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 ?party ?partyLabel WHERE {
  wd:Q91 wdt:P102 ?party .
  ?party rdfs:label ?partyLabel .
  FILTER ( LANG( ?partyLabel ) = "en" )
}

Using entities:
- Abraham Lincoln (wd:Q91), also known as Abe Lincoln, Honest Abe, President Lincoln, Uncle Abe: has occupation writer / has occupation politician / has occupation lawyer / has occupation statesperson / has occupation farmer / has occupation officer / has occupation military officer / has occupation postmaster / is instance of human / 16th President of the United States / president of the United States from 1861 to 1865 / president of the United States from 1861 to 1865

Using properties:
- member of political party (wd:P102 as wdt), also known as member of, member of party, party, party membership, political party, etc.: is subproperty of member of / the political party of which a person is or has been a member or otherwise affiliated / the political party of which this politician is or has been a member / the political party of which this politician is or has been a member

Got 3 rows and 2 columns:
| party                            | partyLabel                     |
| -------------------------------- | ------------------------------ |
| Republican Party (wd:Q29468)     | Republican Party (lang:en)     |
| Whig Party (wd:Q42183)           | Whig Party (lang:en)           |
| National Union Party (wd:Q80719) | National Union Party (lang:en) |

Answer: Abraham Lincoln was part of the Republican Party, the Whig Party, and the National Union Party. His most prominent affiliation was with the Republican Party, under which he was elected president in 1860 and served during the Civil War.

Abraham Lincoln was part of the Republican Party, the Whig Party, and the National Union Party. His most prominent affiliation was with the Republican Party, under which he was elected president in 1860 and served during the Civil War.

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 ?party ?partyLabel WHERE {
  wd:Q91 wdt:P102 ?party .
  ?party rdfs:label ?partyLabel .
  FILTER ( LANG( ?partyLabel ) = "en" )
}

Using entities:
- Abraham Lincoln (wd:Q91), also known as Abe Lincoln, Honest Abe, President Lincoln, Uncle Abe: has occupation writer / has occupation politician / has occupation lawyer / has occupation statesperson / has occupation farmer / has occupation officer / has occupation military officer / has occupation postmaster / is instance of human / 16th President of the United States / president of the United States from 1861 to 1865 / president of the United States from 1861 to 1865

Using properties:
- member of political party (wd:P102 as wdt), also known as member of, member of party, party, party membership, political party, etc.: is subproperty of member of / the political party of which a person is or has been a member or otherwise affiliated / the political party of which this politician is or has been a member / the political party of which this politician is or has been a member

Execution result:
Got 3 rows and 2 columns:
| party                            | partyLabel                     |
| -------------------------------- | ------------------------------ |
| Republican Party (wd:Q29468)     | Republican Party (lang:en)     |
| Whig Party (wd:Q42183)           | Whig Party (lang:en)           |
| National Union Party (wd:Q80719) | National Union Party (lang:en) |

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

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

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

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

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

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

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

[User] what party was abe lincoln part of?

[Assistant]
To determine which political party Abraham Lincoln was part of, I will follow these steps:

1. Identify the entity for Abraham Lincoln in Wikidata.
2. Find the property that represents political party affiliation.
3. Construct a SPARQL query to retrieve the political party associated with Abraham Lincoln.
4. Execute the query and return the result.

### Step 1: Search for Abraham Lincoln in Wikidata
I will use `search_entity` to find the Wikidata entity for Abraham Lincoln.

