PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?headquarters WHERE {
  wd:Q55464116 wdt:P159 ?headquarters
}

Using entities:
- National FFA Foundation (wd:Q55464116): is instance of non-profit organisation / is instance of non-profit organization / is instance of nonprofit organization / https://www.ffa.org/support/foundation

Using properties:
- headquarters location (wd:P159 as wdt), also known as admin HQ, based in, garrison, head office location, head quarters, etc.: is subproperty of significant place / city or town where an organization's headquarters is or has been situated. Use P276 qualifier for specific building / specific location where an organisation's HQ is or has been located / specific location where an organisation's HQ is or has been located

Got 1 row and 1 column:
| headquarters            |
| ----------------------- |
| Indianapolis (wd:Q6346) |

Answer: The National FFA Foundation is located in Indianapolis, United States.

The National FFA Foundation is located in Indianapolis, United States.

SPARQL query over wikidata:
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?headquarters WHERE {
  wd:Q55464116 wdt:P159 ?headquarters
}

Using entities:
- National FFA Foundation (wd:Q55464116): is instance of non-profit organisation / is instance of non-profit organization / is instance of nonprofit organization / https://www.ffa.org/support/foundation

Using properties:
- headquarters location (wd:P159 as wdt), also known as admin HQ, based in, garrison, head office location, head quarters, etc.: is subproperty of significant place / city or town where an organization's headquarters is or has been situated. Use P276 qualifier for specific building / specific location where an organisation's HQ is or has been located / specific location where an organisation's HQ is or has been located

Execution result:
Got 1 row and 1 column:
| headquarters            |
| ----------------------- |
| Indianapolis (wd:Q6346) |

[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] where is the national ffa foundation located today?

[Assistant]
To determine the location of the National FFA Foundation, I need to identify the correct entity representing it in Wikidata and then find its location (typically using the property "located in" or P131 for administrative location, or P17 for country).

### Step 1: Search for the entity "National FFA Foundation"
I will first search for the entity using the search_entity function to find the correct Wikidata item.

Question: National FFA Foundation

Top 10 entity alternatives:
1. National FFA Foundation (wd:Q55464116): is instance of non-profit organisation / is instance of non-profit organization / https://www.ffa.org/support/foundation / is instance of nonprofit organization
2. 2017 National FFA Foundation Convention (wd:Q123701667)
3. 2017 National FFA Foundation Convention Opening Session (wd:Q123701666)
4. National Science Foundation (wd:Q304878), also known as N.S.F., NSF, United States National Science Foundation, U.S. National Science Foundation, US National Science Foundation: is instance of independent agency of the United States government / is instance of research institute / United States government agency / is instance of funding body / is instance of organization / is instance of organisation
5. National Foundation Day (wd:Q1059995), also known as Kenkoku Kinen no Hi, National Foundation Day of Japan: Japanese holiday to celebrate the foundation of Japan. / is instance of public holiday in Japan / is instance of National Foundation Day
6. Gaecheonjeol (wd:Q485634, matched via National Foundation Day), also known as National Foundation Day: is instance of public holiday in South Korea / is instance of National Foundation Day / public holiday in South Korea
7. national foundation (wd:Q2324975), also known as foundation of a country, foundation of a nation: event or process, usually mythical or legendary, through which a nation is founded / is subclass of date of establishment / is instance of historical event / is instance of occurrence / is subclass of founding / is instance of event
8. National Bonsai Foundation (wd:Q3539656): nonprofit organization that was created to sustain the National Bonsai and Penjing Museum / is instance of non-profit organisation / is instance of non-profit organization / is instance of nonprofit organization / is instance of foundation
9. Cuban American National Foundation (wd:Q391051, matched via Cuban-American National Foundation), also known as CANF, Cuban-American National Foundation, FNCA: is instance of organisation / is instance of organization
10. National Sleep Foundation (wd:Q12238011): is instance of charitable organization / is instance of charitable organisation / is instance of non-profit organization / is instance of non-profit organisation / is instance of nonprofit organization / organization

[Assistant]
The correct entity for the National FFA Foundation is **wd:Q55464116**, which is identified as a non-profit organization. Now I will retrieve its location by checking its properties, particularly "located in" (P131) or "country" (P17).

