PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?birthPlaceLabel WHERE {
  wd:Q79904 wdt:P19 ?birthPlace .
  ?birthPlace rdfs:label ?birthPlaceLabel
  FILTER ( LANG( ?birthPlaceLabel ) = 'en' )
}

Using entities:
- J. D. Salinger (wd:Q79904), also known as Jerome David Salinger, Jerome Salinger: has occupation writer / has occupation novelist / is instance of human / American author (1919–2010)

Using properties:
- place of birth (wd:P19 as wdt), also known as birth city, birth location, birth place, birthplace, born, etc.: is subproperty of location / most specific known birth location of a person, animal or fictional character / most specific known (e.g. city instead of country, or ... birth location of a person, animal or fictional character / most specific known (e.g. city instead of country, or ... birth location of a person, animal or fictional character

Got 1 row and 1 column:
| birthPlaceLabel         |
| ----------------------- |
| New York City (lang:en) |

Answer:
The author of *The Catcher in the Rye*, J.D. Salinger, was born in New York City.

Here is the final SPARQL query that retrieves this information:

```sparql
SELECT ?birthPlaceLabel WHERE {
  wd:Q79904 wdt:P19 ?birthPlace .
  ?birthPlace rdfs:label ?birthPlaceLabel FILTER(LANG(?birthPlaceLabel) = 'en')
}
```

This query finds J.D. Salinger (Q79904), retrieves his place of birth, and gets the English label for that location.

answer(kg="wikidata", sparql="SELECT ?birthPlaceLabel WHERE { wd:Q79904 wdt:P19 ?birthPlace . ?birthPlace rdfs:label ?birthPlaceLabel FILTER(LANG(?birthPlaceLabel) = 'en') }", answer="J.D. Salinger, the author of The Catcher in the Rye, was born in New York City.")

The author of *The Catcher in the Rye*, J.D. Salinger, was born in New York City.

Here is the final SPARQL query that retrieves this information:

```sparql
SELECT ?birthPlaceLabel WHERE {
  wd:Q79904 wdt:P19 ?birthPlace .
  ?birthPlace rdfs:label ?birthPlaceLabel FILTER(LANG(?birthPlaceLabel) = 'en')
}
```

This query finds J.D. Salinger (Q79904), retrieves his place of birth, and gets the English label for that location.

answer(kg="wikidata", sparql="SELECT ?birthPlaceLabel WHERE { wd:Q79904 wdt:P19 ?birthPlace . ?birthPlace rdfs:label ?birthPlaceLabel FILTER(LANG(?birthPlaceLabel) = 'en') }", answer="J.D. Salinger, the author of The Catcher in the Rye, was born in New York City.")

SPARQL query over wikidata:
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?birthPlaceLabel WHERE {
  wd:Q79904 wdt:P19 ?birthPlace .
  ?birthPlace rdfs:label ?birthPlaceLabel
  FILTER ( LANG( ?birthPlaceLabel ) = 'en' )
}

Using entities:
- J. D. Salinger (wd:Q79904), also known as Jerome David Salinger, Jerome Salinger: has occupation writer / has occupation novelist / is instance of human / American author (1919–2010)

Using properties:
- place of birth (wd:P19 as wdt), also known as birth city, birth location, birth place, birthplace, born, etc.: is subproperty of location / most specific known birth location of a person, animal or fictional character / most specific known (e.g. city instead of country, or ... birth location of a person, animal or fictional character / most specific known (e.g. city instead of country, or ... birth location of a person, animal or fictional character

Execution result:
Got 1 row and 1 column:
| birthPlaceLabel         |
| ----------------------- |
| New York City (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 https://qlever.dev/api/wikidata 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. For 'main business' prefer more specific occupation items (e.g., real estate entrepreneur Q7301138) over broad labels like business magnate.
  - Population (P1082) and tabular (P4179): use wdt:P1082 for direct values; for time-series use p:P1082 + ps:P1082 + pq:P585 and ORDER BY pq:P585 DESC. Inspect qualifiers (e.g., 'applies to part') and references (pr:P854) to detect scope. When computing density with area (wdt:P2046) confirm area unit/datatype (usually km²), ensure population and area present and >0, and BIND(?population/?area AS ?density).
  - Spouse nationality: do not rely only on P27. Check the spouse's place of birth (P19) and then the birthplace's country (P17) or admin parents (wdt:P131*). Many pre-unification German spouses appear under historical states—map those to modern countries when needed.
  - For languages on countries: prefer wdt:P37 (official language) and wdt:P2936 (language used). wdt:P1412 (languages spoken/written/signed) is more often used for peoples/individuals and may be empty for countries. Try P37 and P2936 first, then fall back to P1412/P407. Fetch English labels with rdfs:label + FILTER(LANG(?l)='en').
  - When filtering by date of birth (P569) use xsd:dateTime comparisons (e.g. >= "1900-01-01T00:00:00Z"^^xsd:dateTime). Inception (P571) often uses Jan-01 placeholders for year-only dates; inspect p:P571 -> ps:P571 and check qualifiers/references for precision. For independence dates, also search for related event statements/items (e.g., 'declaration of independence') and prefer qualifiers/references over assuming day/month from year-only values.
  - 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.
  - 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: use p:P1082 ?stmt . ?stmt ps:P1082 ?pop . OPTIONAL { ?stmt pq:P585 ?date } . To get the most recent value prefer a subquery to compute MAX(?date) per subject and join back to the statement to retrieve the matching population. Avoid HAVING(MAX(?date)=?date) — QLever can error. Inspect qualifiers/references for scope (city-proper vs metro).
  - wdt:P131* can be expensive and may be incomplete. First try direct wdt:P131 for immediate administrative parent(s). If missing, check wdt:P17 (country) and wdt:P625 (coordinates) or the place item's own statements. Prefer bounded traversal (1-2 hops) or explicit parent patterns and use DISTINCT/ORDER/LIMIT to de-duplicate rather than broad P131*.
  - Use search_property_of_entity to find candidate properties but always verify the property's semantics (domain/range) and whether it links to the office, office-holder, or related entity. Test with a small query before relying on results. For creative works, after locating candidate properties, filter results by instance-of (e.g., films wd:Q11424; board games wd:Q131436) to avoid non-work items.
  - Use search_property_of_entity to find relevant properties. Political parties are modelled inconsistently (P1142, P1313, P463, P39/P106). Fallback: inspect party pages/lists and MEP group memberships; document assumptions. For country government type prefer P122 (basic form of government); P1288 is inconsistent. To exclude historical states filter NOT EXISTS { ?item wdt:P576 ?d }.
  - 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.
  - Place of burial (P119): use wdt:P119 to get the direct burial place. If you need the city, follow P119 / wdt:P131 or check the burial place's wdt:P17 (country) or wdt:P625 (coordinates) if P131 is missing. Use p:P119 / ps:P119 / pq: qualifiers when you need burial-date or scope details and inspect references for source/context.
  - P118 (league/competition) is used inconsistently: sometimes on clubs, sometimes directly on players. When finding clubs use ?club wdt:P118 wd:Q... and verify ?club wdt:P31 wd:Q483394. If P118 returns players, filter by ?item wdt:P31 wd:Q5 to detect humans and avoid false positives. To get current players prefer club→p:P54 statements: ?player p:P54 ?stmt; ?stmt ps:P54 ?club. OPTIONAL{ ?stmt pq:P582 ?end } FILTER(!BOUND(?end)). Verify qualifiers/references and DOBs for plausibility.
  - Querying holders of offices (P39): prefer p:P39 / ps:P39 patterns to access qualifiers. To find current holder use: ?person p:P39 ?stmt. ?stmt ps:P39 wd:Q... . OPTIONAL{ ?stmt pq:P582 ?end } FILTER(!BOUND(?end)). Watch for duplicate statements (re-elections)  use DISTINCT or ORDER BY DESC(?start) LIMIT 1 on pq:P580. Avoid HAVING(MAX(...)=...) on QLever; prefer subqueries with ORDER/LIMIT.
  - Headquarters: use wdt:P159 for org HQs. If P159 gives a building follow that building's wdt:P131* (bounded hops). If P159 points to a place, verify its wdt:P31. Don't rely only on P17 for org-country—also check P159 and P276. Use UNION/nested patterns to cover ?org wdt:P17 wd:Q... OR ?org wdt:P159|wdt:P276 ?place . ?place wdt:P17 wd:Q... or ?place wdt:P131* wd:Q...

