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 ?institution ?label WHERE {
  wd:Q117425 wdt:P69 ?institution .
  ?institution rdfs:label ?label .
  FILTER ( LANG( ?label ) = "en" )
}

Using entities:
- S. E. Hinton (wd:Q117425), also known as Susan Eloise Hinton: has occupation screenwriter / has occupation novelist / has occupation children's writer / has occupation writer / has occupation film actor / has occupation autobiographer / is instance of human / American writer

Using properties:
- educated at (wd:P69 as wdt), also known as alma mater, alumna of, alumni of, alumnus of, attended, etc.: is subproperty of affiliation / educational institution attended by subject / educational institution attended by the subject / educational institution attended by the subject

Got 2 rows and 2 columns:
| institution                           | label                             |
| ------------------------------------- | --------------------------------- |
| University of Tulsa (wd:Q1848657)     | University of Tulsa (lang:en)     |
| Will Rogers High School (wd:Q8003051) | Will Rogers High School (lang:en) |

Answer: S.E. Hinton attended the University of Tulsa.

S.E. Hinton attended the University of Tulsa.

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 ?institution ?label WHERE {
  wd:Q117425 wdt:P69 ?institution .
  ?institution rdfs:label ?label .
  FILTER ( LANG( ?label ) = "en" )
}

Using entities:
- S. E. Hinton (wd:Q117425), also known as Susan Eloise Hinton: has occupation screenwriter / has occupation novelist / has occupation children's writer / has occupation writer / has occupation film actor / has occupation autobiographer / is instance of human / American writer

Using properties:
- educated at (wd:P69 as wdt), also known as alma mater, alumna of, alumni of, alumnus of, attended, etc.: is subproperty of affiliation / educational institution attended by subject / educational institution attended by the subject / educational institution attended by the subject

Execution result:
Got 2 rows and 2 columns:
| institution                           | label                             |
| ------------------------------------- | --------------------------------- |
| University of Tulsa (wd:Q1848657)     | University of Tulsa (lang:en)     |
| Will Rogers High School (wd:Q8003051) | Will Rogers High School (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 college did se hinton go?

[Assistant]
To determine which college S.E. Hinton attended, I will follow these steps:

1. Identify the correct entity for S.E. Hinton (Susan Eloise Hinton) in Wikidata.
2. Look for properties related to education or college attendance, such as "educated at" (P69).
3. Construct a SPARQL query to retrieve the college(s) she attended.
4. Execute the query and verify the results.

Let me begin by searching for S.E. Hinton in Wikidata.

Question: S.E. Hinton

Top 10 entity alternatives:
1. Geoffrey Hinton (wd:Q92894), also known as G. E. Hinton, Geoff Hinton, Geoffrey E. Hinton, Geoffrey Everest Hinton: British-Canadian computer scientist and psychologist / has occupation artificial intelligence researcher / has occupation computer scientist / has occupation university teacher / has occupation neuroscientist / has occupation psychologist / is instance of human
2. Hinton (wd:Q1846529), also known as Hinton, IA, Hinton, Iowa: is instance of city in the United States / is instance of city of the United States / city in Iowa, United States
3. Hinton (wd:Q1814667), also known as Hinton, West Virginia, Hinton, WV: city in Summers County, West Virginia, United States / is instance of city of the United States / is instance of city in the United States
4. Hinton (wd:Q2392475), also known as Hinton, OK, Hinton, Oklahoma: human settlement in Caddo County, Oklahoma, United States of America / is instance of town in the United States
5. Hinton (wd:Q1016692): is instance of town in Alberta / town in Alberta, Canada / is instance of town
6. Jerrika Hinton (wd:Q6183091), also known as Jerrika Delayne Hinton: has occupation television actor / has occupation film director / has occupation film actor / has occupation actor / is instance of human / American actress
7. Hinton Waldrist (wd:Q2313506), also known as Hinton Waldrist, Oxfordshire, Hinton Waldrist, Oxon: village and civil parish in Vale of White Horse district, Oxfordshire, England / village and civil parish in Vale of White Horse district, Oxfordshire, England / village in the United Kingdom / is instance of civil parish / is instance of village
8. Milt Hinton (wd:Q491411), also known as Milton J. Hinton, Milton John Hinton: American musician and photographer (1910-2000) / has occupation non-fiction writer / has occupation jazz musician / has occupation photographer / has occupation musician / has occupation singer / is instance of human
9. Tarrant Hinton (wd:Q2328622), also known as Tarrant Hinton, Dorset: village and civil parish in Dorset, United Kingdom / is instance of civil parish / is instance of village
10. Hinton Blewett (wd:Q2556548), also known as Hinton Blewett, Somerset: village in Somerset, England, UK / is instance of civil parish / is instance of village

