PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?coach WHERE {
  wd:Q330120 wdt:P286 ?coach
}

Using entities:
- Carolina Panthers (wd:Q330120): is instance of American football team / American football team / American football team

Using properties:
- head coach (wd:P286 as wdt), also known as club manager, coach, coached by, led by, manager, etc.: on-field manager or head coach of a sports club (not to be ... manager P505, which is not a coaching position) or person / on-field manager or head coach of a sports club (not to be ... manager P505, which is not a coaching position) or person

Answer: Dave Canales

Dave Canales

SPARQL query over wikidata:
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?coach WHERE {
  wd:Q330120 wdt:P286 ?coach
}

Using entities:
- Carolina Panthers (wd:Q330120): is instance of American football team / American football team / American football team

Using properties:
- head coach (wd:P286 as wdt), also known as club manager, coach, coached by, led by, manager, etc.: on-field manager or head coach of a sports club (not to be ... manager P505, which is not a coaching position) or person / on-field manager or head coach of a sports club (not to be ... manager P505, which is not a coaching position) or person

Execution result:
Got 1 row and 1 column:
| coach                       |
| --------------------------- |
| Dave Canales (wd:Q47456134) |

[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 coaches the carolina panthers?

[Assistant]
To determine who coaches the Carolina Panthers, I need to find the current head coach of the team. The Carolina Panthers are a professional American football team in the NFL, and their head coach is a person with a specific occupation.

### Step 1: Identify the entity for the Carolina Panthers
I will first search for the entity representing the Carolina Panthers in Wikidata.

Question: Carolina Panthers

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

[Assistant]
The primary entity for the Carolina Panthers is `wd:Q330120`, which is an American football team. Now, I need to find the property that links the team to its head coach.

### Step 2: Search for properties related to "coach" or "head coach" for the Carolina Panthers
I will use `search_property_of_entity` to find properties associated with the Carolina Panthers that might indicate the head coach.

Question: coach

Top 10 property alternatives:
1. head coach (wd:P286 as p/wdt, matched via coach), also known as club manager, coach, coached by, led by, manager, etc.: on-field manager or head coach of a sports club (not to be ... manager P505, which is not a coaching position) or person / on-field manager or head coach of a sports club (not to be ... manager P505, which is not a coaching position) or person
2. sport (wd:P641 as p/wdt), also known as play, plays, sport played, sports, P641: sport that the subject participates or participated in or is associated with / sport or discipline in which the entity participates or belongs to
3. league or competition (wd:P118 as p/wdt, matched via competition), also known as competition, cup, division, sports league, tournament, etc.: league or competition in which team or player has played, or in which an event occurs / is subproperty of participant in / league in which the team plays / league in which the team plays
4. category for members of a team (wd:P6112 as p/wdt, matched via category for players), also known as category for players, category for team members, P6112: Wikimedia category for players playing for a sports team / is subproperty of topic's main category
5. Flashscore.com team ID (wd:P7876 as p/wdt, matched via www.flashscore.com/team/), also known as flashscore.com/team/, FlashScore.com team ID, https://www.flashscore.com/team/, www.flashscore.com/team/, P7876: identifier for a sports team in the FlashScore.com database
6. home venue (wd:P115 as p/wdt, matched via stadium), also known as arena, ballpark, ground, home field, home ground, etc.: home stadium or venue of a sports team or applicable performing arts organization / home stadium or venue of a sports team or applicable performing arts organization / home stadium or venue of a sports team or applicable performing arts organization / is subproperty of location
7. SportsLogos.net team ID (wd:P9122 as p/wdt, matched via SportsLogos.net ID), also known as SportsLogos.net ID, P9122: identifier for a sports organization on the website Sports Logos
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. social media followers (wd:P8687 as p/wdt, matched via followers), also known as follow count, follower count, follower number, followers, follow number, etc.: number of subscribers on a particular social media website ... time" and property for account. For Twitter, use numeric id.
10. mascot (wd:P822 as p/wdt), also known as P822: mascot of an organization, e.g. a sports team or university / mascot of an organization, e.g. a sports team or university

No other items found

[Assistant]
The property `wdt:P286` (head coach) is the correct property to use for identifying the head coach of the Carolina Panthers. Now, I will retrieve the head coach of the Carolina Panthers using this property.