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. If a query using SERVICE fails (e.g., HTTP 301 redirect), switch to rdfs:label + FILTER(LANG(...)) and/or schema:name. Language items (e.g., results from P2936) often lack rdfs:label@en; expect many hits without English labels—prefer P37 for official languages or map major languages by known QIDs.
- Practical query patterns: use rdfs:label + FILTER(LANG(...)) for labels. Use wdt:Pxxx for direct values; p:Pxxx/ps:Pxxx/pq:Pxxx for qualifiers. For roles: films use P161 (actor), directors P57; space missions use P1029 (crew). Query reverse and filter by instance-of film (wd:Q11424) or human (wd:Q5). For 'city' classification prefer ?x wdt:P31/wdt:P279* wd:Q515; use wdt:P2046 for area but check units/duplicates.
- When selecting latest qualifier-dated values (e.g., pq:P585 for award year or population), prefer a subquery to compute MAX(date) per subject and join back to get the matching statement/value. Avoid HAVING(MAX(?date)=?date) patterns on QLever (can cause engine errors). Use OPTIONAL for qualifiers when dates may be missing and GROUP_CONCAT for multi-values.
- Use search_entity to resolve names and verify instance-of (e.g., wdt:P31=wd:Q5). Note: search_entity can return class/designation items or noisy matches; constrain with instance-of, or search the related entity (e.g., country) and query its members. Use search_property_of_entity/search_autocomplete as fallback and always confirm P31 programmatically before trusting the top match.
- 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.
- QLever endpoints do not support SERVICE wikibase:label — use rdfs:label + FILTER(LANG(...))='en'. Common SPARQL pitfalls: avoid '||' outside patterns (use UNION), put AND '&&' only inside FILTER, prefer VALUES over IN, and use rdfs:label filters to constrain language. When testing existence prefer FILTER EXISTS { ... } or OPTIONAL { ?s wdt:Pxx ?v . FILTER(?v = wd:Q...) } — writing OPTIONAL { ?s wdt:Pxx wd:Q... } creates no ?v for BOUND(?v). When execute() fails, simplify the query and test with list(...).
- 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. Also verify ambiguous item QIDs (e.g., currencies or template items) by checking rdfs:label and instance-of with list(...) before use.
- 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"). When computing derived metrics (density/rates) confirm unit consistency (area units) and datatypes and do calculations inside SPARQL.
- 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; 'cause of death' -> P509; 'manner of death' -> P1196). 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 the author of The Catcher in the Rye born ?

[Assistant]
To determine where the author of *The Catcher in the Rye* was born, I need to follow these steps:

1. Identify the author of *The Catcher in the Rye*.
   - The author is J.D. Salinger.

2. Find the birthplace of J.D. Salinger.
   - This requires locating J.D. Salinger in Wikidata and retrieving his place of birth (property P19).

3. Retrieve the birthplace's label in English for clarity.

Let me begin by searching for J.D. Salinger in Wikidata.

Question: J.D. Salinger

Top 10 entity alternatives:
1. Salinger, J.D (1919-2010), author (wd:Q103878222): is instance of encyclopaedic article / is instance of encyclopedia article / encyclopedia article
2. Nine Gestures for J.D. Salinger (wd:Q132199697): creative work by Mikhail Mansion / is instance of creative work / is instance of application / is instance of exhibit
3. Novelist J.D. Salinger dies aged 91 (wd:Q17694125): is instance of Wikinews article / Wikinews article / Wikinews article / Wikinews article
4. J. D. Salinger (wd:Q79904, matched via Jerome Salinger), also known as Jerome David Salinger, Jerome Salinger: American author (1919–2010) / has occupation novelist / has occupation writer / is instance of human
5. JD Vance (wd:Q28935729, matched via J.D. Vance), also known as James David Hamel, James David Vance, James Donald Bowman, J. D. Hamel, J. D. Vance, etc.: Vice President of the United States since 2025 and accumulates the functions of President of the United States Senate / vice president of the United States since 2025 / has occupation corporate lawyer / has occupation philosopher / has occupation Philosopher / has occupation politician / has occupation financier / has occupation ideologue / has occupation merchant / has occupation writer / has occupation pundit / has occupation skier / is instance of human
6. Joseph Dalton Hooker (wd:Q157501, matched via J.D. Hooker), also known as Hook.f., J.D. Hooker, Joseph Hooker, Sir Hooker, Sir Joseph Dalton Hooker, etc.: British botanist, lichenologist, and surgeon (1817–1911) / has occupation pteridologist / has occupation bryologist / has occupation mycologist / has occupation explorer / has occupation botanist / has occupation surgeon / has occupation writer / is instance of human
7. James Dwight Dana (wd:Q315366, matched via J.D. Dana), also known as James Dana, James D Dana, James D. Dana, J D Dana, J. D. Dana, etc.: American mineralogist, scientist and zoologist (1813-1895) / has occupation scientific illustrator / has occupation university teacher / has occupation carcinologist / has occupation mineralogist / has occupation geologist / has occupation zoologist / has occupation botanist / has occupation explorer / is instance of human
8. Joshua Angrist (wd:Q921499, matched via J.D. Angrist), also known as Angrist, Angrist J, Angrist J., Angrist J D, Angrist J. D., etc.: has occupation university teacher / has occupation econometrician / Israeli-American economist / has occupation economist / has occupation Economist / is instance of human
9. Jan Gossaert (wd:Q346952, matched via J.D. Mabuge), also known as gen. mabuse gossaert jan, gen. Mabuse Jan Gossaert, gen. mabuse jan gossart, Gossaert, gossart jan gen. mabuse, etc.: Flemish painter (1478–1532) / has occupation painter / is instance of human
10. Jan Davidsz. de Heem (wd:Q454656, matched via J.D. Deheem), also known as B. Heem, david de heem, David de Heym, Davidsz de Heem, de Heame, etc.: has occupation botanical illustrator / Dutch-Flemish painter (1606–1684) / has occupation painter / is instance of human

[Assistant]
The correct entity for J.D. Salinger is **Q79904** (J. D. Salinger), identified as an American author. Now I will retrieve his place of birth using the property `wdt:P19` (place of birth).

execute

SELECT ?birthPlace WHERE { wd:Q79904 wdt:P19 ?birthPlace }

Got 1 row and 1 column:
| birthPlace             |
| ---------------------- |
| New York City (wd:Q60) |

[Assistant]
J.D. Salinger was born in New York City. Now, I will retrieve the English label for "New York City" (Q60) to provide a clear answer.

