PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?tournament ?country ?endTime ?location ?edition ?pointInTime ?surface WHERE {
  ?tournament wdt:P361 wd:Q23039138 .
  OPTIONAL {
    ?tournament wdt:P17 ?country .
  }
  OPTIONAL {
    ?tournament wdt:P582 ?endTime .
  }
  OPTIONAL {
    ?tournament wdt:P276 ?location .
  }
  OPTIONAL {
    ?tournament wdt:P393 ?edition .
  }
  OPTIONAL {
    ?tournament wdt:P585 ?pointInTime .
  }
  OPTIONAL {
    ?tournament wdt:P765 ?surface .
  }
}
ORDER BY ASC ( ?endTime )

The details of all tennis tournaments that were part of the 2018 ATP World Tour, including tournament item, country, end time, location, edition number, point in time, and surface played on (where available), are provided in the query result above. The tournaments are sorted in ascending order by end time.

What are the details of all tennis tournaments that were part of the 2018 ATP World Tour? Please include the tournament item, country (if available), end time (if available), location (if available), edition number (if available), point in time (if available), and surface played on (if available), sorted in ascending order by end time.

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

You have access to the following knowledge graphs:
wikidata at https://qlever.cs.uni-freiburg.de/api/wikidata-sebastian with notes:
1. For P39 legislative memberships, filter by pq:P2937 (legislative term) on the p:P39 statement; don’t use P793 for term filtering. For UK MPs, avoid a generic Q16707842-only scan; rely on term qualifiers and proper date overlap on pq:P580/pq:P582.
2. For residence (P551), time bounds are qualifiers on the statement: p:P551/ps:P551 place, pq:P580 start, pq:P582 end. To include containing areas (e.g., NYC boroughs), expand via wdt:P551/wdt:P131*. Durations usually need client-side calc on QLever.
3. Ticker symbols are pq:P249 on p:P414 statements; query via the statement node (?org p:P414 ?st . ?st ps:P414 ?ex ; pq:P249 ?ticker). Use VALUES to pre-limit orgs/exchanges. Don’t expect wdt:P249 on the org. Prefer qualifiers for time-bound tickers.
4. Archives: use p:P485/ps:P485 for the holding institution. Inventory numbers are qualifiers pq:P217 on that P485 statement. Don’t expect wdt:P217 directly on the person/work. “Archive descriptions” may be separate collection items (P195).
5. When listing contained municipalities or similar, prefer wdt:P150* (has parts) from the parent to enumerate children, then join other relations (e.g., twin towns via wdt:P190). Avoid broad wdt:P131+ scans from children; they are slow and can timeout.
6. On QLever, avoid SERVICE wikibase:label (frequent 301). Use OPTIONAL rdfs:label with LANG filters or fetch QIDs then labels separately. For property mapping, (?prop wikibase:directClaim ?p). Pre-limit with subselect/VALUES to avoid timeouts.
7. Employer constraints: to find people employed by UN or international orgs, use wdt:P108 directly for UN (wd:Q1065), or traverse employer to part of (wdt:P361*) UN, or employer wdt:P31 wd:Q484652 (international organization). Combine with other occupations.
8. For sports/events/editions, prefer explicit edition items (e.g., Q47345468) with wdt:P361 linking to the parent series/tour and filter by wdt:P585/P571 for year; avoid P641/P2139 that model sports played or participants, not the edition metadata.
9. For author/creator queries, use occupation wdt:P106 (e.g., author/writer) rather than P31 typing. To list works, prefer the reverse path ^wdt:P50 ?work; P800 (notable work) is incomplete and curated, not a full bibliography.
10. Awards: use p:P166/ps:P166 and constrain award via wdt:P31/wdt:P279* to a target class (e.g., Cannes awards Q28444913). Recipients can be films or people; don’t assume film-specific properties exist. Count/group by recipient type if needed.
11. To select current/active codes or memberships on QLever, use statement nodes (p:/ps:) and MINUS { ?st pq:P582 [] }. For time series counts (e.g., daily members), generate a date series (VALUES/UNNEST), then test overlap with pq:P580/pq:P582 per date.
12. For people’s native names, use wdt:P1559 (name in native language) on the person, not rdfs:label. Return multiple if multiple native languages exist; pick a preferred language client-side if needed.
13. For multi-valued props (e.g., P1082), GROUP BY entity and aggregate (MAX/MIN/SAMPLE) to avoid duplicates; DISTINCT won’t collapse multiple statements. For category/gender counts, prefer indicator sums: SUM(IF(cond,1,0)) over COUNT on OPTIONAL vars.
14. Avoid SERVICE wikibase:label on QLever; it often 301s. Use OPTIONAL rdfs:label with LANG filters, or fetch QIDs first and labels in a follow-up. Pre-limit with subselect/VALUES to avoid timeouts when joining many labels.
15. For P551 duration comparisons, avoid unsupported date arithmetic. If needed, compute overlaps client-side. On-endpoint, you can only compare presence/counts or use simple MIN/MAX of dates (casting and arithmetic are limited in QLever).
16. When excluding specific entities from a relation (e.g., siblings), use FILTER to drop explicit QIDs or FILTER NOT EXISTS with a VALUES list. Ensure you use the exact sibling QIDs returned by the KG, not assumed ones.

General notes for all knowledge graphs:
1. When checking date interval overlaps, handle open intervals (missing start/end) and use xsd:dateTime. Use OR conditions to cover start within, end within, or spanning the whole range.
2. For P39 queries, qualifiers (e.g., P2937 term, P768 electoral district, P4100 parliamentary group) live on the p:P39 statement node. Do not expect them as wdt: properties on the person or use ps: for non-main values.
3. To get sitelink counts, use wikibase:sitelinks on the entity; it returns a single numeric value, so GROUP BY the entity and avoid COUNT over ?sitelink.
4. Use subclass expansion for types: wdt:P31/wdt:P279* target (e.g., dams, educational institutions). This captures items modeled with subclasses.
5. For locations, prefer hierarchies via wdt:P131+ to reach a containing region/state, and wdt:P17 for country. If HQ is a building, P159 ps points to a city; specific site is qualifier pq:P276 on the P159 statement.
6. When excluding or selecting by a legislative term on P39, check pq:P2937 on the relevant statement. Use FILTER NOT EXISTS over p:P39 with ps:P39 target and pq:P2937 value to exclude a term.
7. QLever endpoints may not support Wikidata’s “WITH {…} AS %name” and “INCLUDE %name” syntax. Avoid named subqueries; use nested SELECTs or VALUES instead.
8. The wikibase:label SERVICE often fails on QLever. Prefer rdfs:label with FILTER(LANG(..)="en") or get QIDs only and resolve labels client-side.
9. Avoid COUNT over OPTIONAL variables that may be unbound for all rows; prefer EXISTS/BOUND checks or aggregate over DISTINCT entities to prevent misleading zeros.
10. On QLever, heavy OPTIONAL label/property joins often time out. Pre-limit with a subselect/VALUES over IDs (ORDER BY + LIMIT), then join labels/properties. Or fetch QIDs first and labels in a second, smaller query.
11. For precise date filtering on Wikidata (birth/death), prefer p/psv time nodes and wikibase:timeValue plus timePrecision checks over wdt:P569/P570 to include values with year/month precision and avoid silent drops.
12. When filtering by exact day of birth or event, avoid STRSTARTS on wdt:P569; instead bound an interval [day, next day) with xsd:dateTime to include all precisions. On QLever, add hint:Prior hint:rangeSafe true to improve performance on time ranges.

You can use the following SPARQL prefixes implicitly in all functions:
cc: <http://creativecommons.org/ns#
data: <https://www.wikidata.org/wiki/Special:EntityData/
dct: <http://purl.org/dc/terms/
geo: <http://www.opengis.net/ont/geosparql#
geof: <http://www.opengis.net/def/function/geosparql/
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/
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/
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#
foaf: <http://xmlns.com/foaf/0.1/
dc: <http://purl.org/dc/elements/1.1/
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
qb: <http://purl.org/linked-data/cube#
void: <http://rdfs.org/ns/void#

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.