### Step 3: Query for the head coach of the Carolina Panthers
I will execute a SPARQL query to find the head coach of the Carolina Panthers (`wd:Q330120`) using `wdt:P286`.

execute

SELECT ?coach WHERE { wd:Q330120 wdt:P286 ?coach }

[Assistant]
The head coach of the Carolina Panthers is Dave Canales. I will now provide the final answer with the SPARQL query used.

answer

SELECT ?coach WHERE { wd:Q330120 wdt:P286 ?coach }

Answer: Dave Canales


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:Q16311 wdt:P175 ?actor .
  ?actor rdfs:label ?actorLabel
  FILTER ( LANG( ?actorLabel ) = "en" )
}

Using entities:
- James T. Kirk (wd:Q16311), also known as Captain James Tiberius Kirk, Captain James T. Kirk, Captain Kirk, James Kirk, James Tiberius Kirk, etc.: has occupation explorer / has occupation tactician / has occupation spaceship captain / is instance of comics character / is instance of fictional human / is instance of television character / is instance of literary character / is instance of Star Trek character / is instance of Human / is instance of human from Star Trek / character in the Star Trek media franchise / fictional character from Star Trek

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

Got 4 rows and 2 columns:
| actor                       | actorLabel                |
| --------------------------- | ------------------------- |
| William Shatner (wd:Q16297) | William Shatner (lang:en) |
| Sam Witwer (wd:Q18918)      | Sam Witwer (lang:en)      |
| Paul Wesley (wd:Q270149)    | Paul Wesley (lang:en)     |
| Jimmy Bennett (wd:Q4349)    | Jimmy Bennett (lang:en)   |

Answer: The actors who played Captain James T. Kirk are William Shatner, Sam Witwer, Paul Wesley, and Jimmy Bennett.

The actors who played Captain James T. Kirk are William Shatner, Sam Witwer, Paul Wesley, and Jimmy Bennett.

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:Q16311 wdt:P175 ?actor .
  ?actor rdfs:label ?actorLabel
  FILTER ( LANG( ?actorLabel ) = "en" )
}

Using entities:
- James T. Kirk (wd:Q16311), also known as Captain James Tiberius Kirk, Captain James T. Kirk, Captain Kirk, James Kirk, James Tiberius Kirk, etc.: has occupation explorer / has occupation tactician / has occupation spaceship captain / is instance of comics character / is instance of fictional human / is instance of television character / is instance of literary character / is instance of Star Trek character / is instance of Human / is instance of human from Star Trek / character in the Star Trek media franchise / fictional character from Star Trek

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 4 rows and 2 columns:
| actor                       | actorLabel                |
| --------------------------- | ------------------------- |
| William Shatner (wd:Q16297) | William Shatner (lang:en) |
| Sam Witwer (wd:Q18918)      | Sam Witwer (lang:en)      |
| Paul Wesley (wd:Q270149)    | Paul Wesley (lang:en)     |
| Jimmy Bennett (wd:Q4349)    | Jimmy Bennett (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 played kirk?

[Assistant]
To determine who played Kirk, I need to identify the character "Kirk" and find the actor(s) who portrayed this character. The most famous character named Kirk is Captain James T. Kirk from the Star Trek franchise.

### Step 1: Identify the character "Kirk"
I will first search for the entity corresponding to "Captain James T. Kirk" to confirm its Wikidata identifier.