SELECT ?label WHERE { wd:Q60 rdfs:label ?label FILTER(LANG(?label) = 'en') }

Got 1 row and 1 column:
| label                   |
| ----------------------- |
| New York City (lang:en) |

[Assistant]
The author of *The Catcher in the Rye*, J.D. Salinger, was born in New York City.

Here is the final SPARQL query that retrieves this information:

```sparql
SELECT ?birthPlaceLabel WHERE {
  wd:Q79904 wdt:P19 ?birthPlace .
  ?birthPlace rdfs:label ?birthPlaceLabel FILTER(LANG(?birthPlaceLabel) = 'en')
}
```

This query finds J.D. Salinger (Q79904), retrieves his place of birth, and gets the English label for that location.

answer(kg="wikidata", sparql="SELECT ?birthPlaceLabel WHERE { wd:Q79904 wdt:P19 ?birthPlace . ?birthPlace rdfs:label ?birthPlaceLabel FILTER(LANG(?birthPlaceLabel) = 'en') }", answer="J.D. Salinger, the author of The Catcher in the Rye, was born in New York City.")


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?dissolutionDate WHERE {
  wd:Q213849 wdt:P576 ?dissolutionDate
}

Using entities:
- ATI Technologies (wd:Q213849), also known as Array Technologies Incorporated: is instance of technology company / is instance of business / is instance of defunct organisation / is instance of defunct organization / is instance of enterprise / Canadian technology corporation

Using properties:
- dissolved, abolished or demolished date (wd:P576 as wdt), also known as abolished, abolishment date, ceased date, ceased on, ceased publication, etc.: is subproperty of end time / date or point in time on which the organisation was dissolved/disappeared or the building demolished / point in time at which the subject (organisation, building) ... equipment, "discontinued date" (P2669) for stopping a product

Answer: No, the ATI Company (ATI Technologies) no longer exists. It was dissolved on January 1, 2011, after being acquired by AMD in 2006.

No, the ATI Company (ATI Technologies) no longer exists. It was dissolved on January 1, 2011, after being acquired by AMD in 2006.

SPARQL query over wikidata:
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?dissolutionDate WHERE {
  wd:Q213849 wdt:P576 ?dissolutionDate
}

Using entities:
- ATI Technologies (wd:Q213849), also known as Array Technologies Incorporated: is instance of technology company / is instance of business / is instance of defunct organisation / is instance of defunct organization / is instance of enterprise / Canadian technology corporation

Using properties:
- dissolved, abolished or demolished date (wd:P576 as wdt), also known as abolished, abolishment date, ceased date, ceased on, ceased publication, etc.: is subproperty of end time / date or point in time on which the organisation was dissolved/disappeared or the building demolished / point in time at which the subject (organisation, building) ... equipment, "discontinued date" (P2669) for stopping a product

Execution result:
Got 1 row and 1 column:
| dissolutionDate                     |
| ----------------------------------- |
| 2011-01-01T00:00:00Z (xsd:dateTime) |

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

You should follow a step-by-step approach to generate the SPARQL query:
1. Determine possible entities and properties implied by the user question.
2. Search for the entities and properties in the knowledge graphs. Where applicable, constrain the searches with already identified entities and properties.
3. Gradually build up the SPARQL query using the identified entities and properties. Start with simple queries and add more complexity as needed. Execute intermediate queries to get feedback and to verify your assumptions. You may need to refine or rethink your current plan based on the query results and go back to step 2 if needed, possibly multiple times.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

Available knowledge graphs:
- wikidata at https://qlever.dev/api/wikidata 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. For 'main business' prefer more specific occupation items (e.g., real estate entrepreneur Q7301138) over broad labels like business magnate.
  - Population (P1082) and tabular (P4179): use wdt:P1082 for direct values; for time-series use p:P1082 + ps:P1082 + pq:P585 and ORDER BY pq:P585 DESC. Inspect qualifiers (e.g., 'applies to part') and references (pr:P854) to detect scope. When computing density with area (wdt:P2046) confirm area unit/datatype (usually km²), ensure population and area present and >0, and BIND(?population/?area AS ?density).
  - Spouse nationality: do not rely only on P27. Check the spouse's place of birth (P19) and then the birthplace's country (P17) or admin parents (wdt:P131*). Many pre-unification German spouses appear under historical states—map those to modern countries when needed.
  - For languages on countries: prefer wdt:P37 (official language) and wdt:P2936 (language used). wdt:P1412 (languages spoken/written/signed) is more often used for peoples/individuals and may be empty for countries. Try P37 and P2936 first, then fall back to P1412/P407. Fetch English labels with rdfs:label + FILTER(LANG(?l)='en').
  - When filtering by date of birth (P569) use xsd:dateTime comparisons (e.g. >= "1900-01-01T00:00:00Z"^^xsd:dateTime). Inception (P571) often uses Jan-01 placeholders for year-only dates; inspect p:P571 -> ps:P571 and check qualifiers/references for precision. For independence dates, also search for related event statements/items (e.g., 'declaration of independence') and prefer qualifiers/references over assuming day/month from year-only values.
  - 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.
  - 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: use p:P1082 ?stmt . ?stmt ps:P1082 ?pop . OPTIONAL { ?stmt pq:P585 ?date } . To get the most recent value prefer a subquery to compute MAX(?date) per subject and join back to the statement to retrieve the matching population. Avoid HAVING(MAX(?date)=?date) — QLever can error. Inspect qualifiers/references for scope (city-proper vs metro).
  - wdt:P131* can be expensive and may be incomplete. First try direct wdt:P131 for immediate administrative parent(s). If missing, check wdt:P17 (country) and wdt:P625 (coordinates) or the place item's own statements. Prefer bounded traversal (1-2 hops) or explicit parent patterns and use DISTINCT/ORDER/LIMIT to de-duplicate rather than broad P131*.
  - Use search_property_of_entity to find candidate properties but always verify the property's semantics (domain/range) and whether it links to the office, office-holder, or related entity. Test with a small query before relying on results. For creative works, after locating candidate properties, filter results by instance-of (e.g., films wd:Q11424; board games wd:Q131436) to avoid non-work items.
  - Use search_property_of_entity to find relevant properties. Political parties are modelled inconsistently (P1142, P1313, P463, P39/P106). Fallback: inspect party pages/lists and MEP group memberships; document assumptions. For country government type prefer P122 (basic form of government); P1288 is inconsistent. To exclude historical states filter NOT EXISTS { ?item wdt:P576 ?d }.
  - 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.
  - Place of burial (P119): use wdt:P119 to get the direct burial place. If you need the city, follow P119 / wdt:P131 or check the burial place's wdt:P17 (country) or wdt:P625 (coordinates) if P131 is missing. Use p:P119 / ps:P119 / pq: qualifiers when you need burial-date or scope details and inspect references for source/context.
  - P118 (league/competition) is used inconsistently: sometimes on clubs, sometimes directly on players. When finding clubs use ?club wdt:P118 wd:Q... and verify ?club wdt:P31 wd:Q483394. If P118 returns players, filter by ?item wdt:P31 wd:Q5 to detect humans and avoid false positives. To get current players prefer club→p:P54 statements: ?player p:P54 ?stmt; ?stmt ps:P54 ?club. OPTIONAL{ ?stmt pq:P582 ?end } FILTER(!BOUND(?end)). Verify qualifiers/references and DOBs for plausibility.
  - Querying holders of offices (P39): prefer p:P39 / ps:P39 patterns to access qualifiers. To find current holder use: ?person p:P39 ?stmt. ?stmt ps:P39 wd:Q... . OPTIONAL{ ?stmt pq:P582 ?end } FILTER(!BOUND(?end)). Watch for duplicate statements (re-elections)  use DISTINCT or ORDER BY DESC(?start) LIMIT 1 on pq:P580. Avoid HAVING(MAX(...)=...) on QLever; prefer subqueries with ORDER/LIMIT.
  - Headquarters: use wdt:P159 for org HQs. If P159 gives a building follow that building's wdt:P131* (bounded hops). If P159 points to a place, verify its wdt:P31. Don't rely only on P17 for org-country—also check P159 and P276. Use UNION/nested patterns to cover ?org wdt:P17 wd:Q... OR ?org wdt:P159|wdt:P276 ?place . ?place wdt:P17 wd:Q... or ?place wdt:P131* wd:Q...

