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 ?language ?languageLabel WHERE {
  wd:Q233 wdt:P37 ?language .
  ?language rdfs:label ?languageLabel .
  FILTER ( LANG( ?languageLabel ) = "en" )
}

Using entities:
- Malta (wd:Q233), also known as MLT, MT, Republic of Malta: is instance of sovereign state / is instance of country / country in Europe / island republic in Europe / sovereign state in Southern Europe situated on an archipelago in the Mediterranean Sea / sovereign state in Southern Europe situated on an archipelago in the Mediterranean Sea

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 2 columns:
| language           | languageLabel     |
| ------------------ | ----------------- |
| English (wd:Q1860) | English (lang:en) |
| Maltese (wd:Q9166) | Maltese (lang:en) |

Answer: The Maltese speak Maltese and English as official languages. Maltese is the national language, and English is also an official language used in government and education.

The Maltese speak Maltese and English as official languages. Maltese is the national language, and English is also an official language used in government and education.

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 ?language ?languageLabel WHERE {
  wd:Q233 wdt:P37 ?language .
  ?language rdfs:label ?languageLabel .
  FILTER ( LANG( ?languageLabel ) = "en" )
}

Using entities:
- Malta (wd:Q233), also known as MLT, MT, Republic of Malta: is instance of sovereign state / is instance of country / country in Europe / island republic in Europe / sovereign state in Southern Europe situated on an archipelago in the Mediterranean Sea / sovereign state in Southern Europe situated on an archipelago in the Mediterranean Sea

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 2 columns:
| language           | languageLabel     |
| ------------------ | ----------------- |
| English (wd:Q1860) | English (lang:en) |
| Maltese (wd:Q9166) | Maltese (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 do maltese speak?

[Assistant]
To determine what language the Maltese speak, I need to find the official or primary language spoken in Malta. This involves identifying the country Malta and then finding its official language.

### Step 1: Search for the entity "Malta"
I will first search for the entity corresponding to Malta to confirm its Wikidata identifier.

Question: Malta

Top 10 entity alternatives:
1. Malta (wd:Q233), also known as MLT, MT, Republic of Malta: sovereign state in Southern Europe situated on an archipelago in the Mediterranean Sea / sovereign state in Southern Europe situated on an archipelago in the Mediterranean Sea / is instance of sovereign state / island republic in Europe / is instance of country / country in Europe
2. Malta (wd:Q193896): is instance of island / island in Malta / island in Malta / island of Malta
3. Malta (wd:Q963370), also known as Malta, Montana, Malta, MT: city in and county seat of Phillips County, Montana, United States / is instance of city in the United States / is instance of city of the United States / is instance of county seat
4. Malta (wd:Q993877), also known as Malta, ID, Malta, Idaho: city in Cassia County, Idaho, United States / is instance of city in the United States / is instance of city of the United States
5. Malta (wd:Q340115): municipality in Spittal an der Drau District, Carinthia, Austria / is instance of rural municipality of Austria / is instance of municipality of Austria
6. Malta (wd:Q2672411), also known as Malta, IL: village in DeKalb County, Illinois, United States / is instance of village of Illinois
7. Malta (wd:Q2666766), also known as Malta, OH: village in Morgan County, Ohio, United States / is instance of village of Ohio
8. Malta (wd:Q2329682), also known as Santa Rita do Malta: is instance of municipality of Brazil / municipality in Paraíba, Brazil
9. Malta (wd:Q3708930), also known as Malta, New York, Malta, NY: town in Saratoga County, New York, United States / is instance of town in the United States / is instance of town of New York
10. Malta (wd:Q1632080), also known as Nova: is instance of pop duo / Swedish duo

[Assistant]
The top result is **Malta (wd:Q233)**, which is the sovereign state in Southern Europe. This is the correct entity for the country Malta.

### Step 2: Find the official language of Malta
Now, I will search for properties related to the official language of Malta. I can use `search_property_of_entity` to find relevant properties for Malta (wd:Q233) with the query "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. 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 most relevant property here is **official language (wd:P37)**, which is explicitly defined as the language designated as official by a country or region. This is exactly what we need.

### Step 3: Query for the official language of Malta (wd:Q233)
I will now construct a SPARQL query to retrieve the official language of Malta using `wdt:P37`. I will also fetch the label of the language in English for readability.

execute

SELECT ?language ?languageLabel WHERE { wd:Q233 wdt:P37 ?language . SERVICE wikibase:label { bd:serviceParam wikibase:language "en". } }

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

301 Moved Permanently'

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

### Step 4: Rewrite the query using `rdfs:label` instead of `SERVICE wikibase:label`
I will now execute a corrected SPARQL query that retrieves the official language of Malta and its English label using `rdfs:label` and `FILTER(LANG(?languageLabel) = "en")`.