### Step 2: List the triples for the National FFA Foundation (wd:Q55464116)
I will use the `list` function to inspect its properties and find the location.

list

wd:Q55464116

Got 48 rows and 3 columns, showing the first 10 rows below:
| subject                                | property                         | object                                |
| -------------------------------------- | -------------------------------- | ------------------------------------- |
| National FFA Foundation (wd:Q55464116) | instance of (wdt:P31)            | nonprofit organization (wd:Q163740)   |
| National FFA Foundation (wd:Q55464116) | country (wdt:P17)                | United States (wd:Q30)                |
| National FFA Foundation (wd:Q55464116) | official website (wdt:P856)      | <https://www.ffa.org>                 |
| National FFA Foundation (wd:Q55464116) | headquarters location (wdt:P159) | Indianapolis (wd:Q6346)               |
| National FFA Foundation (wd:Q55464116) | legal form (wdt:P1454)           | 501(c)(3) organization (wd:Q18325436) |
| National FFA Foundation (wd:Q55464116) | X (Twitter) username (wdt:P2002) | nationalffa                           |
| National FFA Foundation (wd:Q55464116) | Facebook username (wdt:P2013)    | nationalffa                           |
| National FFA Foundation (wd:Q55464116) | total revenue (wdt:P2139)        | 17064836 (xsd:decimal)                |
| National FFA Foundation (wd:Q55464116) | total assets (wdt:P2403)         | 41160721 (xsd:decimal)                |
| National FFA Foundation (wd:Q55464116) | donations (wdt:P8093)            | 14065954 (xsd:decimal)                |
| ...                                    | ...                              | ...                                   |

[Assistant]
From the results, I can see that the **National FFA Foundation** has its headquarters located in **Indianapolis (wd:Q6346)**, which is in the **United States (wd:Q30)**. The property `wdt:P159` (headquarters location) directly gives the city.

### Step 3: Confirm the location of Indianapolis
To ensure accuracy, I will verify that Indianapolis is indeed in the United States by checking its country.

wd:Q6346

[Assistant]
Indianapolis is confirmed to be in the United States.

### Final Answer
The National FFA Foundation is headquartered in **Indianapolis, United States**.

I will now provide the final SPARQL query that retrieves this information.

answer

SELECT ?headquarters WHERE { wd:Q55464116 wdt:P159 ?headquarters }

Answer: The National FFA Foundation is located in Indianapolis, United States.


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 ?actor ?actorLabel WHERE {
  wd:Q51746 wdt:P175 ?actor .
  ?actor rdfs:label ?actorLabel .
  FILTER ( LANG( ?actorLabel ) = "en" )
}

Using entities:
- Luke Skywalker (wd:Q51746), also known as Luke Starkiller: has occupation rebel / has occupation mechanic / has occupation Jedi / has occupation starship pilot / is instance of comics character / is instance of fictional human / is instance of video game character / is instance of television character / is instance of film character / is instance of cyborg in a work of fiction / is instance of character from Star Wars / is instance of literary character / is instance of fictional humanoid extraterrestrial / fictional character from Star Wars

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: Mark Hamill

Mark Hamill

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 ?actor ?actorLabel WHERE {
  wd:Q51746 wdt:P175 ?actor .
  ?actor rdfs:label ?actorLabel .
  FILTER ( LANG( ?actorLabel ) = "en" )
}

Using entities:
- Luke Skywalker (wd:Q51746), also known as Luke Starkiller: has occupation rebel / has occupation mechanic / has occupation Jedi / has occupation starship pilot / is instance of comics character / is instance of fictional human / is instance of video game character / is instance of television character / is instance of film character / is instance of cyborg in a work of fiction / is instance of character from Star Wars / is instance of literary character / is instance of fictional humanoid extraterrestrial / fictional character from Star Wars

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 2 columns:
| actor                    | actorLabel            |
| ------------------------ | --------------------- |
| Mark Hamill (wd:Q210447) | Mark Hamill (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] who would play luke skywalker?

[Assistant]
To determine who would play Luke Skywalker, we need to identify the actor(s) who portrayed Luke Skywalker in the Star Wars films. Luke Skywalker is a fictional character, so we are looking for the actor(s) associated with this role.

### Step 1: Identify the entity for Luke Skywalker
First, I will search for the entity corresponding to "Luke Skywalker" in Wikidata.

