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 ?languageLabel WHERE {
  wd:Q79 wdt:P37 ?language .
  ?language rdfs:label ?languageLabel
  FILTER ( LANG( ?languageLabel ) = "en" )
}

Using entities:
- Egypt (wd:Q79), also known as Arab Rep. Egypt, Arab Republic of Egypt, eg, EGY, Rep. Egypt, etc.: is instance of transcontinental country / is instance of sovereign state / is instance of Mediterranean country / is instance of country / country in Africa and Asia / country in Africa and Asia / country in Africa and Asia / country in Northeast Africa and Southwest Asia

Using properties:
- official language (wd:P37 as wdt), also known as language official, language spoken, speaking, spoken in, P37: is subproperty of language used / language designated as official by this item / language designated as official by this item / language designated as official by this item / language designated as official by this item

Got 1 row and 1 column:
| languageLabel    |
| ---------------- |
| Arabic (lang:en) |

Answer:
The main language spoken in Egypt is Arabic.

Here is the final SPARQL query that retrieves this information:

```sparql
SELECT ?languageLabel WHERE {
  wd:Q79 wdt:P37 ?language .
  ?language rdfs:label ?languageLabel FILTER(LANG(?languageLabel) = "en")
}
```

The answer is: **Arabic**.

The main language spoken in Egypt is Arabic.

Here is the final SPARQL query that retrieves this information:

```sparql
SELECT ?languageLabel WHERE {
  wd:Q79 wdt:P37 ?language .
  ?language rdfs:label ?languageLabel FILTER(LANG(?languageLabel) = "en")
}
```

The answer is: **Arabic**.

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 ?languageLabel WHERE {
  wd:Q79 wdt:P37 ?language .
  ?language rdfs:label ?languageLabel
  FILTER ( LANG( ?languageLabel ) = "en" )
}

Using entities:
- Egypt (wd:Q79), also known as Arab Rep. Egypt, Arab Republic of Egypt, eg, EGY, Rep. Egypt, etc.: is instance of transcontinental country / is instance of sovereign state / is instance of Mediterranean country / is instance of country / country in Africa and Asia / country in Africa and Asia / country in Africa and Asia / country in Northeast Africa and Southwest Asia

Using properties:
- official language (wd:P37 as wdt), also known as language official, language spoken, speaking, spoken in, P37: is subproperty of language used / language designated as official by this item / language designated as official by this item / language designated as official by this item / language designated as official by this item

Execution result:
Got 1 row and 1 column:
| languageLabel    |
| ---------------- |
| Arabic (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 language is mainly spoken in egypt?

[Assistant]
To determine the main language spoken in Egypt, I will follow these steps:

1. Identify the entity for Egypt in Wikidata.
2. Find the property that represents the official or main language of a country.
3. Retrieve the language spoken in Egypt using that property.
4. Return the human-readable label of the language.

First, I will search for the entity for Egypt.

