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 ?occ ?occLabel WHERE {
  wd:Q193637 wdt:P106 ?occ .
  ?occ rdfs:label ?occLabel
  FILTER ( LANG( ?occLabel ) = "en" )
}

Using entities:
- Scottie Pippen (wd:Q193637), also known as No Tippin' Pippen, Pip, Robin, Scott Pippen, Scotty Maurice Pippen: has occupation actor / has occupation basketball player / is instance of human / American basketball player

Using properties:
- occupation (wd:P106 as wdt), 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)

Answer: Scottie Pippen was primarily good at basketball, as he was a professional basketball player. He also had a minor role as an actor.

Scottie Pippen was primarily good at basketball, as he was a professional basketball player. He also had a minor role as an actor.

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 ?occ ?occLabel WHERE {
  wd:Q193637 wdt:P106 ?occ .
  ?occ rdfs:label ?occLabel
  FILTER ( LANG( ?occLabel ) = "en" )
}

Using entities:
- Scottie Pippen (wd:Q193637), also known as No Tippin' Pippen, Pip, Robin, Scott Pippen, Scotty Maurice Pippen: has occupation actor / has occupation basketball player / is instance of human / American basketball player

Using properties:
- occupation (wd:P106 as wdt), 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)

Execution result:
Got 2 rows and 2 columns:
| occ                             | occLabel                    |
| ------------------------------- | --------------------------- |
| actor (wd:Q33999)               | actor (lang:en)             |
| basketball player (wd:Q3665646) | basketball player (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 was scottie pippen good at?

[Assistant]
To determine what Scottie Pippen was good at, we need to identify his occupations or skills. Since "good at" can be interpreted as his profession or notable roles, we can look for his occupation(s) in Wikidata.

### Step 1: Search for Scottie Pippen in Wikidata
First, let's search for the entity corresponding to Scottie Pippen.

Question: scottie pippen

Top 10 entity alternatives:
1. Scottie Pippen (wd:Q193637), also known as No Tippin' Pippen, Pip, Robin, Scott Pippen, Scotty Maurice Pippen: has occupation basketball player / American basketball player / has occupation actor / is instance of human
2. Scotty Pippen Jr. (wd:Q100901254, matched via Scottie Pippen Jr.), also known as Scottie Pippen Jr.: has occupation basketball player / American basketball player / is instance of human
3. Slam City with Scottie Pippen (wd:Q3486520): is instance of video game / 1994 video game / 1994 video game / 1994 video game
4. Scottish Terrier (wd:Q39035, matched via Scottie), also known as Aberdeen Terrier, Scottie, Scotty Dog: is instance of dog breed / is subclass of dog / dog breed
5. Scottie Scheffler (wd:Q30161386), also known as Scott Alexander Scheffler: American golfer (1996-) / has occupation actor / is instance of human
6. Katherine MacGregor (wd:Q435455, matched via Scottie MacGregor), also known as Dorlee Deane McGregor, Scottie MacGregor: has occupation television actor / American actress (1925-2018) / has occupation stage actor / has occupation film actor / has occupation dancer / has occupation actor / is instance of human
7. Scottie Barnes (wd:Q66459298): has occupation basketball player / American basketball player / is instance of human
8. Scottie Thompson (wd:Q437912), also known as Susan Scott Thompson, Susan S. Thompson, Susan Thompson: has occupation television actor / has occupation stage actor / has occupation film actor / has occupation actor / is instance of human / American actress
9. Scottie Wilbekin (wd:Q16235973), also known as Scottie Jordan Wilbekin: has occupation basketball player / American basketball player / is instance of human
10. Scottie Upshall (wd:Q2004843), also known as Scott Upshall: has occupation ice hockey player / Canadian ice hockey player / is instance of human

[Assistant]
The top result is Scottie Pippen (wd:Q193637), an American basketball player. We can confirm this is the correct entity by checking its instance-of (P31) to ensure it's a human (wd:Q5).

### Step 2: Verify that Scottie Pippen is a human
Let’s check the instance-of (P31) of Scottie Pippen (wd:Q193637) to confirm it's a human.

list

wd:Q193637

[Assistant]
Great! Scottie Pippen (wd:Q193637) is confirmed as a human (wd:Q5). Now, we can retrieve his occupation(s) using the P106 property (occupation).