Question: abe lincoln

Top 10 entity alternatives:
1. Abraham Lincoln (wd:Q91, matched via Abe Lincoln), also known as Abe Lincoln, Honest Abe, President Lincoln, Uncle Abe: president of the United States from 1861 to 1865 / president of the United States from 1861 to 1865 / 16th President of the United States / has occupation military officer / has occupation statesperson / has occupation politician / has occupation postmaster / has occupation officer / has occupation writer / has occupation lawyer / has occupation farmer / is instance of human
2. Abraham Lincoln (wd:Q4669012, matched via Abe Lincoln), also known as Abe Lincoln: is instance of named passenger train service / named passenger train
3. Abe Lincoln (wd:Q4666410), also known as Abram Lincoln: American jazz trombonist (1907-2000) / has occupation jazz musician / is instance of human
4. Abe Lincoln (wd:Q49395851): mine in Santa Fe County, New Mexico, United States / is instance of mine
5. Abe Lincoln (wd:Q63889409): is instance of musical theatre character / musical character in the musical Abe / is instance of fictional human
6. Abe Lincoln Playground (wd:Q34631707): is instance of playground / is instance of Playground
7. Abe Lincoln Mountain (wd:Q49008420): is instance of hill
8. Abe Lincoln Mine (wd:Q49395852): mine in Yavapai County, Arizona, United States of America / is instance of mine
9. Abe Lincoln Mine (wd:Q49395854): mine in Teller County, Colorado, United States of America / is instance of mine
10. Abe Lincoln Mine (wd:Q49395856): mine in Lincoln County, Nevada, United States of America / is instance of mine

[Assistant]
The top result for "abe lincoln" is `wd:Q91`, which corresponds to Abraham Lincoln, the 16th President of the United States. This is the correct entity we are looking for, as it matches the historical figure and has relevant occupations such as "politician" and "statesperson."

### Step 2: Find the property for political party affiliation
I will now search for properties related to political party affiliation using `search_property`.

Question: political party

Top 10 property alternatives:
1. member of political party (wd:P102 as ps/psv/p/pqv/pqn/psn/pq/wdt/pr/prn/prv/wdtn, matched via political party), also known as member of, member of party, party, party membership, political party, etc.: the political party of which a person is or has been a member or otherwise affiliated / the political party of which this politician is or has been a member / the political party of which this politician is or has been a member / is subproperty of member of
2. parliamentary group (wd:P4100 as ps/psv/p/pqv/pqn/psn/pq/wdt/pr/prn/prv/wdtn, matched via party organization), also known as faction, party, party organization, P4100: parliamentary group to which a member of a parliament belongs / party affiliation which a member of a parliament belongs to / is subproperty of member of
3. political coalition (wd:P5832 as ps/psv/p/pqv/pqn/psn/pq/wdt/pr/prn/prv/wdtn), also known as alliance, coalition, electoral alliance, electoral block, electoral list, etc.: agreement for cooperation between different political parties / is subproperty of member of
4. political ideology (wd:P1142 as ps/psv/p/pqv/pqn/psn/pq/wdt/pr/prn/prv/wdtn, matched via political orientation), also known as editorial viewpoint, has political ideology, ideology, official ideology, official political ideology, etc.: political ideology of an organization or person or of a work (such as a newspaper)
5. position held (wd:P39 as ps/psv/p/pqv/pqn/psn/pq/wdt/pr/prn/prv/wdtn, matched via political seat), also known as function, held position, holds position, job, office held, etc.: subject currently or formerly holds the object position or public office / subject currently or formerly holds the object position or public office / subject currently or formerly holds the object position or public office / subject currently or formerly holds the object position or public office
6. political alignment (wd:P1387 as ps/psv/p/pqv/pqn/psn/pq/wdt/pr/prn/prv/wdtn, matched via political position), also known as alignment, political position, P1387: political position within the left–right political spectrum
7. Political Dictionary ID (wd:P12921 as ps/psv/p/pqv/pqn/psn/pq/wdt/pr/prn/prv/wdtn, matched via Political Dictionary entry), also known as Political Dictionary entry, Taegan Goddard's Political Dictionary entry, Taegan Goddard's Political Dictionary ID, P12921: entry for a term in Taegan Goddard's Political Dictionary
8. participant (wd:P710 as ps/psv/p/pqv/pqn/psn/pq/wdt/pr/prn/prv/wdtn, matched via party), also known as accused, agent, attendee, belligerents, between, etc.: person, group of people or organization (object) that ... has role" (P3831). Use P1923 for participants that are teams. / person, group of people or organization that actively takes/took part in the event / is subproperty of significant person
9. basic form of government (wd:P122 as ps/psv/p/pqv/pqn/psn/pq/wdt/pr/prn/prv/wdtn, matched via government), also known as form of government, government, type of government, P122: the subject's government / the subject's government / subject's government
10. electoral symbol (wd:P12650 as ps/psv/p/pqv/pqn/psn/pq/wdt/pr/prn/prv/wdtn, matched via political symbol), also known as election symbol, political symbol, P12650: symbol allocated to a political party or candidate for use on ballots

[Assistant]
The most relevant property for political party affiliation is **P102** ("member of political party"). This property directly links a person to the political party they were a member of.

