PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?item ?itemLabel ?locCountry ?locCountryLabel ?desigCountry ?desigCountryLabel ?coord WHERE {
  {
    SELECT ?item WHERE {
      ?item wdt:P17 ?locCountry .
      ?item wdt:P1435 ?desig .
      ?desig wdt:P17 ?desigCountry .
      FILTER ( ?desigCountry != ?locCountry )
    }
    GROUP BY ?item
    HAVING ( COUNT( DISTINCT ?desig ) > 1 )
  }
  ?item wdt:P17 ?locCountry .
  ?item wdt:P1435 ?desig .
  ?desig wdt:P17 ?desigCountry .
  FILTER ( ?desigCountry != ?locCountry ) OPTIONAL {
    ?item wdt:P625 ?coord .
  }
  ?item rdfs:label ?itemLabel FILTER ( LANG( ?itemLabel ) = "en" ) .
  ?locCountry rdfs:label ?locCountryLabel FILTER ( LANG( ?locCountryLabel ) = "en" ) .
  ?desigCountry rdfs:label ?desigCountryLabel FILTER ( LANG( ?desigCountryLabel ) = "en" ) .
}
ORDER BY ?itemLabel ?locCountryLabel ?desigCountryLabel
LIMIT 10000

Using properties:
- heritage designation (wd:P1435 as wdt), also known as designation, heritage status, legal protection, listed status, listing, etc.: is subproperty of instance of / is subproperty of has part / is subproperty of has part(s) / heritage designation of a cultural or natural site / the heritage status of a historical site / the heritage status of a historical site
- country (wd:P17 as wdt), also known as host country, land, sovereign state, state, P17: is subproperty of located in the administrative territorial entity / sovereign state that this item is in (not to be used for human beings) / sovereign state that this item is in (not to be used for human beings) / sovereign state that this item is in (not to be used for human beings) / sovereign state that this item is in (not to be used for human beings)
- coordinate location (wd:P625 as wdt), also known as co-ordinate location, co-ordinates, coordinates, co-ords, coords, etc.: coordinates of the subject / coordinates of the subject / geocoordinates of the subject. For Earth, please note that only WGS84 coordinating system is supported at the moment

Got 1,200 rows and 7 columns, showing the first 5 and last 5 rows below:
| item                                                 | itemLabel                                       | locCountry                    | locCountryLabel            | desigCountry      | desigCountryLabel | coord                                       |
| ---------------------------------------------------- | ----------------------------------------------- | ----------------------------- | -------------------------- | ----------------- | ----------------- | ------------------------------------------- |
| Akra, Crimea (wd:Q4059785)                           | Akra, Crimea (lang:en)                          | Bosporan Kingdom (wd:Q321371) | Bosporan Kingdom (lang:en) | Russia (wd:Q159)  | Russia (lang:en)  | POINT(36.426700 45.133100) (geo:wktLiteral) |
| Akra, Crimea (wd:Q4059785)                           | Akra, Crimea (lang:en)                          | Bosporan Kingdom (wd:Q321371) | Bosporan Kingdom (lang:en) | Ukraine (wd:Q212) | Ukraine (lang:en) | POINT(36.426700 45.133100) (geo:wktLiteral) |
| Akra, Crimea (wd:Q4059785)                           | Akra, Crimea (lang:en)                          | Russia (wd:Q159)              | Russia (lang:en)           | Ukraine (wd:Q212) | Ukraine (lang:en) | POINT(36.426700 45.133100) (geo:wktLiteral) |
| Akra, Crimea (wd:Q4059785)                           | Akra, Crimea (lang:en)                          | Ukraine (wd:Q212)             | Ukraine (lang:en)          | Russia (wd:Q159)  | Russia (lang:en)  | POINT(36.426700 45.133100) (geo:wktLiteral) |
| Alcántara Bridge (wd:Q996197)                        | Alcántara Bridge (lang:en)                      | Ancient Rome (wd:Q1747689)    | Ancient Rome (lang:en)     | Spain (wd:Q29)    | Spain (lang:en)   | POINT(-6.892500 39.722500) (geo:wktLiteral) |
| ...                                                  | ...                                             | ...                           | ...                        | ...               | ...               | ...                                         |
| Zhukovsky St., 20 / Samokisha St., 11 (wd:Q96211973) | Zhukovsky St., 20 / Samokisha St., 11 (lang:en) | Soviet Union (wd:Q15180)      | Soviet Union (lang:en)     | Ukraine (wd:Q212) | Ukraine (lang:en) | POINT(34.092778 44.948889) (geo:wktLiteral) |
| Zhukovsky St., 20 / Samokisha St., 11 (wd:Q96211973) | Zhukovsky St., 20 / Samokisha St., 11 (lang:en) | Ukraine (wd:Q212)             | Ukraine (lang:en)          | Russia (wd:Q159)  | Russia (lang:en)  | POINT(34.092778 44.948889) (geo:wktLiteral) |
| Дворец графини Паниной (wd:Q4155917)                 | Дворец графини Паниной (lang:en)                | Russia (wd:Q159)              | Russia (lang:en)           | Ukraine (wd:Q212) | Ukraine (lang:en) | POINT(34.098600 44.435200) (geo:wktLiteral) |
| Дворец графини Паниной (wd:Q4155917)                 | Дворец графини Паниной (lang:en)                | Russia (wd:Q159)              | Russia (lang:en)           | Ukraine (wd:Q212) | Ukraine (lang:en) | POINT(34.098600 44.435200) (geo:wktLiteral) |
| Дворец графини Паниной (wd:Q4155917)                 | Дворец графини Паниной (lang:en)                | Ukraine (wd:Q212)             | Ukraine (lang:en)          | Russia (wd:Q159)  | Russia (lang:en)  | POINT(34.098600 44.435200) (geo:wktLiteral) |

Answer:
I ran the SPARQL query above. Notes and results summary:

- Property used: heritage designation (P1435). I matched designation items to their countries using wdt:P17 on the designation item.
- Item country: for performance I used wdt:P17 on the item (explicit country). I made this assumption because including the administrative parent chain (wdt:P131*) caused timeouts on the endpoint; that more complete approach can be re-run if you want but may require more time.
- Filtering logic: kept only designation records where the designation country (wdt:P17 on the designation item) differs from the item's country, and required that each item have >1 such designation (HAVING COUNT(DISTINCT ?desig) > 1).
- The query returned results (1,200 rows in the execution I ran). Each row corresponds to an item paired with one of the designation countries that differ from the item's country. Coordinates are included when available.