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. If a query using SERVICE fails (e.g., HTTP 301 redirect), switch to rdfs:label + FILTER(LANG(...)) and/or schema:name. Language items (e.g., results from P2936) often lack rdfs:label@en; expect many hits without English labels—prefer P37 for official languages or map major languages by known QIDs.
- Practical query patterns: use rdfs:label + FILTER(LANG(...)) for labels. Use wdt:Pxxx for direct values; p:Pxxx/ps:Pxxx/pq:Pxxx for qualifiers. For roles: films use P161 (actor), directors P57; space missions use P1029 (crew). Query reverse and filter by instance-of film (wd:Q11424) or human (wd:Q5). For 'city' classification prefer ?x wdt:P31/wdt:P279* wd:Q515; use wdt:P2046 for area but check units/duplicates.
- When selecting latest qualifier-dated values (e.g., pq:P585 for award year or population), prefer a subquery to compute MAX(date) per subject and join back to get the matching statement/value. Avoid HAVING(MAX(?date)=?date) patterns on QLever (can cause engine errors). Use OPTIONAL for qualifiers when dates may be missing and GROUP_CONCAT for multi-values.
- Use search_entity to resolve names and verify instance-of (e.g., wdt:P31=wd:Q5). Note: search_entity can return class/designation items or noisy matches; constrain with instance-of, or search the related entity (e.g., country) and query its members. Use search_property_of_entity/search_autocomplete as fallback and always confirm P31 programmatically before trusting the top match.
- 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.
- QLever endpoints do not support SERVICE wikibase:label — use rdfs:label + FILTER(LANG(...))='en'. Common SPARQL pitfalls: avoid '||' outside patterns (use UNION), put AND '&&' only inside FILTER, prefer VALUES over IN, and use rdfs:label filters to constrain language. When testing existence prefer FILTER EXISTS { ... } or OPTIONAL { ?s wdt:Pxx ?v . FILTER(?v = wd:Q...) } — writing OPTIONAL { ?s wdt:Pxx wd:Q... } creates no ?v for BOUND(?v). When execute() fails, simplify the query and test with list(...).
- 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. Also verify ambiguous item QIDs (e.g., currencies or template items) by checking rdfs:label and instance-of with list(...) before use.
- 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"). When computing derived metrics (density/rates) confirm unit consistency (area units) and datatypes and do calculations inside SPARQL.
- 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; 'cause of death' -> P509; 'manner of death' -> P1196). 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] Does the ATI Company still exist?

[Assistant]
To determine whether the ATI Company still exists, I need to find information about the company and check if it has been dissolved or acquired. The ATI Company likely refers to Advanced Micro Devices, Inc. (AMD) subsidiary ATI Technologies, which was acquired by AMD in 2006.

Let me first search for the entity "ATI Company" to confirm its Wikidata identifier.

Question: ATI Company

Top 10 entity alternatives:
1. Atiki Ally Atiki (wd:Q118959000, matched via Atiki Atiki), also known as Atiki Ally, Atiki Atiki: Tanzanian professional basketball player / has occupation basketball player / is instance of human
2. Atiqullah Atifmal (wd:Q19271885): has occupation politician / is instance of human / Afghan politician / Afghan politician / Afghan politician
3. Atiyah, Atiya (wd:Q116366131): is instance of female given name / female given name / female given name / female given name
4. Atikah, Atika (wd:Q116366130): is instance of female given name / female given name / female given name / female given name
5. Atifah, Atifa (wd:Q116366128): is instance of female given name / female given name / female given name / female given name
6. Atif, Atif (wd:Q116364288): is instance of male given name / male given name / male given name / male given name
7. Atinga atinga (wd:Q61885138): is instance of taxon / species of fish
8. Atılım Atılgan (wd:Q90557612): researcher (ORCID 0000-0003-2944-6404) / has occupation researcher / is instance of human
9. Nintendo (wd:Q8093, matched via Nintendo Company), also known as Big N, Nintendō, Nintendo Co., Nintendo Co., Ltd., Nintendo Company, etc.: Japanese multinational video game and consumer electronics company / is instance of video game publisher / is instance of software company / is instance of public company
10. Adidas AG (wd:Q3895, matched via Adidas company), also known as adidas, Adidas company: German multinational corporation / German multinational corporation / is instance of public company / is instance of business

[Assistant]
The search results for "ATI Company" did not return the expected entity for ATI Technologies. Instead, I see unrelated names and other companies like Nintendo and Adidas. This suggests that "ATI Company" may not be directly indexed under that exact name in Wikidata.

Let me try searching for "ATI Technologies" since that is the full name of the company commonly referred to as ATI.

Question: ATI Technologies

Top 10 entity alternatives:
1. ATI Technologies (wd:Q213849), also known as Array Technologies Incorporated: is instance of defunct organisation / is instance of defunct organization / is instance of technology company / Canadian technology corporation / is instance of enterprise / is instance of business
2. Atipa Technologies (wd:Q67904906): American hardware manufacturer / is instance of business
3. Atiki Ally Atiki (wd:Q118959000, matched via Atiki Atiki), also known as Atiki Ally, Atiki Atiki: Tanzanian professional basketball player / has occupation basketball player / is instance of human
4. Atiqullah Atifmal (wd:Q19271885): has occupation politician / is instance of human / Afghan politician / Afghan politician / Afghan politician
5. Atiyah, Atiya (wd:Q116366131): is instance of female given name / female given name / female given name / female given name
6. Atikah, Atika (wd:Q116366130): is instance of female given name / female given name / female given name / female given name
7. Atifah, Atifa (wd:Q116366128): is instance of female given name / female given name / female given name / female given name
8. Atif, Atif (wd:Q116364288): is instance of male given name / male given name / male given name / male given name
9. Atinga atinga (wd:Q61885138): is instance of taxon / species of fish
10. Atılım Atılgan (wd:Q90557612): researcher (ORCID 0000-0003-2944-6404) / has occupation researcher / is instance of human

[Assistant]
I found the correct entity: ATI Technologies (wd:Q213849). The entity is labeled as a "defunct organisation" and "defunct organization," which indicates that it no longer exists as an independent company.