Question: luke skywalker

Top 10 entity alternatives:
1. Luke Skywalker (wd:Q51746), also known as Luke Starkiller: is instance of fictional humanoid extraterrestrial / is instance of cyborg in a work of fiction / is instance of character from Star Wars / is instance of television character / is instance of video game character / fictional character from Star Wars / is instance of literary character / is instance of comics character / is instance of fictional human / has occupation starship pilot / is instance of film character / has occupation mechanic / has occupation rebel / has occupation Jedi
2. Luke Skywalker (wd:Q125304798), also known as 1978 Luke Skywalker: is instance of miniature action figure / 1978 Star Wars miniature action figure
3. Luke Skywalker (Bespin Fatigues) (wd:Q131785930, matched via 1980 Luke Skywalker), also known as 1980 Luke Skywalker: is instance of miniature action figure / 1980 Star Wars miniature action figure
4. Luke Skywalker (Hoth Battle Gear) (wd:Q131787546, matched via 1980 Luke Skywalker), also known as 1980 Luke Skywalker: is instance of miniature action figure / 1980 Star Wars miniature action figure
5. Luke Skywalker: X-Wing Pilot (wd:Q131785637), also known as 1978 Luke Skywalker: X-Wing Pilot: is instance of miniature action figure / 1978 Star Wars miniature action figure
6. Luke Skywalker's lightsaber (wd:Q109322277), also known as Luke Skywalker's laser sword, Luke's laser sword, Luke's lightsaber: fictional lightsaber from the Star Wars universe / is instance of Lightsaber / is instance of lightsaber
7. Luke Skywalker's X-wing starfighter (wd:Q131848835): fictional spacecraft from the Star Wars universe / is instance of fictional spacecraft / is instance of X-wing
8. Luke Skywalker and the Shadows of Mindor (wd:Q6702352): is instance of literary work / 2008 novel by Matthew Stover
9. Gospel of Luke (wd:Q39939, matched via Luke), also known as Gospel According to Luke, Gospel of Saint Luke, Luke: is instance of book of the Bible / book of the New Testament / is instance of Gospel / is instance of gospel
10. Luke the Evangelist (wd:Q128538, matched via Luke), also known as Lucanus, Lukas, Luke, Saint Luke: has occupation iconographer / one of the four evangelists / has occupation evangelist / has occupation physician / has occupation painter / has occupation writer / is instance of human

[Assistant]
The correct entity for the fictional character Luke Skywalker is **wd:Q51746**. Now, I need to find the actor(s) who portrayed Luke Skywalker in the films. To do this, I will look for properties associated with this entity that might indicate the actor(s), such as "portrayed by" or similar.

### Step 2: Search for properties related to "portrayed by" for Luke Skywalker
I will use `search_property_of_entity` to find properties related to portrayal or casting for Luke Skywalker.

Question: portrayed by

Top 10 property alternatives:
1. performer (wd:P175 as p/wdt, matched via portrayed by), 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
2. 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)
3. character type (wd:P9071 as p/wdt), also known as archetype, character archetype, character stereotype, -dere, dere, etc.: generic character type that this fictional character represents / is subproperty of manifestation of
4. creator (wd:P170 as p/wdt, matched via painted by), 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)
5. first appearance (wd:P4584 as p/wdt), also known as appeared first in, debut, first episode, first film, initial appearance, etc.: work in which a fictional/mythical character or entity first appeared / is subproperty of present in work
6. derivative work (wd:P4969 as p/wdt, matched via adapted as), also known as adaptation, adapted as, cover, derived work, has adaptation, etc.: work created from major part of this artwork; work created from major part of this software / new work of art (film, book, software, etc.) derived from major part of this work
7. media franchise (wd:P8345 as p/wdt, matched via presented in media franchise), also known as franchise, mass media franchise, media mix, presented in media franchise, P8345: this creative work belongs to this media franchise
8. member of (wd:P463 as p/wdt), also known as band member of, in musical group, member of musical group, membership, of organization, etc.: organisation, club or musical group to which the subject ... position, such as a member of parliament (use P39 for that) / organization, club or musical group to which the subject ... position, such as a member of parliament (use P39 for that) / organization, club or musical group to which the subject ... position, such as a member of parliament (use P39 for that) / organization, club or musical group to which the subject ... position, such as a member of parliament (use P39 for that) / is subproperty of part of
9. 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
10. image (wd:P18 as p/wdt, matched via portrait), also known as camera picture, Commons image, drawing, File:, graph, etc.: image of relevant illustration of the subject; if available, ... only images which exist on Wikimedia Commons are acceptable / image of relevant illustration of the subject; if available, ... only images which exist on Wikimedia Commons are acceptable / image of relevant illustration of the subject; if available, ... map, flag image, signature image, logo image, collage image) / image of relevant illustration of the subject; if available, ... map, flag image, signature image, logo image, collage image)

No other items found

[Assistant]
The property **"performer" (wd:P175)** is the most relevant here, as it indicates the actor or performer associated with a role in a work. Now, I will query Wikidata to find the performer(s) of Luke Skywalker (wd:Q51746) using this property.

### Step 3: Construct and execute a SPARQL query to find the actor(s) who portrayed Luke Skywalker
I will write a SPARQL query to retrieve the performer(s) of Luke Skywalker and their labels (names) in English.

execute

SELECT ?actor ?actorLabel WHERE { wd:Q51746 wdt:P175 ?actor . SERVICE wikibase:label { bd:serviceParam wikibase:language "en". } }

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: '
<title>301 Moved Permanently</title>

301 Moved Permanently'

[Assistant]
The error occurred because I used `SERVICE wikibase:label`, which is not supported in this environment. Instead, I need to manually fetch the labels using `rdfs:label` with a language filter.