Question: Captain James T. Kirk

Top 10 entity alternatives:
1. James T. Kirk (wd:Q16311, matched via Captain James T. Kirk), also known as Captain James Tiberius Kirk, Captain James T. Kirk, Captain Kirk, James Kirk, James Tiberius Kirk, etc.: character in the Star Trek media franchise / is instance of human from Star Trek / is instance of television character / is instance of Star Trek character / fictional character from Star Trek / is instance of literary character / has occupation spaceship captain / is instance of comics character / is instance of fictional human / has occupation tactician / has occupation explorer / is instance of Human
2. Captain James Towers Kirkland (wd:Q94039613): is instance of scholarly article / is instance of academic article
3. James T. Kirk (wd:Q6143939), also known as James Thompson Kirk: has occupation military officer / Union Army officer (1826–1886) / has occupation merchant / has occupation officer / is instance of human
4. James Thomas Kirk (wd:Q106802878, matched via James T. Kirk), also known as James T. Kirk: Mayor of Elizabeth, New Jersey / has occupation politician / is instance of human
5. James T. Kirk (wd:Q119138548), also known as James T. Kirk (alternate reality): character in Star Trek played by Chris Pine / is instance of human from Star Trek / is instance of Star Trek character / is instance of literary character / has occupation spaceship captain / is instance of comics character / is instance of Human
6. The Trial of Captain Kirk (wd:Q111747230): is instance of Star Trek comic
7. The Autobiography of James T. Kirk (wd:Q54826007): is instance of version, edition or translation
8. The Autobiography of James T. Kirk (wd:Q54826009): is instance of version, edition or translation
9. The Autobiography of James T. Kirk (wd:Q54826008): is instance of version, edition or translation
10. The Autobiography of James T. Kirk (wd:Q54826006): is instance of version, edition or translation

[Assistant]
The most relevant entity for "Captain James T. Kirk" is `wd:Q16311`, which represents the fictional Star Trek character. Now, I need to find the actor(s) who portrayed this character.

### Step 2: Find properties related to "actor" or "portrayed by"
I will search for properties related to "actor" or "portrayed by" for the character `wd:Q16311` to identify the correct property that links the character to the actor(s).

Question: actor

Top 10 property alternatives:
1. performer (wd:P175 as p/wdt, matched via actor), also known as actor, actress, artist, dancer, musical artist, etc.: actor, musician, band or other performer associated with this role or musical work / actor, musician, music group or other performer associated with this work / is subproperty of contributor to the creative work or subject
2. enemy (wd:P7047 as p/wdt), also known as arch-enemy, archenemy, archfoe, archnemesis, archrival, etc.: opponent character or group of this fictive character or group / opponent character or group of this character or group / is subproperty of significant person
3. child (wd:P40 as p/wdt, matched via sons), also known as children, daughter, daughters, descendants, father of, etc.: subject has object as child. Do not use for stepchildren—use "relative" (P1038), qualified with "type of kinship" (P1039) / subject has the object in their family as their offspring son or daughter (independently of their age) / subject has object as biological, foster, and/or adoptive child / is subproperty of significant person / is subproperty of relative
4. 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)
5. creator (wd:P170 as p/wdt, matched via 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)
6. 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
7. unmarried partner (wd:P451 as p/wdt, matched via lover), also known as boyfriend, cohabitant, domestic partner, enbyfriend, girlfriend, etc.: someone with whom the person is in a relationship without being married. Use "spouse" (P26) for married couples / someone with whom the person is in a relationship without being married. Use "spouse" (P26) for married couples / is subproperty of significant person
8. birth name (wd:P1477 as p/wdt, matched via né), also known as birthname, bn, bname, born as, full birth name, etc.: full name of a person at birth, if different from their ... John Peter Doe for Joe Doe, Ann Smith for Ann Miller) / full name of a person at birth, if different from their current, generally used name / full name of a person at birth, if different from their current name / is subproperty of name
9. military branch (wd:P241 as p/wdt, matched via formation), also known as branch, formation, service branch, unit branch, P241: branch to which this military unit, award, office, or person belongs, e.g. Royal Navy / is subproperty of part of
10. sport (wd:P641 as p/wdt, matched via plays), also known as play, plays, sport played, sports, P641: sport that the subject participates or participated in or is associated with / sport or discipline in which the entity participates or belongs to

No other items found

[Assistant]
The property `wdt:P175` (performer) is the correct property to identify the actor(s) who portrayed Captain James T. Kirk. Now, I will construct a SPARQL query to find the actors who played this character by using `wdt:P175` on `wd:Q16311`.

### Step 3: Construct and execute the SPARQL query
I will retrieve the actors who portrayed Captain James T. Kirk and fetch their labels in English for readability.

execute

SELECT ?actor ?actorLabel WHERE { wd:Q16311 wdt:P175 ?actor . ?actor rdfs:label ?actorLabel FILTER(LANG(?actorLabel) = "en") }

Got 4 rows and 2 columns:
| actor                       | actorLabel                |
| --------------------------- | ------------------------- |
| William Shatner (wd:Q16297) | William Shatner (lang:en) |
| Sam Witwer (wd:Q18918)      | Sam Witwer (lang:en)      |
| Paul Wesley (wd:Q270149)    | Paul Wesley (lang:en)     |
| Jimmy Bennett (wd:Q4349)    | Jimmy Bennett (lang:en)   |

[Assistant]
The SPARQL query successfully returned the actors who portrayed Captain James T. Kirk. The main and most well-known actor is William Shatner, who portrayed Kirk in the original Star Trek series and films. Other actors include Sam Witwer (voice in animated series), Paul Wesley (in the Kelvin timeline films), and Jimmy Bennett (as a child in a flashback).