Additional rules:
1. Explain your thought process before and after each step and function call.
2. Do not just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
3. Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
4. 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.
5. 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.
6. 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.
7. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
8. 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.

[User] What are the details of all tennis tournaments that were part of the 2018 ATP World Tour? Please include the tournament item, country (if available), end time (if available), location (if available), edition number (if available), point in time (if available), and surface played on (if available), sorted in ascending order by end time.

[Assistant]
Let's break down the question and plan the SPARQL query step by step:

1. **Identify the entity for "2018 ATP World Tour"**:
   We need the QID for the 2018 ATP World Tour.

2. **Find how tournaments are linked to this tour**:
   Usually, tournaments are linked to a tour/season via a property like "part of the series" or "edition of".

3. **Determine relevant properties for the requested details**:
   - Tournament item: the main entity
   - Country: likely wdt:P17
   - End time: likely wdt:P582
   - Location: likely wdt:P276
   - Edition number: likely wdt:P393
   - Point in time: likely wdt:P585
   - Surface played on: likely wdt:P641 or a more specific property

4. **Sort by end time**.

Let's proceed step by step.

---

**Step 1: Search for "2018 ATP World Tour" entity.**

[Tool]
Top 10 entity alternatives:
1. 2018 ATP World Tour (wd:Q23039138): instance of tennis tour edition, tennis circuit
2. 2018 ATP World Tour Masters 1000 (wd:Q50063551): instance of tennis tour edition, tennis tour
3. ATP Tour, also known as ATP World Tour (wd:Q300008)
4. ATP Finals, also known as ATP World Tour Finals, Tennis Masters Cup (wd:Q270907)
5. ATP World Tour 250 series, also known as ATP 250 Series, International Series Tournaments, International Series tennis tournaments, International Series events, ATP World Tour 250 (wd:Q300017)
6. ATP World Tour 500 series, also known as ATP 500 Series, ATP World Tour 500, ATP Masters 500, ATP Championship Series, Double-Week, ATP Championship Series (wd:Q300018)
7. 2018 UCI World Tour (wd:Q42317185): instance of UCI World Tour, cycling races
8. 2011 ATP World Tour, also known as 2011 atp tour (wd:Q300013): instance of tennis tour edition, men's tennis circuit
9. 2010 ATP World Tour, also known as 2010 atp tour (wd:Q300012): instance of tennis tour edition, tennis circuit
10. 2009 ATP World Tour, also known as Juego 2000 Calendar, Tennis 2009 Calendare ATP ITF, ATP Tour 2009, 2009 ATP Tour, 2009 atp tour (wd:Q300011): instance of tennis tour edition, tennis circuit

[Assistant]
The correct entity for "2018 ATP World Tour" is wd:Q23039138.

Next, we need to find how tournaments are linked to this tour. Typically, tournaments are linked via "part of the series" or "edition of". Let's check which properties are used on this entity or its related tournaments.

I'll search for properties related to "part of" or "edition" for tennis tournaments.

[Tool]
Top 10 property alternatives:
1. instance of, also known as example of, has type, is a, is an, is of type (wd:P31 as wdt/p): type to which this subject corresponds/belongs. Different from P...tains, and the volcano is a type (instance) of volcanic landform
2. topic's main category, also known as category for this topic, Wikipedia category, Wikimedia category, Wiki category, subject category (wd:P910 as wdt/p): main Wikimedia category
3. point in time, also known as year, when, time of event, time, during (wd:P585 as wdt/p): date something took place, existed or a statement was true; for providing time use the "refine date" property (P4241)
4. topic's main template, also known as topic has template, topic's main module, topic's main infobox, topic infobox, template of topic (wd:P1424 as wdt/p): the main template relating to a topic
5. sport, also known as play, plays, sport played, sports (wd:P641 as wdt/p): sport that the subject participates or participated in or is associated with
6. sports season of league or competition, also known as sport season, seasons of, season of sports tournament, season of sports league, season of sports competition (wd:P3450 as wdt/p): property that shows the competition of which the item is a season. Use P5138 for "season of club or team"., subproperty of part of

No other items found

[Tool]
Top 10 property alternatives:
1. instance of, also known as example of, has type, is a, is an, is of type (wd:P31 as wdt/p): type to which this subject corresponds/belongs. Different from P...tains, and the volcano is a type (instance) of volcanic landform
2. topic's main category, also known as category for this topic, Wikipedia category, Wikimedia category, Wiki category, subject category (wd:P910 as wdt/p): main Wikimedia category
3. point in time, also known as year, when, time of event, time, during (wd:P585 as wdt/p): date something took place, existed or a statement was true; for providing time use the "refine date" property (P4241)
4. sport, also known as play, plays, sport played, sports (wd:P641 as wdt/p): sport that the subject participates or participated in or is associated with
5. sports season of league or competition, also known as sport season, seasons of, season of sports tournament, season of sports league, season of sports competition (wd:P3450 as wdt/p): property that shows the competition of which the item is a season. Use P5138 for "season of club or team"., subproperty of part of
6. topic's main template, also known as topic has template, topic's main module, topic's main infobox, topic infobox, template of topic (wd:P1424 as wdt/p): the main template relating to a topic
7. Google Knowledge Graph ID, also known as Google knowledge panel, Google Knowledge Panel ID, kgmid, MREID (wd:P2671 as wdt/p/wdtn): identifier for Google Knowledge Graph API, starting with "/g/". For IDs starting with "/m/", use Freebase ID (P646)

No other items found

[Tool]
Top 10 property alternatives:
1. part of the series, also known as video game series, subseries, series, part of series, listed in (wd:P179 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): series which contains the subject, subproperty of part of
2. collection, also known as series, repository, museum collection, held by, GLAM (wd:P195 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): art, museum, archival, or bibliographic collection of which the subject is part, subproperty of part of
3. season, also known as television season, TV series, TV season, television series, series of television program (wd:P4908 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): season of a series (televison, web, podcast), subproperty of part of
4. series ordinal, also known as unit number, sort order, sorting order, ordinal, series number (wd:P1545 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): position of an item in its parent series (most frequently a 1-ba...d from "ranking" defined as a property for evaluating a quality)
5. has spin-off, also known as series spin-off, series spinoff, spin-offs, television series spin-off, television series spinoff (wd:P2512 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): works that are spin-offs of this item
6. MusicBrainz series ID, also known as MBS, MB series ID, MusicBrainz ID, Series ID, Series MBID (wd:P1407 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): identifier for a series per the MusicBrainz open music encyclopedia
7. number of seasons, also known as number of series, seasons, no. of series, no. of seasons (wd:P2437 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): number of seasons a television or radio series has had, subproperty of number of parts of this work
8. volume, also known as number of part, volume of serial, volume of a book, volume number, vol. (wd:P478 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): volume of a book or music release in a collection/series or a published collection of journal issues in a serial publication
9. history of topic, also known as chronology of subject, timeline of topic, timeline of the topic, timeline of the subject, timeline of subject (wd:P2184 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): item about the historical development of a subject's topic, exam... To list key events of the topic, use "significant event" (P793), subproperty of studied by
10. number of episodes, also known as episodes, series length, no. of episodes, episode count (wd:P1113 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): number of episodes in a film/TV/radio series, subproperty of number of parts of this work

[Tool] Got no rows and 3 columns

[Tool]
Top 10 property alternatives:
1. edition or translation of, also known as translation or edition of, version of, translation of, is a translation of, is an edition of (wd:P629 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): is an edition or translation of this entity
2. edition/version, also known as designation of edition, designation of version, edition, edition designation, edition or version (wd:P9767 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): the official edition or version name of a resource; this name is not considered part of the title or subtitle of the resource
3. has edition or translation, also known as released as, version, translation(s), modified as, has version (wd:P747 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): item that is an edition or translation of this item
4. distribution format, also known as media format, media type, medium, method of distribution, publication format (wd:P437 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): method (or type) of distribution for the subject
5. modified version of, also known as adaptation of, version of, revision of, revised version of, modification of (wd:P5059 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): indicates the work or one of its versions which served as a basi...tation or arrangement resulting in the given version of the work, subproperty of based on
6. edition number, also known as number of event, software version number, version number (wd:P393 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): number of an edition (first, second, ... as 1, 2, ...) or event, subproperty of series ordinal
7. reissue of, also known as repackage, re-release, re-edition (wd:P9237 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): reissue of musical work, release
8. software version identifier, also known as software release number, software release version, software update identifier, software version number, software update number (wd:P348 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): numeric or nominal identifier of a version of a software program or file format, current or past, subproperty of has edition or translation, subproperty of edition number
9. related image, also known as other version, backup image, placeholder image, related picture, replacement image (wd:P6802 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): less fitting image, used only because a better alternative is no...ble, use P18 instead. Value should not be a generic placeholder., subproperty of image
10. ISBN-10, also known as International Standard Book Number-10, isbn, isbn-10, ISBN10 (wd:P957 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): former identifier for a book (edition), ten digits. Used for all...gs; useful for old books or fac-similes not reedited since 2007)