### Step 3: Retrieve Scottie Pippen's occupations
We'll query for his occupation(s) and get the English labels for better readability.

execute

SELECT ?occ ?occLabel WHERE { wd:Q193637 wdt:P106 ?occ . ?occ rdfs:label ?occLabel FILTER(LANG(?occLabel) = "en") }

[Assistant]
Scottie Pippen's occupations are **basketball player** and **actor**.

Given his fame, "basketball player" is his primary and most notable occupation. The "actor" role is likely minor or secondary (e.g., cameos or appearances).

### Final Answer:
Scottie Pippen was primarily good at **basketball**, as he was a professional basketball player. He also had a minor role as an actor.

Now, I'll provide the final SPARQL query and answer.

answer

SELECT ?occ ?occLabel WHERE { wd:Q193637 wdt:P106 ?occ . ?occ rdfs:label ?occLabel FILTER(LANG(?occLabel) = "en") }

Answer: Scottie Pippen was primarily good at basketball, as he was a professional basketball player. He also had a minor role as an actor.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?continent WHERE {
  wd:Q16 wdt:P30 ?continent
}

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

Using properties:
- continent (wd:P30 as 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

Got 1 row and 1 column:
| continent              |
| ---------------------- |
| North America (wd:Q49) |

Answer: Canada belongs to the continent of North America.

Canada belongs to the continent of North America.

SPARQL query over wikidata:
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?continent WHERE {
  wd:Q16 wdt:P30 ?continent
}

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

Using properties:
- continent (wd:P30 as 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

Execution result:
Got 1 row and 1 column:
| continent              |
| ---------------------- |
| North America (wd:Q49) |

[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 continent does canada belong to?

[Assistant]
To determine which continent Canada belongs to, I need to find the continent associated with Canada in the knowledge graph.

Step 1: Search for the entity "Canada" to get its Wikidata identifier.

Question: canada

Top 10 entity alternatives:
1. Canada (wd:Q16), also known as CA, CAN, Dominion of Canada, ISO 3166-1:CA: is instance of sovereign state / country in North America / country in North America / is instance of country
2. La Canyada (wd:Q1553440, matched via Cañada), also known as Cañada: is instance of municipality of the Valencian Community / is instance of municipality of Spain / municipality of Spain
3. Province of Canada (wd:Q1121436, matched via Canada), also known as British Canada, Canada, United Canadas, United Province of Canada: is instance of former administrative territorial entity / 1841–1867 UK possession in North America / 1841–1867 UK possession in North America / is instance of crown colony
4. Canada (wd:Q2569593), also known as French Canada: French colony in New France between 1534 and 1763 / is instance of colony
5. Canada (wd:Q5029265), also known as Canada, KS: is instance of unincorporated community in the United States / unincorporated community in Kansas, United States / unincorporated community in Kansas, United States
6. Canada (wd:Q1031917), also known as Canada, Kentucky, Canada, KY: unincorporated community in Pike County, Kentucky, United States / is instance of unincorporated community in the United States / is instance of town
7. Canada (wd:Q13265795): is instance of literary work / 2012 novel by Richard Ford / novel
8. Canada (wd:Q2684010), also known as Kanada: hamlet in Ooststellingwerf, Netherlands / is instance of buurtschap
9. Canadá (wd:Q20275156): is instance of human settlement / human settlement in Mexico
10. Canada (wd:Q21287484): is instance of Wikimedia permanent duplicated page / is instance of Wikimedia permanent duplicate item / Wikimedia permanent duplicate item

[Assistant]
The top result for "Canada" is wd:Q16, which is identified as a sovereign state/country in North America. This is the correct entity for the country of Canada.

Step 2: Now, I need to find the continent that Canada belongs to. I will check the properties of Canada (wd:Q16) to find the continent. The property for continent is typically P30 (continent).

I will execute a SPARQL query to retrieve the continent of Canada using its Wikidata ID (wd:Q16) and the property P30.

execute

SELECT ?continent WHERE { wd:Q16 wdt:P30 ?continent }

Got 1 row and 1 column:
| continent              |
| ---------------------- |
| North America (wd:Q49) |

[Assistant]
The query result shows that Canada (wd:Q16) belongs to the continent of North America (wd:Q49).