Question: Egypt

Top 10 entity alternatives:
1. Egypt (wd:Q79), also known as Arab Rep. Egypt, Arab Republic of Egypt, eg, EGY, Rep. Egypt, etc.: country in Northeast Africa and Southwest Asia / is instance of transcontinental country / is instance of Mediterranean country / is instance of sovereign state / country in Africa and Asia / country in Africa and Asia / country in Africa and Asia / is instance of country
2. Khedivate of Egypt (wd:Q127861, matched via Egypt), also known as Egypt, Egyptian Khedivate: 1867-1914 monarchy in Northeastern Africa / 1867-1914 monarchy in Northeastern Africa / is instance of transcontinental country / is instance of historical country / is instance of tributary state
3. Egypt Eyalet (wd:Q491507, matched via Egypt), also known as Beylerbeyilik of Egypt, Egypt, Mısır Eyalet, Pashalik of Egypt, QASR of Egypt: is instance of administrative territorial entity of the Ottoman Empire / is instance of Administrative divisions of the Ottoman Empire / is instance of privileged Ottoman province / Egyptian State (1517–1867) / is instance of eyalet / is instance of Eyalet
4. Egypt (wd:Q2083973), also known as Egypt, AK, Egypt, AR: is instance of town in the United States / town in Arkansas
5. Egypt (wd:Q5348306), also known as Egypt, Pennsylvania: is instance of unincorporated community in the United States / human settlement in Pennsylvania, United States
6. Egypt (wd:Q5348296), also known as Egypt, AL, Egypt, Etowah County, Alabama: is instance of census-designated place in the United States / census-designated place in Etowah County, Alabama / is instance of census-designated place
7. Egypt 1156 B.C. (wd:Q3586212, matched via Egypt), also known as Egypt, Egypt 1156 B.C.: Tomb of the Pharaoh: is instance of video game / 1999 video game / 1999 video game / 1999 video game
8. Egypt (wd:Q5348310), also known as Egypt, WV: is instance of unincorporated community in the United States / unincorporated community in Jefferson County, West Virginia
9. Southern Illinois (wd:Q3256684, matched via Egypt), also known as Egypt, Little Egypt: region of Illinois in the United States / is instance of geographical region / is instance of geographic region
10. Egypt (wd:Q5348317): 2004 album by Youssou N'Dour / is instance of album

[Assistant]
The correct entity for Egypt is `wd:Q79`, which represents the Arab Republic of Egypt, a sovereign state in Northeast Africa and Southwest Asia.

Next, I need to find the property that represents the official or main language of a country. I'll search for properties related to "language" for Egypt.

Question: language

Top 10 property alternatives:
1. language used (wd:P2936 as p/wdt, matched via working language), also known as languages used, medium of instruction, used language, uses language, working language, etc.: language widely used (spoken or written) in this place or at this event or organisation
2. official language (wd:P37 as p/wdt, matched via language official), also known as language official, language spoken, speaking, spoken in, P37: language designated as official by this item / language designated as official by this item / language designated as official by this item / language designated as official by this item / is subproperty of language used
3. coat of arms image (wd:P94 as p/wdt, matched via symbol), also known as arms, CoA image, emblem, heraldic, image of coat of arms, representation (heraldic), etc.: image of the item's coat of arms - for the shield part only use P4004 / image of the item's coat of arms / image of the item's coat of arms / is subproperty of image
4. 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))
5. native label (wd:P1705 as p/wdt, matched via official language label), also known as autonym, label in official language, label in original language, name in official language, name in original language, etc.: label for the items in their official language (P37) or their original language (P364) / label for the items in their official language (P37) or their original language (P364) / label for the items in their official language (P37) or their original language (P364) / label for the items in their official language  or their original language / is subproperty of name
6. culture (wd:P2596 as p/wdt), also known as archaeological culture, civilisation, civilization, P2596: human culture or people (or several cultures) associated with this item / human culture or people (or several cultures) associated with this item / human culture or people (or several cultures) associated with this item / is subproperty of part of
7. ethnic group (wd:P172 as p/wdt, matched via culture), also known as (cultural) nationality, culture, ethnicity, ethnic or cultural origin, people, etc.: subject's ethnicity (consensus is that a VERY high standard ... on by scholars, or 3) is fictional and portrayed as such) / subject's ethnicity (consensus is that a VERY high standard ... on by scholars, or 3) is fictional and portrayed as such)
8. 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
9. different from (wd:P1889 as p/wdt, matched via not), also known as confused with, differs from, disambiguated from, distinct from, distinguished from, etc.: item that is different from another item, with which it is often confused / item that is different from another item, with which it may be confused
10. NDL Authority ID (wd:P349 as p/wdt/wdtn, matched via ndl), also known as National Diet Library Auth ID, National Diet Library ID, National Diet Library of Japan authority control ID, National Diet Library of Japan ID, ndl, etc.: identifier for authority control per the National Diet Library of Japan

No other items found

[Assistant]
The property `wdt:P37` (official language) is the most relevant one for determining the main language spoken in Egypt. Now, I will retrieve the official language of Egypt using this property.