[Tool] Got no rows and 3 columns

[Tool]
Top 10 property alternatives:
1. has part(s), also known as has ingredient, has ingredients, had part, has member, has part (wd:P527 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): part of this subject; inverse property of "part of" (P361). See also "has parts of the class" (P2670).
2. applies to part, also known as applies to aspect, applied to, when viewed as, valid for part, section (wd:P518 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): part, aspect, or form of the item to which the claim applies
3. based on, also known as modelled after, inspired by, iteration of, modeled after, input (wd:P144 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): the work(s) or inputs used as the basis for subject item; for fictional analog use P1074, subproperty of references work, tradition or theory, subproperty of inspired by
4. proportion, also known as %, part, percent, ratio, share (wd:P1107 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): to be used as a qualifier, value must be between 0 and 1
5. combines lexemes, also known as contain (lexeme), prefix, contains (lexeme), has part (lexeme), have part (lexeme) (wd:P5238 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): subproperty of derived from lexeme, lexemes combined in this lexeme
6. part of, also known as meronym of, contained within, of, part of-property, section of (wd:P361 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): object of which the subject is a part (if this subject is alread... of "has part" (P527, see also "has parts of the class" (P2670))
7. depicted part, also known as part depicted, part shown, shown part (wd:P5961 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): use as qualifier for "depicts" (P180)
8. parent organization, also known as parent company, parent institution, parent organisation, parent unit, part of (wd:P749 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): parent organization of an organization, opposite of subsidiaries (P355), subproperty of owned by, subproperty of part of
9. partially coincident with, also known as partially include, overlaps, partially in, partial concurrency, overlaps with (wd:P1382 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): object that partially overlaps with the subject in its instances, parts, or members, subproperty of different from
10. number of parts of this work, also known as number of movements, number of parts of this work of art, number of pictures, number of segments of anthology film, number of songs (wd:P2635 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): the number of parts that a work comprises

[Tool] Got no rows and 3 columns

[Tool]
Got 39 rows and 3 columns, showing the first 10 rows below:
| subject                                              | property           | object                             |
| ---------------------------------------------------- | ------------------ | ---------------------------------- |
| 2018 Queen's Club Championships (wd:Q12299856)       | part of (wdt:P361) | 2018 ATP World Tour (wd:Q23039138) |
| 2018 Monte-Carlo Rolex Masters (wd:Q29477409)        | part of (wdt:P361) | 2018 ATP World Tour (wd:Q23039138) |
| 2018 Qatar ExxonMobil Open (wd:Q44318591)            | part of (wdt:P361) | 2018 ATP World Tour (wd:Q23039138) |
| 2018 Tata Open Maharashtra (wd:Q44318733)            | part of (wdt:P361) | 2018 ATP World Tour (wd:Q23039138) |
| 2018 Brisbane International (men) (wd:Q46911399)     | part of (wdt:P361) | 2018 ATP World Tour (wd:Q23039138) |
| 2018 Sydney International (men) (wd:Q46911599)       | part of (wdt:P361) | 2018 ATP World Tour (wd:Q23039138) |
| 2018 ASB Classic (men) (wd:Q46911617)                | part of (wdt:P361) | 2018 ATP World Tour (wd:Q23039138) |
| 2018 Diema Xtra Sofia Open (wd:Q47001464)            | part of (wdt:P361) | 2018 ATP World Tour (wd:Q23039138) |
| 2018 ABN AMRO World Tennis Tournament (wd:Q47227238) | part of (wdt:P361) | 2018 ATP World Tour (wd:Q23039138) |
| 2018 Delray Beach Open (wd:Q47882974)                | part of (wdt:P361) | 2018 ATP World Tour (wd:Q23039138) |
| ...                                                  | ...                | ...                                |

[Tool]
Got 94 rows and 3 columns, showing the first 10 rows below:
| subject                                        | property                                                    | object                                                   |
| ---------------------------------------------- | ----------------------------------------------------------- | -------------------------------------------------------- |
| 2018 Queen's Club Championships (wd:Q12299856) | instance of (wdt:P31)                                       | Queen's Club Championships (wd:Q299685)                  |
| 2018 Queen's Club Championships (wd:Q12299856) | country (wdt:P17)                                           | United Kingdom (wd:Q145)                                 |
| 2018 Queen's Club Championships (wd:Q12299856) | located in the administrative territorial entity (wdt:P131) | London (wd:Q84)                                          |
| 2018 Queen's Club Championships (wd:Q12299856) | Commons category (wdt:P373)                                 | 2018 Fever-Tree Championships                            |
| 2018 Queen's Club Championships (wd:Q12299856) | part of (wdt:P361)                                          | 2018 ATP World Tour (wd:Q23039138)                       |
| 2018 Queen's Club Championships (wd:Q12299856) | location (wdt:P276)                                         | The Queen's Club (wd:Q1748936)                           |
| 2018 Queen's Club Championships (wd:Q12299856) | has part(s) (wdt:P527)                                      | 2018 Queen's Club Championships – singles (wd:Q55082306) |
| 2018 Queen's Club Championships (wd:Q12299856) | sport (wdt:P641)                                            | tennis (wd:Q847)                                         |
| 2018 Queen's Club Championships (wd:Q12299856) | follows (wdt:P155)                                          | 2017 Aegon Championships (wd:Q30246411)                  |
| 2018 Queen's Club Championships (wd:Q12299856) | followed by (wdt:P156)                                      | 2019 Queen's Club Championships (wd:Q64562995)           |
| ...                                            | ...                                                         | ...                                                      |

[Tool]
Top 10 property alternatives:
1. area, also known as acreage, total area, surface area, surface, size (wd:P2046 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): area occupied by an object
2. has surface (wd:P10614 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): the object is the 2-dimensional surface that partly or completely surrounds the subject in 3-dimensional space
3. surface played on, also known as playing surface (wd:P765 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): the surface on which a sporting event is played
4. surface tension (wd:P3013 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): physical property of liquid
5. home venue, also known as venue, stadium, home water, home ground, home field (wd:P115 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): home stadium or venue of a sports team or applicable performing arts organization, subproperty of location
6. surface gravity (wd:P7015 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): gravitational acceleration experienced at the equator of an astronomical body surface
7. substrate of (wd:P2414 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): substrate that an enzyme acts upon to create a product, subproperty of has use
8. number of platform faces, also known as number of platforms, platform faces, platforms (wd:P5595 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): number of continuous platform edges facing a track or vehicle gu...latform numbers). See property talk page for illustrated samples
9. image, also known as img, infobox image, photo, photograph, picture (wd:P18 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
10. destination point, also known as finish, journey destination, stopping at, to, end point (journey) (wd:P1444 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): destination for this route (journey, flight, sailing, exploration, migration, etc.), subproperty of destination of transfer, subproperty of location

[Tool]
Got 1 row and 3 columns:
| subject                                        | property                     | object               |
| ---------------------------------------------- | ---------------------------- | -------------------- |
| 2018 Queen's Club Championships (wd:Q12299856) | surface played on (wdt:P765) | grass (wd:Q47678177) |

[Tool]
Got 1 row and 3 columns:
| subject                                        | property                  | object |
| ---------------------------------------------- | ------------------------- | ------ |
| 2018 Queen's Club Championships (wd:Q12299856) | edition number (wdt:P393) | 116th  |