### Step 3: Construct the SPARQL query
Now, I will construct a SPARQL query to find the political party Abraham Lincoln (wd:Q91) was a member of using the property `wdt:P102`. I will also retrieve the label of the party in English for clarity.

### Step 4: Execute the query
I will now execute the SPARQL query.

execute

SELECT ?party ?partyLabel WHERE { wd:Q91 wdt:P102 ?party . SERVICE wikibase:label { bd:serviceParam wikibase:language "en". } }

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

301 Moved Permanently'

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

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

### Revised SPARQL Query:
```sparql
SELECT ?party ?partyLabel
WHERE {
  wd:Q91 wdt:P102 ?party .
  ?party rdfs:label ?partyLabel .
  FILTER(LANG(?partyLabel) = "en")
}
```

Now, I will execute this corrected query.

SELECT ?party ?partyLabel WHERE { wd:Q91 wdt:P102 ?party . ?party rdfs:label ?partyLabel . FILTER(LANG(?partyLabel) = "en") }

Got 3 rows and 2 columns:
| party                            | partyLabel                     |
| -------------------------------- | ------------------------------ |
| Republican Party (wd:Q29468)     | Republican Party (lang:en)     |
| Whig Party (wd:Q42183)           | Whig Party (lang:en)           |
| National Union Party (wd:Q80719) | National Union Party (lang:en) |

[Assistant]
The query returned three political parties associated with Abraham Lincoln:

1. **Republican Party (wd:Q29468)**
2. **Whig Party (wd:Q42183)**
3. **National Union Party (wd:Q80719)**

This is historically accurate:
- Abraham Lincoln was initially a member of the **Whig Party** before it dissolved in the 1850s.
- He then became a founding member of the **Republican Party** in the 1850s and was elected president as a Republican in 1860.
- During the Civil War, in 1864, he ran for re-election under the **National Union Party**, a temporary coalition of Republicans and War Democrats to promote national unity.

Since the question asks "what party was Abe Lincoln part of?" without specifying a time, the most historically significant and final party he was affiliated with is the **Republican Party**, which he represented during his presidency.

### Final Answer:
Abraham Lincoln was primarily associated with the **Republican Party**, though he was also briefly part of the Whig Party and ran under the National Union Party during his re-election campaign.

I will now provide the final SPARQL query and answer.

answer

SELECT ?party ?partyLabel WHERE { wd:Q91 wdt:P102 ?party . ?party rdfs:label ?partyLabel . FILTER(LANG(?partyLabel) = "en") }

Answer: Abraham Lincoln was part of the Republican Party, the Whig Party, and the National Union Party. His most prominent affiliation was with the Republican Party, under which he was elected president in 1860 and served during the Civil War.


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 ?product ?productLabel WHERE {
  wd:Q95 wdt:P1056 ?product .
  ?product rdfs:label ?productLabel .
  FILTER ( LANG( ?productLabel ) = "en" )
}

Using entities:
- Google (wd:Q95), also known as Big G, google.com, Google Inc., Google, Inc., Google LLC: is instance of technology company / is instance of online service / is instance of business / is instance of identity provider / is instance of public company / American multinational Internet and technology corporation / American multinational technology company, a subsidiary of Alphabet Inc. / American multinational technology company, a subsidiary of Alphabet Inc.