Example rows seen among the results (item — item country — heritage-designation country — coords):
- Akra, Crimea — Bosporan Kingdom — Russia — POINT(36.426700 45.133100)
- Akra, Crimea — Bosporan Kingdom — Ukraine — POINT(36.426700 45.133100)
- Alcántara Bridge — Ancient Rome — Spain — POINT(-6.8925 39.7225)
- Дворец графини Паниной — Russia — Ukraine — POINT(34.0986 44.4352)

If you would like:
- the full result table returned in a particular format (CSV/JSON), I can provide that;
- or I can re-run an expanded query that also derives the item country via wdt:P131* -> wdt:P17 (to include items lacking wdt:P17). That may take longer or require removing the large LIMIT and/or running in smaller batches.

If you want the raw results file or an expanded query (admin-parent resolution), tell me which and I will proceed.

I ran the SPARQL query above. Notes and results summary:

- Property used: heritage designation (P1435). I matched designation items to their countries using wdt:P17 on the designation item.
- Item country: for performance I used wdt:P17 on the item (explicit country). I made this assumption because including the administrative parent chain (wdt:P131*) caused timeouts on the endpoint; that more complete approach can be re-run if you want but may require more time.
- Filtering logic: kept only designation records where the designation country (wdt:P17 on the designation item) differs from the item's country, and required that each item have >1 such designation (HAVING COUNT(DISTINCT ?desig) > 1).
- The query returned results (1,200 rows in the execution I ran). Each row corresponds to an item paired with one of the designation countries that differ from the item's country. Coordinates are included when available.

Example rows seen among the results (item — item country — heritage-designation country — coords):
- Akra, Crimea — Bosporan Kingdom — Russia — POINT(36.426700 45.133100)
- Akra, Crimea — Bosporan Kingdom — Ukraine — POINT(36.426700 45.133100)
- Alcántara Bridge — Ancient Rome — Spain — POINT(-6.8925 39.7225)
- Дворец графини Паниной — Russia — Ukraine — POINT(34.0986 44.4352)

If you would like:
- the full result table returned in a particular format (CSV/JSON), I can provide that;
- or I can re-run an expanded query that also derives the item country via wdt:P131* -> wdt:P17 (to include items lacking wdt:P17). That may take longer or require removing the large LIMIT and/or running in smaller batches.

If you want the raw results file or an expanded query (admin-parent resolution), tell me which and I will proceed.

SPARQL query over wikidata:
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?item ?itemLabel ?locCountry ?locCountryLabel ?desigCountry ?desigCountryLabel ?coord WHERE {
  {
    SELECT ?item WHERE {
      ?item wdt:P17 ?locCountry .
      ?item wdt:P1435 ?desig .
      ?desig wdt:P17 ?desigCountry .
      FILTER ( ?desigCountry != ?locCountry )
    }
    GROUP BY ?item
    HAVING ( COUNT( DISTINCT ?desig ) > 1 )
  }
  ?item wdt:P17 ?locCountry .
  ?item wdt:P1435 ?desig .
  ?desig wdt:P17 ?desigCountry .
  FILTER ( ?desigCountry != ?locCountry ) OPTIONAL {
    ?item wdt:P625 ?coord .
  }
  ?item rdfs:label ?itemLabel FILTER ( LANG( ?itemLabel ) = "en" ) .
  ?locCountry rdfs:label ?locCountryLabel FILTER ( LANG( ?locCountryLabel ) = "en" ) .
  ?desigCountry rdfs:label ?desigCountryLabel FILTER ( LANG( ?desigCountryLabel ) = "en" ) .
}
ORDER BY ?itemLabel ?locCountryLabel ?desigCountryLabel
LIMIT 10000

Using properties:
- heritage designation (wd:P1435 as wdt), also known as designation, heritage status, legal protection, listed status, listing, etc.: is subproperty of instance of / is subproperty of has part / is subproperty of has part(s) / heritage designation of a cultural or natural site / the heritage status of a historical site / the heritage status of a historical site
- country (wd:P17 as wdt), also known as host country, land, sovereign state, state, P17: is subproperty of located in the administrative territorial entity / sovereign state that this item is in (not to be used for human beings) / sovereign state that this item is in (not to be used for human beings) / sovereign state that this item is in (not to be used for human beings) / sovereign state that this item is in (not to be used for human beings)
- coordinate location (wd:P625 as wdt), also known as co-ordinate location, co-ordinates, coordinates, co-ords, coords, etc.: coordinates of the subject / coordinates of the subject / geocoordinates of the subject. For Earth, please note that only WGS84 coordinating system is supported at the moment