[Tool]
Got 1 row and 3 columns:
| subject                                        | property                 | object                              |
| ---------------------------------------------- | ------------------------ | ----------------------------------- |
| 2018 Queen's Club Championships (wd:Q12299856) | point in time (wdt:P585) | 2018-01-01T00:00:00Z (xsd:dateTime) |

[Tool]
Got 1 row and 3 columns:
| subject                                        | property            | object                              |
| ---------------------------------------------- | ------------------- | ----------------------------------- |
| 2018 Queen's Club Championships (wd:Q12299856) | end time (wdt:P582) | 2018-06-24T00:00:00Z (xsd:dateTime) |

[Tool]
Got 1 row and 3 columns:
| subject                                        | property          | object                   |
| ---------------------------------------------- | ----------------- | ------------------------ |
| 2018 Queen's Club Championships (wd:Q12299856) | country (wdt:P17) | United Kingdom (wd:Q145) |

[Tool]
Got 1 row and 3 columns:
| subject                                        | property            | object                         |
| ---------------------------------------------- | ------------------- | ------------------------------ |
| 2018 Queen's Club Championships (wd:Q12299856) | location (wdt:P276) | The Queen's Club (wd:Q1748936) |

[Tool]
Got 39 rows and 7 columns, showing the first 5 and last 5 rows below:
| tournament                                                   | country              | endTime                             | location                            | edition | pointInTime                         | surface                 |
| ------------------------------------------------------------ | -------------------- | ----------------------------------- | ----------------------------------- | ------- | ----------------------------------- | ----------------------- |
| 2018 Swedish Open (wd:Q55391498)                             | Sweden (wd:Q34)      |                                     | Båstad Tennis Stadium (wd:Q5004953) | 71      | 2018-01-01T00:00:00Z (xsd:dateTime) |                         |
| 2018 Tata Open Maharashtra (wd:Q44318733)                    | India (wd:Q668)      | 2018-01-06T00:00:00Z (xsd:dateTime) | Pune (wd:Q1538)                     | 23      | 2018-01-01T00:00:00Z (xsd:dateTime) | hardcourt (wd:Q1330871) |
| 2018 Brisbane International (men) (wd:Q46911399)             |                      | 2018-01-07T00:00:00Z (xsd:dateTime) |                                     | 10      | 2018-01-01T00:00:00Z (xsd:dateTime) |                         |
| 2018 Qatar ExxonMobil Open (wd:Q44318591)                    | Qatar (wd:Q846)      | 2018-01-08T00:00:00Z (xsd:dateTime) | Doha (wd:Q3861)                     | 26      | 2018-01-01T00:00:00Z (xsd:dateTime) |                         |
| 2018 Sydney International (men) (wd:Q46911599)               |                      | 2018-01-13T00:00:00Z (xsd:dateTime) |                                     | 126     | 2018-01-01T00:00:00Z (xsd:dateTime) |                         |
| ...                                                          | ...                  | ...                                 | ...                                 | ...     | ...                                 | ...                     |
| 2018 China Open (men) (wd:Q56819344)                         |                      | 2018-10-07T00:00:00Z (xsd:dateTime) |                                     | 19      | 2018-01-01T00:00:00Z (xsd:dateTime) |                         |
| 2018 Stockholm Open (wd:Q57171456)                           | Sweden (wd:Q34)      | 2018-10-21T00:00:00Z (xsd:dateTime) | Royal Tennis Hall (wd:Q3369172)     | 49      | 2018-10-01T00:00:00Z (xsd:dateTime) | hardcourt (wd:Q1330871) |
| 2018 Kremlin Cup (men) (wd:Q57314287)                        |                      | 2018-10-21T00:00:00Z (xsd:dateTime) |                                     | 29      |                                     |                         |
| 2018 Swiss Indoors (wd:Q57339856)                            | Switzerland (wd:Q39) | 2018-10-28T00:00:00Z (xsd:dateTime) | St. Jakobshalle (wd:Q2318930)       | 49      | 2018-01-01T00:00:00Z (xsd:dateTime) | hardcourt (wd:Q1330871) |
| 2018 Oracle Challenger Series – Houston – Men (wd:Q59994545) |                      | 2018-11-18T00:00:00Z (xsd:dateTime) |                                     |         |                                     |                         |

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX xsd: <http://www.w3.org/2001/XMLSchema#>
SELECT ( ( ?lat1 + ?lat2 ) / 2 AS ?mid_latitude ) ( ( ?lon1 + ?lon2 ) / 2 AS ?mid_longitude ) WHERE {
  wd:Q90 wdt:P625 ?coord1 .
  BIND( STRAFTER( STR( ?coord1 ) , "POINT(" ) AS ?point1 ) BIND( STRBEFORE( ?point1 , ")" ) AS ?point1_vals ) BIND( STRBEFORE( ?point1_vals , " " ) AS ?lon1_str ) BIND( STRAFTER( ?point1_vals , " " ) AS ?lat1_str ) BIND( xsd:float ( ?lon1_str ) AS ?lon1 ) BIND( xsd:float ( ?lat1_str ) AS ?lat1 ) wd:Q240798 wdt:P625 ?coord2 .
  BIND( STRAFTER( STR( ?coord2 ) , "POINT(" ) AS ?point2 ) BIND( STRBEFORE( ?point2 , ")" ) AS ?point2_vals ) BIND( STRBEFORE( ?point2_vals , " " ) AS ?lon2_str ) BIND( STRAFTER( ?point2_vals , " " ) AS ?lat2_str ) BIND( xsd:float ( ?lon2_str ) AS ?lon2 ) BIND( xsd:float ( ?lat2_str ) AS ?lat2 )
}

The geographic midpoint between Paris and Montigny-le-Bretonneux is at latitude 48.8136 and longitude 2.19236.

What is the geographic point that represents the midpoint of the coordinates of Paris (the capital of France) and Montigny-le-Bretonneux (a commune in Yvelines, France)? Return one column for the latitude and one column for the longitude

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

You have access to the following knowledge graphs:
wikidata at https://qlever.cs.uni-freiburg.de/api/wikidata-sebastian with notes:
1. For P39 legislative memberships, filter by pq:P2937 (legislative term) on the p:P39 statement; don’t use P793 for term filtering. For UK MPs, avoid a generic Q16707842-only scan; rely on term qualifiers and proper date overlap on pq:P580/pq:P582.
2. For residence (P551), time bounds are qualifiers on the statement: p:P551/ps:P551 place, pq:P580 start, pq:P582 end. To include containing areas (e.g., NYC boroughs), expand via wdt:P551/wdt:P131*. Durations usually need client-side calc on QLever.
3. Ticker symbols are pq:P249 on p:P414 statements; query via the statement node (?org p:P414 ?st . ?st ps:P414 ?ex ; pq:P249 ?ticker). Use VALUES to pre-limit orgs/exchanges. Don’t expect wdt:P249 on the org. Prefer qualifiers for time-bound tickers.
4. Archives: use p:P485/ps:P485 for the holding institution. Inventory numbers are qualifiers pq:P217 on that P485 statement. Don’t expect wdt:P217 directly on the person/work. “Archive descriptions” may be separate collection items (P195).
5. When listing contained municipalities or similar, prefer wdt:P150* (has parts) from the parent to enumerate children, then join other relations (e.g., twin towns via wdt:P190). Avoid broad wdt:P131+ scans from children; they are slow and can timeout.
6. On QLever, avoid SERVICE wikibase:label (frequent 301). Use OPTIONAL rdfs:label with LANG filters or fetch QIDs then labels separately. For property mapping, (?prop wikibase:directClaim ?p). Pre-limit with subselect/VALUES to avoid timeouts.
7. Employer constraints: to find people employed by UN or international orgs, use wdt:P108 directly for UN (wd:Q1065), or traverse employer to part of (wdt:P361*) UN, or employer wdt:P31 wd:Q484652 (international organization). Combine with other occupations.
8. For sports/events/editions, prefer explicit edition items (e.g., Q47345468) with wdt:P361 linking to the parent series/tour and filter by wdt:P585/P571 for year; avoid P641/P2139 that model sports played or participants, not the edition metadata.
9. For author/creator queries, use occupation wdt:P106 (e.g., author/writer) rather than P31 typing. To list works, prefer the reverse path ^wdt:P50 ?work; P800 (notable work) is incomplete and curated, not a full bibliography.
10. Awards: use p:P166/ps:P166 and constrain award via wdt:P31/wdt:P279* to a target class (e.g., Cannes awards Q28444913). Recipients can be films or people; don’t assume film-specific properties exist. Count/group by recipient type if needed.
11. To select current/active codes or memberships on QLever, use statement nodes (p:/ps:) and MINUS { ?st pq:P582 [] }. For time series counts (e.g., daily members), generate a date series (VALUES/UNNEST), then test overlap with pq:P580/pq:P582 per date.
12. For people’s native names, use wdt:P1559 (name in native language) on the person, not rdfs:label. Return multiple if multiple native languages exist; pick a preferred language client-side if needed.
13. For multi-valued props (e.g., P1082), GROUP BY entity and aggregate (MAX/MIN/SAMPLE) to avoid duplicates; DISTINCT won’t collapse multiple statements. For category/gender counts, prefer indicator sums: SUM(IF(cond,1,0)) over COUNT on OPTIONAL vars.
14. Avoid SERVICE wikibase:label on QLever; it often 301s. Use OPTIONAL rdfs:label with LANG filters, or fetch QIDs first and labels in a follow-up. Pre-limit with subselect/VALUES to avoid timeouts when joining many labels.
15. For P551 duration comparisons, avoid unsupported date arithmetic. If needed, compute overlaps client-side. On-endpoint, you can only compare presence/counts or use simple MIN/MAX of dates (casting and arithmetic are limited in QLever).
16. When excluding specific entities from a relation (e.g., siblings), use FILTER to drop explicit QIDs or FILTER NOT EXISTS with a VALUES list. Ensure you use the exact sibling QIDs returned by the KG, not assumed ones.