[Assistant]
The top result is Geoffrey Hinton, a well-known computer scientist, but we are looking for S.E. Hinton, the author of *The Outsiders*. The correct person is likely not among the top results, so I will refine the search by including more context, such as "Susan Hinton" or "author," to narrow it down.

Let me try searching with "Susan Hinton author":

Question: Susan Hinton author

Top 10 entity alternatives:
1. S. E. Hinton (wd:Q117425, matched via Susan Eloise Hinton), also known as Susan Eloise Hinton: has occupation children's writer / has occupation autobiographer / has occupation screenwriter / has occupation film actor / has occupation novelist / has occupation writer / is instance of human / American writer
2. Susan Mary Hinton (wd:Q76250464), also known as Hon. Susan Mary Hinton: is instance of human / (1932-2014)
3. Warner, Susan Bogert (1819-1885), author (wd:Q103884145): is instance of encyclopaedic article / is instance of encyclopedia article / encyclopedia article
4. Anthony, Katharine Susan (1877-1965), author (wd:Q103845203): is instance of encyclopaedic article / is instance of encyclopedia article / encyclopedia article
5. The author file: Susan Cox. (wd:Q48562733): scientific article published in February 2012 / scientific article published in February 2012 / scientific article published in February 2012 / is instance of scholarly article / is instance of academic article
6. Susannah Powell Mason (wd:Q96636872, matched via Susannah "Susan" Mason), also known as Susannah "Susan" Mason, Susannah "Susan" Powell: is instance of human / (1761 - 1836)
7. Susannah "Susan" Patterson Bixby (wd:Q130760006, matched via Susannah "Susan" Hathaway), also known as Susannah "Susan" Hathaway, Susannah "Susan" Patterson Hathaway: 22 Mar 1845 - 3 Feb 1906 / is instance of human
8. Susannah "Susan" Huntington (wd:Q122811311), also known as Susan Kent, Susannah "Susan" Kent: is instance of human
9. Susannah (Susan) Howland (wd:Q121600768): is instance of human / 1791 - 1872
10. Susan Susanti (wd:Q109695917): Indonesian political candidate / has occupation politician / is instance of human

[Assistant]
Great! I found the correct entity for S.E. Hinton: **wd:Q117425** (S. E. Hinton), the American author of *The Outsiders*. Now, I need to find out which college she attended.

I will check the properties associated with this entity to locate the "educated at" property (P69), which typically indicates the educational institutions a person attended.

Let me list the triples for S.E. Hinton to explore her properties:

list

wd:Q117425

[Assistant]
I see that the "educated at" property (P69) is not immediately visible in the first few triples. To confirm whether it exists, I will search for properties related to education or university attendance for S.E. Hinton using `search_property_of_entity`.

Let me search for properties related to "education" or "college":