I will revise the SPARQL query to use `rdfs:label` with `FILTER(LANG(?actorLabel) = "en")` to get the English labels of the actors.

### Step 4: Rewrite the SPARQL query without `SERVICE wikibase:label`
I will now execute the corrected SPARQL query.

SELECT ?actor ?actorLabel WHERE { wd:Q51746 wdt:P175 ?actor . ?actor rdfs:label ?actorLabel . FILTER(LANG(?actorLabel) = "en") }

[Assistant]
The SPARQL query successfully returned the actor who portrayed Luke Skywalker: **Mark Hamill**.

### Final Answer:
The actor who played Luke Skywalker is **Mark Hamill**.

I will now provide the final SPARQL query and answer.

answer

SELECT ?actor ?actorLabel WHERE { wd:Q51746 wdt:P175 ?actor . ?actor rdfs:label ?actorLabel . FILTER(LANG(?actorLabel) = "en") }

Answer: Mark Hamill


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 ?country ?countryLabel WHERE {
  ?country wdt:P31 wd:Q3624078 ; wdt:P37 wd:Q1321 .
  FILTER NOT EXISTS {
    ?country wdt:P31 wd:Q3024240
  }
  .
  FILTER NOT EXISTS {
    ?country wdt:P31 wd:Q244381
  }
  .
  ?country rdfs:label ?countryLabel .
  FILTER ( LANG( ?countryLabel ) = "en" )
}
ORDER BY ?countryLabel

Using entities:
- Spanish (wd:Q1321), also known as Castilian, Castilian language, es, esp, Español, etc.: is instance of modern language / is instance of human language / is instance of natural language / is instance of language / is subclass of Castilian / is subclass of West Iberian / is subclass of West Iberian languages / language / Romance language originating in the Iberian Peninsula / Romance language originating on the Iberian peninsula
- microstate (wd:Q244381), also known as ministate: is subclass of sovereign state / sovereign state having a very small population or very small land area
- historical country (wd:Q3024240), also known as country or state that doesn't exist, country or state that no longer exists, defunct state, former country, former state, etc.: is subclass of former or current state / is subclass of political territorial entity / is subclass of former administrative territorial entity / country, state or territory that once existed
- sovereign state (wd:Q3624078), also known as country, nation, sovereign country, sovereign nation, Westphalian state: is subclass of country / is subclass of state / political organisation with a centralised independent government / political organisation with a centralised independent government / state that has the highest authority over a territory

Using properties:
- instance of (wd:P31 as wdt), also known as example of, has type, is a, is an, is of type, etc.: that class of which this subject is a particular example and ... a subclass of mountain (and an instance of volcanic landform) / type to which this subject corresponds/belongs. Different ... and the volcano is a type (instance) of volcanic landform
- official language (wd:P37 as wdt), also known as language official, language spoken, speaking, spoken in, P37: is subproperty of language used / language designated as official by this item / language designated as official by this item / language designated as official by this item / language designated as official by this item

Got 20 rows and 2 columns, showing the first 5 and last 5 rows below:
| country              | countryLabel         |
| -------------------- | -------------------- |
| Argentina (wd:Q414)  | Argentina (lang:en)  |
| Bolivia (wd:Q750)    | Bolivia (lang:en)    |
| Chile (wd:Q298)      | Chile (lang:en)      |
| Colombia (wd:Q739)   | Colombia (lang:en)   |
| Costa Rica (wd:Q800) | Costa Rica (lang:en) |
| ...                  | ...                  |
| Paraguay (wd:Q733)   | Paraguay (lang:en)   |
| Peru (wd:Q419)       | Peru (lang:en)       |
| Spain (wd:Q29)       | Spain (lang:en)      |
| Uruguay (wd:Q77)     | Uruguay (lang:en)    |
| Venezuela (wd:Q717)  | Venezuela (lang:en)  |

Answer: The countries that have Spanish as a national (official) language are: Argentina, Bolivia, Chile, Colombia, Costa Rica, Cuba, Dominican Republic, Ecuador, El Salvador, Equatorial Guinea, Guatemala, Honduras, Mexico, Nicaragua, Panama, Paraguay, Peru, Spain, Uruguay, and Venezuela.

The countries that have Spanish as a national (official) language are: Argentina, Bolivia, Chile, Colombia, Costa Rica, Cuba, Dominican Republic, Ecuador, El Salvador, Equatorial Guinea, Guatemala, Honduras, Mexico, Nicaragua, Panama, Paraguay, Peru, Spain, Uruguay, and Venezuela.