### Final Answer:
The actors who played Captain James T. Kirk are:
- William Shatner
- Sam Witwer
- Paul Wesley
- Jimmy Bennett

I will now provide the final SPARQL query and answer.

answer

SELECT ?actor ?actorLabel WHERE { wd:Q16311 wdt:P175 ?actor . ?actor rdfs:label ?actorLabel FILTER(LANG(?actorLabel) = "en") }

Answer: The actors who played Captain James T. Kirk are William Shatner, Sam Witwer, Paul Wesley, and Jimmy Bennett.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?placeOfDeath WHERE {
  wd:Q1317 wdt:P20 ?placeOfDeath
}

Using entities:
- Osama bin Laden (wd:Q1317), also known as Crankshaft, Osama bin Mohammed bin Awad bin Laden, Usama bin Laden, Usāmah bin Muḥammad bin ‘Awaḍ bin Lādin: has occupation terrorist / has occupation civil engineer / has occupation Civil engineer / has occupation jihadist / has occupation businessperson / is instance of human / Saudi terrorist and co-founder of al-Qaeda (1957–2011) / Saudi terrorist and co-founder of al-Qaeda (1957–2011)

Using properties:
- place of death (wd:P20 as wdt), also known as death location, death place, deathplace, died, died in, etc.: is subproperty of location / most specific known (e.g. city instead of country, or ... death location of a person, animal or fictional character / most specific known (e.g. city instead of country, or ... death location of a person, animal or fictional character / most specific known (e.g. city instead of country, or ... death location of a person, animal or fictional character

Answer: Osama bin Laden was killed in Osama bin Laden's compound in Abbottabad.

Osama bin Laden was killed in Osama bin Laden's compound in Abbottabad.

SPARQL query over wikidata:
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?placeOfDeath WHERE {
  wd:Q1317 wdt:P20 ?placeOfDeath
}

Using entities:
- Osama bin Laden (wd:Q1317), also known as Crankshaft, Osama bin Mohammed bin Awad bin Laden, Usama bin Laden, Usāmah bin Muḥammad bin ‘Awaḍ bin Lādin: has occupation terrorist / has occupation civil engineer / has occupation Civil engineer / has occupation jihadist / has occupation businessperson / is instance of human / Saudi terrorist and co-founder of al-Qaeda (1957–2011) / Saudi terrorist and co-founder of al-Qaeda (1957–2011)

Using properties:
- place of death (wd:P20 as wdt), also known as death location, death place, deathplace, died, died in, etc.: is subproperty of location / most specific known (e.g. city instead of country, or ... death location of a person, animal or fictional character / most specific known (e.g. city instead of country, or ... death location of a person, animal or fictional character / most specific known (e.g. city instead of country, or ... death location of a person, animal or fictional character

Execution result:
Got 1 row and 1 column:
| placeOfDeath                                           |
| ------------------------------------------------------ |
| Osama bin Laden's compound in Abbottabad (wd:Q3065522) |

[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 was osama bin laden killed?

[Assistant]
To determine where Osama bin Laden was killed, I will follow these steps:

1. First, I will search for the entity corresponding to "Osama bin Laden" in Wikidata.
2. Once I have the correct entity, I will examine its properties to find information about the location of his death.
3. I will construct a SPARQL query to retrieve the location of his death.
4. Finally, I will execute the query and provide the answer.

Let me begin by searching for the entity for "Osama bin Laden".