Question: education

Top 10 property alternatives:
1. educated at (wd:P69 as p/wdt, matched via education), also known as alma mater, alumna of, alumni of, alumnus of, attended, etc.: educational institution attended by the subject / educational institution attended by the subject / educational institution attended by subject / is subproperty of affiliation
2. occupation (wd:P106 as p/wdt, matched via career), also known as avocation, career, craft, employ, employment, etc.: occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39) / occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39) / occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)
3. award received (wd:P166 as p/wdt, matched via honors), also known as award, awarded, awards, awards received, award won, etc.: award or recognition received by a person, organisation or creative work / award or recognition received by a person, organization or creative work / award or recognition received by a person, organization or creative work / awards received by a person, organisation or creative work
4. country of citizenship (wd:P27 as p/wdt, matched via nation), also known as citizen of, citizenship, country, (legal) nationality, nation, etc.: the object is a country that recognizes the subject as its citizen / the object is a country that recognizes the subject as its citizen / is subproperty of country
5. notable work (wd:P800 as p/wdt, matched via work), also known as artwork, author of, bibliography, books by, creator of, etc.: notable scientific, artistic or literary work, or other work of significance among subject's works / notable scientific, artistic or literary work, or other work of significance among subject's works
6. languages spoken, written or signed (wd:P1412 as p/wdt, matched via language), also known as language, language of expression, language read, language signed, languages of expression, etc.: language(s) that a person or a people speaks, writes or signs, including the native language(s) / language(s) that a person speaks or writes, including the native language(s) / language(s) that a person speaks or writes, including the native language(s)
7. Open Library ID (wd:P648 as p/wdt/wdtn, matched via OLID), also known as OL ID, OLID, Open Library author ID, OpenLibrary author ID, Open Library book ID, etc.: identifier in "the Internet Archive" for information about a work ("W"), edition ("M") or author ("A") of a book / identifier for a work ("W"), edition ("M") or author ("A") for book data of the Internet Archive
8. place of birth (wd:P19 as p/wdt), also known as birth city, birth location, birth place, birthplace, born, etc.: 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 / most specific known birth location of a person, animal or fictional character / is subproperty of location
9. official website (wd:P856 as p/wdt, matched via homepage), also known as home page, homepage, home page (official), homepage (official), official homepage, etc.: URL of the official page of an item (current or former). ... see the "Hijacked or dead websites" section of the Talk page / is subproperty of URL
10. 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)

No other items found

[Assistant]
Perfect! I found the property **P69 (educated at)**, which is exactly what I need. Now I will construct a SPARQL query to retrieve the educational institution(s) S.E. Hinton attended.

The query will:
- Select the institution (`?institution`) linked via `wdt:P69`.
- Retrieve the label of the institution in English using `rdfs:label` and `FILTER(LANG(?label) = "en")`.

Let me execute the query:

execute

SELECT ?institution ?label WHERE { wd:Q117425 wdt:P69 ?institution . ?institution rdfs:label ?label . FILTER(LANG(?label) = "en") }

Got 2 rows and 2 columns:
| institution                           | label                             |
| ------------------------------------- | --------------------------------- |
| University of Tulsa (wd:Q1848657)     | University of Tulsa (lang:en)     |
| Will Rogers High School (wd:Q8003051) | Will Rogers High School (lang:en) |

[Assistant]
The query results show that S.E. Hinton attended two educational institutions:

1. **University of Tulsa** (higher education)
2. **Will Rogers High School** (secondary education)

Since the question asks specifically about "college," the relevant answer is the **University of Tulsa**.

I will now provide the final answer with the SPARQL query used.

answer

SELECT ?institution ?label WHERE { wd:Q117425 wdt:P69 ?institution . ?institution rdfs:label ?label . FILTER(LANG(?label) = "en") }

Answer: S.E. Hinton attended the University of Tulsa.


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 ?label WHERE {
  wd:Q7184 wdt:P159 ?headquarters .
  ?headquarters rdfs:label ?label .
  FILTER ( LANG( ?label ) = "en" )
}

Using entities:
- NATO (wd:Q7184), also known as NATO Alliance, North Atlantic Alliance, North Atlantic Treaty Organisation, North Atlantic Treaty Organization: is instance of multinational military coalition / is instance of military alliance / is instance of intergovernmental organisation / is instance of intergovernmental organization / is instance of international organisation / is instance of international organization / intergovernmental military alliance / intergovernmental military alliance / intergovernmental military alliance between 32 member states / intergovernmental military alliance between 32 member states

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

Got 1 row and 1 column:
| label                      |
| -------------------------- |
| City of Brussels (lang:en) |

Answer: The NATO headquarters are located in the City of Brussels.

The NATO headquarters are located in the City of Brussels.

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 ?label WHERE {
  wd:Q7184 wdt:P159 ?headquarters .
  ?headquarters rdfs:label ?label .
  FILTER ( LANG( ?label ) = "en" )
}

Using entities:
- NATO (wd:Q7184), also known as NATO Alliance, North Atlantic Alliance, North Atlantic Treaty Organisation, North Atlantic Treaty Organization: is instance of multinational military coalition / is instance of military alliance / is instance of intergovernmental organisation / is instance of intergovernmental organization / is instance of international organisation / is instance of international organization / intergovernmental military alliance / intergovernmental military alliance / intergovernmental military alliance between 32 member states / intergovernmental military alliance between 32 member states

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

Execution result:
Got 1 row and 1 column:
| label                      |
| -------------------------- |
| City of Brussels (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] where are the nato headquarters located?