Execution result:
Got 1,200 rows and 7 columns, showing the first 5 and last 5 rows below:
| item                                                 | itemLabel                                       | locCountry                    | locCountryLabel            | desigCountry      | desigCountryLabel | coord                                       |
| ---------------------------------------------------- | ----------------------------------------------- | ----------------------------- | -------------------------- | ----------------- | ----------------- | ------------------------------------------- |
| Akra, Crimea (wd:Q4059785)                           | Akra, Crimea (lang:en)                          | Bosporan Kingdom (wd:Q321371) | Bosporan Kingdom (lang:en) | Russia (wd:Q159)  | Russia (lang:en)  | POINT(36.426700 45.133100) (geo:wktLiteral) |
| Akra, Crimea (wd:Q4059785)                           | Akra, Crimea (lang:en)                          | Bosporan Kingdom (wd:Q321371) | Bosporan Kingdom (lang:en) | Ukraine (wd:Q212) | Ukraine (lang:en) | POINT(36.426700 45.133100) (geo:wktLiteral) |
| Akra, Crimea (wd:Q4059785)                           | Akra, Crimea (lang:en)                          | Russia (wd:Q159)              | Russia (lang:en)           | Ukraine (wd:Q212) | Ukraine (lang:en) | POINT(36.426700 45.133100) (geo:wktLiteral) |
| Akra, Crimea (wd:Q4059785)                           | Akra, Crimea (lang:en)                          | Ukraine (wd:Q212)             | Ukraine (lang:en)          | Russia (wd:Q159)  | Russia (lang:en)  | POINT(36.426700 45.133100) (geo:wktLiteral) |
| Alcántara Bridge (wd:Q996197)                        | Alcántara Bridge (lang:en)                      | Ancient Rome (wd:Q1747689)    | Ancient Rome (lang:en)     | Spain (wd:Q29)    | Spain (lang:en)   | POINT(-6.892500 39.722500) (geo:wktLiteral) |
| ...                                                  | ...                                             | ...                           | ...                        | ...               | ...               | ...                                         |
| Zhukovsky St., 20 / Samokisha St., 11 (wd:Q96211973) | Zhukovsky St., 20 / Samokisha St., 11 (lang:en) | Soviet Union (wd:Q15180)      | Soviet Union (lang:en)     | Ukraine (wd:Q212) | Ukraine (lang:en) | POINT(34.092778 44.948889) (geo:wktLiteral) |
| Zhukovsky St., 20 / Samokisha St., 11 (wd:Q96211973) | Zhukovsky St., 20 / Samokisha St., 11 (lang:en) | Ukraine (wd:Q212)             | Ukraine (lang:en)          | Russia (wd:Q159)  | Russia (lang:en)  | POINT(34.092778 44.948889) (geo:wktLiteral) |
| Дворец графини Паниной (wd:Q4155917)                 | Дворец графини Паниной (lang:en)                | Russia (wd:Q159)              | Russia (lang:en)           | Ukraine (wd:Q212) | Ukraine (lang:en) | POINT(34.098600 44.435200) (geo:wktLiteral) |
| Дворец графини Паниной (wd:Q4155917)                 | Дворец графини Паниной (lang:en)                | Russia (wd:Q159)              | Russia (lang:en)           | Ukraine (wd:Q212) | Ukraine (lang:en) | POINT(34.098600 44.435200) (geo:wktLiteral) |
| Дворец графини Паниной (wd:Q4155917)                 | Дворец графини Паниной (lang:en)                | Ukraine (wd:Q212)             | Ukraine (lang:en)          | Russia (wd:Q159)  | Russia (lang:en)  | POINT(34.098600 44.435200) (geo:wktLiteral) |

[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] Which items have a heritage designation from a country different from the country they are located in, and have more than one such designation? Please include their labels, the labels of their countries, the labels of the countries of their heritage designations, and their coordinates if available. Order results by item label, country label, and heritage designation country label.

[Assistant]
I will search for the Wikidata property for "heritage designation" to confirm which property to use (I expect P1435). I'll run a property search next.

Question: heritage designation

Top 10 property alternatives:
1. heritage designation (wd:P1435 as pq/pqn/prv/ps/psn/pqv/prn/wdt/psv/wdtn/pr/p), also known as designation, heritage status, legal protection, listed status, listing, etc.: heritage designation of a cultural or natural site / the heritage status of a historical site / the heritage status of a historical site / is subproperty of instance of / is subproperty of has part(s) / is subproperty of has part
2. dedicated heritage entity (wd:P8786 as pq/pqn/prv/ps/psn/pqv/prn/wdt/psv/wdtn/pr/p), also known as associated heritage entity, has museum, P8786: heritage entity dedicated to or associated with the item's subject
3. Heritage NL ID (wd:P933 as pq/pqn/prv/ps/psn/pqv/prn/wdt/psv/wdtn/pr/p, matched via heritagefoundation.ca ID), also known as heritagefoundation.ca ID, Heritage Foundation of Newfoundland and Labrador heritage property ID ID, Heritage Foundation of Newfoundland & Labrador heritage property ID, P933: identifier of Heritage Foundation of Newfoundland and Labrador heritage property
4. Cultural Heritage Online (Japan) heritage ID (wd:P12144 as pq/pqn/prv/ps/psn/pqv/prn/wdt/psv/wdtn/pr/p), also known as P12144: identifier for heritage assets on Cultural Heritage Online
5. intangible cultural heritage status (wd:P3259 as pq/pqn/prv/ps/psn/pqv/prn/wdt/psv/wdtn/pr/p), also known as P3259: status of an item that is designated as intangible heritage / status of an item that is designated as intangible heritage
6. Argentinian Historic Heritage ID (wd:P4587 as pq/pqn/prv/ps/psn/pqv/prn/wdt/psv/wdtn/pr/p, matched via Comisión Nacional de Monumentos, de Lugares y de Bienes Históricos ID), also known as Comisión Nacional de Monumentos, de Lugares y de Bienes Históricos ID, P4587: identifier for historic heritage object included in the national index of Argentina
7. military designation (wd:P798 as pq/pqn/prv/ps/psn/pqv/prn/wdt/psv/wdtn/pr/p, matched via designation), also known as 1962 US military aerospace vehicle designation, designation, MAD, mdsd, mildes, etc.: officially assigned designation for a vehicle in military service
8. UNESCO ICH ID (wd:P10221 as pq/pqn/prv/ps/psn/pqv/prn/wdt/psv/wdtn/pr/p, matched via UNESCO Intangible Cultural Heritage identifier), also known as List of Intangible Cultural Heritage in Need of Urgent Safeguarding ID, List of Intangible Cultural Heritage in Need of Urgent Safeguarding identifier, Register of Good Safeguarding Practices ID, Register of Good Safeguarding Practices identifier, Representative List of the Intangible Cultural Heritage of Humanity ID, etc.: identifier of an item on the UNESCO Intangible Cultural Heritage Lists
9. World Heritage criteria (wd:P2614 as pq/pqn/prv/ps/psn/pqv/prn/wdt/psv/wdtn/pr/p), also known as WHS criteria, P2614: selection criteria for UNESCO's cultural and natural 'World Heritage' designation since 2005
10. provisional designation (wd:P490 as pq/pqn/prv/ps/psn/pqv/prn/wdt/psv/wdtn/pr/p), also known as P490: designation of an astronomical body after its discovery and before its official name / designation of an astronomical body after its discovery and before its official name

[Assistant]
I'll run a SPARQL query that:
- finds items with heritage designations (P1435),
- determines the item's country via wdt:P17 or via an admin parent (wdt:P131* -> wdt:P17),
- finds the country of each heritage designation (wdt:P17 on the designation item),
- keeps only designation records where designation country differs from the item's country,
- selects items that have more than one such designation (COUNT(DISTINCT ?desig) > 1),
- returns one row per item + designation country (with labels and coordinates),
- ordered by item label, item country label, designation country label.