SELECT ?language ?languageLabel WHERE { wd:Q233 wdt:P37 ?language . ?language rdfs:label ?languageLabel . FILTER(LANG(?languageLabel) = "en") }

Got 2 rows and 2 columns:
| language           | languageLabel     |
| ------------------ | ----------------- |
| English (wd:Q1860) | English (lang:en) |
| Maltese (wd:Q9166) | Maltese (lang:en) |

[Assistant]
The query returns two official languages of Malta: **English** and **Maltese**. Both are recognized as official languages in Malta.

### Final Answer:
The Maltese speak **Maltese** and **English** as official languages. Maltese is the national language and the most widely spoken, while English is also an official language used in government, education, and business.

I will now provide the final SPARQL query and answer.

answer

SELECT ?language ?languageLabel WHERE { wd:Q233 wdt:P37 ?language . ?language rdfs:label ?languageLabel . FILTER(LANG(?languageLabel) = "en") }

Answer: The Maltese speak Maltese and English as official languages. Maltese is the national language, and English is also an official language used in government and education.


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 ?originLabel WHERE {
  wd:Q8216 wdt:P144 ?origin .
  ?origin rdfs:label ?originLabel .
  FILTER ( LANG( ?originLabel ) = "en" )
}

Using entities:
- Greek alphabet (wd:Q8216), also known as Greek, Greek script: is instance of natural writing system / is instance of bicameral script / is instance of alphabet / script used to write the Greek language

Using properties:
- based on (wd:P144 as wdt), also known as adaptation of, adapted from, based on work, based upon, continuation of, etc.: is subproperty of references work, tradition or theory / is subproperty of inspired by / the work(s) or inputs used as the basis for subject item; for fictional analog use P1074 / the work(s) used as basis for subject

Got 1 row and 1 column:
| originLabel                 |
| --------------------------- |
| Phoenician script (lang:en) |

Answer: The Greek alphabet came from the Phoenician script.

The Greek alphabet came from the Phoenician script.

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 ?originLabel WHERE {
  wd:Q8216 wdt:P144 ?origin .
  ?origin rdfs:label ?originLabel .
  FILTER ( LANG( ?originLabel ) = "en" )
}

Using entities:
- Greek alphabet (wd:Q8216), also known as Greek, Greek script: is instance of natural writing system / is instance of bicameral script / is instance of alphabet / script used to write the Greek language

Using properties:
- based on (wd:P144 as wdt), also known as adaptation of, adapted from, based on work, based upon, continuation of, etc.: is subproperty of references work, tradition or theory / is subproperty of inspired by / the work(s) or inputs used as the basis for subject item; for fictional analog use P1074 / the work(s) used as basis for subject

Execution result:
Got 1 row and 1 column:
| originLabel                 |
| --------------------------- |
| Phoenician script (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 did the greek alphabet come from?

[Assistant]
To determine where the Greek alphabet came from, I need to find information about its origin. The Greek alphabet is a writing system, so I should look for entities related to its origin or development.

Step 1: Search for entities related to the "Greek alphabet" to identify the correct item in Wikidata.

Question: Greek alphabet

Top 10 entity alternatives:
1. Greek alphabet (wd:Q8216), also known as Greek, Greek script: script used to write the Greek language / is instance of natural writing system / is instance of bicameral script / is instance of alphabet
2. history of the Greek alphabet (wd:Q2627294, matched via Greek alphabet history), also known as Greek alphabet history, the Greek alphabet history: is instance of aspect of history / aspect of history
3. Greek Albanian alphabet (wd:Q3305475): Greek alphabet adapted for writing the Albanian language / is instance of alphabet
4. extended greek alphabet (wd:Q3237041): is subclass of Greek letter
5. Greek spelling alphabet (wd:Q17003959): spelling alphabet for Greek letters / is instance of spelling alphabet
6. ancient Greek alphabet (wd:Q3611036), also known as archaic Greek alphabet: is instance of alphabet / writing system
7. archaic Greek alphabets (wd:Q2839562): Local variants of the ancient Greek alphabet / is subclass of Greek alphabet / is instance of alphabet
8. Inscriptions in Greek Alphabet (wd:Q106814190): drawing - Sir Robert Smirke the younger / is instance of drawing
9. Inscriptions in Greek Alphabet (wd:Q106814193): drawing - Sir Robert Smirke the younger (YCBA B1977.14.581) / is instance of drawing
10. Lexilogos Ancient Greek > Latin alphabet conversion (wd:Q124337511, matched via Greek > Latin alphabet conversion), also known as Ancient Greek > Latin alphabet conversion, Greek > Latin alphabet conversion, Lexilogos Greek > Latin alphabet conversion: Romanization system of Ancient Greek characters into the Latin script / is instance of romanisation system

[Assistant]
The primary entity for the Greek alphabet is wd:Q8216, which is described as a "natural writing system" and an "alphabet." I will now investigate its origin by exploring its properties, particularly those related to its development or origin.