Now, I will provide the final answer with the SPARQL query used.

answer

SELECT ?continent WHERE { wd:Q16 wdt:P30 ?continent }

Answer: Canada belongs to the continent of North America.


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 ?governmentType ?governmentTypeLabel WHERE {
  wd:Q30 wdt:P31 ?governmentType .
  ?governmentType rdfs:label ?governmentTypeLabel
  FILTER ( LANG( ?governmentTypeLabel ) = "en" )
}

Using entities:
- United States (wd:Q30), also known as America, Merica, Murica, the States, the United States, etc.: is instance of superpower / is instance of constitutional republic / is instance of sovereign state / is instance of federal republic / is instance of Federal republic / is instance of democratic republic / is instance of country / country in North America / country in North America / country primarily located in North America

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

Got 6 rows and 2 columns:
| governmentType                        | governmentTypeLabel               |
| ------------------------------------- | --------------------------------- |
| superpower (wd:Q1489259)              | superpower (lang:en)              |
| constitutional republic (wd:Q1520223) | constitutional republic (lang:en) |
| sovereign state (wd:Q3624078)         | sovereign state (lang:en)         |
| federal republic (wd:Q512187)         | federal republic (lang:en)        |
| democratic republic (wd:Q5255892)     | democratic republic (lang:en)     |
| country (wd:Q6256)                    | country (lang:en)                 |

Answer: The United States currently has a federal republic form of government, as indicated by its classification as a federal republic, constitutional republic, and democratic republic in the knowledge graph. The most comprehensive description is 'federal republic'.

The United States currently has a federal republic form of government, as indicated by its classification as a federal republic, constitutional republic, and democratic republic in the knowledge graph. The most comprehensive description is 'federal republic'.

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 ?governmentType ?governmentTypeLabel WHERE {
  wd:Q30 wdt:P31 ?governmentType .
  ?governmentType rdfs:label ?governmentTypeLabel
  FILTER ( LANG( ?governmentTypeLabel ) = "en" )
}

Using entities:
- United States (wd:Q30), also known as America, Merica, Murica, the States, the United States, etc.: is instance of superpower / is instance of constitutional republic / is instance of sovereign state / is instance of federal republic / is instance of Federal republic / is instance of democratic republic / is instance of country / country in North America / country in North America / country primarily located in North America

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

Execution result:
Got 6 rows and 2 columns:
| governmentType                        | governmentTypeLabel               |
| ------------------------------------- | --------------------------------- |
| superpower (wd:Q1489259)              | superpower (lang:en)              |
| constitutional republic (wd:Q1520223) | constitutional republic (lang:en) |
| sovereign state (wd:Q3624078)         | sovereign state (lang:en)         |
| federal republic (wd:Q512187)         | federal republic (lang:en)        |
| democratic republic (wd:Q5255892)     | democratic republic (lang:en)     |
| country (wd:Q6256)                    | country (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 kind of government does the united states have currently?

[Assistant]
To determine the type of government the United States currently has, I need to find information about the governmental system of the United States in the knowledge graph.

Step 1: Search for the entity "United States" to get its Wikidata identifier.

Question: United States

Top 10 entity alternatives:
1. United States (wd:Q30), also known as America, Merica, Murica, the States, the United States, etc.: country primarily located in North America / is instance of constitutional republic / is instance of democratic republic / is instance of Federal republic / is instance of federal republic / is instance of sovereign state / is instance of superpower / country in North America / country in North America / is instance of country
2. United States (wd:Q3604334): is subclass of federation / is instance of concept
3. United States (wd:Q3965121): is instance of television series / is instance of serial / television series / television series
4. United States (wd:Q16959097): 2009 studio album by Paul Gilbert / album by Paul Gilbert / album by Paul Gilbert / is instance of album
5. United States (wd:Q110654358): article in The New International Encyclopædia / is instance of encyclopaedic article / is instance of encyclopedia article
6. United States at the 2013 Summer Universiade (wd:Q17027772, matched via United States), also known as United States: is instance of nation at sport competition / sporting event delegation
7. United States (wd:Q126018149): scientific article published in 1983 / is instance of scholarly article / is instance of academic article
8. United States (wd:Q125912238): scientific article published in 1977 / is instance of scholarly article / is instance of academic article
9. United States (wd:Q114921086): scientific article published in October 1942 / scientific article published in October 1942 / scientific article published in 1942 / is instance of scholarly article / is instance of academic article
10. United States (wd:Q111146427): is instance of scholarly article / is instance of academic article / scientific article