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 ?country ?countryLabel WHERE {
  ?country wdt:P31 wd:Q3624078 ; wdt:P37 wd:Q1321 .
  FILTER NOT EXISTS {
    ?country wdt:P31 wd:Q3024240
  }
  .
  FILTER NOT EXISTS {
    ?country wdt:P31 wd:Q244381
  }
  .
  ?country rdfs:label ?countryLabel .
  FILTER ( LANG( ?countryLabel ) = "en" )
}
ORDER BY ?countryLabel

Using entities:
- Spanish (wd:Q1321), also known as Castilian, Castilian language, es, esp, Español, etc.: is instance of modern language / is instance of human language / is instance of natural language / is instance of language / is subclass of Castilian / is subclass of West Iberian / is subclass of West Iberian languages / language / Romance language originating in the Iberian Peninsula / Romance language originating on the Iberian peninsula
- microstate (wd:Q244381), also known as ministate: is subclass of sovereign state / sovereign state having a very small population or very small land area
- historical country (wd:Q3024240), also known as country or state that doesn't exist, country or state that no longer exists, defunct state, former country, former state, etc.: is subclass of former or current state / is subclass of political territorial entity / is subclass of former administrative territorial entity / country, state or territory that once existed
- sovereign state (wd:Q3624078), also known as country, nation, sovereign country, sovereign nation, Westphalian state: is subclass of country / is subclass of state / political organisation with a centralised independent government / political organisation with a centralised independent government / state that has the highest authority over a territory

Using properties:
- instance of (wd:P31 as wdt), also known as example of, has type, is a, is an, is of type, etc.: that class of which this subject is a particular example and ... a subclass of mountain (and an instance of volcanic landform) / type to which this subject corresponds/belongs. Different ... and the volcano is a type (instance) of volcanic landform
- official language (wd:P37 as wdt), also known as language official, language spoken, speaking, spoken in, P37: is subproperty of language used / language designated as official by this item / language designated as official by this item / language designated as official by this item / language designated as official by this item

Execution result:
Got 20 rows and 2 columns, showing the first 5 and last 5 rows below:
| country              | countryLabel         |
| -------------------- | -------------------- |
| Argentina (wd:Q414)  | Argentina (lang:en)  |
| Bolivia (wd:Q750)    | Bolivia (lang:en)    |
| Chile (wd:Q298)      | Chile (lang:en)      |
| Colombia (wd:Q739)   | Colombia (lang:en)   |
| Costa Rica (wd:Q800) | Costa Rica (lang:en) |
| ...                  | ...                  |
| Paraguay (wd:Q733)   | Paraguay (lang:en)   |
| Peru (wd:Q419)       | Peru (lang:en)       |
| Spain (wd:Q29)       | Spain (lang:en)      |
| Uruguay (wd:Q77)     | Uruguay (lang:en)    |
| Venezuela (wd:Q717)  | Venezuela (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 countries have spanish as the national language?

[Assistant]
To determine which countries have Spanish as a national language, I will follow these steps:

1. **Identify the relevant property**: I need to find a property in Wikidata that links a country to its official or national language. The most relevant property is likely `wdt:P37` (official language).

2. **Identify the entity for Spanish**: I need to find the Wikidata item for the Spanish language. I will search for "Spanish language" to get its QID.

3. **Construct the query**: I will query for all countries (instances of `wd:Q3624078` or `wd:Q3624078` for sovereign states) that have Spanish (`wd:Q1321`) as their official language using `wdt:P37`.

4. **Verify the results**: I will ensure the results are countries and not other entities by checking their instance-of (`wdt:P31`) values.

Let me begin by searching for the Spanish language entity.