Step 2: Use `list` to examine the triples associated with wd:Q8216 (Greek alphabet) to identify relevant properties such as origin, derived from, or historical development.

list

wd:Q8216

Got 794 rows and 3 columns, showing the first 10 rows below:
| subject                   | property                                       | object                                                                                |
| ------------------------- | ---------------------------------------------- | ------------------------------------------------------------------------------------------ |
| Greek alphabet (wd:Q8216) | instance of (wdt:P31)                          | alphabet (wd:Q9779)                                                                        |
| Greek alphabet (wd:Q8216) | language of work or name (wdt:P407)            | Greek (wd:Q9129)                                                                           |
| Greek alphabet (wd:Q8216) | Commons category (wdt:P373)                    | Greek alphabet                                                                             |
| Greek alphabet (wd:Q8216) | image (wdt:P18)                                | <http://commons.wikimedia.org/wiki/Special:FilePath/Griechisches%20Stra%C3%9Fenschild.JPG> |
| Greek alphabet (wd:Q8216) | Freebase ID (wdt:P646)                         | /m/0358gm                                                                                |
| Greek alphabet (wd:Q8216) | inception (wdt:P571)                           | -0900-01-01T00:00:00Z (xsd:dateTime)                                                       |
| Greek alphabet (wd:Q8216) | has part(s) (wdt:P527)                         | Φ (wd:Q10029)                                                                              |
| Greek alphabet (wd:Q8216) | described by source (wdt:P1343)                | wd:Q2041543                                                                                |
| Greek alphabet (wd:Q8216) | Library of Congress authority ID (wdtn:P244)   | <http://id.loc.gov/authorities/names/sh85057152>                                           |
| Greek alphabet (wd:Q8216) | on focus list of Wikimedia project (wdt:P5008) | wd:Q5460604                                                                                |
| ...                       | ...                                            | ...                                                                                |

[Assistant]
From the triples, I see that the Greek alphabet (wd:Q8216) has an "inception" date (wdt:P571) around 900 BCE, but there is no direct property indicating its origin or source. However, the property "described by source" (wdt:P1343) links to wd:Q2041543, which might provide context. Additionally, historically, the Greek alphabet is known to have been derived from the Phoenician alphabet. I should check if there is a property like "derived from" or "originated from" that connects the Greek alphabet to the Phoenician alphabet.

Step 3: Search for properties related to "derived from" or "origin" to see if any such property links the Greek alphabet to its source.