[Assistant]
To determine where the NATO headquarters are located, I need to find the entity representing NATO and then identify its location.

Step 1: Search for the entity "NATO" in Wikidata.

Question: NATO

Top 10 entity alternatives:
1. NATO (wd:Q7184), also known as NATO Alliance, North Atlantic Alliance, North Atlantic Treaty Organisation, North Atlantic Treaty Organization: intergovernmental military alliance between 32 member states / intergovernmental military alliance between 32 member states / is instance of multinational military coalition / is instance of intergovernmental organization / is instance of intergovernmental organisation / is instance of international organisation / is instance of international organization / intergovernmental military alliance / intergovernmental military alliance / is instance of military alliance
2. .nato (wd:Q753137): is instance of top-level domain / top-level domain
3. Cinema United (wd:Q2076915, matched via NATO), also known as National Association of Theatre Owners, NATO: American motion picture exhibition trade organization / is instance of film organisation / is instance of film organization / is instance of trade association
4. NATO (wd:Q1940923): 1994 studio album by Laibach / is instance of album
5. nato wood (wd:Q3337031, matched via nato), also known as mora, mora wood, nato: the wood from tropical trees in the genus Mora / is instance of type of wood / is subclass of hardwood
6. Nato (wd:Q10605515): island in Lemland, Åland Islands, Finland / is instance of island
7. Nåtö (wd:Q24453737): is instance of village in Finland / island in Finland Proper, Finland / is instance of island
8. Nato (wd:Q6980174): is instance of human settlement / human settlement in Madagascar / human settlement in Madagascar / human settlement in Madagascar
9. Jeanne Natoire (wd:Q34725664, matched via Nato), also known as Mademoiselle Natoire, Mlle Natoire, Nato: French Painter (c. 1700–1776) / has occupation painter / is instance of human
10. Nato (wd:Q37003759): is instance of family name / is instance of surname / family name / family name / surname

[Assistant]
The correct entity for NATO is Q7184, which is described as an intergovernmental military alliance. Now, I will look for the property that indicates the location of NATO headquarters.

Step 2: Search for properties related to the location of NATO (Q7184).

Question: location

Top 10 property alternatives:
1. location (wd:P276 as p/wdt), also known as based in, city, from, held by, in, etc.: location of the object, structure or event. In the case of an ... use P706. Use P7153 for locations associated with the object / location of the item, physical object or event is within. In ... use P131. In case of a distinct terrain feature use P706. / location of the item, physical object or event is within. In ... use P131. In case of a distinct terrain feature use P706.
2. country (wd:P17 as p/wdt), 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
3. headquarters location (wd:P159 as p/wdt, matched via headquarters locality), also known as admin HQ, based in, garrison, head office location, head quarters, etc.: city or town where an organization's headquarters is or has been situated. Use P276 qualifier for specific building / specific location where an organisation's HQ is or has been located / specific location where an organisation's HQ is or has been located / is subproperty of significant place
4. described by source (wd:P1343 as p/wdt, matched via found in), also known as defined in, described by biography, described by encyclopedia, described by obituary, described by reference work, etc.: dictionary, encyclopaedia, etc. where this item is described / work where this item is described / is subproperty of attested in
5. street address (wd:P6375 as p/wdt, matched via address), also known as address, full address, located at street address, mail address, mailing address, etc.: full street address where subject is located. Include ... use also P669 if the street has its own separate item / full street address that the subject is located at. Include ... use also P669 if the street is known as a separate element / full street address that the subject is located at. Include ... use also P669 if the street is known as a separate element
6. owner of (wd:P1830 as p/wdt, matched via owns), also known as owns, owns property, shareholder of, P1830: entities owned by the subject / entities owned by the subject / entities owned by the subject
7. has subsidiary (wd:P355 as p/wdt, matched via owns), also known as daughter company, daughter organization, has imprint, imprint, owns, etc.: subsidiary of a company or organization; generally a fully ... division" (P199). Opposite of parent organization (P749). / subsidiary of a company or organization / is subproperty of has part(s) / is subproperty of owner of / is subproperty of has part
8. Library of Congress authority ID (wd:P244 as p/wdt/wdtn, matched via LOC ID), also known as Authority LCCN, LCAuth ID, LCAuth identifier, LCCN, LCCN (LCSH), etc.: Library of Congress name authority (persons, families, ... by 8-10 digits (see regex). For manifestations, use P1144] / Library of Congress ID for authority control for persons and organisations (for books use P1144) / Library of Congress control number for a name or subject authority record
9. locator map image (wd:P242 as p/wdt, matched via map), also known as locator map, map, map image, P242: geographic map image which highlights the location of the subject within some larger entity / geographic map image which highlights the location of the subject / geographic map image which highlights the location of the subject / is subproperty of image
10. KANTO ID (wd:P8980 as p/wdt/wdtn, matched via KANTO), also known as Asteri ID, finaf, KANTO, P8980: identifier for a person or an organization in the database KANTO curated by the National Library of Finland / is subproperty of URN-NBN

