Dourif to ensure accuracy.

Step 4: Retrieve the label for Brad Dourif (wd:Q329734).

SELECT ?label WHERE { wd:Q329734 rdfs:label ?label FILTER(LANG(?label) = "en") }

Got 1 row and 1 column:
| label                 |
| --------------------- |
| Brad Dourif (lang:en) |

[Assistant]
The voice actor for Chucky in Child's Play is Brad Dourif. I now have the final answer and will provide the SPARQL query and response.

answer

SELECT ?performer WHERE { wd:Q25097 wdt:P175 ?performer }

Answer: Brad Dourif


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?timeZone WHERE {
  wd:Q84 wdt:P421 ?timeZone
}

Using entities:
- London (wd:Q84), also known as Augusta, Big Smoke, Kaerlud, Karelundein, LDN, etc.: is instance of financial center / is instance of financial centre / is instance of national capital / is instance of megacity / is instance of metropolis / is instance of Metropolis / is instance of global city / is instance of geographic location / is instance of city / is instance of largest city / capital and largest city of England and the United Kingdom / capital of England and the United Kingdom

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

Answer: London, UK, is in the Europe/London time zone, which corresponds to Greenwich Mean Time (GMT) during standard time and British Summer Time (BST) during daylight saving time.

London, UK, is in the Europe/London time zone, which corresponds to Greenwich Mean Time (GMT) during standard time and British Summer Time (BST) during daylight saving time.

SPARQL query over wikidata:
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?timeZone WHERE {
  wd:Q84 wdt:P421 ?timeZone
}

Using entities:
- London (wd:Q84), also known as Augusta, Big Smoke, Kaerlud, Karelundein, LDN, etc.: is instance of financial center / is instance of financial centre / is instance of national capital / is instance of megacity / is instance of metropolis / is instance of Metropolis / is instance of global city / is instance of geographic location / is instance of city / is instance of largest city / capital and largest city of England and the United Kingdom / capital of England and the United Kingdom

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

Execution result:
Got 4 rows and 1 column:
| timeZone                        |
| ------------------------------- |
| Europe/London (wd:Q16894228)    |
| Greenwich Mean Time (wd:Q30192) |
| UTC±00:00 (wd:Q6574)            |
| UTC+01:00 (wd:Q6655)            |

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

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. Search for the 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. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