[Assistant]
The top result for "United States" is wd:Q30, which is identified as a country and has multiple instance-of relationships including "constitutional republic," "democratic republic," and "federal republic." This suggests that the United States has a federal republic system with constitutional and democratic elements.

Step 2: To confirm the type of government, I will query the entity wd:Q30 to retrieve its instance-of (P31) values and their labels to get human-readable descriptions of its governmental system.

execute

SELECT ?governmentType ?governmentTypeLabel WHERE { wd:Q30 wdt:P31 ?governmentType . ?governmentType rdfs:label ?governmentTypeLabel FILTER(LANG(?governmentTypeLabel) = "en") }

Got 6 rows and 2 columns:
| governmentType                        | governmentTypeLabel               |
| ------------------------------------- | --------------------------------- |
| superpower (wd:Q1489259)              | superpower (lang:en)              |
| constitutional republic (wd:Q1520223) | constitutional republic (lang:en) |
| sovereign state (wd:Q3624078)         | sovereign state (lang:en)         |
| federal republic (wd:Q512187)         | federal republic (lang:en)        |
| democratic republic (wd:Q5255892)     | democratic republic (lang:en)     |
| country (wd:Q6256)                    | country (lang:en)                 |

[Assistant]
The results show that the United States (wd:Q30) is classified as a constitutional republic, a federal republic, and a democratic republic. These terms are not mutually exclusive and describe different aspects of its governmental system:

- **Federal republic**: Indicates that the government is structured as a federation of states with a republican form of government.
- **Constitutional republic**: Indicates that the government operates under a constitution that limits the powers of government and protects individual rights.
- **Democratic republic**: Indicates that the government is based on democratic principles, with elected representatives.

The most comprehensive and commonly used term to describe the U.S. government is **"federal republic"**, as it captures the structure of power distribution between the federal government and the states, along with the republican form of governance.

Thus, the United States currently has a **federal republic** form of government.

I will now provide the final SPARQL query and answer.

answer

SELECT ?governmentType ?governmentTypeLabel WHERE { wd:Q30 wdt:P31 ?governmentType . ?governmentType rdfs:label ?governmentTypeLabel FILTER(LANG(?governmentTypeLabel) = "en") }

Answer: The United States currently has a federal republic form of government, as indicated by its classification as a federal republic, constitutional republic, and democratic republic in the knowledge graph. The most comprehensive description is 'federal republic'.


PREFIX p: <http://www.wikidata.org/prop/>
PREFIX pq: <http://www.wikidata.org/prop/qualifier/>
PREFIX ps: <http://www.wikidata.org/prop/statement/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?startDate WHERE {
  wd:Q33866 p:P39 ?stmt .
  ?stmt ps:P39 wd:Q11696 .
  ?stmt pq:P580 ?startDate
}

Using entities:
- President of the United States (wd:Q11696), also known as American President, POTUS, President of America, President of the United States of America, President of the U.S., etc.: is instance of elective office / is instance of head of state / is instance of commander-in-chief / is instance of President / is instance of president / is instance of Head of government / is instance of head of government / head of state and head of government of the United States of America
- Theodore Roosevelt (wd:Q33866), also known as Teddy Roosevelt, Theodore Roosevelt, Jr.: has occupation autobiographer / has occupation politician / has occupation statesperson / has occupation writer / has occupation historian / has occupation diarist / has occupation essayist / has occupation naturalist / has occupation conservationist / has occupation husbandry worker / has occupation ornithologist / has occupation explorer / is instance of human / 26th President of the United States from 1901 to 1909

Using properties:
- position held (wd:P39 as p/ps), also known as function, held position, holds position, job, office held, etc.: subject currently or formerly holds the object position or public office / subject currently or formerly holds the object position or public office / subject currently or formerly holds the object position or public office / subject currently or formerly holds the object position or public office
- start time (wd:P580 as pq), also known as began, beginning, building date, effective, effectivity, etc.: is subproperty of point in time / indicates the time an item begins to exist or a statement starts being valid / indicates the time an item begins to exist or a statement starts being valid / time an entity begins to exist or a statement starts being valid

Answer: Theodore Roosevelt took office as President of the United States on September 14, 1901.