Question: Spanish language

Top 10 entity alternatives:
1. Spanish (wd:Q1321, matched via Spanish language), also known as Castilian, Castilian language, es, esp, Español, etc.: Romance language originating in the Iberian Peninsula / Romance language originating on the Iberian peninsula / is subclass of West Iberian languages / is instance of natural language / is instance of modern language / is instance of human language / is subclass of West Iberian / is subclass of Castilian / is instance of language / language
2. Spanish Language (wd:Q110262534): Stack Exchange site for linguists, teachers, students and ... general wanting to discuss the finer points of the language / is instance of Stack Exchange forum site
3. [Spanish language] (wd:Q80351209): scientific article published on 01 April 2004 / is instance of scholarly article / is instance of academic article
4. Spanish Wikipedia (wd:Q8449, matched via Spanish language Wikipedia), also known as eswiki, ESWIKI, es.wikipedia, eswikipedia, es.wikipedia.org, etc.: is instance of Wikipedia language edition / Spanish-language edition of Wikipedia / is instance of MediaWiki instance / Spanish version of Wikipedia
5. Rioplatense Spanish (wd:Q509780, matched via Rioplatense Spanish language), also known as Rioplatense Spanish language: variant of Spanish spoken in Argentina and Uruguay / is subclass of Spanish language in South America / is instance of dialect
6. Mexican Spanish (wd:Q616620, matched via Mexican Spanish language), also known as Chicano Spanish, es-mx, es_MX, mejicano, mexicano, etc.: dialect of Spanish spoken and written in Mexico / dialect of Spanish spoken and written in Mexic / is instance of Spanish dialects and varieties / is subclass of North American Spanish
7. Spanish Sign Language (wd:Q3100814), also known as LSE, SSL, ssp: sign language used mainly by deaf people in Spain / is subclass of Spanish Sign language family / is instance of modern language / is instance of sign language / is instance of language
8. Old Spanish (wd:Q1088025, matched via Old Spanish language), also known as Mediaeval Castilian, Mediaeval Spanish, Medieval Castilian, Medieval Spanish, Old Castilian, etc.: early form of the Spanish language in use between the 10th and 15th centuries / is instance of historical language / early form of the Spanish language / is subclass of Castilian
9. Salvadoran Spanish (wd:Q7406481, matched via Salvadoran Spanish language), also known as El Salvador Spanish, es-sv, es_SV, Salvadoran Spanish language, .sv: Spanish spoken and written in El Salvador / is subclass of Central American Spanish / is instance of dialect
10. Thesaurus:penis (Spanish language) (wd:Q30713037), also known as Thesaurus:pene: is instance of Wiktionary thesaurus page

[Assistant]
The correct entity for the Spanish language is `wd:Q1321` (Spanish). Now I will search for the property that links a country to its official language. I will search for properties related to "official language".

Question: official language

Top 10 property alternatives:
1. official language (wd:P37 as ps/psv/p/pqv/pqn/psn/pq/wdt/pr/prn/prv/wdtn), also known as language official, language spoken, speaking, spoken in, P37: language designated as official by this item / language designated as official by this item / language designated as official by this item / language designated as official by this item / is subproperty of language used
2. native label (wd:P1705 as ps/psv/p/pqv/pqn/psn/pq/wdt/pr/prn/prv/wdtn, matched via official language name), also known as autonym, label in official language, label in original language, name in official language, name in original language, etc.: label for the items in their official language (P37) or their original language (P364) / label for the items in their official language (P37) or their original language (P364) / label for the items in their official language (P37) or their original language (P364) / label for the items in their official language  or their original language / is subproperty of name
3. original language of film or TV show (wd:P364 as ps/psv/p/pqv/pqn/psn/pq/wdt/pr/prn/prv/wdtn, matched via original language), also known as created on language, language of the original work, media language, original language, P364: language in which a film or a performance work was originally ... and songs; use P407 ("language of work or name") instead. / language in which a film or a performance work was originally ... written works; use P407 ("language of work or name") instead. / language in which a film or a performance work was originally ... written works; use P407 ("language of work or name") instead. / is subproperty of language of work or name
4. language used (wd:P2936 as ps/psv/p/pqv/pqn/psn/pq/wdt/pr/prn/prv/wdtn, matched via working language), also known as languages used, medium of instruction, used language, uses language, working language, etc.: language widely used (spoken or written) in this place or at this event or organisation
5. native language (wd:P103 as ps/psv/p/pqv/pqn/psn/pq/wdt/pr/prn/prv/wdtn, matched via first language), also known as first language, L1 speaker of, language native, mother tongue, P103: language or languages a person has learned from early childhood / is subproperty of languages spoken, written or signed / language or languages a person has learned from birth / language or languages a person has learned from birth
6. language regulatory body (wd:P1018 as ps/psv/p/pqv/pqn/psn/pq/wdt/pr/prn/prv/wdtn, matched via language authority), also known as language authority, regulatory body, P1018: regulatory body of a language
7. language of work or name (wd:P407 as ps/psv/p/pqv/pqn/psn/pq/wdt/pr/prn/prv/wdtn, matched via used language), also known as audio language, available in, broadcasting language, language, language of name, etc.: language associated with this creative work (such as books, ... (P103) and "languages spoken, written or signed" (P1412)) / language associated with this creative work (such as books, ... (P103) and "languages spoken, written or signed" (P1412)) / language associated with this work or name (for persons use P103 and P1412)
8. languages spoken, written or signed (wd:P1412 as ps/psv/p/pqv/pqn/psn/pq/wdt/pr/prn/prv/wdtn, matched via used language), also known as language, language of expression, language read, language signed, languages of expression, etc.: language(s) that a person or a people speaks, writes or signs, including the native language(s) / language(s) that a person speaks or writes, including the native language(s) / language(s) that a person speaks or writes, including the native language(s)
9. programmed in (wd:P277 as ps/psv/p/pqv/pqn/psn/pq/wdt/pr/prn/prv/wdtn, matched via language), also known as language, programming language, written in, P277: the programming language(s) in which the software is developed
10. Ethnologue language status (wd:P3823 as ps/psv/p/pqv/pqn/psn/pq/wdt/pr/prn/prv/wdtn, matched via language status), also known as EGIDS, language status, P3823: language status identifier by Ethnologue.com using EGIDS scale / language status identifier by Ethnologue.com using EGIDS scale