SELECT ?language WHERE { wd:Q79 wdt:P37 ?language }

[Assistant]
The official language of Egypt is Arabic, represented by the entity `wd:Q13955`. To provide the human-readable label for this language, I will fetch the label for `wd:Q13955`.

SELECT ?languageLabel WHERE { wd:Q13955 rdfs:label ?languageLabel FILTER(LANG(?languageLabel) = "en") }

Got 1 row and 1 column:
| languageLabel    |
| ---------------- |
| Arabic (lang:en) |

[Assistant]
The main language spoken in Egypt is Arabic.

Here is the final SPARQL query that retrieves this information:

```sparql
SELECT ?languageLabel WHERE {
  wd:Q79 wdt:P37 ?language .
  ?language rdfs:label ?languageLabel FILTER(LANG(?languageLabel) = "en")
}
```

The answer is: **Arabic**.


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?language WHERE {
  wd:Q45 wdt:P37 ?language
}

Using entities:
- Portugal (wd:Q45), also known as POR, Portuguese Republic, PRT: is instance of colonial power / is instance of sovereign state / is instance of country / country in Europe / country in Southwestern Europe / country in Southwestern Europe / republic in Southwestern Europe

Using properties:
- official language (wd:P37 as wdt), also known as language official, language spoken, speaking, spoken in, P37: is subproperty of language used / language designated as official by this item / language designated as official by this item / language designated as official by this item / language designated as official by this item

Got 2 rows and 1 column:
| language              |
| --------------------- |
| Mirandese (wd:Q13330) |
| Portuguese (wd:Q5146) |

Answer: Portuguese people primarily speak Portuguese. Mirandese is also an official regional language in Portugal, but Portuguese is the dominant and most widely spoken language.

Portuguese people primarily speak Portuguese. Mirandese is also an official regional language in Portugal, but Portuguese is the dominant and most widely spoken language.

SPARQL query over wikidata:
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?language WHERE {
  wd:Q45 wdt:P37 ?language
}

Using entities:
- Portugal (wd:Q45), also known as POR, Portuguese Republic, PRT: is instance of colonial power / is instance of sovereign state / is instance of country / country in Europe / country in Southwestern Europe / country in Southwestern Europe / republic in Southwestern Europe

Using properties:
- official language (wd:P37 as wdt), also known as language official, language spoken, speaking, spoken in, P37: is subproperty of language used / language designated as official by this item / language designated as official by this item / language designated as official by this item / language designated as official by this item

Execution result:
Got 2 rows and 1 column:
| language              |
| --------------------- |
| Mirandese (wd:Q13330) |
| Portuguese (wd:Q5146) |

[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 do portuguese people speak?

[Assistant]
To determine what Portuguese people speak, I need to identify the language spoken in Portugal. This involves finding the official or primary language associated with Portugal.

Step 1: Identify the entity for Portugal.
I will search for the entity representing Portugal in Wikidata.

Question: Portugal

Top 10 entity alternatives:
1. Portugal (wd:Q45), also known as POR, Portuguese Republic, PRT: republic in Southwestern Europe / is instance of sovereign state / country in Southwestern Europe / country in Southwestern Europe / is instance of colonial power / is instance of country / country in Europe
2. Portugal (wd:Q14110517): is instance of toponymic surname / is instance of family name / is instance of surname / family name / family name / surname
3. Portugal (wd:Q21087356): comic book Cyril Pedrosa / is instance of comics
4. Portugal (wd:Q7232531): is instance of constituency of the European Parliament / constituency of the European Parliament
5. Portugal (wd:Q130240890): edition in ''The National Anthems of the Allies'' (1917) / is instance of version, edition or translation
6. Portugal (wd:Q10638037): is instance of single / single
7. Portugal (wd:Q19536374): is instance of musical work/composition
8. Portugal (wd:Q17614311): farm in Beemster, Netherlands; Rijksmonument / is instance of farm
9. Portugal (wd:Q22323850): is instance of short film / short film
10. Portugal (wd:Q31697898): mountain in South Africa / is instance of mountain

[Assistant]
The top result for Portugal is wd:Q45, which represents the sovereign state of Portugal in Southwestern Europe. This is the correct entity to use.