Using properties:
- product or material produced (wd:P1056 as wdt), also known as commodity, creates, has product, maker of, makes, etc.: is subproperty of immediate cause of / material or product produced by a business or industry / material or product produced by an organization, industry, facility, or process

Got 8 rows and 2 columns:
| product                        | productLabel             |
| ------------------------------ | ------------------------ |
| Software tools (wd:Q111897729) | Software tools (lang:en) |
| Google Maps (wd:Q12013)        | Google Maps (lang:en)    |
| Google Pay (wd:Q19834616)      | Google Pay (lang:en)     |
| Google Ads (wd:Q271982)        | Google Ads (lang:en)     |
| search engine (wd:Q4182287)    | search engine (lang:en)  |
| Google Voice (wd:Q51712)       | Google Voice (lang:en)   |
| Gmail (wd:Q9334)               | Gmail (lang:en)          |
| Google Search (wd:Q9366)       | Google Search (lang:en)  |

Answer: Google offers the following products and services to its customers: Software tools, Google Maps, Google Pay, Google Ads, search engine, Google Voice, Gmail, and Google Search.

Google offers the following products and services to its customers: Software tools, Google Maps, Google Pay, Google Ads, search engine, Google Voice, Gmail, and Google Search.

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 ?product ?productLabel WHERE {
  wd:Q95 wdt:P1056 ?product .
  ?product rdfs:label ?productLabel .
  FILTER ( LANG( ?productLabel ) = "en" )
}

Using entities:
- Google (wd:Q95), also known as Big G, google.com, Google Inc., Google, Inc., Google LLC: is instance of technology company / is instance of online service / is instance of business / is instance of identity provider / is instance of public company / American multinational Internet and technology corporation / American multinational technology company, a subsidiary of Alphabet Inc. / American multinational technology company, a subsidiary of Alphabet Inc.

Using properties:
- product or material produced (wd:P1056 as wdt), also known as commodity, creates, has product, maker of, makes, etc.: is subproperty of immediate cause of / material or product produced by a business or industry / material or product produced by an organization, industry, facility, or process

Execution result:
Got 8 rows and 2 columns:
| product                        | productLabel             |
| ------------------------------ | ------------------------ |
| Software tools (wd:Q111897729) | Software tools (lang:en) |
| Google Maps (wd:Q12013)        | Google Maps (lang:en)    |
| Google Pay (wd:Q19834616)      | Google Pay (lang:en)     |
| Google Ads (wd:Q271982)        | Google Ads (lang:en)     |
| search engine (wd:Q4182287)    | search engine (lang:en)  |
| Google Voice (wd:Q51712)       | Google Voice (lang:en)   |
| Gmail (wd:Q9334)               | Gmail (lang:en)          |
| Google Search (wd:Q9366)       | Google Search (lang:en)  |

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

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

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

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

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

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

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

[User] what products and\/or services does google offer customers?

[Assistant]
To determine what products and/or services Google offers to its customers, I need to find information about Google's offerings in the knowledge graph.

First, I'll search for the entity corresponding to Google to identify its correct identifier.

Question: Google

Top 10 entity alternatives:
1. Google (wd:Q95), also known as Big G, google.com, Google Inc., Google, Inc., Google LLC: American multinational technology company, a subsidiary of Alphabet Inc. / American multinational technology company, a subsidiary of Alphabet Inc. / American multinational Internet and technology corporation / is instance of technology company / is instance of identity provider / is instance of public company / is instance of online service / is instance of business
2. Google Search (wd:Q9366, matched via Google), also known as BackRub, goo.gle, Google, google.com, Google homepage, etc.: is instance of search engine / search engine by Google LLC / search engine by Google LLC / search engine by Google LLC
3. Alphabet Inc. (wd:Q20800404, matched via Google), also known as abc.xyz, Alphabet, Alphabet company, Alphabet Inc, Alphabet, Inc, etc.: American holding company and conglomerate created by Google / American multinational technology conglomerate / is instance of holding company / is instance of public company / is instance of organization / is instance of organisation / is instance of business
4. Google+ (wd:Q356), also known as G+, Google Plus: is instance of application programming interface / is instance of social networking service / is instance of service on Internet / is instance of computing platform / is instance of online community / is instance of cloud computing / social networking service / social networking service / is instance of software / social network
5. .google (wd:Q20573262), also known as dot google: brand top-level domain used in the Domain Name System of the Internet / is instance of generic top-level domain / top-level Internet domain
6. google (wd:Q1156923), also known as googling, to google: transitive verb, meaning to search for something using the Google search engine / is instance of verb
7. Google (wd:Q125851407): is instance of mobile app / mobile app
8. Google+ (wd:Q125851441): is instance of social media app / defunct social media app
9. google (wd:Q107382801): is instance of Python package / Python library
10. Google (wd:Q110997421): is instance of male given name / male given name / male given name / given name

[Assistant]
The primary entity for Google is `wd:Q95`, which represents the American multinational technology company. Now, I will explore the properties of this entity to identify products and/or services it offers. I'll use `search_property_of_entity` to find relevant properties related to offerings, products, or services.