Available knowledge graphs:
- wikidata at http://localhost:7001 with prefix index for entities and similarity index for properties, and notes:
  - P106 = occupation. Use wdt:P106 to get occupations and fetch English labels with rdfs:label + FILTER(LANG(?label)="en"). When returning human occupations confirm the subject is human (wdt:P31 wd:Q5) to avoid non-human items.
  - Population (P1082) and tabular (P4179): use wdt:P1082 for quick/direct values; for time-series/point-in-time use p:P1082 + ps:P1082 + pq:P585 and ORDER BY pq:P585 DESC. Inspect statement qualifiers (e.g., 'applies to part') and prov:wasDerivedFrom references (pr:P854 etc.) to detect city-proper vs metro/prefecture scopes before using values.
  - Common person properties: P31 (instance of human Q5), P106 (occupation), P569 (date of birth), P19 (place of birth), P27 (country of citizenship), P21 (sex/gender), P166 (award received). Use wdt: for direct values when possible.
  - P17 (country) can be incomplete/misleading for places (historical/overseas tags). To get modern cities in a country combine: instance-of city (P31=Q515) + wdt:P17 OR use wdt:P131* to find an admin parent whose wdt:P17 = the country. Also cross-check coordinates (P625) or admin hierarchy to spot outliers.
  - When filtering by date of birth (P569) use xsd:dateTime comparisons (e.g. >= "1900-01-01T00:00:00Z"^^xsd:dateTime). Be aware many items have year-only or imprecise dates and coverage is biased toward notable/public figures (sportspeople, politicians, artists).
  - To retrieve qualifiers (e.g., award year) use the statement/qualifier pattern: p:Pxxx / ps:Pxxx / pq:P585. Use wdt:Pxxx for normalized/direct values when you don't need qualifiers. Example: p:P166 + pq:P585 gives award year.
  - To get a person's occupations: use wdt:P106 for direct/normalized values and rdfs:label for human-readable names (FILTER(LANG(...))). Example: wd:Q... wdt:P106 ?occ . ?occ rdfs:label ?occLabel . FILTER(LANG(?occLabel)="en").
  - P166 = award received. Use wdt:P166 for normalized/direct values when you only need award items. To get award years or qualifiers use p:P166 / ps:P166 / pq:P585. Many statements lack pq:P585 — use OPTIONAL { ?stmt pq:P585 ?date } and ORDER BY DESC(?date). When listing award winners, filter ?person wdt:P31 wd:Q5 to ensure humans.
  - Population time-series pattern: wd:Q... p:P1082 ?stmt . ?stmt ps:P1082 ?pop . OPTIONAL { ?stmt pq:P585 ?date } . ORDER BY DESC(?date). pq:P585 is the point-in-time qualifier. IMPORTANT: time-series may mix scopes (city proper vs metro) — e.g., Tokyo has a 2016 entry ~38,140,000 likely metro vs smaller city figures. Inspect qualifiers/references for scope before use.
  - Use wdt:P131* to traverse the admin hierarchy and compare wdt:P17 on the place vs an admin parent to detect historical/colonial country assignments. When mismatches appear, inspect the admin parent's instance-of (P31), labels, qualifiers and references to interpret the historical scope.
  - wdt:P106 often yields multiple occupations for a person. Use GROUP_CONCAT(DISTINCT ?occLabel; separator=", ") or return multiple rows. Always fetch labels with rdfs:label + FILTER(LANG(?label)="en") to get readable occupation names.
  - When a search_entity returns multiple hits (person vs sculpture vs memorial), confirm you selected the human/statements by checking wdt:P31 (instance of) and relevant wdt: properties (e.g., wdt:P106). This avoids using a non-human QID by mistake.
  - search_autocomplete can be constrained with a SPARQL pattern containing ?search (e.g., SELECT * WHERE { ?search wdt:P31 wd:Q5 }). Use constraints to focus results (e.g., humans) and avoid ambiguous fallbacks; if it returns no results, fallback to search_entity and verify wdt:P31.
  - Use search_property_of_entity to find relevant properties for an entity (e.g., 'award' -> P166) and search_object_of_property to discover candidate objects (e.g., 'physicist' for P106). This reduces guessing P/Q ids and surfaces qualifiers.
  - Inspect statement references and qualifiers: use prov:wasDerivedFrom on p: statements to find sources, and check qualifiers (e.g., 'applies to part' or other scope qualifiers) to disambiguate city vs metro vs admin area. Reference labels can be empty; inspect reference node properties for URLs or publication dates.

Index types used for entities and properties:
- Prefix index: Retrieves items by overlap between query keywords and item words. The query keywords can match item words exactly or as prefixes.
- Similarity index: Retrieves items by cosine similarity between their embeddings and the query embedding.