Step 2: Find the official language of Portugal.
I will now search for properties related to the language spoken in Portugal. I'll use search_property_of_entity to find properties associated with Portugal that might indicate its language.

Question: language

Top 10 property alternatives:
1. language used (wd:P2936 as p/wdt, matched via working language), also known as languages used, medium of instruction, used language, uses language, working language, etc.: language widely used (spoken or written) in this place or at this event or organisation
2. official language (wd:P37 as p/wdt, matched via language official), also known as language official, language spoken, speaking, spoken in, P37: language designated as official by this item / language designated as official by this item / language designated as official by this item / language designated as official by this item / is subproperty of language used
3. coat of arms image (wd:P94 as p/wdt, matched via symbol), also known as arms, CoA image, emblem, heraldic, image of coat of arms, representation (heraldic), etc.: image of the item's coat of arms - for the shield part only use P4004 / image of the item's coat of arms / image of the item's coat of arms / is subproperty of image
4. located in/on physical feature (wd:P706 as p/wdt, matched via on), also known as geographical region, is in, is on, landform, located on island, etc.: located on the specified landform or body of water. Should ... (provinces, states, countries, etc.). / located on the specified (geo)physical feature. Should not be ... political/administrative (P131) or a mountain range (P4552). / is subproperty of location / is subproperty of part of
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. native label (wd:P1705 as p/wdt, matched via official language label), also known as autonym, label in official language, label in original language, name in official language, name in original language, etc.: label for the items in their official language (P37) or their original language (P364) / label for the items in their official language (P37) or their original language (P364) / label for the items in their official language (P37) or their original language (P364) / label for the items in their official language  or their original language / is subproperty of name
7. culture (wd:P2596 as p/wdt), also known as archaeological culture, civilisation, civilization, P2596: human culture or people (or several cultures) associated with this item / human culture or people (or several cultures) associated with this item / human culture or people (or several cultures) associated with this item / is subproperty of part of
8. 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
9. NDL Authority ID (wd:P349 as p/wdt/wdtn, matched via ndl), also known as National Diet Library Auth ID, National Diet Library ID, National Diet Library of Japan authority control ID, National Diet Library of Japan ID, ndl, etc.: identifier for authority control per the National Diet Library of Japan
10. 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

No other items found

[Assistant]
The property "official language" (wdt:P37) is the most relevant here, as it directly indicates the language designated as official by a country.

Step 3: Query for the official language of Portugal using wdt:P37.
I will now execute a SPARQL query to find the official language of Portugal (wd:Q45) using the property wdt:P37.

execute

SELECT ?language WHERE { wd:Q45 wdt:P37 ?language }

Got 2 rows and 1 column:
| language              |
| --------------------- |
| Mirandese (wd:Q13330) |
| Portuguese (wd:Q5146) |

[Assistant]
The query shows that Portugal has two official languages: Portuguese (wd:Q5146) and Mirandese (wd:Q13330). However, Portuguese is the primary and most widely spoken language, while Mirandese is a regional language spoken in a small area of northeastern Portugal.

Since the question asks "what do Portuguese people speak?" — implying the primary or most common language — the answer is Portuguese.

I will now provide the final answer with the SPARQL query that retrieves this information.

answer

SELECT ?language WHERE { wd:Q45 wdt:P37 ?language }

Answer: Portuguese people primarily speak Portuguese. Mirandese is also an official regional language in Portugal, but Portuguese is the dominant and most widely spoken language.