[Assistant]
The property for "official language" is `wdt:P37`. Now I will construct a SPARQL query to find all countries (instances of `wd:Q3624078` for sovereign states) that have Spanish (`wd:Q1321`) as their official language.

I will query for:
- Items with `wdt:P31 wd:Q3624078` (sovereign states).
- That have `wdt:P37 wd:Q1321` (official language is Spanish).
- Return the country's label in English.

Let me execute this query.

execute

SELECT ?country ?countryLabel WHERE { ?country wdt:P31 wd:Q3624078 ; wdt:P37 wd:Q1321 . SERVICE wikibase:label { bd:serviceParam wikibase:language "en". } }

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: '
<title>301 Moved Permanently</title>

301 Moved Permanently'

[Assistant]
The error occurred because I used `SERVICE wikibase:label`, which is not supported in this environment. I need to use `rdfs:label` with a language filter instead.

I will revise the query to use `rdfs:label` with `FILTER(LANG(?countryLabel) = "en")` to get the English labels of the countries.

Here is the corrected SPARQL query:

SELECT ?country ?countryLabel WHERE { ?country wdt:P31 wd:Q3624078 ; wdt:P37 wd:Q1321 . ?country rdfs:label ?countryLabel . FILTER(LANG(?countryLabel) = "en") }

Got 21 rows and 2 columns, showing the first 5 and last 5 rows below:
| country                            | countryLabel                 |
| ---------------------------------- | ---------------------------- |
| Kingdom of Patones (wd:Q131839713) | Kingdom of Patones (lang:en) |
| Cuba (wd:Q241)                     | Cuba (lang:en)               |
| Spain (wd:Q29)                     | Spain (lang:en)              |
| Chile (wd:Q298)                    | Chile (lang:en)              |
| Argentina (wd:Q414)                | Argentina (lang:en)          |
| ...                                | ...                          |
| Costa Rica (wd:Q800)               | Costa Rica (lang:en)         |
| Panama (wd:Q804)                   | Panama (lang:en)             |
| Nicaragua (wd:Q811)                | Nicaragua (lang:en)          |
| Mexico (wd:Q96)                    | Mexico (lang:en)             |
| Equatorial Guinea (wd:Q983)        | Equatorial Guinea (lang:en)  |

[Assistant]
The query returned 21 countries where Spanish is an official language. However, I notice one anomaly: "Kingdom of Patones" (wd:Q131839713) appears in the results. This is not a recognized sovereign state, so it might be an error or a fictional entity. I should ensure that only legitimate sovereign states are included.

To refine the results, I will check the instance-of (`wdt:P31`) of the countries to ensure they are indeed sovereign states. The main class for sovereign states is `wd:Q3624078`, but sometimes other subclasses or misclassified items may appear. I will verify that the results are valid by cross-checking with known sovereign states.

Alternatively, I can use `wdt:P17` (country) in combination with `wdt:P37` to ensure we are only retrieving valid countries. However, since we are already filtering by `wdt:P31 wd:Q3624078`, the issue might be that "Kingdom of Patones" is incorrectly classified as a sovereign state.

I will check the instance-of of "Kingdom of Patones" to see what it is classified as.

list

wd:Q131839713

[Assistant]
The entity "Kingdom of Patones" (wd:Q131839713) is incorrectly classified as a sovereign state, microstate, and historical country. This is likely a mistake in Wikidata, as "Kingdom of Patones" is not a recognized sovereign state. To exclude such erroneous entries, I will refine the query to exclude items that are also classified as "historical country" (`wd:Q3024240`) or "microstate" (`wd:Q244381`), as these may indicate non-standard or incorrect classifications.

I will modify the query to exclude these unwanted subclasses while keeping only items that are sovereign states (`wd:Q3624078`) and not classified as historical countries or microstates.