To confirm this, I will check the entity's details to verify its status and acquisition history. Specifically, I will look for properties that indicate its dissolution or acquisition, such as the date it was dissolved (P576) or if it was acquired by another company (P137).

list

wd:Q213849

Got 314 rows and 3 columns, showing the first 10 rows below:
| subject                       | property                    | object                                                                                |
| ----------------------------- | --------------------------- | ------------------------------------------------------------------------------------- |
| ATI Technologies (wd:Q213849) | instance of (wdt:P31)       | business (wd:Q4830453)                                                                |
| ATI Technologies (wd:Q213849) | country (wdt:P17)           | Canada (wd:Q16)                                                                       |
| ATI Technologies (wd:Q213849) | Commons category (wdt:P373) | ATI Technologies                                                                      |
| ATI Technologies (wd:Q213849) | image (wdt:P18)             | <http://commons.wikimedia.org/wiki/Special:FilePath/Atitechnologiessiliconvalley.jpg> |
| ATI Technologies (wd:Q213849) | Freebase ID (wdt:P646)      | /m/01824j                                                                             |
| ATI Technologies (wd:Q213849) | inception (wdt:P571)        | 1985-08-01T00:00:00Z (xsd:dateTime)                                                   |
| ATI Technologies (wd:Q213849) | official name (wdt:P1448)   | ATI Technologies Inc. (lang:en)                                                       |
| ATI Technologies (wd:Q213849) | official website (wdt:P856) | <http://www.ati.com/>                                                                 |
| ATI Technologies (wd:Q213849) | followed by (wdt:P156)      | AMD (wd:Q128896)                                                                      |
| ATI Technologies (wd:Q213849) | different from (wdt:P1889)  | ATI Systems (wd:Q76809554)                                                            |
| ...                           | ...                         | ...                                                                                |

[Assistant]
From the list of triples, I can see that ATI Technologies (wd:Q213849) has the following relevant properties:

- **P156 (followed by)**: AMD (wd:Q128896) — This indicates that ATI Technologies was succeeded by AMD, which is consistent with AMD's acquisition of ATI in 2006.
- **P576 (dissolved or abolished)**: Not present in the first 10 rows, but since it is labeled as a "defunct organisation," it is likely dissolved.
- **P571 (inception)**: 1985 — The company was founded in 1985.
- **P17 (country)**: Canada — The company was based in Canada.

To confirm that ATI Technologies no longer exists as an independent entity, I will check if it has a dissolution date (P576) or if it was acquired by AMD (P137 — acquired by). I will also check if AMD has any statement indicating the acquisition of ATI.

Question: dissolved

Top 10 property alternatives:
1. dissolved, abolished or demolished date (wd:P576 as p/wdt, matched via dissolved), also known as abolished, abolishment date, ceased date, ceased on, ceased publication, etc.: point in time at which the subject (organisation, building) ... equipment, "discontinued date" (P2669) for stopping a product / date or point in time on which the organisation was dissolved/disappeared or the building demolished / is subproperty of end time
2. different from (wd:P1889 as p/wdt, matched via not), also known as confused with, differs from, disambiguated from, distinct from, distinguished from, etc.: item that is different from another item, with which it is often confused / item that is different from another item, with which it may be confused
3. inception (wd:P571 as p/wdt, matched via formation), also known as broke ground, built, commenced on date, commencement date, completed, etc.: time when an entity begins to exist; for date of official opening use P1619 / time when an entity begins to exist; for date of official opening use P1619 / date or point in time when the organisation / object was founded / created / is subproperty of start time
4. followed by (wd:P156 as p/wdt, matched via then), also known as comes before, continued as, next, next element, next is, etc.: immediately following item in a series of which the subject ... replaced, e.g. political offices, use "replaced by" (P1366)] / immediately following item in a series of which the subject ... replaced, e.g. political offices, use "replaced by" (P1366)] / immediately following item in a series of which the subject ... replaced, e.g. political offices, use "replaced by" (P1366)]
5. replaced by (wd:P1366 as p/wdt, matched via becomes), also known as becomes, continued by, heir, mediatised to, next job holder, etc.: other person or item which continues the item by replacing it ... identical, but adds to the series (e.g. books in a series). / person or state or item who replaces another in an office, ... by) if the item is not replaced, e.g. books in a series / is subproperty of followed by
6. parent organization (wd:P749 as p/wdt, matched via holding), also known as chapter of, has organizational parent, holding, holding company, owned by (company or organisation), etc.: parent organization or unit of an organization or unit, ... organization (Q43229) and organization unit (Q10387680) / is subproperty of owned by / is subproperty of part of
7. image (wd:P18 as p/wdt, matched via still), also known as camera picture, Commons image, drawing, File:, graph, etc.: image of relevant illustration of the subject; if available, ... only images which exist on Wikimedia Commons are acceptable / image of relevant illustration of the subject; if available, ... only images which exist on Wikimedia Commons are acceptable / image of relevant illustration of the subject; if available, ... map, flag image, signature image, logo image, collage image) / image of relevant illustration of the subject; if available, ... map, flag image, signature image, logo image, collage image)
8. country (wd:P17 as p/wdt, matched via state), also known as host country, land, sovereign state, state, P17: sovereign state that this item is in (not to be used for human beings) / sovereign state that this item is in (not to be used for human beings) / sovereign state that this item is in (not to be used for human beings) / sovereign state that this item is in (not to be used for human beings) / is subproperty of located in the administrative territorial entity
9. instance of (wd:P31 as p/wdt, matched via is a), also known as example of, has type, is a, is an, is of type, etc.: that class of which this subject is a particular example and ... a subclass of mountain (and an instance of volcanic landform) / type to which this subject corresponds/belongs. Different ... instance of mountain; volcanoes form a subclass of mountains / type to which this subject corresponds/belongs. Different ... is an instance of mountain; volcano is a subclass of mountain
10. total revenue (wd:P2139 as p/wdt, matched via turnover), also known as gross revenue, income, net sales, revenue, sales, etc.: income gained by an organization during a given time frame. Not to be confused with fiscal revenue

No other items found

[Assistant]
I see that the property "dissolved, abolished or demolished date" (P576) is available. Let me check if ATI Technologies has a dissolution date.

wd:Q213849

[Assistant]
I now have confirmed that ATI Technologies (wd:Q213849) has a dissolution date of January 1, 2011 (P576). This confirms that the company no longer exists as an independent entity.

Additionally, I observed that it was followed by AMD (wd:Q128896), which is consistent with AMD's acquisition of ATI in 2006. The dissolution date of 2011 likely marks the formal end of the ATI brand or legal entity after integration into AMD.

Thus, the answer to the question "Does the ATI Company still exist?" is **no**, because it was dissolved on January 1, 2011.