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 ?player ?playerLabel WHERE {
  ?player wdt:P647 wd:Q162990 .
  ?player rdfs:label ?playerLabel .
  FILTER ( LANG( ?playerLabel ) = "en" )
}

Using entities:
- Cleveland Cavaliers (wd:Q162990), also known as Cavaliers, Cavs, Cleveland Cavs: is instance of basketball team / National Basketball Association team in Cleveland, Ohio

Using properties:
- drafted by (wd:P647 as wdt), also known as P647: by which team the player was drafted / which team the player was drafted by

Got 117 rows and 2 columns, showing the first 5 and last 5 rows below:
| player                        | playerLabel                |
| ----------------------------- | -------------------------- |
| Larry Sanders (wd:Q1034012)   | Larry Sanders (lang:en)    |
| LeBron James (wd:Q108870659)  | LeBron James (lang:en)     |
| Eddie Jordan (wd:Q1134403)    | Eddie Jordan (lang:en)     |
| Reggie Geary (wd:Q115509)     | Reggie Geary (lang:en)     |
| DeSagana Diop (wd:Q1179612)   | DeSagana Diop (lang:en)    |
| ...                           | ...                        |
| Austin Carr (wd:Q933952)      | Austin Carr (lang:en)      |
| Winston Bennett (wd:Q943368)  | Winston Bennett (lang:en)  |
| Mickey Dillard (wd:Q962929)   | Mickey Dillard (lang:en)   |
| Ben McDonald (wd:Q967072)     | Ben McDonald (lang:en)     |
| Tristan Thompson (wd:Q973212) | Tristan Thompson (lang:en) |

Answer: The Cleveland Cavaliers have drafted 117 players in NBA history. Notable players include LeBron James, Austin Carr, and Tristan Thompson. The full list includes all players selected by the team in the NBA draft, as recorded in Wikidata.

The Cleveland Cavaliers have drafted 117 players in NBA history. Notable players include LeBron James, Austin Carr, and Tristan Thompson. The full list includes all players selected by the team in the NBA draft, as recorded in Wikidata.

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 ?player ?playerLabel WHERE {
  ?player wdt:P647 wd:Q162990 .
  ?player rdfs:label ?playerLabel .
  FILTER ( LANG( ?playerLabel ) = "en" )
}

Using entities:
- Cleveland Cavaliers (wd:Q162990), also known as Cavaliers, Cavs, Cleveland Cavs: is instance of basketball team / National Basketball Association team in Cleveland, Ohio

Using properties:
- drafted by (wd:P647 as wdt), also known as P647: by which team the player was drafted / which team the player was drafted by

Execution result:
Got 117 rows and 2 columns, showing the first 5 and last 5 rows below:
| player                        | playerLabel                |
| ----------------------------- | -------------------------- |
| Larry Sanders (wd:Q1034012)   | Larry Sanders (lang:en)    |
| LeBron James (wd:Q108870659)  | LeBron James (lang:en)     |
| Eddie Jordan (wd:Q1134403)    | Eddie Jordan (lang:en)     |
| Reggie Geary (wd:Q115509)     | Reggie Geary (lang:en)     |
| DeSagana Diop (wd:Q1179612)   | DeSagana Diop (lang:en)    |
| ...                           | ...                        |
| Austin Carr (wd:Q933952)      | Austin Carr (lang:en)      |
| Winston Bennett (wd:Q943368)  | Winston Bennett (lang:en)  |
| Mickey Dillard (wd:Q962929)   | Mickey Dillard (lang:en)   |
| Ben McDonald (wd:Q967072)     | Ben McDonald (lang:en)     |
| Tristan Thompson (wd:Q973212) | Tristan Thompson (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 the cleveland cavaliers draft?

[Assistant]
To answer the question "Who did the Cleveland Cavaliers draft?", we need to identify the players drafted by the Cleveland Cavaliers in the NBA draft. This requires finding draft picks associated with the Cleveland Cavaliers team.

### Step 1: Identify the entity for the Cleveland Cavaliers
First, we need to find the Wikidata entity for the Cleveland Cavaliers.

Let's search for "Cleveland Cavaliers".