General notes across knowledge graphs:
- Use rdfs:label + FILTER(LANG(?label)="en") for labels; avoid SERVICE wikibase:label. Use wdt:Pxxx for normalized/direct values when qualifiers aren't needed. Use p:Pxxx / ps:Pxxx / pq:Pxxx to access statement qualifiers (e.g., award year via pq:P585). When dates matter, prefer xsd:dateTime and watch for year-only precision.
- Practical query patterns: use rdfs:label + FILTER(LANG(...)) for labels. Use wdt:Pxxx for direct/normalized values when qualifiers aren't needed. Use p:Pxxx / ps:Pxxx / pq:Pxxx to access qualifiers (dates via pq:P585). For dates use xsd:dateTime and expect year-only precision. For places: combine P17 with P131 or coordinate (P625) filters to avoid historical/overseas mismatches.
- Use OPTIONAL for pq: qualifiers (e.g., pq:P585), sort by qualifier (ORDER BY pq:P585 DESC) to prefer recent values. Use GROUP_CONCAT to combine multiple labels/values in one row. Watch for typed literals (xsd:dateTime, xsd:decimal) when filtering or sorting.
- Before querying, use search_entity to resolve human-friendly names to wd:Q identifiers and verify instance-of (e.g., check wdt:P31 = wd:Q5 for humans) to avoid ambiguous matches. Prefer the top match but programmatically confirm P31 before using its data.
- Use search_property to confirm property identifiers (e.g., "country" -> P17) before embedding them in queries. This prevents mistakes from assuming an ID and helps pick the best property if multiple choices exist.
- search_autocomplete can fall back to an unconstrained search or error when there are too many candidates. If this happens (e.g., "more than the maximum supported number of subject candidates"), retry with narrower constraints such as instance-of (wdt:P31), additional type filters, or short prefixes to reduce the candidate set; otherwise fallback to search_entity and verify wdt:P31.
- Use list(...) to inspect all triples on an entity for exploration, but expect large results for notable items. Prefer wdt: properties or targeted p:/ps:/pq: patterns in SPARQL when you need normalized values or qualifiers, respectively.
- Before embedding property or item IDs in SPARQL, use search_property, search_property_of_entity, and search_object_of_property to discover the appropriate P/PID or object QIDs. This reduces errors from guessing IDs and surfaces better property alternatives and qualifiers.
- search_constrained and search_autocomplete can return no results for constrained queries or when the index is large. If they fail, fallback to search_entity + verify P31 (or use search_property_of_entity). Constrain with instance-of (wdt:P31) or other properties in the SPARQL to improve matches.
- When selecting awards by year, prefer xsd:dateTime range filters (e.g., >= "2001-01-01T00:00:00Z"^^xsd:dateTime && < "2002-01-01T00:00:00Z"^^xsd:dateTime) instead of YEAR() for portability and precision.
- When selecting award winners via wdt:P166, filter ?person wdt:P31 wd:Q5 to ensure humans — fictional characters or non-humans may have award claims. If you need award years use p:P166 / ps:P166 / pq:P585 and OPTIONAL { ?stmt pq:P585 ?year } to retrieve qualifier years.
- Use wdt:P625 (coordinates) together with wdt:P131* and wdt:P17 checks to validate a place's modern country or to filter by geography. When country labels mismatch historically, inspect admin parents and coordinates to resolve whether the item refers to historical/colonial scope or current boundaries.
- Prefer wdt:Pxxx for normalized/direct values when qualifiers aren't needed. Use p:Pxxx / ps:Pxxx / pq:Pxxx to access qualifiers (e.g., pq:P585 for award year). Always fetch labels with rdfs:label + FILTER(LANG(?label) = "en").
- If search_autocomplete returns too many candidates or errors, retry with constraints (e.g., SELECT * WHERE { ?search wdt:P31 wd:Q5 }) or narrower query text. If still failing, fallback to search_entity and verify wdt:P31 for type checks.
- For award-year queries use p:P166 / ps:P166 / pq:P585 to access award statements and year qualifiers. Filter by xsd:dateTime ranges (e.g., >= "2020-01-01T00:00:00Z"^^xsd:dateTime && < "2021-01-01T00:00:00Z"^^xsd:dateTime) instead of YEAR() for robustness.
- Use search_property_of_entity to surface relevant properties for an entity (e.g., 'birth' -> P569/P19). list(...) can inspect triples but may return large results for notable items—prefer targeted wdt: patterns (wdt:Pxxx) or p:/ps:/pq: patterns when you need qualifiers.

SPARQL prefixes for use in function calls:
- bd: <http://www.bigdata.com/rdf#
- cc: <http://creativecommons.org/ns#
- data: <https://www.wikidata.org/wiki/Special:EntityData/
- dc: <http://purl.org/dc/elements/1.1/
- dct: <http://purl.org/dc/terms/
- foaf: <http://xmlns.com/foaf/0.1/
- geo: <http://www.opengis.net/ont/geosparql#
- geof: <http://www.opengis.net/def/function/geosparql/
- gn: <http://www.geonames.org/ontology#
- hint: <http://www.bigdata.com/queryHints#
- 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/
- qb: <http://purl.org/linked-data/cube#
- qfn: <http://qlever.cs.uni-freiburg.de/function#
- ql: <http://qlever.cs.uni-freiburg.de/builtin-functions/
- qlss: <https://qlever.cs.uni-freiburg.de/spatialSearch/
- 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/
- void: <http://rdfs.org/ns/void#
- 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#