Question: derived from

Top 10 property alternatives:
1. natural product of taxon (wd:P1582 as ps/psv/p/pqv/pqn/psn/pq/wdt/pr/prn/prv/wdtn, matched via derived from), also known as comes from (taxon), derived from, fruit of (taxon), made from, produced by taxon, etc.: links a natural product with its source (animal, plant, fungal, algal, etc.) / links a natural product with its source (animal, plant, fungal, algal, etc.)
2. based on (wd:P144 as ps/psv/p/pqv/pqn/psn/pq/wdt/pr/prn/prv/wdtn, matched via derived from), also known as adaptation of, adapted from, based on work, based upon, continuation of, etc.: the work(s) or inputs used as the basis for subject item; for fictional analog use P1074 / is subproperty of references work, tradition or theory / the work(s) used as basis for subject / is subproperty of inspired by
3. derived from lexeme (wd:P5191 as ps/psv/p/pqv/pqn/psn/pq/wdt/pr/prn/prv/wdtn, matched via derived from), also known as derived from, etymology, history of a word, loaned from, origin of a word, etc.: most direct lexeme(s) this one has developed from / most direct lexeme(s) this one has developed from / most direct lexeme(s) this one has developed from
4. object form (wd:P5548 as ps/psv/p/pqv/pqn/psn/pq/wdt/pr/prn/prv/wdtn, matched via derived from form), also known as combined form, compound form, derived from form, from form, P5548: (qualifier) statement applies only to listed forms of statement's object
5. object sense (wd:P5980 as ps/psv/p/pqv/pqn/psn/pq/wdt/pr/prn/prv/wdtn, matched via derived from sense), also known as derived from sense, sense derivation, P5980: (qualifier) statement applies only to listed senses of statement's object
6. semantic derivation of (wd:P12410 as ps/psv/p/pqv/pqn/psn/pq/wdt/pr/prn/prv/wdtn, matched via derived from sense), also known as derived from sense, sense derived from sense, P12410: links a lexeme sense to a particular sense it is derived from
7. location of formation (wd:P740 as ps/psv/p/pqv/pqn/psn/pq/wdt/pr/prn/prv/wdtn, matched via comes from), also known as comes from, formation location, formation place, formed in, founded in, etc.: location where a group or organisation was formed / location where a group or organization was formed / is subproperty of location of creation
8. country of origin (wd:P495 as ps/psv/p/pqv/pqn/psn/pq/wdt/pr/prn/prv/wdtn, matched via comes from), also known as comes from, CoO, country, originates from, origin country, etc.: country of origin of this item (creative work, food, phrase, product, etc.) / country of origin of this item (creative work, food, phrase, product, etc.) / country of origin of this item (creative work, food, phrase, product, etc.) / is subproperty of significant place / is subproperty of country
9. develops from (wd:P3094 as ps/psv/p/pqv/pqn/psn/pq/wdt/pr/prn/prv/wdtn, matched via developed from), also known as antecedent anatomical structure, developed from, evolved from, evolves from, P3094: this class of items develops from another class of items (biology)
10. made from material (wd:P186 as ps/psv/p/pqv/pqn/psn/pq/wdt/pr/prn/prv/wdtn, matched via formed from), also known as be made in, built from, built out of, constructed from, constructed out of, etc.: material the subject or the object is made of or derived from (do not confuse with P10672 which is used for processes) / material the subject is made of or derived from / is subproperty of uses

[Assistant]
The property "based on" (wdt:P144) seems most relevant for cultural or systemic derivations, such as writing systems. I will now check if the Greek alphabet is linked to the Phoenician alphabet using this property.

Step 4: Search for objects of the property "based on" (wdt:P144) for the Greek alphabet (wd:Q8216) to see if it is derived from the Phoenician alphabet.

Question: Greek alphabet

Top 10 entity alternatives:
1. Greek alphabet (wd:Q8216), also known as Greek, Greek script: script used to write the Greek language / is instance of natural writing system / is instance of bicameral script / is instance of alphabet
2. alphabet (wd:Q9779), also known as ABC, alphabetic writing system: standard set of letters present in some written languages / is subclass of segmental writing system / is instance of type of writing system / is subclass of writing system / is subclass of class
3. Cyrillic script (wd:Q8209, matched via Cyrillic alphabet), also known as Cyrillic, Cyrillic alphabet, cyrl, Kiril: writing system developed in Bulgaria and used for various oriental Eurasian languages / is subclass of natural writing system / is instance of writing system
4. Arabic alphabet (wd:Q8196): alphabet for Arabic and other languages / is instance of unicase alphabet / is instance of Semitic alphabet
5. Greek mythology (wd:Q34726), also known as ancient Greek mythology, Greek myths: is instance of mythology / myths of ancient Greece
6. Hebrew alphabet (wd:Q33513), also known as alefbet, Hebr, Hebrew abjad, Jewish abjad, Jewish alphabet: Semitic alphabet used for writing Hebrew, Samaritan, Yiddish, Judaeo-Spanish, and other Jewish languages / is instance of Hebrew script based alphabet / is instance of natural writing system / is instance of unicase alphabet / is instance of abjad
7. Phoenician script (wd:Q26752, matched via Phoenician alphabet), also known as Early Linear script, Phnx, Phoenician abjad, Phoenician alphabet: abjad found in Canaanite and Aramaic inscriptions across the Mediterranean from the 11th–2nd centuries BCE / is instance of natural writing system / is instance of unicase alphabet / is instance of Semitic alphabet / is instance of abjad
8. Armenian alphabet (wd:Q11932), also known as Armenian script, Armn: alphabet used to write the Armenian language / is instance of constructed writing system / is instance of bicameral script / is instance of alphabet
9. Russian alphabet (wd:Q187846): alphabet that uses letters from the Cyrillic script / is instance of Cyrillic-script alphabet / is instance of Cyrillic alphabet / is subclass of Cyrillic script / is subclass of Cyrillic
10. Tibetan alphabet (wd:Q46861), also known as Tibetan script, Tibt: abugida writing system used to write certain Tibetic languages / abugida used to write the Tibetic languages and others / is instance of natural writing system / is instance of unicase alphabet / is instance of abugida

No other items found

No literal items found

[Assistant]
The search result shows that the Phoenician script (wd:Q26752) is a top match for the property "based on" (wdt:P144) in relation to the Greek alphabet. This confirms that the Greek alphabet is derived from the Phoenician script.