General notes for all knowledge graphs:
1. When checking date interval overlaps, handle open intervals (missing start/end) and use xsd:dateTime. Use OR conditions to cover start within, end within, or spanning the whole range.
2. For P39 queries, qualifiers (e.g., P2937 term, P768 electoral district, P4100 parliamentary group) live on the p:P39 statement node. Do not expect them as wdt: properties on the person or use ps: for non-main values.
3. To get sitelink counts, use wikibase:sitelinks on the entity; it returns a single numeric value, so GROUP BY the entity and avoid COUNT over ?sitelink.
4. Use subclass expansion for types: wdt:P31/wdt:P279* target (e.g., dams, educational institutions). This captures items modeled with subclasses.
5. For locations, prefer hierarchies via wdt:P131+ to reach a containing region/state, and wdt:P17 for country. If HQ is a building, P159 ps points to a city; specific site is qualifier pq:P276 on the P159 statement.
6. When excluding or selecting by a legislative term on P39, check pq:P2937 on the relevant statement. Use FILTER NOT EXISTS over p:P39 with ps:P39 target and pq:P2937 value to exclude a term.
7. QLever endpoints may not support Wikidata’s “WITH {…} AS %name” and “INCLUDE %name” syntax. Avoid named subqueries; use nested SELECTs or VALUES instead.
8. The wikibase:label SERVICE often fails on QLever. Prefer rdfs:label with FILTER(LANG(..)="en") or get QIDs only and resolve labels client-side.
9. Avoid COUNT over OPTIONAL variables that may be unbound for all rows; prefer EXISTS/BOUND checks or aggregate over DISTINCT entities to prevent misleading zeros.
10. On QLever, heavy OPTIONAL label/property joins often time out. Pre-limit with a subselect/VALUES over IDs (ORDER BY + LIMIT), then join labels/properties. Or fetch QIDs first and labels in a second, smaller query.
11. For precise date filtering on Wikidata (birth/death), prefer p/psv time nodes and wikibase:timeValue plus timePrecision checks over wdt:P569/P570 to include values with year/month precision and avoid silent drops.
12. When filtering by exact day of birth or event, avoid STRSTARTS on wdt:P569; instead bound an interval [day, next day) with xsd:dateTime to include all precisions. On QLever, add hint:Prior hint:rangeSafe true to improve performance on time ranges.

You can use the following SPARQL prefixes implicitly in all functions:
cc: <http://creativecommons.org/ns#
data: <https://www.wikidata.org/wiki/Special:EntityData/
dct: <http://purl.org/dc/terms/
geo: <http://www.opengis.net/ont/geosparql#
geof: <http://www.opengis.net/def/function/geosparql/
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/
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/
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#
foaf: <http://xmlns.com/foaf/0.1/
dc: <http://purl.org/dc/elements/1.1/
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
qb: <http://purl.org/linked-data/cube#
void: <http://rdfs.org/ns/void#

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.

Additional rules:
1. Explain your thought process before and after each step and function call.
2. Do not just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
3. Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
4. 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.
5. 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.
6. 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.
7. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
8. 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.

[User] What is the geographic point that represents the midpoint of the coordinates of Paris (the capital of France) and Montigny-le-Bretonneux (a commune in Yvelines, France)? Return one column for the latitude and one column for the longitude

[Assistant]
Let's break down the question:

1. We need the coordinates (latitude and longitude) of Paris and Montigny-le-Bretonneux.
2. We then need to compute the midpoint between these two coordinates. Since SPARQL on Wikidata does not support arithmetic on coordinates directly, we will:
   - Retrieve the coordinates for both places.
   - Extract their latitude and longitude using the geo:lat and geo:long properties (or similar).
   - Compute the average (midpoint) of the latitudes and longitudes using SPARQL's math functions.

First, let's find the Wikidata entities for Paris and Montigny-le-Bretonneux.

I'll search for "Paris" and "Montigny-le-Bretonneux" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Paris, also known as Lutetia, City of Love, City of Light (wd:Q90): instance of territorial collectivity of France with special status, capital city and largest city of France, instance of department of France, instance of largest city, instance of global city, instance of metropolis, instance of megacity
2. Paris Saint-Germain FC, also known as Paris Saint-Germain Football Club, PSGFC, PSG, Paris SG, Paris Saint-Germain F.C. (wd:Q483020): association football club in Paris, France, instance of association football club
3. Paris, also known as Alexander, Alexandros (wd:Q167646): instance of mythological Greek character, mythological son of Priam, king of Troy, herder
4. Paris, also known as Paris, Texas, Paris, TX (wd:Q830149): city in and county seat of Lamar County, Texas, United States, instance of city in the United States, instance of county seat
5. Paris, also known as Paris, ID, Paris, Idaho (wd:Q984459): instance of city in the United States, city in Idaho, United States
6. Paris, also known as Paris, IL, Paris Illinois, Paris, Illinois (wd:Q576584): instance of city in the United States, city in Illinois
7. Paris (wd:Q162121): instance of taxon, genus of plants
8. Paris, also known as Paris, Kentucky, Paris, KY (wd:Q3181341): county seat of Bourbon County, Kentucky, United States, instance of city in the United States, instance of county seat
9. Paris, also known as Paris, AR, Paris, Arkansas (wd:Q79917): instance of city in the United States, city in Arkansas, United States
10. Äynu, also known as Ainu, Ainu (China), Äynu language, Ejnu, Ejnu language (wd:Q27927)

[Tool]
Top 10 entity alternatives:
1. Montigny-le-Bretonneux (wd:Q240798): instance of commune of France, commune in Yvelines, France
2. AS Montigny-le-Bretonneux (wd:Q2868096): instance of women's association football team, football club
3. canton of Montigny-le-Bretonneux (wd:Q1726322): instance of canton of France, canton of France
4. temple de Montigny-le-Bretonneux (wd:Q60428202): meeting house located in Yvelines, in France, instance of Protestant church building
5. Mayor of Montigny-le-Bretonneux (wd:Q62587392)
6. municipality of Montigny-le-Bretonneux, also known as Montigny-le-Bretonneux city government, Administration of Montigny-le-Bretonneux, City of Montigny-le-Bretonneux (wd:Q118540991): municipal government of Montigny-le-Bretonneux, France, instance of administration municipale of France
7. Église Saint-Martin de Montigny-le-Bretonneux (wd:Q41802011): church located in Yvelines, in France, instance of church building
8. église Saint-Pierre-du-Lac de Montigny-le-Bretonneux (wd:Q41802014): church located in Yvelines, in France, instance of church building
9. Église Saint-Quentin-des-Sources de Montigny-le-Bretonneux (wd:Q41802013): church located in Yvelines, in France, instance of church building
10. town hall of Montigny-le-Bretonneux (wd:Q119319373): town hall located in Yvelines department, France, instance of facility