Theodore Roosevelt took office as President of the United States on September 14, 1901.

SPARQL query over wikidata:
PREFIX p: <http://www.wikidata.org/prop/>
PREFIX pq: <http://www.wikidata.org/prop/qualifier/>
PREFIX ps: <http://www.wikidata.org/prop/statement/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?startDate WHERE {
  wd:Q33866 p:P39 ?stmt .
  ?stmt ps:P39 wd:Q11696 .
  ?stmt pq:P580 ?startDate
}

Using entities:
- President of the United States (wd:Q11696), also known as American President, POTUS, President of America, President of the United States of America, President of the U.S., etc.: is instance of elective office / is instance of head of state / is instance of commander-in-chief / is instance of President / is instance of president / is instance of Head of government / is instance of head of government / head of state and head of government of the United States of America
- Theodore Roosevelt (wd:Q33866), also known as Teddy Roosevelt, Theodore Roosevelt, Jr.: has occupation autobiographer / has occupation politician / has occupation statesperson / has occupation writer / has occupation historian / has occupation diarist / has occupation essayist / has occupation naturalist / has occupation conservationist / has occupation husbandry worker / has occupation ornithologist / has occupation explorer / is instance of human / 26th President of the United States from 1901 to 1909

Using properties:
- position held (wd:P39 as p/ps), also known as function, held position, holds position, job, office held, etc.: subject currently or formerly holds the object position or public office / subject currently or formerly holds the object position or public office / subject currently or formerly holds the object position or public office / subject currently or formerly holds the object position or public office
- start time (wd:P580 as pq), also known as began, beginning, building date, effective, effectivity, etc.: is subproperty of point in time / indicates the time an item begins to exist or a statement starts being valid / indicates the time an item begins to exist or a statement starts being valid / time an entity begins to exist or a statement starts being valid

Execution result:
Got 1 row and 1 column:
| startDate                           |
| ----------------------------------- |
| 1901-09-14T00:00:00Z (xsd:dateTime) |

[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] when did president theodore roosevelt take office?

[Assistant]
To determine when President Theodore Roosevelt took office, I need to find the date he assumed the presidency of the United States. This information is typically stored in Wikidata as a property related to his role as president.

### Step 1: Identify the entity for Theodore Roosevelt
I'll start by searching for the entity corresponding to Theodore Roosevelt.

Question: theodore roosevelt

Top 10 entity alternatives:
1. Theodore Roosevelt (wd:Q33866), also known as Teddy Roosevelt, Theodore Roosevelt, Jr.: 26th President of the United States from 1901 to 1909 / has occupation husbandry worker / has occupation conservationist / has occupation autobiographer / has occupation ornithologist / has occupation statesperson / has occupation naturalist / has occupation politician / has occupation historian / has occupation explorer / has occupation essayist / has occupation diarist / has occupation writer / is instance of human
2. Theodore Roosevelt Sr. (wd:Q3564517, matched via Theodore Roosevelt), also known as Theodore Roosevelt, Theodore Roosevelt, Sr.: American businessman, father of U.S. President Theodore Roosevelt (1831–1878) / has occupation philanthropist / has occupation entrepreneur / has occupation Entrepreneur / is instance of human
3. Theodore Roosevelt, Rough Rider (wd:Q16169361, matched via Roosevelt (Theodore)), also known as Equestrian statue of Roosevelt as rough‐rider, Roosevelt (Theodore), Rough Rider: Bronze sculpture by Alexander Phimister Proctor / is instance of statue
4. Theodore Roosevelt (wd:Q112205732): is instance of television series / is instance of serial / television miniseries
5. Theodore Roosevelt (wd:Q19103041): is instance of oration / speech by Leonard Wood
6. Theodore Roosevelt (wd:Q19103038): magazine article written by William Allen White / is instance of magazine article
7. Rosa 'Theodore Roosevelt' (wd:Q96278445, matched via Theodore Roosevelt), also known as Theodore Roosevelt: is instance of rose cultivar / rose cultivar
8. Theodore Roosevelt (wd:Q97990600), also known as IMO 5235026: ship launched in 1920 / is instance of ship
9. Theodore Roosevelt (wd:Q124251263): is instance of male given name / male given name
10. Theodore Roosevelt (wd:Q28796800): painting by John Singer Sargent / painting by John Singer Sargent / is instance of painting