Here is the updated SPARQL query:

execute

SELECT ?country ?countryLabel WHERE { ?country wdt:P31 wd:Q3624078 ; wdt:P37 wd:Q1321 . FILTER NOT EXISTS { ?country wdt:P31 wd:Q3024240 } . FILTER NOT EXISTS { ?country wdt:P31 wd:Q244381 } . ?country rdfs:label ?countryLabel . FILTER(LANG(?countryLabel) = "en") }

Got 20 rows and 2 columns, showing the first 5 and last 5 rows below:
| country                     | countryLabel                |
| --------------------------- | --------------------------- |
| Cuba (wd:Q241)              | Cuba (lang:en)              |
| Spain (wd:Q29)              | Spain (lang:en)             |
| Chile (wd:Q298)             | Chile (lang:en)             |
| Argentina (wd:Q414)         | Argentina (lang:en)         |
| Peru (wd:Q419)              | Peru (lang:en)              |
| ...                         | ...                         |
| Costa Rica (wd:Q800)        | Costa Rica (lang:en)        |
| Panama (wd:Q804)            | Panama (lang:en)            |
| Nicaragua (wd:Q811)         | Nicaragua (lang:en)         |
| Mexico (wd:Q96)             | Mexico (lang:en)            |
| Equatorial Guinea (wd:Q983) | Equatorial Guinea (lang:en) |

[Assistant]
The refined query now returns 20 countries where Spanish is an official language, and the erroneous "Kingdom of Patones" has been successfully excluded. The results include well-known Spanish-speaking countries such as Spain, Mexico, Argentina, Colombia, and others.

The list of countries where Spanish is an official language is:

- Cuba
- Spain
- Chile
- Argentina
- Peru
- Venezuela
- Bolivia
- Ecuador
- Paraguay
- Uruguay
- Guatemala
- El Salvador
- Honduras
- Nicaragua
- Costa Rica
- Panama
- Mexico
- Equatorial Guinea
- Dominican Republic
- Puerto Rico (Note: Puerto Rico is a territory of the United States, not a sovereign state, but it is included in Wikidata as having Spanish as an official language. However, since we filtered for sovereign states, it should not appear. Let me verify if it is in the list.)

Wait — I notice that Puerto Rico (`wd:Q47521`) is not in the list, which is correct because it is not a sovereign state. The 20 countries listed are all sovereign states.

Let me verify the full list by retrieving all results explicitly.

I will now finalize the answer with the complete list of countries.

SELECT ?country ?countryLabel WHERE { ?country wdt:P31 wd:Q3624078 ; wdt:P37 wd:Q1321 . FILTER NOT EXISTS { ?country wdt:P31 wd:Q3024240 } . FILTER NOT EXISTS { ?country wdt:P31 wd:Q244381 } . ?country rdfs:label ?countryLabel . FILTER(LANG(?countryLabel) = "en") } ORDER BY ?countryLabel

Got 20 rows and 2 columns, showing the first 5 and last 5 rows below:
| country              | countryLabel         |
| -------------------- | -------------------- |
| Argentina (wd:Q414)  | Argentina (lang:en)  |
| Bolivia (wd:Q750)    | Bolivia (lang:en)    |
| Chile (wd:Q298)      | Chile (lang:en)      |
| Colombia (wd:Q739)   | Colombia (lang:en)   |
| Costa Rica (wd:Q800) | Costa Rica (lang:en) |
| ...                  | ...                  |
| Paraguay (wd:Q733)   | Paraguay (lang:en)   |
| Peru (wd:Q419)       | Peru (lang:en)       |
| Spain (wd:Q29)       | Spain (lang:en)      |
| Uruguay (wd:Q77)     | Uruguay (lang:en)    |
| Venezuela (wd:Q717)  | Venezuela (lang:en)  |

[Assistant]
The final list of 20 sovereign countries where Spanish is an official language is as follows:

- Argentina
- Bolivia
- Chile
- Colombia
- Costa Rica
- Cuba
- Dominican Republic
- Ecuador
- El Salvador
- Equatorial Guinea
- Guatemala
- Honduras
- Mexico
- Nicaragua
- Panama
- Paraguay
- Peru
- Spain
- Uruguay
- Venezuela

These are all sovereign states with Spanish as an official language, and the query has successfully excluded non-sovereign or incorrectly classified entities.

I will now provide the final SPARQL query and answer.

answer

SELECT ?country ?countryLabel WHERE { ?country wdt:P31 wd:Q3624078 ; wdt:P37 wd:Q1321 . FILTER NOT EXISTS { ?country wdt:P31 wd:Q3024240 } . FILTER NOT EXISTS { ?country wdt:P31 wd:Q244381 } . ?country rdfs:label ?countryLabel . FILTER(LANG(?countryLabel) = "en") } ORDER BY ?countryLabel

Answer: The countries that have Spanish as a national (official) language are: Argentina, Bolivia, Chile, Colombia, Costa Rica, Cuba, Dominican Republic, Ecuador, El Salvador, Equatorial Guinea, Guatemala, Honduras, Mexico, Nicaragua, Panama, Paraguay, Peru, Spain, Uruguay, and Venezuela.