Question: osama bin laden

Top 10 entity alternatives:
1. Osama bin Laden (wd:Q1317), also known as Crankshaft, Osama bin Mohammed bin Awad bin Laden, Usama bin Laden, Usāmah bin Muḥammad bin ‘Awaḍ bin Lādin: Saudi terrorist and co-founder of al-Qaeda (1957–2011) / Saudi terrorist and co-founder of al-Qaeda (1957–2011) / has occupation civil engineer / has occupation Civil engineer / has occupation businessperson / has occupation terrorist / has occupation jihadist / is instance of human
2. Osama bin Laden (wd:Q10612826): is instance of individual animal / rogue bull elephant in India
3. death of Osama bin Laden (wd:Q19085, matched via Osama bin Laden death), also known as Geronimo EKIA, killing of Bin Laden, killing of Osama bin Laden, Operation Neptune Spear, Osama bin Laden death, etc.: U.S. military operation in Abbottabad, Pakistan / is instance of military operation / is instance of assassination / is instance of occurrence / is instance of event
4. Osama bin Laden bodyguards (wd:Q7105668): bodyguards of Osama Bin Laden
5. Operation Osama Bin Laden (wd:Q122824240): is instance of video game / 2021 video game
6. Meeting Osama Bin Laden (wd:Q129687082): is instance of television film / is instance of Television film / 2004 Television film
7. Targeted: Osama Bin Laden (wd:Q129687094): is instance of television film / is instance of Television film / 2004 Television film
8. Osama Bin Laden Tape (wd:Q110056559): is instance of Saturday Night Live sketch / sketch from Saturday Night Live
9. Fatwas of Osama bin Laden (wd:Q5437340): is subclass of fatwa / is subclass of Fatwa
10. Search for Osama bin Laden (wd:Q10900938): manhunt for Osama bin Laden

[Assistant]
The correct entity for Osama bin Laden is `wd:Q1317`, which is identified as a human and the Saudi terrorist and co-founder of al-Qaeda. Now, I will investigate the properties of this entity to find information about the location of his death.

I will use the `list` function to examine the triples associated with `wd:Q1317` to locate the property that indicates the place of death.

list

wd:Q1317

Got 1,086 rows and 3 columns, showing the first 10 rows below:
| subject                    | property                         | object                                                                                |
| -------------------------- | -------------------------------- | --------------------------------------------------------------------------------------- |
| Osama bin Laden (wd:Q1317) | instance of (wdt:P31)            | human (wd:Q5)                                                                           |
| Osama bin Laden (wd:Q1317) | occupation (wdt:P106)            | terrorist (wd:Q12414919)                                                                |
| Osama bin Laden (wd:Q1317) | sex or gender (wdt:P21)          | male (wd:Q6581097)                                                                      |
| Osama bin Laden (wd:Q1317) | given name (wdt:P735)            | Osama (wd:Q10067197)                                                                    |
| Osama bin Laden (wd:Q1317) | date of birth (wdt:P569)         | 1957-03-10T00:00:00Z (xsd:dateTime)                                                     |
| Osama bin Laden (wd:Q1317) | Commons category (wdt:P373)      | Osama bin Laden                                                                         |
| Osama bin Laden (wd:Q1317) | image (wdt:P18)                  | <http://commons.wikimedia.org/wiki/Special:FilePath/Osama%20bin%20Laden%20portrait.jpg> |
| Osama bin Laden (wd:Q1317) | family name (wdt:P734)           | Bin-Laden (wd:Q111033818)                                                               |
| Osama bin Laden (wd:Q1317) | country of citizenship (wdt:P27) | Saudi Arabia (wd:Q851)                                                                  |
| Osama bin Laden (wd:Q1317) | Freebase ID (wdt:P646)           | /m/05mg9                                                                                |
| ...                        | ...                              | ...                                                                                |

[Assistant]
From the list of triples, I can see that the property for "place of death" is not immediately visible. However, I know that the property for "place of death" in Wikidata is typically `wdt:P20`. I will now search for this property explicitly using `search_property_of_entity` to confirm its existence and retrieve the value.