No other items found

[Assistant]
The property "headquarters location" (wdt:P159) is the most relevant for finding the location of NATO's headquarters. Now, I will retrieve the headquarters location of NATO using this property.

Step 3: Execute a SPARQL query to find the headquarters location of NATO (wd:Q7184) using wdt:P159.

execute

SELECT ?headquarters WHERE { wd:Q7184 wdt:P159 ?headquarters }

Got 1 row and 1 column:
| headquarters               |
| -------------------------- |
| City of Brussels (wd:Q239) |

[Assistant]
The NATO headquarters are located in the City of Brussels (Q239). Now, I will confirm the label of this location in English to provide a clear answer.

Step 4: Retrieve the English label for the headquarters location (wd:Q239).

SELECT ?label WHERE { wd:Q239 rdfs:label ?label . FILTER(LANG(?label) = "en") }

Got 1 row and 1 column:
| label                      |
| -------------------------- |
| City of Brussels (lang:en) |

[Assistant]
The NATO headquarters are located in the City of Brussels. I will now provide the final SPARQL query and answer.

answer

SELECT ?label WHERE { wd:Q7184 wdt:P159 ?headquarters . ?headquarters rdfs:label ?label . FILTER(LANG(?label) = "en") }

Answer: The NATO headquarters are located in the City of Brussels.


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 ?book ?bookLabel ?date WHERE {
  ?book wdt:P50 wd:Q207 .
  ?book rdfs:label ?bookLabel .
  FILTER ( LANG( ?bookLabel ) = "en" ) .
  ?book wdt:P577 ?date .
}
ORDER BY DESC ( ?date )
LIMIT 1

Using entities:
- George W. Bush (wd:Q207), also known as Bush, Bush 43, Bush, George W., Bush Jr., Dubya, etc.: has occupation officer / has occupation politician / has occupation businessperson / has occupation statesperson / has occupation financier / has occupation painter / has occupation military officer / has occupation autobiographer / has occupation motivational speaker / has occupation rugby union player / is instance of human / 43rd President of the United States / 43rd President of the United States / President of the United States from 2001 to 2009

Using properties:
- author (wd:P50 as wdt), also known as co-author, creator, maker, playwright, poet, etc.: is subproperty of creator / main creator(s) of a written work (use on works, not humans) / main creator(s) of a written work (use on works, not humans) / main creator(s) of a written work (use on works, not humans); ... name string) when Wikidata item is unknown or does not exist
- publication date (wd:P577 as wdt), also known as air date, airdate, be published during, be published in, broadcast date, etc.: is subproperty of point in time / date or point in time a work is first published or released / date or point in time a work is first published or released / date or point in time when a work was first published or released

Answer: The title of George W. Bush's newest book is 'Portraits of Courage', published in 2017.

The title of George W. Bush's newest book is 'Portraits of Courage', published in 2017.