Question: Cleveland Cavaliers

Top 10 entity alternatives:
1. Cleveland Cavaliers (wd:Q162990), also known as Cavaliers, Cavs, Cleveland Cavs: National Basketball Association team in Cleveland, Ohio / is instance of basketball team
2. history of the Cleveland Cavaliers (wd:Q20710370, matched via Cleveland Cavaliers history), also known as Cleveland Cavaliers history, the Cleveland Cavaliers history: is instance of aspect of history / aspect of history
3. 2022–23 Cleveland Cavaliers season (wd:Q112133040): NBA professional basketball team season / is instance of basketball team season
4. 2023–24 Cleveland Cavaliers season (wd:Q118908694): is instance of basketball team season / 2023–24 NBA season by team
5. 2015–16 Cleveland Cavaliers season (wd:Q20020792): NBA professional basketball team season (won championship) / is instance of basketball team season
6. 2018–19 Cleveland Cavaliers season (wd:Q54958273): season of National Basketball Association team the Cleveland Cavaliers / is instance of basketball team season
7. 2021–22 Cleveland Cavaliers season (wd:Q107570641): NBA season for the Cleveland Cavaliers (2021-2022) / is instance of basketball team season
8. 2017–18 Cleveland Cavaliers season (wd:Q30641924): NBA professional basketball team season / is instance of basketball team season
9. 2016–17 Cleveland Cavaliers season (wd:Q24909427), also known as 2016-17 Cleveland Cavaliers season: NBA professional basketball team season / is instance of basketball team season
10. 2019–20 Cleveland Cavaliers season (wd:Q63859185): NBA professional basketball team season / is instance of basketball team season

[Assistant]
The main entity for the Cleveland Cavaliers is `wd:Q162990`, which is the basketball team itself. Now, we need to find out which players were drafted by the Cleveland Cavaliers.

### Step 2: Identify the property for draft picks
We need to find a property that links the Cleveland Cavaliers to the players they drafted. In Wikidata, draft picks are often recorded using properties like:

- `wdt:P1178` — "drafted by" (used for athletes drafted by teams)
- `wdt:P159` — "headquarters" (not relevant here)
- `wdt:P1346` — "winner" (not relevant)

Let’s check if `wdt:P1178` is used for drafting players by teams.

We can search for properties related to "draft" for the Cleveland Cavaliers.

Question: draft

Top 10 property alternatives:
1. 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))
2. logo image (wd:P154 as p/wdt, matched via mark), also known as insignia, logo, logomark, mark, marque, etc.: graphic mark or emblem commonly used by commercial enterprises, organisations and products / graphic mark or emblem commonly used by commercial enterprises, organisations and products / graphic mark or emblem commonly used by commercial enterprises, organizations and products / graphic mark or emblem commonly used by commercial enterprises, organizations and products / is subproperty of icon
3. 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
4. official website (wd:P856 as p/wdt, matched via official page), 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
5. home venue (wd:P115 as p/wdt, matched via venue), also known as arena, ballpark, ground, home field, home ground, etc.: home stadium or venue of a sports team or applicable performing arts organization / home stadium or venue of a sports team or applicable performing arts organization / home stadium or venue of a sports team or applicable performing arts organization / is subproperty of location
6. image (wd:P18 as p/wdt, matched via portrait), also known as camera picture, Commons image, drawing, File:, graph, etc.: image of relevant illustration of the subject; if available, ... only images which exist on Wikimedia Commons are acceptable / image of relevant illustration of the subject; if available, ... only images which exist on Wikimedia Commons are acceptable / image of relevant illustration of the subject; if available, ... map, flag image, signature image, logo image, collage image) / image of relevant illustration of the subject; if available, ... map, flag image, signature image, logo image, collage image)
7. Library of Congress authority ID (wd:P244 as p/wdt/wdtn, matched via P244), 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
8. Commons category (wd:P373 as p/wdt, matched via P373), also known as category Commons, category on Commons, category on Wikimedia Commons, category Wikipedia Commons, commonscat, etc.: name of the Wikimedia Commons category containing files related to this item (without the prefix "Category:") / name of the Wikimedia Commons category containing files related to this item (without the prefix "Category") / name of the Wikimedia Commons category containing files related to this item (without the prefix "Category")
9. instance of (wd:P31 as p/wdt, matched via P31), 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)
10. VIAF cluster ID (wd:P214 as p/wdt/wdtn, matched via P214), also known as VIAF, VIAF ID, VIAF identifier, viaf.org ID, Virtual International Authority File, etc.: identifier for the Virtual International Authority File ... note: VIAF is a cluster, the ID can include multiple items / Virtual International Authority File identifier