Now I'll execute that query to verify results.

execute

SELECT ?item ?itemLabel ?locCountry ?locCountryLabel ?desigCountry ?desigCountryLabel ?coord WHERE {
  {
    # Subquery to select items that have more than one heritage designation coming from a country different than the item's country
    SELECT ?item WHERE {
      ?item wdt:P1435 ?desig .
      ?desig wdt:P17 ?desigCountry .
      OPTIONAL { ?item wdt:P17 ?locCountryDirect . }
      OPTIONAL { ?item wdt:P131* ?admin . ?admin wdt:P17 ?locCountryAdmin . }
      BIND(COALESCE(?locCountryDirect, ?locCountryAdmin) AS ?locCountry)
      FILTER(BOUND(?locCountry))
      FILTER(?desigCountry != ?locCountry)
    }
    GROUP BY ?item
    HAVING(COUNT(DISTINCT ?desig) > 1)
  }
  ?item wdt:P1435 ?desig .
  ?desig wdt:P17 ?desigCountry .
  OPTIONAL { ?item wdt:P17 ?locCountryDirect . }
  OPTIONAL { ?item wdt:P131* ?admin . ?admin wdt:P17 ?locCountryAdmin . }
  BIND(COALESCE(?locCountryDirect, ?locCountryAdmin) AS ?locCountry)
  FILTER(BOUND(?locCountry))
  FILTER(?desigCountry != ?locCountry)
  OPTIONAL { ?item wdt:P625 ?coord . }
  # labels
  ?item rdfs:label ?itemLabel FILTER(LANG(?itemLabel) = "en") .
  ?locCountry rdfs:label ?locCountryLabel FILTER(LANG(?locCountryLabel) = "en") .
  ?desigCountry rdfs:label ?desigCountryLabel FILTER(LANG(?desigCountryLabel) = "en") .
}
ORDER BY ?itemLabel ?locCountryLabel ?desigCountryLabel
LIMIT 10000

SPARQL execution failed:
HTTPConnectionPool(host='localhost', port=7001): Read timed out. (read timeout=30)

[Assistant]
Retrying the SPARQL query (previous attempt timed out). I'll run the same query again.

SELECT ?item ?itemLabel ?locCountry ?locCountryLabel ?desigCountry ?desigCountryLabel ?coord WHERE {
  {
    SELECT ?item WHERE {
      ?item wdt:P1435 ?desig .
      ?desig wdt:P17 ?desigCountry .
      OPTIONAL { ?item wdt:P17 ?locCountryDirect . }
      OPTIONAL { ?item wdt:P131* ?admin . ?admin wdt:P17 ?locCountryAdmin . }
      BIND(COALESCE(?locCountryDirect, ?locCountryAdmin) AS ?locCountry)
      FILTER(BOUND(?locCountry))
      FILTER(?desigCountry != ?locCountry)
    }
    GROUP BY ?item
    HAVING(COUNT(DISTINCT ?desig) > 1)
  }
  ?item wdt:P1435 ?desig .
  ?desig wdt:P17 ?desigCountry .
  OPTIONAL { ?item wdt:P17 ?locCountryDirect . }
  OPTIONAL { ?item wdt:P131* ?admin . ?admin wdt:P17 ?locCountryAdmin . }
  BIND(COALESCE(?locCountryDirect, ?locCountryAdmin) AS ?locCountry)
  FILTER(BOUND(?locCountry))
  FILTER(?desigCountry != ?locCountry)
  OPTIONAL { ?item wdt:P625 ?coord . }
  ?item rdfs:label ?itemLabel FILTER(LANG(?itemLabel) = "en") .
  ?locCountry rdfs:label ?locCountryLabel FILTER(LANG(?locCountryLabel) = "en") .
  ?desigCountry rdfs:label ?desigCountryLabel FILTER(LANG(?desigCountryLabel) = "en") .
}
ORDER BY ?itemLabel ?locCountryLabel ?desigCountryLabel
LIMIT 10000

SPARQL execution failed:
HTTPConnectionPool(host='localhost', port=7001): Read timed out. (read timeout=30)

[Assistant]
I'll retry with a simpler query that only uses wdt:P17 (explicit country on the item) to reduce execution time. This misses items lacking wdt:P17 but is a reasonable tradeoff if the endpoint times out. I'll run the simplified query now.

SELECT ?item ?itemLabel ?locCountry ?locCountryLabel ?desigCountry ?desigCountryLabel ?coord WHERE {
  {
    SELECT ?item WHERE {
      ?item wdt:P17 ?locCountry .
      ?item wdt:P1435 ?desig .
      ?desig wdt:P17 ?desigCountry .
      FILTER(?desigCountry != ?locCountry)
    }
    GROUP BY ?item
    HAVING(COUNT(DISTINCT ?desig) > 1)
  }
  ?item wdt:P17 ?locCountry .
  ?item wdt:P1435 ?desig .
  ?desig wdt:P17 ?desigCountry .
  FILTER(?desigCountry != ?locCountry)
  OPTIONAL { ?item wdt:P625 ?coord . }
  ?item rdfs:label ?itemLabel FILTER(LANG(?itemLabel) = "en") .
  ?locCountry rdfs:label ?locCountryLabel FILTER(LANG(?locCountryLabel) = "en") .
  ?desigCountry rdfs:label ?desigCountryLabel FILTER(LANG(?desigCountryLabel) = "en") .
}
ORDER BY ?itemLabel ?locCountryLabel ?desigCountryLabel
LIMIT 10000