[Tool]
Top 10 property alternatives:
1. coordinate location, also known as gps co-ordinates, wgs 84, gps coordinates, gps location, latitude (wd:P625 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): geocoordinates of the subject. For Earth, please note that only WGS84 coordinating system is supported at the moment
2. this zoological name is coordinate with, also known as coordinate name (wd:P2743 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): links coordinate zoological names, subproperty of different from
3. time index, also known as relative time, temporal coordinate, time coordinate, timestamp (wd:P4895 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): indicate when something happens relative to its beginning
4. genomic start, also known as Genloc Start, start coordinate, genomic from, Genloc From, from (wd:P644 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): genomic starting coordinate of the biological sequence (e.g. a gene)
5. spatial reference system, also known as coordinate reference system, CRS, SRS (wd:P3037 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): frame of reference used to produce a map
6. y-offset, also known as ordinate, y-axis (wd:P8685 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): offset on the y-axis or secondary axis
7. genomic end, also known as Genloc Stop, stop coordinate, stop, Genloc End, genomic stop (wd:P645 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): genomic ending coordinate of the biological sequence (e.g. a gene)
8. ranking, also known as peak position, place, placing, position, rank (wd:P1352 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): subject's ordinal position as qualitatively evaluated relative to other members of a group
9. orientation, also known as direction, facing, faces, face, alignment (wd:P7469 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): axis of alignment of an item, or direction perpendicular to its primary face (specify with P518 if necessary)
10. political alignment, also known as alignment, political position (wd:P1387 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): political position within the left–right political spectrum

[Tool]
Got 1 row and 3 columns:
| subject        | property                       | object                                     |
| -------------- | ------------------------------ | ------------------------------------------ |
| Paris (wd:Q90) | coordinate location (wdt:P625) | POINT(2.352222 48.856667) (geo:wktLiteral) |

[Tool]
Got 1 row and 3 columns:
| subject                             | property                       | object                                     |
| ----------------------------------- | ------------------------------ | ------------------------------------------ |
| Montigny-le-Bretonneux (wd:Q240798) | coordinate location (wdt:P625) | POINT(2.032500 48.770556) (geo:wktLiteral) |

[Assistant]
We have the following coordinates:
- Paris (wd:Q90): POINT(2.352222 48.856667) → longitude 2.352222, latitude 48.856667
- Montigny-le-Bretonneux (wd:Q240798): POINT(2.032500 48.770556) → longitude 2.032500, latitude 48.770556

To find the midpoint:
- Midpoint latitude = (48.856667 + 48.770556) / 2 = 48.8136115
- Midpoint longitude = (2.352222 + 2.032500) / 2 = 2.192361

We need to write a SPARQL query that:
1. Retrieves the coordinates for both entities.
2. Extracts the latitude and longitude from the geo:wktLiteral.
3. Computes the average for each.

Wikidata's QLever endpoint supports the ql:coordinates function to extract lat/lon from geo:wktLiteral.

Let's build the query accordingly.

[Tool]
Call to function execute returned an error:
failed to parse input: parse error at position 222 for token [ with content '[' (the input most likely does not follow the grammar)

[Assistant]
It appears that the use of array indexing (e.g., ?coords[0]) is not supported in QLever's SPARQL implementation. Instead, we need to extract the latitude and longitude directly from the geo:wktLiteral using string manipulation.

The geo:wktLiteral for a point is of the form "POINT(longitude latitude)", so we can use STRAFTER and STRBEFORE to extract the numbers.

Let's write a query that:
- Retrieves the wktLiteral for both cities.
- Extracts longitude and latitude as xsd:float.
- Computes the average.

I'll proceed with this approach.

[Tool]
Got 1 row and 2 columns:
| mid_latitude          | mid_longitude         |
| --------------------- | --------------------- |
| 48.8136 (xsd:decimal) | 2.19236 (xsd:decimal) |

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?commune ( SAMPLE( ?label ) AS ?communeLabel ) WHERE {
  ?commune wdt:P31 wd:Q17318027 .
  ?commune wdt:P17 wd:Q1028 .
  OPTIONAL {
    ?commune rdfs:label ?label FILTER ( LANG( ?label ) = "en" )
  }
}
GROUP BY ?commune

Got 1,276 rows and 2 columns, showing the first 5 and last 5 rows below:
| commune                           | communeLabel             |
| --------------------------------- | ------------------------ |
| Telouet (wd:Q1010760)             | Telouet (en)             |
| M'Hamid El Ghizlane (wd:Q1014625) | M'Hamid El Ghizlane (en) |
| Nkob (wd:Q10334921)               | Nkob (en)                |
| Sidi Borja (wd:Q11131837)         | Sidi Borja (en)          |
| Sidi Ouaaziz (wd:Q11220738)       | Sidi Ouaaziz (en)        |
| ...                               | ...                      |
| Bouarg (wd:Q894944)               | Bouarg (en)              |
| Bab Taza (wd:Q920156)             | Bab Taza (en)            |
| Souk Tlet El Gharb (wd:Q952999)   | Souk Tlet El Gharb (en)  |
| Oulad Youssef (wd:Q956049)        | Oulad Youssef (en)       |
| Alnif (wd:Q984312)                | Alnif (en)               |

The rural communes of Morocco are all entities that are instances of 'rural commune of Morocco' (wd:Q17318027) and are located in Morocco (wd:Q1028). There are over 1,200 such communes, including examples like Telouet, M'Hamid El Ghizlane, Nkob, Sidi Borja, and Sidi Ouaaziz. The full list can be retrieved using the provided SPARQL query.

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

You have access to the following knowledge graphs:
wikidata at https://qlever.cs.uni-freiburg.de/api/wikidata-sebastian with notes:
1. For P39 legislative memberships, filter by pq:P2937 (legislative term) on the p:P39 statement; don’t use P793 for term filtering. For UK MPs, avoid a generic Q16707842-only scan; rely on term qualifiers and proper date overlap on pq:P580/pq:P582.
2. For residence (P551), time bounds are qualifiers on the statement: p:P551/ps:P551 place, pq:P580 start, pq:P582 end. To include containing areas (e.g., NYC boroughs), expand via wdt:P551/wdt:P131*. Durations usually need client-side calc on QLever.
3. Ticker symbols are pq:P249 on p:P414 statements; query via the statement node (?org p:P414 ?st . ?st ps:P414 ?ex ; pq:P249 ?ticker). Use VALUES to pre-limit orgs/exchanges. Don’t expect wdt:P249 on the org. Prefer qualifiers for time-bound tickers.
4. Archives: use p:P485/ps:P485 for the holding institution. Inventory numbers are qualifiers pq:P217 on that P485 statement. Don’t expect wdt:P217 directly on the person/work. “Archive descriptions” may be separate collection items (P195).
5. When listing contained municipalities or similar, prefer wdt:P150* (has parts) from the parent to enumerate children, then join other relations (e.g., twin towns via wdt:P190). Avoid broad wdt:P131+ scans from children; they are slow and can timeout.
6. On QLever, avoid SERVICE wikibase:label (frequent 301). Use OPTIONAL rdfs:label with LANG filters or fetch QIDs then labels separately. For property mapping, (?prop wikibase:directClaim ?p). Pre-limit with subselect/VALUES to avoid timeouts.
7. Employer constraints: to find people employed by UN or international orgs, use wdt:P108 directly for UN (wd:Q1065), or traverse employer to part of (wdt:P361*) UN, or employer wdt:P31 wd:Q484652 (international organization). Combine with other occupations.
8. For sports/events/editions, prefer explicit edition items (e.g., Q47345468) with wdt:P361 linking to the parent series/tour and filter by wdt:P585/P571 for year; avoid P641/P2139 that model sports played or participants, not the edition metadata.
9. For author/creator queries, use occupation wdt:P106 (e.g., author/writer) rather than P31 typing. To list works, prefer the reverse path ^wdt:P50 ?work; P800 (notable work) is incomplete and curated, not a full bibliography.
10. Awards: use p:P166/ps:P166 and constrain award via wdt:P31/wdt:P279* to a target class (e.g., Cannes awards Q28444913). Recipients can be films or people; don’t assume film-specific properties exist. Count/group by recipient type if needed.
11. To select current/active codes or memberships on QLever, use statement nodes (p:/ps:) and MINUS { ?st pq:P582 [] }. For time series counts (e.g., daily members), generate a date series (VALUES/UNNEST), then test overlap with pq:P580/pq:P582 per date.
12. For people’s native names, use wdt:P1559 (name in native language) on the person, not rdfs:label. Return multiple if multiple native languages exist; pick a preferred language client-side if needed.
13. For multi-valued props (e.g., P1082), GROUP BY entity and aggregate (MAX/MIN/SAMPLE) to avoid duplicates; DISTINCT won’t collapse multiple statements. For category/gender counts, prefer indicator sums: SUM(IF(cond,1,0)) over COUNT on OPTIONAL vars.
14. Avoid SERVICE wikibase:label on QLever; it often 301s. Use OPTIONAL rdfs:label with LANG filters, or fetch QIDs first and labels in a follow-up. Pre-limit with subselect/VALUES to avoid timeouts when joining many labels.
15. For P551 duration comparisons, avoid unsupported date arithmetic. If needed, compute overlaps client-side. On-endpoint, you can only compare presence/counts or use simple MIN/MAX of dates (casting and arithmetic are limited in QLever).
16. When excluding specific entities from a relation (e.g., siblings), use FILTER to drop explicit QIDs or FILTER NOT EXISTS with a VALUES list. Ensure you use the exact sibling QIDs returned by the KG, not assumed ones.