[Assistant]
The correct entity for Theodore Roosevelt, the 26th President of the United States, is `wd:Q33866`. This entity is marked as a human (P31=wd:Q5) and has occupations including politician and statesperson, confirming it is the correct person.

### Step 2: Find the property for when he took office
I need to find the property that indicates when someone assumed the presidency. This is likely "start time" (P580) or "assumed office" (P39 with qualifier). I'll check properties related to his presidency.

I'll use `search_property_of_entity` to find properties related to his presidency or office-taking.

Question: presidency

Top 10 property alternatives:
1. position held (wd:P39 as p/wdt, matched via political office held), also known as function, held position, holds position, job, office held, etc.: subject currently or formerly holds the object position or public office / subject currently or formerly holds the object position or public office / subject currently or formerly holds the object position or public office / subject currently or formerly holds the object position or public office
2. US Congress Bio ID (wd:P1157 as p/wdt, matched via bioguide.congress.gov), also known as Biographical Directory of the United States Congress identifier, bioguide.congress.gov, Bioguide US Congress, congbio, US Congress Bio identifier, etc.: identifier for a person on the Biographical Directory of the United States Congress
3. country of citizenship (wd:P27 as p/wdt, matched via nation), 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
4. conflict (wd:P607 as p/wdt, matched via war), also known as battle, engagement, in action, in conflict, military conflict, etc.: battles, wars or other military engagements in which the person or item participated / battles, wars or engagements in which the person or item participated / is subproperty of participant in
5. candidacy in election (wd:P3602 as p/wdt, matched via election candidacy), also known as candidate in, candidate in election, election candidacy, ran in election, running in election, etc.: election where the subject is a candidate / election where the subject is a candidate / is subproperty of participant in
6. member of political party (wd:P102 as p/wdt, matched via party), also known as member of, member of party, party, party membership, political party, etc.: the political party of which a person is or has been a member or otherwise affiliated / the political party of which this politician is or has been a member / the political party of which this politician is or has been a member / is subproperty of member of
7. family (wd:P53 as p/wdt, matched via dynasty), also known as dynasty, house, member of family, noble family, royal house, etc.: family, including dynasty and nobility houses. Not family name (use P734 for family name). / family, including dynasty and nobility houses. Not family name (use P734 for family name) / family, including dynasty and nobility houses. Not family name (use P734 for family name) / is subproperty of member of
8. nominated for (wd:P1411 as p/wdt, matched via nomination to), also known as finalist for, finalist for award, have nomination to, nominated for award, nomination received, etc.: award nomination received by a person, organisation or creative work (inspired from "award received" (Property:P166)) / award nomination received by a person, organisation or creative work (inspired from "award received" (Property:P166))
9. time period (wd:P2348 as p/wdt), also known as oge (oge akụkọ ihe mere eme ma ọ bụ oge, oge egwuregwu, oge ... omebe iwu wdg) nke isiokwu ahụ mere ma ọ bụ nke ejikọtara ya., P2348: time period (historic period or era, sports season, theatre ... in which the subject occurred or with which it is associated / historic period or era in which the subject occurred
10. UK National Archives ID (wd:P3029 as p/wdt, matched via The National Archives), also known as National Archives ID, UK, NRA ID, PRO, Public Record Office, The National Archives, etc.: identifier for a person, family or organisation, in the UK's National Archives database / identifier for a person, family or organisation, in the UK's National Archives database

No other items found

[Assistant]
The most relevant property here is **P39 (position held)**, which captures the positions a person has held, including the presidency. To find when he took office, I need to look at the statements for P39 with the value of "President of the United States" and extract the start time (P580) qualifier.

### Step 3: Find the value for "President of the United States"
I'll search for the QID corresponding to "President of the United States" to use in the query.