No other items found

[Assistant]
The search for properties related to "draft" for the Cleveland Cavaliers did not return `wdt:P1178` (drafted by) directly. However, `wdt:P1178` is a standard property used in Wikidata to indicate which team drafted a player. We should verify if this property exists and is used for players associated with the Cleveland Cavaliers.

Let’s search for the property `drafted by` directly to confirm its ID.

Question: drafted by

Top 10 property alternatives:
1. drafted by (wd:P647 as ps/psv/p/pqv/pqn/psn/pq/wdt/pr/prn/prv/wdtn), also known as P647: by which team the player was drafted / which team the player was drafted by
2. study or design for (wd:P6606 as ps/psv/p/pqv/pqn/psn/pq/wdt/pr/prn/prv/wdtn, matched via draft for), also known as design for, draft for, first version of, preparatory work for, study for, etc.: finished work of art for which the subject is a preliminary study, design, or conceptual drawing / finished work of art for which the subject is a preliminary study, design or conceptual drawing
3. theorized by (wd:P8403 as ps/psv/p/pqv/pqn/psn/pq/wdt/pr/prn/prv/wdtn, matched via proposed by), also known as author, authored by, defined by, explained by, named by, etc.: subject who suggested or proposed this concept or immaterial invention / subject who suggested or proposed this concept or immaterial invention
4. author (wd:P50 as ps/psv/p/pqv/pqn/psn/pq/wdt/pr/prn/prv/wdtn, matched via written by), also known as co-author, creator, maker, playwright, poet, etc.: main creator(s) of a written work (use on works, not humans); ... name string) when Wikidata item is unknown or does not exist / main creator(s) of a written work (use on works, not humans) / main creator(s) of a written work (use on works, not humans) / is subproperty of creator
5. developer (wd:P178 as ps/psv/p/pqv/pqn/psn/pq/wdt/pr/prn/prv/wdtn, matched via written by), also known as created by, dev, developed by, game dev, game developer, etc.: organisation or person that developed this item / organization or person that developed the item / is subproperty of creator
6. screenwriter (wd:P58 as ps/psv/p/pqv/pqn/psn/pq/wdt/pr/prn/prv/wdtn, matched via written by), also known as film script by, game writer, scenarist, screenplay by, scriptwriter, etc.: author(s) of the screenplay or script for this work / author(s) of the screenplay or script for this work / person(s) who wrote the script for subject item / is subproperty of film crew member / is subproperty of author
7. composer (wd:P86 as ps/psv/p/pqv/pqn/psn/pq/wdt/pr/prn/prv/wdtn, matched via written by), also known as composed by, film score by, musical score by, music by, songwriter, etc.: person(s) who wrote the music [for lyricist, use "lyrics by" (P676)] / person(s) who wrote the music; also use P676 for lyricist / person(s) who wrote the music; also use P676 for lyricist / is subproperty of creator
8. discoverer or inventor (wd:P61 as ps/psv/p/pqv/pqn/psn/pq/wdt/pr/prn/prv/wdtn, matched via devised by), also known as created by, developed by, developer, devised by, discovered by, etc.: subject who discovered, first described, invented, or developed this discovery or invention or scientific hypothesis or theory / discovered, first described, or invented by / discovered, first described, or invented by
9. has written for (wd:P6872 as ps/psv/p/pqv/pqn/psn/pq/wdt/pr/prn/prv/wdtn, matched via written for), also known as is writing for, writer for, writes for, written for, wrote for, etc.: publication an author has contributed to / publication an author has contributed to
10. location of creation (wd:P1071 as ps/psv/p/pqv/pqn/psn/pq/wdt/pr/prn/prv/wdtn, matched via written at), also known as assembly location, built at, built in, composed at, created at, etc.: place where the item was conceived or made; where applicable, location of final assembly / is subproperty of significant place

[Assistant]
Great! We found the property `wdt:P647` — "drafted by" — which links a player to the team that drafted them.