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 ?book ?bookLabel ?date WHERE {
  ?book wdt:P50 wd:Q207 .
  ?book rdfs:label ?bookLabel .
  FILTER ( LANG( ?bookLabel ) = "en" ) .
  ?book wdt:P577 ?date .
}
ORDER BY DESC ( ?date )
LIMIT 1

Using entities:
- George W. Bush (wd:Q207), also known as Bush, Bush 43, Bush, George W., Bush Jr., Dubya, etc.: has occupation officer / has occupation politician / has occupation businessperson / has occupation statesperson / has occupation financier / has occupation painter / has occupation military officer / has occupation autobiographer / has occupation motivational speaker / has occupation rugby union player / is instance of human / 43rd President of the United States / 43rd President of the United States / President of the United States from 2001 to 2009

Using properties:
- author (wd:P50 as wdt), also known as co-author, creator, maker, playwright, poet, etc.: is subproperty of creator / main creator(s) of a written work (use on works, not humans) / main creator(s) of a written work (use on works, not humans) / main creator(s) of a written work (use on works, not humans); ... name string) when Wikidata item is unknown or does not exist
- publication date (wd:P577 as wdt), also known as air date, airdate, be published during, be published in, broadcast date, etc.: is subproperty of point in time / date or point in time a work is first published or released / date or point in time a work is first published or released / date or point in time when a work was first published or released

Execution result:
Got 1 row and 3 columns:
| book                                | bookLabel                      | date                                |
| ----------------------------------- | ------------------------------ | ----------------------------------- |
| Portraits of Courage (wd:Q29097574) | Portraits of Courage (lang:en) | 2017-01-01T00:00:00Z (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 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 is the title of george bush's new book?

[Assistant]
To determine the title of George Bush's new book, I need to identify which George Bush is being referred to, as there are two prominent U.S. presidents with that name: George H. W. Bush and George W. Bush. Given the context of "new book," it is more likely referring to George W. Bush, as he is more recently active in publishing.

### Step 1: Identify the correct George Bush
I will first search for entities related to "George Bush" to determine which one is more relevant.

Question: george bush

Top 10 entity alternatives:
1. George W. Bush (wd:Q207, matched via George Bush), also known as Bush, Bush 43, Bush, George W., Bush Jr., Dubya, etc.: President of the United States from 2001 to 2009 / has occupation motivational speaker / 43rd President of the United States / 43rd President of the United States / has occupation rugby union player / has occupation military officer / has occupation businessperson / has occupation autobiographer / has occupation statesperson / has occupation politician / has occupation financier / has occupation officer / has occupation painter / is instance of human
2. George H. W. Bush (wd:Q23505, matched via George Bush), also known as Bush 41, Bush I, Bush Senior, Bush Sr., George Bush, etc.: President of the United States from 1989 to 1993 / has occupation baseball player / has occupation aircraft pilot / has occupation autobiographer / has occupation naval officer / has occupation entrepreneur / has occupation Entrepreneur / has occupation statesperson / has occupation politician / has occupation diplomat / has occupation Pilot / has occupation pilot / is instance of human
3. George Bush (wd:Q5537488): American biblical scholar and pastor (1796–1859) / has occupation writer / has occupation pastor / is instance of human
4. George Bush (wd:Q28445429), also known as George Edward Bush: has occupation association football player / association football player (1883-1936) / has occupation soccer player / is instance of human
5. George Bush (wd:Q5537484): has occupation engineer / is instance of human / racing driver
6. George Bush (wd:Q107224832), also known as Simmons: person in the Aberdeen Register of Returned Convicts 1869-1939 / is instance of human
7. George Bush (wd:Q100766406): has occupation basketball player / is instance of human / basketball player
8. George Bush (wd:Q47512688): painting by Daniel Bennett Schwartz / painting by Daniel Bennett Schwartz / is instance of painting
9. George Bush (wd:Q47509378): painting by Ronald N. Sherr / is instance of painting
10. George P. Bush (wd:Q3101841), also known as George Prescott Bush: has occupation military officer / has occupation businessperson / has occupation politician / has occupation officer / has occupation teacher / has occupation lawyer / is instance of human / American businessman / American businessman

[Assistant]
From the search results, the two most prominent individuals are:

1. **George W. Bush** (wd:Q207) — 43rd President of the United States, known for publishing books after his presidency.
2. **George H. W. Bush** (wd:Q23505) — 41st President of the United States, also an autobiographer.

Since the question asks for the **new** book, and George W. Bush has published more recently (e.g., *The American Dream: A Vision for the Future* in 2023), I will focus on George W. Bush.