General notes for all knowledge graphs:
1. When checking date interval overlaps, handle open intervals (missing start/end) and use xsd:dateTime. Use OR conditions to cover start within, end within, or spanning the whole range.
2. For P39 queries, qualifiers (e.g., P2937 term, P768 electoral district, P4100 parliamentary group) live on the p:P39 statement node. Do not expect them as wdt: properties on the person or use ps: for non-main values.
3. To get sitelink counts, use wikibase:sitelinks on the entity; it returns a single numeric value, so GROUP BY the entity and avoid COUNT over ?sitelink.
4. Use subclass expansion for types: wdt:P31/wdt:P279* target (e.g., dams, educational institutions). This captures items modeled with subclasses.
5. For locations, prefer hierarchies via wdt:P131+ to reach a containing region/state, and wdt:P17 for country. If HQ is a building, P159 ps points to a city; specific site is qualifier pq:P276 on the P159 statement.
6. When excluding or selecting by a legislative term on P39, check pq:P2937 on the relevant statement. Use FILTER NOT EXISTS over p:P39 with ps:P39 target and pq:P2937 value to exclude a term.
7. QLever endpoints may not support Wikidata’s “WITH {…} AS %name” and “INCLUDE %name” syntax. Avoid named subqueries; use nested SELECTs or VALUES instead.
8. The wikibase:label SERVICE often fails on QLever. Prefer rdfs:label with FILTER(LANG(..)="en") or get QIDs only and resolve labels client-side.
9. Avoid COUNT over OPTIONAL variables that may be unbound for all rows; prefer EXISTS/BOUND checks or aggregate over DISTINCT entities to prevent misleading zeros.
10. On QLever, heavy OPTIONAL label/property joins often time out. Pre-limit with a subselect/VALUES over IDs (ORDER BY + LIMIT), then join labels/properties. Or fetch QIDs first and labels in a second, smaller query.
11. For precise date filtering on Wikidata (birth/death), prefer p/psv time nodes and wikibase:timeValue plus timePrecision checks over wdt:P569/P570 to include values with year/month precision and avoid silent drops.
12. When filtering by exact day of birth or event, avoid STRSTARTS on wdt:P569; instead bound an interval [day, next day) with xsd:dateTime to include all precisions. On QLever, add hint:Prior hint:rangeSafe true to improve performance on time ranges.

You can use the following SPARQL prefixes implicitly in all functions:
cc: <http://creativecommons.org/ns#
data: <https://www.wikidata.org/wiki/Special:EntityData/
dct: <http://purl.org/dc/terms/
geo: <http://www.opengis.net/ont/geosparql#
geof: <http://www.opengis.net/def/function/geosparql/
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/
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/
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#
foaf: <http://xmlns.com/foaf/0.1/
dc: <http://purl.org/dc/elements/1.1/
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
qb: <http://purl.org/linked-data/cube#
void: <http://rdfs.org/ns/void#

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.

Additional rules:
1. Explain your thought process before and after each step and function call.
2. Do not just use or make up entity or property identifiers without verifying their existence in the knowledge graphs first.
3. Always execute your final SPARQL query before giving an answer to make sure it returns the expected results.
4. 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.
5. 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.
6. 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.
7. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
8. 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.

[User] What are the rural communes of Morocco?

[Assistant]
Let's break down the question:

1. We are looking for "rural communes" in "Morocco".
2. In Wikidata, administrative divisions like "commune" are usually modeled as entities with instance of (P31) "commune" or a subclass, and "rural commune" may be a specific subclass or instance.
3. We need to ensure these communes are located in Morocco (country: Morocco).

Step 1: Search for the entity for "rural commune" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. rural commune of Morocco, also known as rural commune (wd:Q17318027)
2. rural commune of Vietnam, also known as Xã, xã, xa (wd:Q2389082)
3. commune rurale de Nojaï-Iourt (wd:Q24636444): human settlement in Nozhay-Yurtovsky District, Chechen Republic, Russia, instance of rural settlement in Russia
4. Health in a Rural Hippie Commune (wd:Q41557175): scientific article published on August 24, 1970, instance of scholarly article
5. L'habitat rural dans une commune bretonne. (wd:Q127723686): instance of scholarly article, scholarly article
6. [Rural pharmacy and the communes.] (wd:Q78953786): scientific article published on 01 July 1960, instance of scholarly article
7. Paris Commune, also known as Commune (wd:Q133132): instance of administrative territorial entity, Revolutionary city council of Paris in 1871, instance of social experiment, instance of organization, instance of group action, instance of insurgency, instance of commune
8. commune of France, also known as commune (France), commune (wd:Q484170)
9. commune, also known as comune (wd:Q3266850)
10. commune (wd:Q517760)

[Assistant]
The top result is "rural commune of Morocco" (wd:Q17318027), which is exactly what we need.

Step 2: We need to find all entities that are instances of (P31) "rural commune of Morocco" (wd:Q17318027), and are located in Morocco.

However, since "rural commune of Morocco" is already specific, the location constraint may be redundant, but we can include it for precision.

Step 3: Let's check if "rural commune of Morocco" is used as an instance (P31) or subclass (P279) for entities, and what property is used for "country" (likely P17).

I'll check the properties of a known rural commune to confirm.