I will now provide the final SPARQL query and answer.

answer

SELECT ?dissolutionDate WHERE { wd:Q213849 wdt:P576 ?dissolutionDate }

Answer: No, the ATI Company (ATI Technologies) no longer exists. It was dissolved on January 1, 2011, after being acquired by AMD in 2006.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?instrument ?instrumentLabel WHERE {
  wd:Q1779 wdt:P1303 ?instrument .
  ?instrument rdfs:label ?instrumentLabel .
  FILTER ( LANG( ?instrumentLabel ) = "en" ) .
}

Using entities:
- Louis Armstrong (wd:Q1779), also known as Dipper, Louis Daniel Armstrong, Pops, Satch, Satchelmouth, etc.: has occupation radio personality / has occupation bandleader / has occupation songwriter / has occupation recording artist / has occupation writer / has occupation actor / has occupation street artist / has occupation film actor / has occupation singer / has occupation jazz musician / has occupation conductor / has occupation film score composer / has occupation orchestra leader / has occupation trumpeter / is instance of human / American jazz musician, trumpeter and singer (1901–1971)

Using properties:
- instrument (wd:P1303 as wdt), also known as instrument played, instrument(s), instruments, instrument taught, musical instrument, etc.: is subproperty of uses / musical instrument that a person plays or teaches or used in a music occupation

Got 3 rows and 2 columns:
| instrument           | instrumentLabel   |
| -------------------- | ----------------- |
| voice (wd:Q17172850) | voice (lang:en)   |
| cornet (wd:Q202027)  | cornet (lang:en)  |
| trumpet (wd:Q8338)   | trumpet (lang:en) |

Answer: Louis Armstrong played the trumpet, cornet, and voice.

Louis Armstrong played the trumpet, cornet, and voice.

SPARQL query over wikidata:
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?instrument ?instrumentLabel WHERE {
  wd:Q1779 wdt:P1303 ?instrument .
  ?instrument rdfs:label ?instrumentLabel .
  FILTER ( LANG( ?instrumentLabel ) = "en" ) .
}

Using entities:
- Louis Armstrong (wd:Q1779), also known as Dipper, Louis Daniel Armstrong, Pops, Satch, Satchelmouth, etc.: has occupation radio personality / has occupation bandleader / has occupation songwriter / has occupation recording artist / has occupation writer / has occupation actor / has occupation street artist / has occupation film actor / has occupation singer / has occupation jazz musician / has occupation conductor / has occupation film score composer / has occupation orchestra leader / has occupation trumpeter / is instance of human / American jazz musician, trumpeter and singer (1901–1971)

Using properties:
- instrument (wd:P1303 as wdt), also known as instrument played, instrument(s), instruments, instrument taught, musical instrument, etc.: is subproperty of uses / musical instrument that a person plays or teaches or used in a music occupation

Execution result:
Got 3 rows and 2 columns:
| instrument           | instrumentLabel   |
| -------------------- | ----------------- |
| voice (wd:Q17172850) | voice (lang:en)   |
| cornet (wd:Q202027)  | cornet (lang:en)  |
| trumpet (wd:Q8338)   | trumpet (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 https://qlever.dev/api/wikidata 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. For 'main business' prefer more specific occupation items (e.g., real estate entrepreneur Q7301138) over broad labels like business magnate.
  - Population (P1082) and tabular (P4179): use wdt:P1082 for direct values; for time-series use p:P1082 + ps:P1082 + pq:P585 and ORDER BY pq:P585 DESC. Inspect qualifiers (e.g., 'applies to part') and references (pr:P854) to detect scope. When computing density with area (wdt:P2046) confirm area unit/datatype (usually km²), ensure population and area present and >0, and BIND(?population/?area AS ?density).
  - Spouse nationality: do not rely only on P27. Check the spouse's place of birth (P19) and then the birthplace's country (P17) or admin parents (wdt:P131*). Many pre-unification German spouses appear under historical states—map those to modern countries when needed.
  - For languages on countries: prefer wdt:P37 (official language) and wdt:P2936 (language used). wdt:P1412 (languages spoken/written/signed) is more often used for peoples/individuals and may be empty for countries. Try P37 and P2936 first, then fall back to P1412/P407. Fetch English labels with rdfs:label + FILTER(LANG(?l)='en').
  - When filtering by date of birth (P569) use xsd:dateTime comparisons (e.g. >= "1900-01-01T00:00:00Z"^^xsd:dateTime). Inception (P571) often uses Jan-01 placeholders for year-only dates; inspect p:P571 -> ps:P571 and check qualifiers/references for precision. For independence dates, also search for related event statements/items (e.g., 'declaration of independence') and prefer qualifiers/references over assuming day/month from year-only values.
  - 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.
  - 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: use p:P1082 ?stmt . ?stmt ps:P1082 ?pop . OPTIONAL { ?stmt pq:P585 ?date } . To get the most recent value prefer a subquery to compute MAX(?date) per subject and join back to the statement to retrieve the matching population. Avoid HAVING(MAX(?date)=?date) — QLever can error. Inspect qualifiers/references for scope (city-proper vs metro).
  - wdt:P131* can be expensive and may be incomplete. First try direct wdt:P131 for immediate administrative parent(s). If missing, check wdt:P17 (country) and wdt:P625 (coordinates) or the place item's own statements. Prefer bounded traversal (1-2 hops) or explicit parent patterns and use DISTINCT/ORDER/LIMIT to de-duplicate rather than broad P131*.
  - Use search_property_of_entity to find candidate properties but always verify the property's semantics (domain/range) and whether it links to the office, office-holder, or related entity. Test with a small query before relying on results. For creative works, after locating candidate properties, filter results by instance-of (e.g., films wd:Q11424; board games wd:Q131436) to avoid non-work items.
  - Use search_property_of_entity to find relevant properties. Political parties are modelled inconsistently (P1142, P1313, P463, P39/P106). Fallback: inspect party pages/lists and MEP group memberships; document assumptions. For country government type prefer P122 (basic form of government); P1288 is inconsistent. To exclude historical states filter NOT EXISTS { ?item wdt:P576 ?d }.
  - 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.
  - Place of burial (P119): use wdt:P119 to get the direct burial place. If you need the city, follow P119 / wdt:P131 or check the burial place's wdt:P17 (country) or wdt:P625 (coordinates) if P131 is missing. Use p:P119 / ps:P119 / pq: qualifiers when you need burial-date or scope details and inspect references for source/context.
  - P118 (league/competition) is used inconsistently: sometimes on clubs, sometimes directly on players. When finding clubs use ?club wdt:P118 wd:Q... and verify ?club wdt:P31 wd:Q483394. If P118 returns players, filter by ?item wdt:P31 wd:Q5 to detect humans and avoid false positives. To get current players prefer club→p:P54 statements: ?player p:P54 ?stmt; ?stmt ps:P54 ?club. OPTIONAL{ ?stmt pq:P582 ?end } FILTER(!BOUND(?end)). Verify qualifiers/references and DOBs for plausibility.
  - Querying holders of offices (P39): prefer p:P39 / ps:P39 patterns to access qualifiers. To find current holder use: ?person p:P39 ?stmt. ?stmt ps:P39 wd:Q... . OPTIONAL{ ?stmt pq:P582 ?end } FILTER(!BOUND(?end)). Watch for duplicate statements (re-elections)  use DISTINCT or ORDER BY DESC(?start) LIMIT 1 on pq:P580. Avoid HAVING(MAX(...)=...) on QLever; prefer subqueries with ORDER/LIMIT.
  - Headquarters: use wdt:P159 for org HQs. If P159 gives a building follow that building's wdt:P131* (bounded hops). If P159 points to a place, verify its wdt:P31. Don't rely only on P17 for org-country—also check P159 and P276. Use UNION/nested patterns to cover ?org wdt:P17 wd:Q... OR ?org wdt:P159|wdt:P276 ?place . ?place wdt:P17 wd:Q... or ?place wdt:P131* wd:Q...