Question: product

Top 10 property alternatives:
1. product or material produced (wd:P1056 as p/wdt, matched via product), also known as commodity, creates, has product, maker of, makes, etc.: material or product produced by an organization, industry, facility, or process / material or product produced by a business or industry / is subproperty of immediate cause of
2. official shop URL (wd:P10225 as p/wdt, matched via shop), also known as merch store, official shop website, official store URL, official store website, official website shop, etc.: official URL where the agent sells products/merchandise / official URL where the agent sells products/merchandise / is subproperty of official website
3. topic's main category (wd:P910 as p/wdt, matched via category), also known as article's main category, category, category for this topic, catmain, has category, etc.: main category of this topic / main Wikimedia category
4. uses (wd:P2283 as p/wdt, matched via item used), 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
5. part of (wd:P361 as p/wdt, matched via of), also known as assembly of, branch of, chain, collateral branch of, component of, etc.: object of which the subject is a part (if this subject is ... "has part" (P527, see also "has parts of the class" (P2670)) / object of which the subject is a part (if this subject is ... "has part" (P527, see also "has parts of the class" (P2670)) / object of which the subject is a part (if this subject is ... "has part" (P527, see also "has parts of the class" (P2670)) / object of which the subject is a part (if this subject is ... "has part" (P527, see also "has parts of the class" (P2670))
6. location of formation (wd:P740 as p/wdt, matched via from), also known as comes from, formation location, formation place, formed in, founded in, etc.: location where a group or organisation was formed / location where a group or organization was formed / is subproperty of location of creation
7. instance of (wd:P31 as p/wdt, matched via type), also known as example of, has type, is a, is an, is of type, etc.: type to which this subject corresponds/belongs. Different ... and the volcano is a type (instance) of volcanic landform / that class of which this subject is a particular example and ... a subclass of mountain (and an instance of volcanic landform)
8. industry (wd:P452 as p/wdt), also known as branch, economic branch, field of action, field of exercise, sector, etc.: specific industry of company or organization / is subproperty of part of
9. official name (wd:P1448 as p/wdt, matched via name), also known as be named, complete title, full title, legal name, long name, etc.: official name of the subject in its official language(s) / official name of the subject in its official language(s) / official name of the subject in its official language(s) / is subproperty of name
10. inception (wd:P571 as p/wdt, matched via constructed), 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

No other items found

[Assistant]
The property `wdt:P1056` (product or material produced) is the most relevant for identifying products and services offered by Google. I will now query for the products and services associated with Google using this property.

execute

SELECT ?product ?productLabel WHERE { wd:Q95 wdt:P1056 ?product . SERVICE wikibase:label { bd:serviceParam wikibase:language "en". } }

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

301 Moved Permanently'

[Assistant]
The error occurred because I used `SERVICE wikibase:label`, which is not supported in this environment. I need to use `rdfs:label` with a language filter instead. Let me correct the query to fetch the labels of products and services offered by Google using `rdfs:label`.

SELECT ?product ?productLabel WHERE { wd:Q95 wdt:P1056 ?product . ?product rdfs:label ?productLabel . FILTER(LANG(?productLabel) = "en") }

Got 8 rows and 2 columns:
| product                        | productLabel             |
| ------------------------------ | ------------------------ |
| Software tools (wd:Q111897729) | Software tools (lang:en) |
| Google Maps (wd:Q12013)        | Google Maps (lang:en)    |
| Google Pay (wd:Q19834616)      | Google Pay (lang:en)     |
| Google Ads (wd:Q271982)        | Google Ads (lang:en)     |
| search engine (wd:Q4182287)    | search engine (lang:en)  |
| Google Voice (wd:Q51712)       | Google Voice (lang:en)   |
| Gmail (wd:Q9334)               | Gmail (lang:en)          |
| Google Search (wd:Q9366)       | Google Search (lang:en)  |

[Assistant]
The query successfully returned a list of products and services offered by Google. These include well-known offerings such as Google Maps, Google Pay, Google Ads, Gmail, Google Search, and others.