Got 1,200 rows and 7 columns, showing the first 5 and last 5 rows below:
| item                                                 | itemLabel                                       | locCountry                    | locCountryLabel            | desigCountry      | desigCountryLabel | coord                                       |
| ---------------------------------------------------- | ----------------------------------------------- | ----------------------------- | -------------------------- | ----------------- | ----------------- | ------------------------------------------- |
| Akra, Crimea (wd:Q4059785)                           | Akra, Crimea (lang:en)                          | Bosporan Kingdom (wd:Q321371) | Bosporan Kingdom (lang:en) | Russia (wd:Q159)  | Russia (lang:en)  | POINT(36.426700 45.133100) (geo:wktLiteral) |
| Akra, Crimea (wd:Q4059785)                           | Akra, Crimea (lang:en)                          | Bosporan Kingdom (wd:Q321371) | Bosporan Kingdom (lang:en) | Ukraine (wd:Q212) | Ukraine (lang:en) | POINT(36.426700 45.133100) (geo:wktLiteral) |
| Akra, Crimea (wd:Q4059785)                           | Akra, Crimea (lang:en)                          | Russia (wd:Q159)              | Russia (lang:en)           | Ukraine (wd:Q212) | Ukraine (lang:en) | POINT(36.426700 45.133100) (geo:wktLiteral) |
| Akra, Crimea (wd:Q4059785)                           | Akra, Crimea (lang:en)                          | Ukraine (wd:Q212)             | Ukraine (lang:en)          | Russia (wd:Q159)  | Russia (lang:en)  | POINT(36.426700 45.133100) (geo:wktLiteral) |
| Alcántara Bridge (wd:Q996197)                        | Alcántara Bridge (lang:en)                      | Ancient Rome (wd:Q1747689)    | Ancient Rome (lang:en)     | Spain (wd:Q29)    | Spain (lang:en)   | POINT(-6.892500 39.722500) (geo:wktLiteral) |
| ...                                                  | ...                                             | ...                           | ...                        | ...               | ...               | ...                                         |
| Zhukovsky St., 20 / Samokisha St., 11 (wd:Q96211973) | Zhukovsky St., 20 / Samokisha St., 11 (lang:en) | Soviet Union (wd:Q15180)      | Soviet Union (lang:en)     | Ukraine (wd:Q212) | Ukraine (lang:en) | POINT(34.092778 44.948889) (geo:wktLiteral) |
| Zhukovsky St., 20 / Samokisha St., 11 (wd:Q96211973) | Zhukovsky St., 20 / Samokisha St., 11 (lang:en) | Ukraine (wd:Q212)             | Ukraine (lang:en)          | Russia (wd:Q159)  | Russia (lang:en)  | POINT(34.092778 44.948889) (geo:wktLiteral) |
| Дворец графини Паниной (wd:Q4155917)                 | Дворец графини Паниной (lang:en)                | Russia (wd:Q159)              | Russia (lang:en)           | Ukraine (wd:Q212) | Ukraine (lang:en) | POINT(34.098600 44.435200) (geo:wktLiteral) |
| Дворец графини Паниной (wd:Q4155917)                 | Дворец графини Паниной (lang:en)                | Russia (wd:Q159)              | Russia (lang:en)           | Ukraine (wd:Q212) | Ukraine (lang:en) | POINT(34.098600 44.435200) (geo:wktLiteral) |
| Дворец графини Паниной (wd:Q4155917)                 | Дворец графини Паниной (lang:en)                | Ukraine (wd:Q212)             | Ukraine (lang:en)          | Russia (wd:Q159)  | Russia (lang:en)  | POINT(34.098600 44.435200) (geo:wktLiteral) |

[Assistant]
I will finalize by returning the SPARQL query I executed (the simplified one using wdt:P17 for the item's country) and a short summary of the results and assumptions. Then I'll stop.

answer

SELECT ?item ?itemLabel ?locCountry ?locCountryLabel ?desigCountry ?desigCountryLabel ?coord WHERE {
  {
    SELECT ?item WHERE {
      ?item wdt:P17 ?locCountry .
      ?item wdt:P1435 ?desig .
      ?desig wdt:P17 ?desigCountry .
      FILTER(?desigCountry != ?locCountry)
    }
    GROUP BY ?item
    HAVING(COUNT(DISTINCT ?desig) > 1)
  }
  ?item wdt:P17 ?locCountry .
  ?item wdt:P1435 ?desig .
  ?desig wdt:P17 ?desigCountry .
  FILTER(?desigCountry != ?locCountry)
  OPTIONAL { ?item wdt:P625 ?coord . }
  ?item rdfs:label ?itemLabel FILTER(LANG(?itemLabel) = "en") .
  ?locCountry rdfs:label ?locCountryLabel FILTER(LANG(?locCountryLabel) = "en") .
  ?desigCountry rdfs:label ?desigCountryLabel FILTER(LANG(?desigCountryLabel) = "en") .
}
ORDER BY ?itemLabel ?locCountryLabel ?desigCountryLabel
LIMIT 10000

Answer:
I ran the SPARQL query above. Notes and results summary:

- Property used: heritage designation (P1435). I matched designation items to their countries using wdt:P17 on the designation item.
- Item country: for performance I used wdt:P17 on the item (explicit country). I made this assumption because including the administrative parent chain (wdt:P131*) caused timeouts on the endpoint; that more complete approach can be re-run if you want but may require more time.
- Filtering logic: kept only designation records where the designation country (wdt:P17 on the designation item) differs from the item's country, and required that each item have >1 such designation (HAVING COUNT(DISTINCT ?desig) > 1).
- The query returned results (1,200 rows in the execution I ran). Each row corresponds to an item paired with one of the designation countries that differ from the item's country. Coordinates are included when available.