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. If a query using SERVICE fails (e.g., HTTP 301 redirect), switch to rdfs:label + FILTER(LANG(...)) and/or schema:name. Language items (e.g., results from P2936) often lack rdfs:label@en; expect many hits without English labels—prefer P37 for official languages or map major languages by known QIDs.
- Practical query patterns: use rdfs:label + FILTER(LANG(...)) for labels. Use wdt:Pxxx for direct values; p:Pxxx/ps:Pxxx/pq:Pxxx for qualifiers. For roles: films use P161 (actor), directors P57; space missions use P1029 (crew). Query reverse and filter by instance-of film (wd:Q11424) or human (wd:Q5). For 'city' classification prefer ?x wdt:P31/wdt:P279* wd:Q515; use wdt:P2046 for area but check units/duplicates.
- When selecting latest qualifier-dated values (e.g., pq:P585 for award year or population), prefer a subquery to compute MAX(date) per subject and join back to get the matching statement/value. Avoid HAVING(MAX(?date)=?date) patterns on QLever (can cause engine errors). Use OPTIONAL for qualifiers when dates may be missing and GROUP_CONCAT for multi-values.
- Use search_entity to resolve names and verify instance-of (e.g., wdt:P31=wd:Q5). Note: search_entity can return class/designation items or noisy matches; constrain with instance-of, or search the related entity (e.g., country) and query its members. Use search_property_of_entity/search_autocomplete as fallback and always confirm P31 programmatically before trusting the top match.
- 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.
- QLever endpoints do not support SERVICE wikibase:label — use rdfs:label + FILTER(LANG(...))='en'. Common SPARQL pitfalls: avoid '||' outside patterns (use UNION), put AND '&&' only inside FILTER, prefer VALUES over IN, and use rdfs:label filters to constrain language. When testing existence prefer FILTER EXISTS { ... } or OPTIONAL { ?s wdt:Pxx ?v . FILTER(?v = wd:Q...) } — writing OPTIONAL { ?s wdt:Pxx wd:Q... } creates no ?v for BOUND(?v). When execute() fails, simplify the query and test with list(...).
- 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. Also verify ambiguous item QIDs (e.g., currencies or template items) by checking rdfs:label and instance-of with list(...) before use.
- 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"). When computing derived metrics (density/rates) confirm unit consistency (area units) and datatypes and do calculations inside SPARQL.
- 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; 'cause of death' -> P509; 'manner of death' -> P1196). list(...) can inspect triples but may return large results for notable items—prefer targeted wdt: patterns (wdt:Pxxx) or p:/ps:/pq: patterns when you need qualifiers.

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

Additional rules to follow:
- Explain your thought process before and after each step and function call.
- Do not just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
- Do not ask the user for clarifications without first attempting to complete the task. If the task input is incomplete or ambiguous, try to make reasonable assumptions and document them.
- Do not use "SERVICE wikibase:label { bd:serviceParam wikibase:language ..." in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.
- Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
- The SPARQL query should always return the actual identifiers / IRIs of the items in its result. It additionally may return labels or other human-readable information, but they are optional and should be put within optional clauses unless explicitly requested by the user.
- Do not stop early if there are still obvious improvements to be made to the SPARQL query. For example, keep refining your SPARQL query if its result contains irrelevant items or is missing items you expected.
- Do not perform additional computation (e.g. filtering, sorting, calculations) on the result of the SPARQL query to determine the answer. All computation should be done solely within SPARQL.
- For questions with a "True" or "False" answer the SPARQL query should be an ASK query.

[User] What instruments did Louis Armstrong play?

[Assistant]
To determine the instruments Louis Armstrong played, I will follow these steps:

1. Identify Louis Armstrong's entity in Wikidata using a search.
2. Explore his properties to find information about the instruments he played.
3. Construct a SPARQL query to retrieve the instruments associated with him.

### Step 1: Search for Louis Armstrong's entity
I will use the `search_entity` function to find Louis Armstrong's Wikidata item.

Question: louis armstrong

Top 10 entity alternatives:
1. Louis Armstrong (wd:Q1779), also known as Dipper, Louis Daniel Armstrong, Pops, Satch, Satchelmouth, etc.: American jazz musician, trumpeter and singer (1901–1971) / has occupation film score composer / has occupation radio personality / has occupation recording artist / has occupation orchestra leader / has occupation street artist / has occupation jazz musician / has occupation film actor / has occupation songwriter / has occupation bandleader / has occupation trumpeter / has occupation conductor / has occupation writer / has occupation singer / has occupation actor / is instance of human
2. Louis Armstrong (wd:Q132754304): online exhibition from Louis Armstrong House and Archives, Queens College, City University of New York / is instance of online exhibition
3. Louis Armstrong (wd:Q100721665): college basketball player (1991–1992) Northern Iowa / has occupation basketball player / is instance of human
4. Louis Armstrong (wd:Q98823980): photograph by Lisette Model (MET, 2019.33) / is instance of photograph
5. Louis Armstrong Stadium (wd:Q1029132): tennis venue in New York City from 1978 to 2016 / is instance of tennis venue
6. Louis Armstrong Park (wd:Q931042): park in New Orleans, Louisiana, U.S. / is instance of urban park
7. Louis Armstrong House (wd:Q6686652), also known as Louis Armstrong House Museum: NY location listed on National Register of Historic Places / is instance of African-American museum / is instance of historic house museum / is instance of biographical museum / is instance of music museum
8. Louise Armstrong (wd:Q6688616): has occupation human rights activist / has occupation children's writer / American writer and feminist / has occupation writer / is instance of human
9. Louis Armstrong Stadium (wd:Q47487977): tennis stadium opened in 2018, replacing a 1978 venue of the same name / is instance of tennis venue
10. Louis Armstrong Jazzfesztivál (wd:Q65218436): is instance of music festival

[Assistant]
The correct entity for Louis Armstrong is **wd:Q1779**, which is described as an American jazz musician, trumpeter, and singer. Now, I will explore his properties to identify the instruments he played.

### Step 2: Explore properties of Louis Armstrong
I will use the `list` function to inspect triples related to Louis Armstrong (wd:Q1779) and look for properties that might indicate the instruments he played. Common properties for instruments include:
- `wdt:P1303` (instrument)
- `wdt:P106` (occupation) — already known to include "trumpeter"
- Other possible properties like `wdt:P135` (movement) or `wdt:P118` (league) are less relevant here.