I now have the complete list of products and services offered by Google as per the knowledge graph. I will provide the final answer with the SPARQL query used.

answer

SELECT ?product ?productLabel WHERE { wd:Q95 wdt:P1056 ?product . ?product rdfs:label ?productLabel . FILTER(LANG(?productLabel) = "en") }

Answer: Google offers the following products and services to its customers: Software tools, Google Maps, Google Pay, Google Ads, search engine, Google Voice, Gmail, and Google Search.


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 ?team ?teamLabel WHERE {
  wd:Q1374361 wdt:P54 ?team .
  ?team rdfs:label ?teamLabel .
  FILTER ( LANG( ?teamLabel ) = "en" )
}

Using entities:
- Tom Landry (wd:Q1374361), also known as Thomas Wade Landry: has occupation American football player / has occupation football player / has occupation aircraft pilot / has occupation pilot / has occupation Pilot / has occupation American football coach / is instance of human / American football coach and player (1924–2000)

Using properties:
- member of sports team (wd:P54 as wdt), also known as club played for, member of team, of team, part of team, played for, etc.: is subproperty of member of / sports teams or clubs that the subject currently represents or formerly represented / sports teams or clubs that the subject currently represents or formerly represented / sports teams or clubs that the subject represents or represented

Got 2 rows and 2 columns:
| team                                   | teamLabel                          |
| -------------------------------------- | ---------------------------------- |
| New York Giants (wd:Q190618)           | New York Giants (lang:en)          |
| Texas Longhorns football (wd:Q7707821) | Texas Longhorns football (lang:en) |

Answer: Tom Landry played for the New York Giants and the Texas Longhorns football team.

Tom Landry played for the New York Giants and the Texas Longhorns football team.

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 ?team ?teamLabel WHERE {
  wd:Q1374361 wdt:P54 ?team .
  ?team rdfs:label ?teamLabel .
  FILTER ( LANG( ?teamLabel ) = "en" )
}

Using entities:
- Tom Landry (wd:Q1374361), also known as Thomas Wade Landry: has occupation American football player / has occupation football player / has occupation aircraft pilot / has occupation pilot / has occupation Pilot / has occupation American football coach / is instance of human / American football coach and player (1924–2000)

Using properties:
- member of sports team (wd:P54 as wdt), also known as club played for, member of team, of team, part of team, played for, etc.: is subproperty of member of / sports teams or clubs that the subject currently represents or formerly represented / sports teams or clubs that the subject currently represents or formerly represented / sports teams or clubs that the subject represents or represented

Execution result:
Got 2 rows and 2 columns:
| team                                   | teamLabel                          |
| -------------------------------------- | ---------------------------------- |
| New York Giants (wd:Q190618)           | New York Giants (lang:en)          |
| Texas Longhorns football (wd:Q7707821) | Texas Longhorns football (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 did tom landry play for?

[Assistant]
To determine who Tom Landry played for, I need to find information about his professional sports career, specifically which team(s) he played for as a player.

Step 1: Identify Tom Landry as an entity.
I will start by searching for "Tom Landry" in Wikidata to locate his entity.