[Tool]
Got 104 rows and 3 columns, showing the first 10 rows below:
| subject                                 | property                         | object                                                     |
| --------------------------------------- | -------------------------------- | ---------------------------------------------------------- |
| rural commune of Morocco (wd:Q17318027) | country (wdt:P17)                | Morocco (wd:Q1028)                                         |
| rural commune of Morocco (wd:Q17318027) | part of (wdt:P361)               | circle of Morocco (wd:Q23019196)                           |
| rural commune of Morocco (wd:Q17318027) | subclass of (wdt:P279)           | administrative territorial entity of Morocco (wd:Q4115671) |
| rural commune of Morocco (wd:Q17318027) | has part(s) (wdt:P527)           | centre (wd:Q23925390)                                      |
| rural commune of Morocco (wd:Q17318027) | topic's main category (wdt:P910) | wd:Q8689472                                                |
| rural commune of Morocco (wd:Q17318027) | quantity (wdt:P1114)             | 1282 (xsd:decimal)                                         |
| rural commune of Morocco (wd:Q17318027) | KBpedia ID (wdtn:P8408)          | <http://kbpedia.org/kko/rc/RuralCommune-Morocco>           |
| rural commune of Morocco (wd:Q17318027) | wdt:P31279                       | administrative region (wd:Q3455524)                        |
| rural commune of Morocco (wd:Q17318027) | schema:description               | administrative division of Morocco (en)                    |
| rural commune of Morocco (wd:Q17318027) | schema:name                      | commune rurale du Maroc (fr)                               |
| ...                                     | ...                              | ...                                                        |

[Tool]
Top 10 property alternatives:
1. quantity, also known as number of instances, total number, total, qty, occurrences (wd:P1114 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): number of instances of this subject in the universe of the subje...e actual number of instances in Wikidata may be lower or higher)
2. instance of, also known as example of, has type, is a, is an, is of type (wd:P31 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): type to which this subject corresponds/belongs. Different from P...tains, and the volcano is a type (instance) of volcanic landform
3. is metaclass for, also known as is metaclass of, metaclass of, metaclass for, is an abstraction for concept of, is a metaclass for (wd:P8225 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): all instances of the subject are subclasses of the object
4. subproperty of, also known as parent property, superproperty, subPropertyOf, subclass of property, rdfs:subPropertyOf (wd:P1647 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): all resources related by this property are also related by that property, subproperty of related property
5. Wikidata property example, also known as example of property, Wikidata property sample, property sample, property example, for example (wd:P1855 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): example where this Wikidata property is used; target item is one...ualifier the property being described given the associated value
6. subclass of, also known as subcategory of, subgenre of, sort of, subtype of, type of (wd:P279 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain
7. individual of taxon, also known as is individual of the taxon, taxon of the item, taxon of subject, taxon of item, species of this individual (wd:P10241 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): the taxon of an individual named organism (animal, plant), subproperty of instance of
8. model item, also known as best example, example item, featured item, for example, sample (wd:P5869 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): defines which item is a best practice example of modelling a sub...lue of this property, usage instructions at Wikidata:Model items
9. class of non-item property value, also known as values are instances of (wd:P10726 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): class of the value of a property whose value datatype is not Item. The class should only include acceptable values for the property, subproperty of Wikidata item of this property
10. date of the latest one, also known as date of the latest instance, date of the most recent instance, latest instance (wd:P7125 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): qualifier: when the latest element of a quantity appeared/took place

[Tool]
Got 10 rows and 1 column:
| commune                           |
| --------------------------------- |
| Telouet (wd:Q1010760)             |
| M'Hamid El Ghizlane (wd:Q1014625) |
| Nkob (wd:Q10334921)               |
| Sidi Borja (wd:Q11131837)         |
| Sidi Ouaaziz (wd:Q11220738)       |
| Ouizeght (wd:Q11285966)           |
| Afourar (wd:Q1158785)             |
| Daoura (wd:Q1165464)              |
| Sid L'Mokhtar (wd:Q1169573)       |
| Lalla Mimouna (wd:Q1169828)       |

[Tool]
Got 100 rows and 1 column, showing the first 5 and last 5 rows below:
| commune                           |
| --------------------------------- |
| Telouet (wd:Q1010760)             |
| M'Hamid El Ghizlane (wd:Q1014625) |
| Nkob (wd:Q10334921)               |
| Sidi Borja (wd:Q11131837)         |
| Sidi Ouaaziz (wd:Q11220738)       |
| ...                               |
| Bni Chegdale (wd:Q12199532)       |
| Bni Frassen (wd:Q12199592)        |
| Bni Lent (wd:Q12199611)           |
| Bni Leit (wd:Q12199612)           |
| Bni Hilal (wd:Q12199659)          |

[Tool]
Got 100 rows and 1 column, showing the first 5 and last 5 rows below:
| commune                           |
| --------------------------------- |
| Telouet (wd:Q1010760)             |
| M'Hamid El Ghizlane (wd:Q1014625) |
| Nkob (wd:Q10334921)               |
| Sidi Borja (wd:Q11131837)         |
| Sidi Ouaaziz (wd:Q11220738)       |
| ...                               |
| Bni Chegdale (wd:Q12199532)       |
| Bni Frassen (wd:Q12199592)        |
| Bni Lent (wd:Q12199611)           |
| Bni Leit (wd:Q12199612)           |
| Bni Hilal (wd:Q12199659)          |

[Tool]
Got 200 rows and 1 column, showing the first 5 and last 5 rows below:
| commune                           |
| --------------------------------- |
| Telouet (wd:Q1010760)             |
| M'Hamid El Ghizlane (wd:Q1014625) |
| Nkob (wd:Q10334921)               |
| Sidi Borja (wd:Q11131837)         |
| Sidi Ouaaziz (wd:Q11220738)       |
| ...                               |
| Chtouka (wd:Q12218399)            |
| Chaibate (wd:Q12218880)           |
| Chougrane (wd:Q12219457)          |
| Saddina (wd:Q12219919)            |
| Azzaba (wd:Q12224806)             |

[Tool]
Got 500 rows and 1 column, showing the first 5 and last 5 rows below:
| commune                           |
| --------------------------------- |
| Telouet (wd:Q1010760)             |
| M'Hamid El Ghizlane (wd:Q1014625) |
| Nkob (wd:Q10334921)               |
| Sidi Borja (wd:Q11131837)         |
| Sidi Ouaaziz (wd:Q11220738)       |
| ...                               |
| Dzouz (wd:Q20414082)              |
| Bni Mathar (wd:Q20414402)         |
| Sfassif (wd:Q20415523)            |
| Boumerieme (wd:Q20415560)         |
| Es-Sfalat (wd:Q20416059)          |

[Tool]
Got 1,000 rows and 1 column, showing the first 5 and last 5 rows below:
| commune                                 |
| --------------------------------------- |
| Telouet (wd:Q1010760)                   |
| M'Hamid El Ghizlane (wd:Q1014625)       |
| Nkob (wd:Q10334921)                     |
| Sidi Borja (wd:Q11131837)               |
| Sidi Ouaaziz (wd:Q11220738)             |
| ...                                     |
| Jaidate (wd:Q6123514)                   |
| Taghramt (wd:Q6137989)                  |
| Jaqma (wd:Q6159370)                     |
| Jbabra (wd:Q6168632)                    |
| Sidi Mohamed Ben Mansour (wd:Q61872997) |

[Tool]
Got 1,276 rows and 1 column, showing the first 5 and last 5 rows below:
| commune                           |
| --------------------------------- |
| Telouet (wd:Q1010760)             |
| M'Hamid El Ghizlane (wd:Q1014625) |
| Nkob (wd:Q10334921)               |
| Sidi Borja (wd:Q11131837)         |
| Sidi Ouaaziz (wd:Q11220738)       |
| ...                               |
| Bouarg (wd:Q894944)               |
| Bab Taza (wd:Q920156)             |
| Souk Tlet El Gharb (wd:Q952999)   |
| Oulad Youssef (wd:Q956049)        |
| Alnif (wd:Q984312)                |

[Tool]
Got 1,276 rows and 2 columns, showing the first 5 and last 5 rows below:
| commune                           | communeLabel             |
| --------------------------------- | ------------------------ |
| Telouet (wd:Q1010760)             | Telouet (en)             |
| M'Hamid El Ghizlane (wd:Q1014625) | M'Hamid El Ghizlane (en) |
| Nkob (wd:Q10334921)               | Nkob (en)                |
| Sidi Borja (wd:Q11131837)         | Sidi Borja (en)          |
| Sidi Ouaaziz (wd:Q11220738)       | Sidi Ouaaziz (en)        |
| ...                               | ...                      |
| Bouarg (wd:Q894944)               | Bouarg (en)              |
| Bab Taza (wd:Q920156)             | Bab Taza (en)            |
| Souk Tlet El Gharb (wd:Q952999)   | Souk Tlet El Gharb (en)  |
| Oulad Youssef (wd:Q956049)        | Oulad Youssef (en)       |
| Alnif (wd:Q984312)                | Alnif (en)               |

[Tool] Stopped generation process