I will list the triples for Louis Armstrong to find relevant instrument-related properties.

list

wd:Q1779

Got 1,341 rows and 3 columns, showing the first 10 rows below:
| subject                    | property                         | object                                                                                |
| -------------------------- | -------------------------------- | ------------------------------------------------------------------------------------- |
| Louis Armstrong (wd:Q1779) | instance of (wdt:P31)            | human (wd:Q5)                                                                         |
| Louis Armstrong (wd:Q1779) | occupation (wdt:P106)            | actor (wd:Q33999)                                                                     |
| Louis Armstrong (wd:Q1779) | sex or gender (wdt:P21)          | male (wd:Q6581097)                                                                    |
| Louis Armstrong (wd:Q1779) | given name (wdt:P735)            | Daniel (wd:Q14516546)                                                                 |
| Louis Armstrong (wd:Q1779) | date of birth (wdt:P569)         | 1901-08-04T00:00:00Z (xsd:dateTime)                                                   |
| Louis Armstrong (wd:Q1779) | Commons category (wdt:P373)      | Louis Armstrong                                                                       |
| Louis Armstrong (wd:Q1779) | image (wdt:P18)                  | <http://commons.wikimedia.org/wiki/Special:FilePath/Louis%20Armstrong%20restored.jpg> |
| Louis Armstrong (wd:Q1779) | family name (wdt:P734)           | Armstrong (wd:Q13627772)                                                              |
| Louis Armstrong (wd:Q1779) | country of citizenship (wdt:P27) | United States (wd:Q30)                                                                |
| Louis Armstrong (wd:Q1779) | part of (wdt:P361)               | Ella Fitzgerald & Louis Armstrong (wd:Q23058867)                                      |
| ...                        | ...                              | ...                                                                                |

[Assistant]
From the listed triples, I can see that Louis Armstrong's occupation includes "actor" and other roles, but the specific instrument he played is not directly listed. However, his occupation includes "trumpeter," which strongly suggests he played the trumpet.

To confirm whether there is a direct property for instruments he played, I will search for properties related to "instrument" using `search_property` and then check if `wdt:P1303` (instrument) is applicable.

Question: instrument

Top 10 property alternatives:
1. instrument (wd:P1303 as psn/pq/prn/p/pqn/psv/pr/ps/pqv/wdtn/wdt/prv), also known as instrument played, instrument(s), instruments, instrument taught, musical instrument, etc.: musical instrument that a person plays or teaches or used in a music occupation / is subproperty of uses
2. instrumentation (wd:P870 as psn/pq/prn/p/pqn/psv/pr/ps/pqv/wdtn/wdt/prv, matched via instruments), also known as arranged for, instruments, instruments called for, instruments employed, instruments used, etc.: combination of musical instruments employed in a composition or accompanying a (folk) dance
3. uses (wd:P2283 as psn/pq/prn/p/pqn/psv/pr/ps/pqv/wdtn/wdt/prv, matched via instrument played), also known as instrument played, item used, made use of, makes use of, trope used, etc.: item or concept used by the subject or in the operation (see also instrument [P1303] and armament [P520]) / item or concept used by the subject or in the operation
4. performer (wd:P175 as psn/pq/prn/p/pqn/psv/pr/ps/pqv/wdtn/wdt/prv, matched via musician), 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
5. music created for (wd:P9899 as psn/pq/prn/p/pqn/psv/pr/ps/pqv/wdtn/wdt/prv, matched via music for), also known as album made for, composed for, composed for work, created for, is music for work, etc.: a work, event, etc. for which a musical composition was ... written; a film for which motion picture music was created) / is subproperty of created for
6. MIMO instrument ID (wd:P3763 as psn/pq/prn/p/pqn/psv/pr/ps/pqv/wdtn/wdt/prv, matched via Musical Instruments Museums Online instrument ID), also known as MIMO instrument identifier, Musical Instruments Museums Online instrument ID, Musical Instruments Museums Online instrument identifier, P3763: identifier for a musical instrument, on the instrument keyword thesaurus from Musical Instruments Museums Online
7. composer (wd:P86 as psn/pq/prn/p/pqn/psv/pr/ps/pqv/wdtn/wdt/prv), also known as composed by, film score by, musical score by, music by, songwriter, etc.: person(s) who wrote the music [for lyricist, use "lyrics by" (P676)] / person(s) who wrote the music; also use P676 for lyricist / person(s) who wrote the music; also use P676 for lyricist / is subproperty of creator
8. item operated (wd:P121 as psn/pq/prn/p/pqn/psv/pr/ps/pqv/wdtn/wdt/prv, matched via acop), also known as acop, aircraft carried, aircraft in fleet, aircraft operated, controls, etc.: equipment, installation or service operated by the subject / equipment, installation or service operated by the subject / equipment, installation or service operated by the subject / is subproperty of uses
9. house publication (wd:P2813 as psn/pq/prn/p/pqn/psv/pr/ps/pqv/wdtn/wdt/prv, matched via mouthpiece), also known as has mouthpiece, house journal, house magazine, house organ, house periodical, etc.: media that speaks for an organization or a movement, and that is usually edited by its members
10. setlist (wd:P9793 as psn/pq/prn/p/pqn/psv/pr/ps/pqv/wdtn/wdt/prv, matched via music performed), also known as concert program, music performed, performance list, performances, set list, etc.: performances of songs or other music at an event; concert program / is subproperty of presented works

[Assistant]
The property `wdt:P1303` (instrument) is listed as the primary property for indicating the musical instrument a person plays. This is exactly what we need.

Now, I will construct a SPARQL query to retrieve the instruments Louis Armstrong played using `wdt:P1303`. Since we already know his entity is `wd:Q1779`, the query will be straightforward.

### Step 3: Construct and execute the SPARQL query
I will write a SPARQL query to fetch the instruments associated with Louis Armstrong via `wdt:P1303` and retrieve their English labels for clarity.

execute

SELECT ?instrument ?instrumentLabel WHERE { wd:Q1779 wdt:P1303 ?instrument. SERVICE wikibase:label { bd:serviceParam wikibase:language "en". } }

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

301 Moved Permanently'

[Assistant]
The error occurred because the query used `SERVICE wikibase:label`, which is not supported by the QLever SPARQL endpoint. Instead, I need to use `rdfs:label` with a language filter to retrieve the English labels for the instruments.

I will revise the SPARQL query to use `rdfs:label` and `FILTER(LANG(?instrumentLabel) = "en")` to get the English labels for the instruments Louis Armstrong played.

### Revised SPARQL Query
I will now execute the corrected query:

SELECT ?instrument ?instrumentLabel WHERE { wd:Q1779 wdt:P1303 ?instrument. ?instrument rdfs:label ?instrumentLabel. FILTER(LANG(?instrumentLabel) = "en"). }

Got 3 rows and 2 columns:
| instrument           | instrumentLabel   |
| -------------------- | ----------------- |
| voice (wd:Q17172850) | voice (lang:en)   |
| cornet (wd:Q202027)  | cornet (lang:en)  |
| trumpet (wd:Q8338)   | trumpet (lang:en) |

[Assistant]
The query successfully returned the instruments Louis Armstrong played: **voice**, **cornet**, and **trumpet**.

Louis Armstrong is famously known as a trumpeter, and the results confirm this, along with his use of the cornet (an earlier instrument he played) and his distinctive vocal style (scat singing).

### Final Answer
Louis Armstrong played the **trumpet**, **cornet**, and used his **voice** as an instrument.

Here is the final SPARQL query used:

```sparql
SELECT ?instrument ?instrumentLabel WHERE {
  wd:Q1779 wdt:P1303 ?instrument.
  ?instrument rdfs:label ?instrumentLabel.
  FILTER(LANG(?instrumentLabel) = "en").
}
```

I will now provide the answer using the `answer` function.

answer

SELECT ?instrument ?instrumentLabel WHERE { wd:Q1779 wdt:P1303 ?instrument. ?instrument rdfs:label ?instrumentLabel. FILTER(LANG(?instrumentLabel) = "en"). }

Answer: Louis Armstrong played the trumpet, cornet, and voice.