Example rows seen among the results (item — item country — heritage-designation country — coords):
- Akra, Crimea — Bosporan Kingdom — Russia — POINT(36.426700 45.133100)
- Akra, Crimea — Bosporan Kingdom — Ukraine — POINT(36.426700 45.133100)
- Alcántara Bridge — Ancient Rome — Spain — POINT(-6.8925 39.7225)
- Дворец графини Паниной — Russia — Ukraine — POINT(34.0986 44.4352)

If you would like:
- the full result table returned in a particular format (CSV/JSON), I can provide that;
- or I can re-run an expanded query that also derives the item country via wdt:P131* -> wdt:P17 (to include items lacking wdt:P17). That may take longer or require removing the large LIMIT and/or running in smaller batches.

If you want the raw results file or an expanded query (admin-parent resolution), tell me which and I will proceed.


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX xsd: <http://www.w3.org/2001/XMLSchema#>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?person ?personLabel ?dod WHERE {
  ?person wdt:P31 wd:Q5 ; wdt:P570 ?dod .
  OPTIONAL {
    ?person rdfs:label ?personLabel .
    FILTER ( LANG( ?personLabel ) = "en" )
  }
  FILTER ( ?dod >= "2021-01-01T00:00:00Z" ^^ xsd:dateTime && ?dod < "2021-02-01T00:00:00Z" ^^ xsd:dateTime )
}
ORDER BY ?dod ?personLabel
LIMIT 500

Using entities:
- human (wd:Q5), also known as human being, humans, individual Homo sapiens, individual human, modern humans, etc.: is instance of class of organisms known by one particular common name / is instance of organisms known by a particular common name / is subclass of mammal / is subclass of natural person / is subclass of omnivore / is subclass of person / is subclass of individual animal / any member of Homo sapiens, unique extant species of the genus Homo / common name of Homo sapiens, unique extant species of the genus Homo / common name of Homo sapiens, unique extant species of the genus Homo / common name of Homo sapiens, unique extant species of the genus Homo, from embryo to adult

Using properties:
- instance of (wd:P31 as wdt), also known as example of, has type, is a, is an, is of type, etc.: that class of which this subject is a particular example and ... a subclass of mountain (and an instance of volcanic landform) / type to which this subject corresponds/belongs. Different ... and the volcano is a type (instance) of volcanic landform
- date of death (wd:P570 as wdt), also known as date of the end, dead, death, death date, deathdate, etc.: is subproperty of dissolved, abolished or demolished / is subproperty of dissolved, abolished or demolished date / is subproperty of end time / date on which the subject died / date on which the subject died / date on which the subject died

Answer:
I executed the SPARQL shown above. It returned 500 matching humans (limited to 500). Many items do not have an English rdfs:label; the query returns the item IRIs (wd:Q...) and the date of death values (xsd:dateTime). Sample rows from the result set include (IRI — English label if present — date of death):

- wd:Q104884489 — (no English label) — 2021-01-01T00:00:00Z
- wd:Q112460526 — (no English label) — 2021-01-01T00:00:00Z
- wd:Q112441387 — (no English label) — 2021-01-01T00:00:00Z
- wd:Q112424673 — (no English label) — 2021-01-01T00:00:00Z
- wd:Q105955429 — (no English label) — 2021-01-01T00:00:00Z
...
- wd:Q92204978 — Brenda Bettinson — 2021-01-01T00:00:00Z
- wd:Q130720127 — Brendan Guerin — 2021-01-01T00:00:00Z
- wd:Q59967308 — Brendan Lehane — 2021-01-01T00:00:00Z
- wd:Q4963027 — Brian Baker — 2021-01-01T00:00:00Z
- wd:Q4963099 — Brian Bender — 2021-01-01T00:00:00Z

If you want the complete list of all 500 rows, I can:
- return them here as plain text (all rows), or
- provide a downloadable CSV/TSV, or
- apply additional filters (e.g., only items that have English labels, or restrict to people with occupations, countries, etc.).

Which would you prefer?

I executed the SPARQL shown above. It returned 500 matching humans (limited to 500). Many items do not have an English rdfs:label; the query returns the item IRIs (wd:Q...) and the date of death values (xsd:dateTime). Sample rows from the result set include (IRI — English label if present — date of death):

- wd:Q104884489 — (no English label) — 2021-01-01T00:00:00Z
- wd:Q112460526 — (no English label) — 2021-01-01T00:00:00Z
- wd:Q112441387 — (no English label) — 2021-01-01T00:00:00Z
- wd:Q112424673 — (no English label) — 2021-01-01T00:00:00Z
- wd:Q105955429 — (no English label) — 2021-01-01T00:00:00Z
...
- wd:Q92204978 — Brenda Bettinson — 2021-01-01T00:00:00Z
- wd:Q130720127 — Brendan Guerin — 2021-01-01T00:00:00Z
- wd:Q59967308 — Brendan Lehane — 2021-01-01T00:00:00Z
- wd:Q4963027 — Brian Baker — 2021-01-01T00:00:00Z
- wd:Q4963099 — Brian Bender — 2021-01-01T00:00:00Z

If you want the complete list of all 500 rows, I can:
- return them here as plain text (all rows), or
- provide a downloadable CSV/TSV, or
- apply additional filters (e.g., only items that have English labels, or restrict to people with occupations, countries, etc.).

Which would you prefer?