Additional rules to follow:
- Explain your thought process before and after each step and function call.
- Do not just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
- Do not ask the user for clarifications without first attempting to complete the task. If the task input is incomplete or ambiguous, try to make reasonable assumptions and document them.
- 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.
- Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
- 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.
- 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.
- 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.
- For questions with a "True" or "False" answer the SPARQL query should be an ASK query.

[User] what is london uk time zone?

[Assistant]
To determine the time zone of London, UK, I need to find the time zone information associated with London. This can be done by querying Wikidata for the time zone of London.

Step 1: Identify the entity for London, UK.
I will first search for the entity corresponding to London in Wikidata.

Question: London

Top 10 entity alternatives:
1. London (wd:Q84), also known as Augusta, Big Smoke, Kaerlud, Karelundein, LDN, etc.: capital and largest city of England and the United Kingdom / capital of England and the United Kingdom / is instance of geographic location / is instance of financial center / is instance of financial centre / is instance of national capital / is instance of largest city / is instance of global city / is instance of Metropolis / is instance of metropolis / is instance of megacity / is instance of city
2. City of London (wd:Q23311, matched via London), also known as City and County of the City of London, City of London (unparished area), London, Square Mile, the City: city, ceremonial county and local government district that ... central business district in the London Region in England, UK / city, ceremonial county and local government district that ... and the primary central business district (CBD) of London / is instance of district of the United Kingdom / is instance of Ceremonial counties of England / is instance of ceremonial county of England / is instance of district with city status / is instance of central business district / is instance of financial centre / is instance of financial center / is instance of unparished area / is instance of city
3. London (wd:Q92561), also known as City of London, London, ON, London, Ontario: is instance of separated municipality in Ontario / is instance of single-tier municipality / city in Southwestern Ontario, Canada / is instance of big city / is instance of city
4. London (wd:Q3061911), also known as London, Kentucky, London, KY: is instance of city of the United States / is instance of city in the United States / city in Kentucky, United States
5. London (wd:Q1001456), also known as London, OH, London, Ohio: city in Madison County, Ohio, United States / city in Madison County, Ohio, United States / is instance of city in the United States / is instance of city of the United States / is instance of county seat
6. London (wd:Q79348), also known as London, AR, London, Arkansas: city in Pope County, Arkansas, United States / is instance of city in the United States / is instance of city of the United States
7. London (wd:Q586353), also known as London, CA, London, California: census designated place in Tulare County, California, United States / is instance of census-designated place in the United States / is instance of census-designated place
8. London Recordings (wd:Q935090, matched via London), also known as London, London Records: record label headquartered in the United Kingdom / is instance of record label / is instance of business
9. London (wd:Q1749384): 2005 film directed by Hunter Richards / is instance of film
10. London (wd:Q2477346), also known as Ronton: is instance of human settlement / human settlement in Kiribati / human settlement in Kiribati / settlement in Kiribati

[Assistant]
The top result for "London" is wd:Q84, which corresponds to London, the capital of England and the United Kingdom. This is the correct entity to use for our query.

Step 2: Find the time zone property for London.
I will now search for properties related to "time zone" for the entity wd:Q84 (London) to identify the correct property that holds the time zone information.