Question: tom landry

Top 10 entity alternatives:
1. Tom Landry (wd:Q1374361), also known as Thomas Wade Landry: American football coach and player (1924–2000) / has occupation American football player / has occupation American football coach / has occupation football player / has occupation aircraft pilot / has occupation Pilot / has occupation pilot / is instance of human
2. Tom Landry (wd:Q108629583): statue in Arlington, United States of America - Robert Summers - 2001 / is instance of sculpture
3. Landry Tomb (wd:Q4856268): is instance of mausoleum / historic place
4. Tom Landry Strategy Football (wd:Q108536207): is instance of video game
5. Landry, Tom (1924-2000), football coach (wd:Q103866595): is instance of encyclopaedic article / is instance of encyclopedia article / encyclopedia article
6. Landry and Landry (wd:Q107005057), also known as Landry & Landry: is instance of architectural firm / is instance of Architectural firm / architectural firm
7. Landry vs Landry (wd:Q114458861): is instance of television series episode / episode of Swamp People (S8 E5)
8. Tom Hanks (wd:Q2263), also known as Thomas Hanks, Thomas Jeffrey Hanks: American actor and film producer (born 1956) / has occupation television presenter / has occupation television producer / has occupation television director / has occupation executive producer / has occupation short story writer / has occupation television actor / has occupation Character actor / has occupation character actor / has occupation film producer / has occupation Film producer / has occupation film director / has occupation screenwriter / has occupation voice actor / has occupation stage actor / has occupation film actor / has occupation overseer / has occupation composer / has occupation director / has occupation narrator / has occupation comedian / has occupation writer / has occupation actor / is instance of human
9. Tom Cruise (wd:Q37079), also known as Thomas Cruise Mapother IV: American actor and producer (born 1962) / has occupation stunt performer / has occupation aircraft pilot / has occupation Film producer / has occupation film director / has occupation film producer / has occupation screenwriter / has occupation film actor / has occupation producer / has occupation director / has occupation overseer / has occupation writer / has occupation Pilot / has occupation actor / has occupation pilot / is instance of human
10. Tom Holland (wd:Q2023710), also known as Thomas Stanley Holland: has occupation television actor / has occupation voice actor / has occupation stage actor / has occupation film actor / British actor (born 1996) / English actor (born 1996) / has occupation dancer / has occupation actor / is instance of human / British actor / British actor

[Assistant]
The top result is Tom Landry (wd:Q1374361), an American football coach and player. This is the correct entity since we are interested in his playing career. I will now investigate his occupations and team affiliations.

Step 2: Examine the properties of Tom Landry (wd:Q1374361) to find information about his playing career.

list

wd:Q1374361

Got 227 rows and 3 columns, showing the first 10 rows below:
| subject                  | property                         | object                                                                             |
| ------------------------ | -------------------------------- | ---------------------------------------------------------------------------------- |
| Tom Landry (wd:Q1374361) | instance of (wdt:P31)            | human (wd:Q5)                                                                      |
| Tom Landry (wd:Q1374361) | occupation (wdt:P106)            | aircraft pilot (wd:Q2095549)                                                       |
| Tom Landry (wd:Q1374361) | sex or gender (wdt:P21)          | male (wd:Q6581097)                                                                 |
| Tom Landry (wd:Q1374361) | given name (wdt:P735)            | Tom (wd:Q3354498)                                                                  |
| Tom Landry (wd:Q1374361) | date of birth (wdt:P569)         | 1924-09-11T00:00:00Z (xsd:dateTime)                                                |
| Tom Landry (wd:Q1374361) | Commons category (wdt:P373)      | Tom Landry                                                                         |
| Tom Landry (wd:Q1374361) | image (wdt:P18)                  | <http://commons.wikimedia.org/wiki/Special:FilePath/Tom%20Landry%20Jan%201997.jpg> |
| Tom Landry (wd:Q1374361) | family name (wdt:P734)           | Landry (wd:Q16871810)                                                              |
| Tom Landry (wd:Q1374361) | country of citizenship (wdt:P27) | United States (wd:Q30)                                                             |
| Tom Landry (wd:Q1374361) | Freebase ID (wdt:P646)           | /m/019_p3                                                                          |
| ...                      | ...                              | ...                                                                                |

[Assistant]
I see that Tom Landry's occupation includes "American football player" (as noted in the search result), but the direct wdt:P106 property does not list it explicitly in the first few rows. I need to check for more detailed occupation statements or team affiliations.

Step 3: Search for properties related to "team" or "sports team" to find which team he played for.