### Step 2: Check George W. Bush's properties to find his books
I will now look at the properties of George W. Bush (wd:Q207) to identify any book-related properties. Books are often linked via the "work" or "author" relationship. In Wikidata, authors are linked to their works via **P50 (author)**, and works are often instances of **Q47461344 (book)** or **Q571 (book)**.

I will check for works authored by George W. Bush.

list

wd:Q207

[Assistant]
The result is empty, which suggests that the direct property `wdt:P50` (author) is not used for linking George W. Bush to his books. This is common in Wikidata — sometimes the relationship is reversed: books have the author as a qualifier.

So, I will instead search for works (books) where George W. Bush is listed as the author using the **statement pattern** with `p:P50` (author statement) and `ps:P50` (statement value).

I will also check for items that are instances of book (Q571) or literary work (Q47461344) and authored by George W. Bush.

### Step 3: Search for books authored by George W. Bush
I will construct a SPARQL query to find works (books) authored by George W. Bush (wd:Q207), filtering for items that are instances of book (Q571) or literary work (Q47461344), and retrieve their titles (rdfs:label).

execute

SELECT ?book ?bookLabel WHERE { ?book wdt:P50 wd:Q207 . ?book wdt:P31 wd:Q571 . SERVICE wikibase:label { bd:serviceParam wikibase:language "en" } }

[Assistant]
The query returned no results, which suggests that the books authored by George W. Bush may not be directly linked via `wdt:P31 wd:Q571` (book). In Wikidata, some works are classified under more specific types or may not have the `P31` (instance of) property explicitly set.

Let me try a broader approach: find all works (any type) authored by George W. Bush and check their labels. I'll remove the `P31` filter to see if any books appear.

SELECT ?book ?bookLabel WHERE { ?book wdt:P50 wd:Q207 . 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 must use `rdfs:label` with a language filter instead, as per the guidelines.

Let me rewrite the query using `rdfs:label` and `FILTER(LANG(?bookLabel) = "en")` to get the English labels of works authored by George W. Bush.

SELECT ?book ?bookLabel WHERE { ?book wdt:P50 wd:Q207 . ?book rdfs:label ?bookLabel . FILTER(LANG(?bookLabel) = "en") }

Got 398 rows and 2 columns, showing the first 5 and last 5 rows below:
| book                                                                                | bookLabel                                                                                |
| ----------------------------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------- |
| Remarks by US President George W. Bush at the NATO Accession Ceremony in Washington DC, USA (wd:Q112243677) | Remarks by US President George W. Bush at the NATO Accession Ceremony in Washington DC, USA (lang:en) |
| Executive Order 13470 (wd:Q1383597)                                                                         | Executive Order 13470 (lang:en)                                                                       |
| Proclamation 7750 of the President of the USA (wd:Q18330735)                                                | Proclamation 7750 of the President of the USA (lang:en)                                               |
| 41: A Portrait of My Father (wd:Q18786479)                                                                  | 41: A Portrait of My Father (lang:en)                                                                 |
| Freedom and Fear Are at War (wd:Q19036080)                                                                  | Freedom and Fear Are at War (lang:en)                                                                 |
| ...                                                                                | ...                                                                                |
| Executive Order 13438 (wd:Q5419892)                                                                         | Executive Order 13438 (lang:en)                                                                       |
| Executive Order 13440 (wd:Q5419893)                                                                         | Executive Order 13440 (lang:en)                                                                       |
| A Charge to Keep (wd:Q60416508)                                                                             | A Charge to Keep (lang:en)                                                                            |
| Transcript of President Bush's address (wd:Q61743801)                                                       | Transcript of President Bush's address (lang:en)                                                      |
| Decision Points (wd:Q942966)                                                                                | Decision Points (lang:en)                                                                             |

[Assistant]
Now I have results! The list includes several books authored by George W. Bush. Notable ones are:

- **"A Charge to Keep"** (wd:Q60416508)
- **"Decision Points"** (wd:Q942966)
- **"41: A Portrait of My Father"** (wd:Q18786479)

I need to determine which is the **newest** book. To do this, I can check the publication dates. In Wikidata, publication dates for books are often stored as qualifiers on the authorship statement (`p:P50` → `pq:P577` for publication date).