To finalize, I will construct a SPARQL query to retrieve the origin of the Greek alphabet using the "based on" property (wdt:P144) and return the label of the origin in English.

Step 5: Construct and execute a SPARQL query to get the origin of the Greek alphabet.

execute

SELECT ?originLabel WHERE { wd:Q8216 wdt:P144 ?origin . ?origin rdfs:label ?originLabel . FILTER(LANG(?originLabel) = "en") }

Got 1 row and 1 column:
| originLabel                 |
| --------------------------- |
| Phoenician script (lang:en) |

[Assistant]
The SPARQL query confirms that the Greek alphabet originated from the Phoenician script.

Final answer:

answer

SELECT ?originLabel WHERE { wd:Q8216 wdt:P144 ?origin . ?origin rdfs:label ?originLabel . FILTER(LANG(?originLabel) = "en") }

Answer: The Greek alphabet came from the Phoenician script.


[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 movies did tupac star in?

[Assistant]
To find the movies that Tupac starred in, I need to:

1. Identify the correct entity for Tupac (Tupac Shakur) in Wikidata.
2. Find the property that links a person to the movies they starred in (typically P161: actor).
3. Construct a SPARQL query to retrieve the movies (items) associated with Tupac via this property.
4. Optionally, retrieve the English labels of the movies for better readability.

Let me start by searching for the entity for Tupac Shakur.

Question: tupac shakur

Top 10 entity alternatives:
1. Tupac Shakur (wd:Q6107), also known as 2Pac, Lesane Crooks, Lesane Parish Crooks, Makaveli, Tupac, etc.: has occupation television actor / American rapper (1971–1996) / has occupation film actor / has occupation songwriter / has occupation lyricist / has occupation Lyricist / has occupation activist / has occupation writer / has occupation rapper / has occupation singer / has occupation actor / is instance of human / has occupation poet
2. murder of Tupac Shakur (wd:Q3882218, matched via Tupac Shakur killing), also known as killing of Tupac Shakur, Tupac Shakur killing, Tupac Shakur murder, Tupac Shakur's killing, Tupac Shakur's murder: unsolved murder of American hip hop artist / is instance of drive-by shooting / is instance of unsolved murder / is instance of murder
3. Tupac Shakur Legacy (wd:Q7853473): is instance of written work / book by Jamal Joseph
4. Tupac Shakur Legacy (wd:Q60387003): is instance of version, edition or translation / 2006 edition
5. Thug Angel: The Life of an Outlaw (wd:Q11704796, matched via Tupac Shakur: Thug Angel), also known as Tupac Shakur: Thug Angel: 2002 film by Peter Spirer / is instance of film
6. The Killing of Tupac Shakur (wd:Q7744388): is instance of literary work / book by Cathy Scott
7. The Killing of Tupac Shakur (wd:Q131689833): is instance of version, edition or translation / paperback edition (en)
8. Túpac Amaru (wd:Q296269), also known as José Gabriel CONDORCANQUI, Thupa Amaro, Thupaq Amaru, Tupac Amaru, Túpac Amaru I, etc.: 4th and last Inca Emperor of the Kingdom of Vilcabamba / has occupation sovereign / is instance of human
9. Assata Shakur (wd:Q467961), also known as Joanne Deborah Byron: American activist and convicted felon who was a member of the Black Panther Party and Black Liberation Army / has occupation political activist / has occupation editing staff / has occupation terrorist / has occupation activist / has occupation writer / is instance of human / has occupation poet
10. Túpac Huallpa (wd:Q381846), also known as Tupac Huallpa: 16th Inca Emperor under the crown of Spain / has occupation sovereign / is instance of human

[Assistant]
The correct entity for Tupac Shakur is `wd:Q6107`, which is identified as a human with occupations including film actor and television actor. Now I will check the properties associated with this entity to confirm the property used for movies he starred in (likely P161: actor).

I'll use `search_property_of_entity` to find properties related to his acting roles.
<tool_call>
{"name": "search_property_of_entity", "kg": "wikidata", "entity": "wd:Q6107", "query": "actor"}
</tool_call>