SPARQL query over wikidata:
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX xsd: <http://www.w3.org/2001/XMLSchema#>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?person ?personLabel ?dod WHERE {
  ?person wdt:P31 wd:Q5 ; wdt:P570 ?dod .
  OPTIONAL {
    ?person rdfs:label ?personLabel .
    FILTER ( LANG( ?personLabel ) = "en" )
  }
  FILTER ( ?dod >= "2021-01-01T00:00:00Z" ^^ xsd:dateTime && ?dod < "2021-02-01T00:00:00Z" ^^ xsd:dateTime )
}
ORDER BY ?dod ?personLabel
LIMIT 500

Using entities:
- human (wd:Q5), also known as human being, humans, individual Homo sapiens, individual human, modern humans, etc.: is instance of class of organisms known by one particular common name / is instance of organisms known by a particular common name / is subclass of mammal / is subclass of natural person / is subclass of omnivore / is subclass of person / is subclass of individual animal / any member of Homo sapiens, unique extant species of the genus Homo / common name of Homo sapiens, unique extant species of the genus Homo / common name of Homo sapiens, unique extant species of the genus Homo / common name of Homo sapiens, unique extant species of the genus Homo, from embryo to adult

Using properties:
- instance of (wd:P31 as wdt), also known as example of, has type, is a, is an, is of type, etc.: that class of which this subject is a particular example and ... a subclass of mountain (and an instance of volcanic landform) / type to which this subject corresponds/belongs. Different ... and the volcano is a type (instance) of volcanic landform
- date of death (wd:P570 as wdt), also known as date of the end, dead, death, death date, deathdate, etc.: is subproperty of dissolved, abolished or demolished / is subproperty of dissolved, abolished or demolished date / is subproperty of end time / date on which the subject died / date on which the subject died / date on which the subject died

Execution result:
Got 500 rows and 3 columns, showing the first 5 and last 5 rows below:
| person                          | personLabel                | dod                                 |
| ------------------------------- | -------------------------- | ----------------------------------- |
| wd:Q104884489                   |                            | 2021-01-01T00:00:00Z (xsd:dateTime) |
| wd:Q112460526                   |                            | 2021-01-01T00:00:00Z (xsd:dateTime) |
| wd:Q112441387                   |                            | 2021-01-01T00:00:00Z (xsd:dateTime) |
| wd:Q112424673                   |                            | 2021-01-01T00:00:00Z (xsd:dateTime) |
| wd:Q105955429                   |                            | 2021-01-01T00:00:00Z (xsd:dateTime) |
| ...                             | ...                        | ...                                 |
| Brenda Bettinson (wd:Q92204978) | Brenda Bettinson (lang:en) | 2021-01-01T00:00:00Z (xsd:dateTime) |
| Brendan Guerin (wd:Q130720127)  | Brendan Guerin (lang:en)   | 2021-01-01T00:00:00Z (xsd:dateTime) |
| Brendan Lehane (wd:Q59967308)   | Brendan Lehane (lang:en)   | 2021-01-01T00:00:00Z (xsd:dateTime) |
| Brian Baker (wd:Q4963027)       | Brian Baker (lang:en)      | 2021-01-01T00:00:00Z (xsd:dateTime) |
| Brian Bender (wd:Q4963099)      | Brian Bender (lang:en)     | 2021-01-01T00:00:00Z (xsd:dateTime) |

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

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

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

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

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

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

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

[User] What are the names and dates of death of humans who died between January 1, 2021, and January 31, 2021, ordered by their date of death and name and limited to 500 results?

[Assistant]
Step 1: Identify likely properties/entities. I expect "date of death" (P570) and "human" (Q5, instance of via P31). I'll search for the "date of death" property to confirm its identifier. I'll also search for the "human" entity to confirm Q5. I'll call the property and entity search functions next.

Question: date of death

Top 10 property alternatives:
1. date of death (wd:P570 as pq/pqn/prv/ps/psn/pqv/prn/wdt/psv/wdtn/pr/p), also known as date of the end, dead, death, death date, deathdate, etc.: is subproperty of dissolved, abolished or demolished date / is subproperty of dissolved, abolished or demolished / date on which the subject died / date on which the subject died / date on which the subject died / is subproperty of end time
2. date of burial or cremation (wd:P4602 as pq/pqn/prv/ps/psn/pqv/prn/wdt/psv/wdtn/pr/p, matched via date of cremation), also known as burial date, cremation date, date of cremation, funeral date, P4602: date on which the person was buried or cremated soon after death / is subproperty of point in time
3. place of death (wd:P20 as pq/pqn/prv/ps/psn/pqv/prn/wdt/psv/wdtn/pr/p), also known as death location, death place, deathplace, died, died in, etc.: most specific known (e.g. city instead of country, or ... death location of a person, animal or fictional character / most specific known (e.g. city instead of country, or ... death location of a person, animal or fictional character / most specific known (e.g. city instead of country, or ... death location of a person, animal or fictional character / is subproperty of location
4. date of disappearance (wd:P746 as pq/pqn/prv/ps/psn/pqv/prn/wdt/psv/wdtn/pr/p), also known as date of missing, disappeared, last known alive before disappearance, last seen, missing since, etc.: date or point of time a missing person was seen or otherwise known to be alive for the last time / is subproperty of end time
5. discontinued date (wd:P2669 as pq/pqn/prv/ps/psn/pqv/prn/wdt/psv/wdtn/pr/p, matched via ceased date), also known as ceased date, date discontinued, date of discontinuation, date product was discontinued, discontinuation date, etc.: date that the availability of a product or service was ... retirement" (P730) for pieces or classes of equipment / date that the availability of a product was discontinued; see also "dissolved, abolished or demolished" (P576) / is subproperty of end time
6. dissolved, abolished or demolished date (wd:P576 as pq/pqn/prv/ps/psn/pqv/prn/wdt/psv/wdtn/pr/p, matched via ceased date), also known as abolished, abolishment date, ceased date, ceased on, ceased publication, etc.: point in time at which the subject (organisation, building) ...  "discontinued date" (P2669) for stopping a product / date or point in time on which the organisation was dissolved/disappeared or the building demolished / is subproperty of end time
7. date of birth (wd:P569 as pq/pqn/prv/ps/psn/pqv/prn/wdt/psv/wdtn/pr/p), also known as birth date, birthdate, birth year, birthyear, born, etc.: is subproperty of date of foundation or creation / date on which the subject was born / date on which the subject was born / date on which the subject was born / is subproperty of inception
8. cause of death (wd:P509 as pq/pqn/prv/ps/psn/pqv/prn/wdt/psv/wdtn/pr/p, matched via died of), also known as death cause, died of, die from, die of, method of murder, etc.: underlying or immediate cause of death.  Underlying cause ... category, e.g. natural causes, accident, homicide, suicide / underlying or immediate cause of death.  Underlying cause ... category, e.g. natural causes, accident, homicide, suicide / an item describing the cause of a person or specific organism's death. Samples: leukaemia, car crash / medical cause of a person or specific organism's death (not to be confused with P1196)
9. number of deaths (wd:P1120 as pq/pqn/prv/ps/psn/pqv/prn/wdt/psv/wdtn/pr/p, matched via deaths), also known as dead, death count, death number, deaths, death toll, etc.: total (cumulative) number of people who died since start as a direct result of an event or cause / number of ALL people who died as a direct result of an event or cause / number of ALL people who died as a direct result of an event or cause
10. date of resignation (wd:P9667 as pq/pqn/prv/ps/psn/pqv/prn/wdt/psv/wdtn/pr/p), also known as official date of resignation, official resignation date, resignation date, P9667: date of official resignation of the head of a government in ... to stay in place until the formation of a new executive / is subproperty of dissolved, abolished or demolished date / is subproperty of dissolved, abolished or demolished / is subproperty of significant event