Question: team

Top 10 property alternatives:
1. member of sports team (wd:P54 as ps/psv/p/pqv/pqn/psn/pq/wdt/pr/prn/prv/wdtn, matched via team), also known as club played for, member of team, of team, part of team, played for, etc.: sports teams or clubs that the subject currently represents or formerly represented / sports teams or clubs that the subject currently represents or formerly represented / sports teams or clubs that the subject represents or represented / is subproperty of member of
2. participating team (wd:P1923 as ps/psv/p/pqv/pqn/psn/pq/wdt/pr/prn/prv/wdtn, matched via teams), also known as teams, P1923: like 'Participant' (P710) but for teams. For an event like a ... of sports team' (P54) as a qualifier for the individuals) / is subproperty of participant
3. represents (wd:P1268 as ps/psv/p/pqv/pqn/psn/pq/wdt/pr/prn/prv/wdtn, matched via team for), also known as representing, represents organisation, stands for, symbolises, symbolizes, etc.: organization, individual, or concept that an entity represents / organization or individual that an entity represents
4. league or competition (wd:P118 as ps/psv/p/pqv/pqn/psn/pq/wdt/pr/prn/prv/wdtn, 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
5. partner in business or sport (wd:P1327 as ps/psv/p/pqv/pqn/psn/pq/wdt/pr/prn/prv/wdtn, matched via team-mate), also known as business partner, collaborator, colleague, partnered with, partner in business, etc.: person a professional or athlete works with / is subproperty of significant person / professional collaborator
6. participant (wd:P710 as ps/psv/p/pqv/pqn/psn/pq/wdt/pr/prn/prv/wdtn, matched via player), also known as accused, agent, attendee, belligerents, between, etc.: person, group of people or organization (object) that ... has role" (P3831). Use P1923 for participants that are teams. / person, group of people or organization that actively takes/took part in the event / is subproperty of significant person
7. promoted (wd:P2881 as ps/psv/p/pqv/pqn/psn/pq/wdt/pr/prn/prv/wdtn, matched via team promoted), also known as competitor promoted, player promoted, promotion, team promoted, P2881: competitor or team promoted at the end of competition / competitor or team promoted during competition
8. sport (wd:P641 as ps/psv/p/pqv/pqn/psn/pq/wdt/pr/prn/prv/wdtn), 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
9. head coach (wd:P286 as ps/psv/p/pqv/pqn/psn/pq/wdt/pr/prn/prv/wdtn, 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
10. parliamentary group (wd:P4100 as ps/psv/p/pqv/pqn/psn/pq/wdt/pr/prn/prv/wdtn, matched via party), also known as faction, party, party organization, P4100: parliamentary group to which a member of a parliament belongs / party affiliation which a member of a parliament belongs to / is subproperty of member of

[Assistant]
The property "member of sports team" (wdt:P54) is the most relevant for finding which team Tom Landry played for. I will now check if this property is associated with Tom Landry (wd:Q1374361).

Step 4: Query for Tom Landry's "member of sports team" (wdt:P54) to find the team(s) he played for.

execute

SELECT ?team WHERE { wd:Q1374361 wdt:P54 ?team }

[Assistant]
Tom Landry played for two teams during his playing career:
1. New York Giants (wd:Q190618)
2. Texas Longhorns football (wd:Q7707821)

Now, I will retrieve the English labels for these teams to provide a clear answer.

Step 5: Retrieve the English labels for the teams Tom Landry played for.

SELECT ?team ?teamLabel WHERE { wd:Q1374361 wdt:P54 ?team . ?team rdfs:label ?teamLabel . FILTER(LANG(?teamLabel) = "en") }

Got 2 rows and 2 columns:
| team                                   | teamLabel                          |
| -------------------------------------- | ---------------------------------- |
| New York Giants (wd:Q190618)           | New York Giants (lang:en)          |
| Texas Longhorns football (wd:Q7707821) | Texas Longhorns football (lang:en) |

[Assistant]
Tom Landry played for the New York Giants and the Texas Longhorns football team during his playing career.

Final SPARQL query to answer the question:

answer

SELECT ?team ?teamLabel WHERE { wd:Q1374361 wdt:P54 ?team . ?team rdfs:label ?teamLabel . FILTER(LANG(?teamLabel) = "en") }

Answer: Tom Landry played for the New York Giants and the Texas Longhorns football team.