Question: death

Top 10 property alternatives:
1. date of death (wd:P570 as p/wdt, matched via death), also known as date of the end, dead, death, death date, deathdate, etc.: is subproperty of dissolved, abolished or demolished date / is subproperty of dissolved, abolished or demolished / date on which the subject died / date on which the subject died / date on which the subject died / is subproperty of end time
2. manner of death (wd:P1196 as p/wdt, matched via death manner), also known as circumstance of death, death manner, death type, nature of death, type of death, etc.: general circumstances of a person's death; e.g. natural ... mechanism, e.g. heart attack, trauma, pneumonia etc. / general circumstances of a person's death; e.g. natural ... mechanism, e.g. heart attack, trauma, pneumonia etc. / general circumstances of a person's death; e.g. natural ... mechanism, e.g. heart attack, trauma, pneumonia...
3. place of death (wd:P20 as p/wdt, matched via death place), also known as death location, death place, deathplace, died, died in, etc.: most specific known (e.g. city instead of country, or ... death location of a person, animal or fictional character / most specific known (e.g. city instead of country, or ... death location of a person, animal or fictional character / most specific known (e.g. city instead of country, or ... death location of a person, animal or fictional character / is subproperty of location
4. cause of death (wd:P509 as p/wdt, matched via death cause), also known as death cause, died of, die from, die of, method of murder, etc.: underlying or immediate cause of death.  Underlying cause ... category, e.g. natural causes, accident, homicide, suicide / underlying or immediate cause of death.  Underlying cause ... category, e.g. natural causes, accident, homicide, suicide / an item describing the cause of a person or specific organism's death. Samples: leukaemia, car crash / medical cause of a person or specific organism's death (not to be confused with P1196)
5. killed by (wd:P157 as p/wdt), also known as assassin, assassinated by, executed by, executioner, killer, etc.: person or organization who killed the subject / is subproperty of significant person / person who killed the subject
6. place of burial (wd:P119 as p/wdt, matched via interment), also known as ashes scattered at, burial location, burial place, buried at, buried in, etc.: location of grave, resting place, place of ash-scattering, ... places: e.g., re-burials, parts of body buried separately. / location of grave, resting place, place of ash-scattering, ... places: e.g., re-burials, parts of body buried separately. / location of grave, resting place, place of ash-scattering, ... e.g. re-burials, cenotaphs, parts of body buried separately / location of grave, resting place, place of ash-scattering, etc, (e.g. city or cemetery) for a person / is subproperty of location
7. significant event (wd:P793 as p/wdt, matched via outcome), also known as big event, event, fate, important event, key event, etc.: significant or notable events associated with the subject / significant or notable events associated with the subject / significant or notable events associated with the subject
8. birth name (wd:P1477 as p/wdt, matched via nee), also known as birthname, bn, bname, born as, full birth name, etc.: full name of a person at birth, if different from their ... John Peter Doe for Joe Doe, Ann Smith for Ann Miller) / full name of a person at birth, if different from their current, generally used name / full name of a person at birth, if different from their current name / is subproperty of name
9. described by source (wd:P1343 as p/wdt, matched via entry), also known as defined in, described by biography, described by encyclopedia, described by obituary, described by reference work, etc.: dictionary, encyclopaedia, etc. where this item is described / work where this item is described / is subproperty of attested in
10. child (wd:P40 as p/wdt, matched via son), also known as children, daughter, daughters, descendants, father of, etc.: subject has object as child. Do not use for stepchildren—use "relative" (P1038), qualified with "type of kinship" (P1039) / subject has the object in their family as their offspring son or daughter (independently of their age) / subject has object as biological, foster, and/or adoptive child / is subproperty of significant person / is subproperty of relative

No other items found

[Assistant]
The property `wdt:P20` (place of death) is confirmed as the correct property to use. Now, I will construct a SPARQL query to retrieve the place of death for Osama bin Laden (`wd:Q1317`) using this property. The query will directly fetch the value of `wdt:P20` for this entity.

execute

SELECT ?placeOfDeath WHERE { wd:Q1317 wdt:P20 ?placeOfDeath }

[Assistant]
The SPARQL query has successfully returned the place of death for Osama bin Laden as "Osama bin Laden's compound in Abbottabad" with the Wikidata identifier `wd:Q3065522`.

To provide a more human-readable answer, I will now retrieve the label for this location (`wd:Q3065522`) in English to confirm its name.

SELECT ?label WHERE { wd:Q3065522 rdfs:label ?label . FILTER(LANG(?label) = "en") }

[Assistant]
The place where Osama bin Laden was killed is "Osama bin Laden's compound in Abbottabad." This is confirmed by the Wikidata entry and its English label.

I will now provide the final SPARQL query and answer.