[Assistant]
I'll search for the "human" entity (expected to be Q5) to confirm its identifier before using it in the query.

Question: human

Top 10 entity alternatives:
1. human (wd:Q5), also known as human being, humans, individual Homo sapiens, individual human, modern humans, etc.: common name of Homo sapiens, unique extant species of the genus Homo, from embryo to adult / is instance of class of organisms known by one particular common name / common name of Homo sapiens, unique extant species of the genus Homo / common name of Homo sapiens, unique extant species of the genus Homo / any member of Homo sapiens, unique extant species of the genus Homo / is instance of organisms known by a particular common name / is subclass of individual animal / is subclass of natural person / is subclass of omnivore / is subclass of mammal / is subclass of person
2. Homo sapiens (wd:Q15978631, matched via human), also known as human, human being, human beings, humans, man, etc.: is instance of taxon / species of mammal / species of mammal / species of mammal
3. Uman (wd:Q208499, matched via Humań), also known as Humań: is instance of city of regional significance of Ukraine / city in Cherkasy Oblast in central Ukraine
4. Human (wd:Q849189): is instance of album / 1991 album by Death
5. Human Entertainment (wd:Q2408214, matched via Human), also known as Human, Human Corporation: is instance of video game developer company / Japanese video game developer and publisher / is instance of video game developer
6. Human (wd:Q919463): 2008 song by The Killers / is instance of single / is instance of song
7. Human (wd:Q20629223): 2015 film by Yann Arthus-Bertrand / is instance of film
8. Human (wd:Q27921626): 2016 song by Rag'n'Bone Man / is instance of single / is instance of song
9. Human (wd:Q735359): 2008 studio album by Brandy / 2008 studio album by Brandy / 2008 studio album by Brandy / is instance of album
10. Human (wd:Q1145446): original song written and composed by Jimmy Jam and Terry Lewis; first recorded by The Human League / is instance of musical work/composition

[Assistant]
I'll run a SPARQL SELECT that finds items that are humans (wdt:P31 wd:Q5) with a date of death (wdt:P570) between 2021-01-01 (inclusive) and 2021-02-01 (exclusive). I'll retrieve the item IRI, its English label if present, and the death date, ordering by death date then name, limited to 500. Now I'll execute that query.

execute

PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX xsd: <http://www.w3.org/2001/XMLSchema#>

SELECT ?person ?personLabel ?dod WHERE {
  ?person wdt:P31 wd:Q5 ;
          wdt:P570 ?dod .
  OPTIONAL { ?person rdfs:label ?personLabel . FILTER(LANG(?personLabel) = "en") }
  FILTER(
    ?dod >= "2021-01-01T00:00:00Z"^^xsd:dateTime &&
    ?dod <  "2021-02-01T00:00:00Z"^^xsd:dateTime
  )
}
ORDER BY ?dod ?personLabel
LIMIT 500

[Assistant]
After running the query I got 500 results (the maximum you requested). Many returned items lack an English rdfs:label; the results include the item IRIs and the death dates. I include the exact SPARQL I ran below and a short summary. If you want the full table exported (CSV/TSV) or want me to return the full 500-row list here, tell me and I will provide it.

answer

PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX xsd: <http://www.w3.org/2001/XMLSchema#>

SELECT ?person ?personLabel ?dod WHERE {
  ?person wdt:P31 wd:Q5 ;
          wdt:P570 ?dod .
  OPTIONAL { ?person rdfs:label ?personLabel . FILTER(LANG(?personLabel) = "en") }
  FILTER(
    ?dod >= "2021-01-01T00:00:00Z"^^xsd:dateTime &&
    ?dod <  "2021-02-01T00:00:00Z"^^xsd:dateTime
  )
}
ORDER BY ?dod ?personLabel
LIMIT 500

Answer:
I executed the SPARQL shown above. It returned 500 matching humans (limited to 500). Many items do not have an English rdfs:label; the query returns the item IRIs (wd:Q...) and the date of death values (xsd:dateTime). Sample rows from the result set include (IRI — English label if present — date of death):

- wd:Q104884489 — (no English label) — 2021-01-01T00:00:00Z
- wd:Q112460526 — (no English label) — 2021-01-01T00:00:00Z
- wd:Q112441387 — (no English label) — 2021-01-01T00:00:00Z
- wd:Q112424673 — (no English label) — 2021-01-01T00:00:00Z
- wd:Q105955429 — (no English label) — 2021-01-01T00:00:00Z
...
- wd:Q92204978 — Brenda Bettinson — 2021-01-01T00:00:00Z
- wd:Q130720127 — Brendan Guerin — 2021-01-01T00:00:00Z
- wd:Q59967308 — Brendan Lehane — 2021-01-01T00:00:00Z
- wd:Q4963027 — Brian Baker — 2021-01-01T00:00:00Z
- wd:Q4963099 — Brian Bender — 2021-01-01T00:00:00Z

If you want the complete list of all 500 rows, I can:
- return them here as plain text (all rows), or
- provide a downloadable CSV/TSV, or
- apply additional filters (e.g., only items that have English labels, or restrict to people with occupations, countries, etc.).

Which would you prefer?