### Step 4: Find the publication dates of George W. Bush's books
I will now extend the query to include the publication date (`pq:P577`) for each book, ordered by date descending to find the most recent one.

I'll also include the book title and publication date in the result.

SELECT ?book ?bookLabel ?date WHERE { ?book wdt:P50 wd:Q207 . ?book rdfs:label ?bookLabel . FILTER(LANG(?bookLabel) = "en") . ?stmt p:P50 ?book . ?stmt pq:P577 ?date . } ORDER BY DESC(?date)

[Assistant]
The query returned no results, which suggests that the publication date (`P577`) is not directly linked as a qualifier on the authorship statement (`p:P50`) for these books. This is unusual, but possible — sometimes the publication date is stored directly on the book item via `wdt:P577`.

Let me try querying for the publication date directly on the book items using `wdt:P577` instead of qualifiers.

SELECT ?book ?bookLabel ?date WHERE { ?book wdt:P50 wd:Q207 . ?book rdfs:label ?bookLabel . FILTER(LANG(?bookLabel) = "en") . ?book wdt:P577 ?date . } ORDER BY DESC(?date)

Got 20 rows and 3 columns, showing the first 5 and last 5 rows below:
| book                                                  | bookLabel                                        | date                                |
| ----------------------------------------------------- | ------------------------------------------------ | ----------------------------------- |
| Portraits of Courage (wd:Q29097574)                   | Portraits of Courage (lang:en)                   | 2017-01-01T00:00:00Z (xsd:dateTime) |
| 41: A Portrait of My Father (wd:Q18786479)            | 41: A Portrait of My Father (lang:en)            | 2014-11-11T00:00:00Z (xsd:dateTime) |
| Decision Points (wd:Q942966)                          | Decision Points (lang:en)                        | 2010-11-09T00:00:00Z (xsd:dateTime) |
| Proclamation 8325 (wd:Q43983370)                      | Proclamation 8325 (lang:en)                      | 2008-12-02T00:00:00Z (xsd:dateTime) |
| Executive Order 13470 (wd:Q1383597)                   | Executive Order 13470 (lang:en)                  | 2008-08-04T00:00:00Z (xsd:dateTime) |
| ...                                                   | ...                                              | ...                                 |
| Executive Order 13233 (wd:Q5419885)                   | Executive Order 13233 (lang:en)                  | 2001-11-05T00:00:00Z (xsd:dateTime) |
| Transcript of President Bush's address (wd:Q61743801) | Transcript of President Bush's address (lang:en) | 2001-09-21T00:00:00Z (xsd:dateTime) |
| Freedom and Fear Are at War (wd:Q19036080)            | Freedom and Fear Are at War (lang:en)            | 2001-09-20T00:00:00Z (xsd:dateTime) |
| A Charge to Keep (wd:Q4655824)                        | A Charge to Keep (lang:en)                       | 1999-01-01T00:00:00Z (xsd:dateTime) |
| A Charge to Keep (wd:Q60416508)                       | A Charge to Keep (lang:en)                       | 1999-01-01T00:00:00Z (xsd:dateTime) |

[Assistant]
Now I have the publication dates! The most recent book authored by George W. Bush is:

- **"Portraits of Courage"** (wd:Q29097574), published on **2017-01-01**

This is the newest book among those listed. Although there may be newer works (e.g., speeches or proclamations), "Portraits of Courage" is a full-length book, and the next closest is "41: A Portrait of My Father" from 2014.

### Step 5: Confirm "Portraits of Courage" is a book
To ensure this is a book and not a different type of work, I'll check its instance of (`P31`) value.

list

wd:Q29097574

[Assistant]
The item "Portraits of Courage" is classified as a **literary work** (wd:Q7725634), which confirms it is a book.

### Final Answer:
The title of George W. Bush's newest book is **"Portraits of Courage"**, published in 2017.

I will now provide the final SPARQL query and answer.

answer

SELECT ?book ?bookLabel ?date WHERE { ?book wdt:P50 wd:Q207 . ?book rdfs:label ?bookLabel . FILTER(LANG(?bookLabel) = "en") . ?book wdt:P577 ?date . } ORDER BY DESC(?date) LIMIT 1

Answer: The title of George W. Bush's newest book is 'Portraits of Courage', published in 2017.