Question: time zone

Top 10 property alternatives:
1. located in time zone (wd:P421 as p/wdt, matched via time zone), also known as time zone, timezone, TZ, P421: time zone for this item / time zone for this item / time zone for this item / time zone for this item
2. coordinate location (wd:P625 as p/wdt, matched via longitude), also known as co-ordinate location, co-ordinates, coordinates, co-ords, coords, etc.: geocoordinates of the subject. For Earth, please note that only WGS84 coordinating system is supported at the moment / coordinates of the subject / coordinates of the subject
3. located in/on physical feature (wd:P706 as p/wdt, matched via geographical region), also known as geographical region, is in, is on, landform, located on island, etc.: located on the specified landform or body of water. Should ... (provinces, states, countries, etc.). / located on the specified (geo)physical feature. Should not be ... political/administrative (P131) or a mountain range (P4552). / is subproperty of location / is subproperty of part of
4. located in the administrative territorial entity (wd:P131 as p/wdt, matched via locality), also known as administrative territorial entity, administrative territory, city, happens in, in, etc.: the item is located on the territory of the following ... the item falls only partially into the administrative entity. / the item is located on the territory of the following ... the item falls only partially into the administrative entity. / the item is located on the territory of the following administrative entity / the item is located on the territory of the following administrative entity / is subproperty of location / is subproperty of part of
5. GeoNames ID (wd:P1566 as p/wdt/wdtn, matched via GeoNames), also known as GeoNames, Geonames Id, P1566: identifier in the GeoNames geographical database / identifier in the GeoNames geographical database / identifier in the GeoNames geographical database
6. continent (wd:P30 as p/wdt), also known as P30: is subproperty of located in/on physical feature / is subproperty of located on terrain feature / continent of which the subject is a part / continent of which the subject is a part / continent of which the subject is a part
7. postal code (wd:P281 as p/wdt, matched via ZIP+4), also known as pincode, PIN Code, postal index number, post code, postcode, etc.: identifier assigned by postal authorities for the subject area or building / identifier assigned by postal authorities for the subject area / identifier assigned by postal authorities for the subject area
8. country (wd:P17 as p/wdt), also known as host country, land, sovereign state, state, P17: sovereign state that this item is in (not to be used for human beings) / sovereign state that this item is in (not to be used for human beings) / sovereign state that this item is in (not to be used for human beings) / sovereign state that this item is in (not to be used for human beings) / is subproperty of located in the administrative territorial entity
9. twinned administrative body (wd:P190 as p/wdt, matched via twin cities), also known as partner city, partner town, sister city, sister town, twin cities, etc.: twin towns, sister cities, twinned municipalities and other ... legally or informally acknowledged by their governments / twin towns, sister cities, twinned municipalities and other localities / twin towns, sister cities, twinned municipalities and other localities
10. highest point (wd:P610 as p/wdt, matched via zenith), also known as elevation of highest point, extreme point highest, highest peak, pinnacle, summit, etc.: point with the highest elevation in the country, region, city, town, or area / point with highest elevation in the country, region, city or area / point with highest elevation in a region or path / is subproperty of has part(s) / is subproperty of has part

No other items found

[Assistant]
The property "located in time zone" (wdt:P421) is the correct property to use for finding the time zone of London.

Step 3: Construct and execute a SPARQL query to retrieve the time zone of London (wd:Q84).
I will now write a SPARQL query to get the time zone of London using the property wdt:P421.

execute

SELECT ?timeZone WHERE { wd:Q84 wdt:P421 ?timeZone }

[Assistant]
The query returned four time zone values for London. Let's analyze them:

1. **Europe/London (wd:Q16894228)**: This is the IANA time zone identifier for London, which is the standard used in modern systems.
2. **Greenwich Mean Time (wd:Q30192)**: This is the historical time zone used in London, especially during winter months.
3. **UTC±00:00 (wd:Q6574)**: This is the standard time offset for London, equivalent to GMT.
4. **UTC+01:00 (wd:Q6655)**: This corresponds to British Summer Time (BST), which is used during daylight saving time.

The most accurate and standard representation of London's time zone is **Europe/London**, as it encompasses both GMT and BST depending on the time of year. This is the IANA time zone identifier and is widely used in computing and international standards.

Thus, the correct answer is that London, UK, is in the **Europe/London** time zone.

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

answer

SELECT ?timeZone WHERE { wd:Q84 wdt:P421 ?timeZone }

Answer: London, UK, is in the Europe/London time zone, which corresponds to Greenwich Mean Time (GMT) during standard time and British Summer Time (BST) during daylight saving time.