Now, we need to find all players who were drafted by the Cleveland Cavaliers (`wd:Q162990`). The query will:

- Find all items (`?player`) where `wdt:P647` (drafted by) is `wd:Q162990` (Cleveland Cavaliers).
- Optionally, get the label of each player in English for readability.

We'll construct a SPARQL query to retrieve this information.

### Step 3: Construct and execute the SPARQL query
Let’s write and execute the query:

execute

SELECT ?player ?playerLabel WHERE { ?player wdt:P647 wd:Q162990. 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 we used `SERVICE wikibase:label`, which is not supported in this environment. We must use `rdfs:label` with a language filter instead.

Let’s revise the query to use `rdfs:label` and filter for English labels.

### Step 4: Rewrite the SPARQL query without `SERVICE wikibase:label`
We'll now use:
- `?player wdt:P647 wd:Q162990` to find players drafted by the Cavaliers.
- `?player rdfs:label ?playerLabel` to get their labels.
- `FILTER(LANG(?playerLabel) = "en")` to get only English labels.

Let’s execute the corrected query:

SELECT ?player ?playerLabel WHERE { ?player wdt:P647 wd:Q162990. ?player rdfs:label ?playerLabel . FILTER(LANG(?playerLabel) = "en") }

Got 117 rows and 2 columns, showing the first 5 and last 5 rows below:
| player                        | playerLabel                |
| ----------------------------- | -------------------------- |
| Larry Sanders (wd:Q1034012)   | Larry Sanders (lang:en)    |
| LeBron James (wd:Q108870659)  | LeBron James (lang:en)     |
| Eddie Jordan (wd:Q1134403)    | Eddie Jordan (lang:en)     |
| Reggie Geary (wd:Q115509)     | Reggie Geary (lang:en)     |
| DeSagana Diop (wd:Q1179612)   | DeSagana Diop (lang:en)    |
| ...                           | ...                        |
| Austin Carr (wd:Q933952)      | Austin Carr (lang:en)      |
| Winston Bennett (wd:Q943368)  | Winston Bennett (lang:en)  |
| Mickey Dillard (wd:Q962929)   | Mickey Dillard (lang:en)   |
| Ben McDonald (wd:Q967072)     | Ben McDonald (lang:en)     |
| Tristan Thompson (wd:Q973212) | Tristan Thompson (lang:en) |

[Assistant]
The query successfully returned 117 players drafted by the Cleveland Cavaliers, with their English labels. This confirms that the property `wdt:P647` ("drafted by") correctly links players to the team.

### Final Answer
The Cleveland Cavaliers have drafted 117 players in NBA history. Some notable names include LeBron James, Austin Carr, and Tristan Thompson. The full list includes all players selected by the team in the NBA draft, as recorded in Wikidata.

Here is the final SPARQL query that retrieves the list of players drafted by the Cleveland Cavaliers:

```sparql
SELECT ?player ?playerLabel WHERE {
  ?player wdt:P647 wd:Q162990.
  ?player rdfs:label ?playerLabel .
  FILTER(LANG(?playerLabel) = "en")
}
```

This query returns the Wikidata IDs and English names of all players drafted by the Cleveland Cavaliers.

answer

SELECT ?player ?playerLabel WHERE { ?player wdt:P647 wd:Q162990. ?player rdfs:label ?playerLabel . FILTER(LANG(?playerLabel) = "en") }

Answer: The Cleveland Cavaliers have drafted 117 players in NBA history. Notable players include LeBron James, Austin Carr, and Tristan Thompson. The full list includes all players selected by the team in the NBA draft, as recorded in Wikidata.