The SPARQL query used to determine the place of death is:

```sparql
SELECT ?placeOfDeath WHERE { wd:Q1317 wdt:P20 ?placeOfDeath }
```

And the answer is:

Osama bin Laden was killed in Osama bin Laden's compound in Abbottabad.

answer

SELECT ?placeOfDeath WHERE { wd:Q1317 wdt:P20 ?placeOfDeath }

Answer: Osama bin Laden was killed in Osama bin Laden's compound in Abbottabad.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?country WHERE {
  wd:Q5680 wdt:P131 ?admin .
  ?admin wdt:P17 ?country .
}

Using entities:
- Nineveh (wd:Q5680): is instance of ancient city / is instance of type site / is instance of tell / is instance of archaeological site / ancient Assyrian city, capital of the Neo-Assyrian Empire

Using properties:
- located in the administrative territorial entity (wd:P131 as wdt), also known as administrative territorial entity, administrative territory, city, happens in, in, etc.: is subproperty of location / is subproperty of part of / the item is located on the territory of the following administrative entity / the item is located on the territory of the following administrative entity / the item is located on the territory of the following ... the item falls only partially into the administrative entity. / the item is located on the territory of the following ... the item falls only partially into the administrative entity.
- country (wd:P17 as wdt), also known as host country, land, sovereign state, state, P17: is subproperty of located in the administrative territorial entity / sovereign state that this item is in (not to be used for human beings) / sovereign state that this item is in (not to be used for human beings) / sovereign state that this item is in (not to be used for human beings) / sovereign state that this item is in (not to be used for human beings)

Got 1 row and 1 column:
| country        |
| -------------- |
| Iraq (wd:Q796) |

Answer:
The ancient city of Nineveh is located in modern-day Iraq. The SPARQL query confirms that Nineveh (wd:Q5680) is administratively part of Mosul (wd:Q83317), which in turn is located in Iraq (wd:Q796).

### Final Answer:
Nineveh is located in modern-day Iraq.

```sparql
SELECT ?country WHERE {
  wd:Q5680 wdt:P131 ?admin .
  ?admin wdt:P17 ?country .
}
```

The ancient city of Nineveh is located in modern-day Iraq. The SPARQL query confirms that Nineveh (wd:Q5680) is administratively part of Mosul (wd:Q83317), which in turn is located in Iraq (wd:Q796).

### Final Answer:
Nineveh is located in modern-day Iraq.

```sparql
SELECT ?country WHERE {
  wd:Q5680 wdt:P131 ?admin .
  ?admin wdt:P17 ?country .
}
```

SPARQL query over wikidata:
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?country WHERE {
  wd:Q5680 wdt:P131 ?admin .
  ?admin wdt:P17 ?country .
}

Using entities:
- Nineveh (wd:Q5680): is instance of ancient city / is instance of type site / is instance of tell / is instance of archaeological site / ancient Assyrian city, capital of the Neo-Assyrian Empire

Using properties:
- located in the administrative territorial entity (wd:P131 as wdt), also known as administrative territorial entity, administrative territory, city, happens in, in, etc.: is subproperty of location / is subproperty of part of / the item is located on the territory of the following administrative entity / the item is located on the territory of the following administrative entity / the item is located on the territory of the following ... the item falls only partially into the administrative entity. / the item is located on the territory of the following ... the item falls only partially into the administrative entity.
- country (wd:P17 as wdt), also known as host country, land, sovereign state, state, P17: is subproperty of located in the administrative territorial entity / sovereign state that this item is in (not to be used for human beings) / sovereign state that this item is in (not to be used for human beings) / sovereign state that this item is in (not to be used for human beings) / sovereign state that this item is in (not to be used for human beings)

Execution result:
Got 1 row and 1 column:
| country        |
| -------------- |
| Iraq (wd:Q796) |

[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 nineveh city?

[Assistant]
To determine the location of Nineveh City, I need to find its geographical and administrative details in the knowledge graph. Nineveh is an ancient city, so I will first search for its entity in Wikidata to confirm its identity and then retrieve its location information.