Question: President of the United States

Top 10 entity alternatives:
1. President of the United States (wd:Q11696), also known as American President, POTUS, President of America, President of the United States of America, President of the U.S., etc.: head of state and head of government of the United States of America / is instance of commander-in-chief / is instance of Head of government / is instance of head of government / is instance of elective office / is instance of head of state / is instance of President / is instance of president
2. cultural depictions of John F. Kennedy (wd:Q17512211, matched via President of the United States), also known as cultural depictions of JFK, cultural depictions of John Fitzgerald Kennedy, cultural depictions of President John F. Kennedy, cultural depictions of President Kennedy, President of the United States: John F. Kennedy depicted in culture / is instance of cultural depiction
3. President of the United States (wd:Q125680992): fictional position in the Grand Theft Auto video game series (HD) / is instance of fictional office, position, or title
4. Jimmy Carter (wd:Q23685, matched via 39th President of the United States), also known as 39th President of the United States, James Carter, James Earl Carter, James Earl Carter Jr., James Earl Carter, Jr., etc.: President of the United States from 1977 to 1981 / President of the United States from 1977 to 1981 / has occupation human rights activist / has occupation Environmentalist / has occupation environmentalist / has occupation businessperson / has occupation peace activist / has occupation autobiographer / has occupation naval officer / has occupation statesperson / has occupation humanitarian / has occupation politician / has occupation submariner / has occupation novelist / has occupation engineer / has occupation diplomat / has occupation writer / has occupation farmer / is instance of human
5. 2024 United States presidential election (wd:Q101110072, matched via 47th President of the United States), also known as 2024 American presidential election, 2024 POTUS election, 2024 United States presidential race, 2024 USA presidential election, 2024 US presidential campaign, etc.: is instance of United States presidential election / 60th quadrennial U.S. presidential election / 60th quadrennial U.S. presidential election
6. Vice President of the United States (wd:Q11699), also known as President of the Senate, President of the United States Senate, United States Vice President, United States VP, USA VP, etc.: second-highest constitutional office in the United States / is instance of president of the senate / is instance of elective office / is instance of vice president
7. President of Mexico (wd:Q628004, matched via President of the United Mexican States), also known as President of the United Mexican States: is subclass of President of the Republic / head of state of the country of Mexico / head of state of the country of Mexico / is subclass of head of government / is subclass of Head of government / is subclass of commander-in-chief / is instance of public office
8. President-elect of the United States (wd:Q1467287), also known as President-Elect: winning candidate of the U.S. presidential election in the time before inauguration / is subclass of president-elect / is instance of position
9. Acting President of the United States (wd:Q2123628): person acting as POTUS when the president is unavailable / is subclass of acting president
10. seal of the president of the United States (wd:Q524901, matched via President of the United States seal), also known as President of the United States seal, the president of the United States seal: is instance of national seal / seal

[Assistant]
The correct entity for "President of the United States" is `wd:Q11696`.

### Step 4: Construct the SPARQL query
Now I will construct a SPARQL query to find when Theodore Roosevelt (`wd:Q33866`) assumed the office of President of the United States (`wd:Q11696`) by querying the `p:P39` (position held) statements, and extracting the start time (`pq:P580`) qualifier.

The query will:
- Find statements where `wd:Q33866` holds position `wd:Q11696`.
- Extract the start time (`pq:P580`) from those statements.
- Return the date.

I'll execute this query.

execute

SELECT ?startDate WHERE { wd:Q33866 p:P39 ?stmt . ?stmt ps:P39 wd:Q11696 . ?stmt pq:P580 ?startDate }

[Assistant]
Theodore Roosevelt took office as President of the United States on **September 14, 1901**. This occurred after the assassination of President William McKinley, under whom Roosevelt was serving as Vice President.

### Final Answer:
The SPARQL query successfully retrieved the date Theodore Roosevelt assumed the presidency.

I will now provide the final answer.

answer

SELECT ?startDate WHERE { wd:Q33866 p:P39 ?stmt . ?stmt ps:P39 wd:Q11696 . ?stmt pq:P580 ?startDate }

Answer: Theodore Roosevelt took office as President of the United States on September 14, 1901.