### Step 1: Search for the entity "Nineveh"
I will use `search_entity` to find the Wikidata entity for Nineveh.

Question: Nineveh

Top 10 entity alternatives:
1. Nineveh (wd:Q5680): ancient Assyrian city, capital of the Neo-Assyrian Empire / is instance of archaeological site / is instance of ancient city / is instance of type site / is instance of tell
2. Upper Mesopotamia (wd:Q311819, matched via Nineveh), also known as Al-Jazira, Assyria, Jazira, Ninawa, Nineveh, etc.: northern portion of region between Tigris and Euphrates rivers, now part of Iraq, Syria and Turkey / is instance of geographical region / is instance of geographic region
3. Nineveh (wd:Q14688715), also known as Nineveh, IN, Nineveh, Indiana: is instance of unincorporated community in the United States / unincorporated community in Johnson County, Indiana
4. Nineveh (wd:Q3477846), also known as Nineveh, New York, Nineveh, NY: is instance of unincorporated community in the United States / human settlement in New York, United States of America
5. Nineveh (wd:Q18353599), also known as Nineveh, Missouri, Nineveh, MO: is instance of unincorporated community in the United States / human settlement in Adair County, Missouri, United States
6. Nineveh (wd:Q111036727), also known as Nineveh (Brooke Ligertwood song), Nineveh (song): is instance of digital promotional single / 2022 song by Brooke Ligertwood
7. Nineveh (wd:Q14955822), also known as Nineveh, England: is instance of Wikipedia article covering multiple topics / name of multiple places in England, UK
8. Nineveh (wd:Q24259678), also known as Nineveh, Pennsylvania: human settlement in Greene County, Pennsylvania, United States / is instance of unincorporated community in the United States
9. Nineveh (wd:Q7038585), also known as Nineveh, Victoria County, Nova Scotia: human settlement in Victoria County, Nova Scotia, Canada / is instance of human settlement
10. Nineveh (wd:Q7038584), also known as Nineveh, Lunenburg, Nova Scotia: human settlement in Lunenburg County, Nova Scotia, Canada / is instance of human settlement

[Assistant]
The primary and most relevant entity for the ancient city of Nineveh is **wd:Q5680**, which is described as an ancient Assyrian city and the capital of the Neo-Assyrian Empire. The other entries refer to modern places with the same name, which are not relevant to the historical context of the question.

### Step 2: Retrieve the location details of Nineveh (wd:Q5680)
Now, I will query for the location of Nineveh (wd:Q5680) by checking its coordinates (P625) and its administrative hierarchy (P131) to determine its modern-day location.

I will use the `list` function to inspect the triples associated with Nineveh (wd:Q5680) to find relevant properties such as coordinates (P625) and country (P17) or administrative division (P131).

list

wd:Q5680

[Assistant]
The coordinates for Nineveh (wd:Q5680) are **43.15° N, 36.3667° E**, which places it in modern-day Iraq.

To confirm the modern country, I will check the administrative hierarchy (P131) or the country (P17) associated with Nineveh.

I will now check for the country (P17) or administrative parent (P131) of Nineveh.

wd:Q5680

[Assistant]
Nineveh is located within the administrative territorial entity of **Mosul (wd:Q83317)**. Now, I will check the country to which Mosul belongs by querying its country (P17).

wd:Q83317

[Assistant]
Mosul (wd:Q83317) is located in **Iraq (wd:Q796)**. Therefore, the ancient city of Nineveh is located in modern-day Iraq.

### Final SPARQL Query
To provide a complete and concise answer, I will construct a SPARQL query that retrieves the modern country where Nineveh is located by following the administrative hierarchy from Nineveh → Mosul → Iraq.

The query will:
1. Start with Nineveh (wd:Q5680).
2. Traverse the administrative hierarchy (P131) to find Mosul.
3. Find the country (P17) of Mosul.

Here is the final SPARQL query:

execute

SELECT ?country WHERE { wd:Q5680 wdt:P131 ?admin . ?admin wdt:P17 ?country . }

Got 1 row and 1 column:
| country        |
| -------------- |
| Iraq (wd:Q796) |

[Assistant]
The ancient city of Nineveh is located in modern-day Iraq. The SPARQL query confirms that Nineveh (wd:Q5680) is administratively part of Mosul (wd:Q83317), which in turn is located in Iraq (wd:Q796).

### Final Answer:
Nineveh is located in modern-day Iraq.

```sparql
SELECT ?country WHERE {
  wd:Q5680 wdt:P131 ?admin .
  ?admin wdt:P17 ?country .
}
```