PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT DISTINCT ?tournament ?tLabel ?country ?endTime ?location ?edition ?pointInTime ?surface WHERE {
  ?tournament wdt:P361 wd:Q23039138 .
  OPTIONAL {
    ?tournament rdfs:label ?tLabel .
    FILTER ( LANG( ?tLabel ) = "en" )
  }
  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 ?endTime
LIMIT 500

Using entities:
- 2018 ATP World Tour (wd:Q23039138): is instance of tennis tour edition / tennis circuit

Using properties:
- 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)
- location (wd:P276 as wdt), also known as based in, city, from, held by, in, etc.: location of the item, physical object or event is within. In ... use P131. In case of a distinct terrain feature use P706. / location of the item, physical object or event is within. In ... use P131. In case of a distinct terrain feature use P706. / location of the object, structure or event. In the case of an ... use P706. Use P7153 for locations associated with the object
- part of (wd:P361 as wdt), also known as assembly of, branch of, chain, collateral branch of, component of, etc.: object of which the subject is a part (if this subject is ... "has part" (P527, see also "has parts of the class" (P2670)) / object of which the subject is a part (if this subject is ... "has part" (P527, see also "has parts of the class" (P2670)) / object of which the subject is a part (if this subject is ... "has part" (P527, see also "has parts of the class" (P2670)) / object of which the subject is a part (if this subject is ... "has part" (P527, see also "has parts of the class" (P2670))
- edition number (wd:P393 as wdt), also known as number of event, software version number, version number, P393: is subproperty of series ordinal / number of an edition (first, second, ... as 1, 2, ...) or event / number of this edition (first, second, ... as 1, 2, ...) of a book or event
- end time (wd:P582 as wdt), also known as abolished, cease date, cease operation, cease time, closed, etc.: is subproperty of point in time / indicates the time an item ceases to exist or a statement stops being valid / indicates the time an item ceases to exist or a statement stops being valid / moment when an entity ceases to exist and a statement stops being entirely valid or no longer be true
- point in time (wd:P585 as wdt), also known as as of, at time, by date, date, during, etc.: date something took place, existed or a statement was true; for providing time use the "refine date" property (P4241) / time and date something took place, existed or a statement was true / time and date something took place, existed or a statement was true / time and date something took place, existed or a statement was true
- surface played on (wd:P765 as wdt), also known as playing surface, P765: the surface on which a sporting event is played

Answer:
I ran a query to retrieve all tournaments that are part of the 2018 ATP World Tour (items with wdt:P361 wd:Q23039138). The query returns one row per tournament with these columns: tournament (IRI), tLabel (English label of the tournament item), country (IRI, if available), endTime (if available), location (IRI, if available), edition (P393, if available), pointInTime (P585, if available), and surface (P765, IRI, if available). Results are sorted in ascending order by endTime.

Query results: the query returned 39 tournament items. Some fields are missing for some tournaments (they are optional and not present on every item). If you would like, I can present the full result table here, or export it as CSV/JSON for easier inspection.

I ran a query to retrieve all tournaments that are part of the 2018 ATP World Tour (items with wdt:P361 wd:Q23039138). The query returns one row per tournament with these columns: tournament (IRI), tLabel (English label of the tournament item), country (IRI, if available), endTime (if available), location (IRI, if available), edition (P393, if available), pointInTime (P585, if available), and surface (P765, IRI, if available). Results are sorted in ascending order by endTime.

Query results: the query returned 39 tournament items. Some fields are missing for some tournaments (they are optional and not present on every item). If you would like, I can present the full result table here, or export it as CSV/JSON for easier inspection.

SPARQL query over wikidata:
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT DISTINCT ?tournament ?tLabel ?country ?endTime ?location ?edition ?pointInTime ?surface WHERE {
  ?tournament wdt:P361 wd:Q23039138 .
  OPTIONAL {
    ?tournament rdfs:label ?tLabel .
    FILTER ( LANG( ?tLabel ) = "en" )
  }
  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 ?endTime
LIMIT 500

Using entities:
- 2018 ATP World Tour (wd:Q23039138): is instance of tennis tour edition / tennis circuit

Using properties:
- 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)
- location (wd:P276 as wdt), also known as based in, city, from, held by, in, etc.: location of the item, physical object or event is within. In ... use P131. In case of a distinct terrain feature use P706. / location of the item, physical object or event is within. In ... use P131. In case of a distinct terrain feature use P706. / location of the object, structure or event. In the case of an ... use P706. Use P7153 for locations associated with the object
- part of (wd:P361 as wdt), also known as assembly of, branch of, chain, collateral branch of, component of, etc.: object of which the subject is a part (if this subject is ... "has part" (P527, see also "has parts of the class" (P2670)) / object of which the subject is a part (if this subject is ... "has part" (P527, see also "has parts of the class" (P2670)) / object of which the subject is a part (if this subject is ... "has part" (P527, see also "has parts of the class" (P2670)) / object of which the subject is a part (if this subject is ... "has part" (P527, see also "has parts of the class" (P2670))
- edition number (wd:P393 as wdt), also known as number of event, software version number, version number, P393: is subproperty of series ordinal / number of an edition (first, second, ... as 1, 2, ...) or event / number of this edition (first, second, ... as 1, 2, ...) of a book or event
- end time (wd:P582 as wdt), also known as abolished, cease date, cease operation, cease time, closed, etc.: is subproperty of point in time / indicates the time an item ceases to exist or a statement stops being valid / indicates the time an item ceases to exist or a statement stops being valid / moment when an entity ceases to exist and a statement stops being entirely valid or no longer be true
- point in time (wd:P585 as wdt), also known as as of, at time, by date, date, during, etc.: date something took place, existed or a statement was true; for providing time use the "refine date" property (P4241) / time and date something took place, existed or a statement was true / time and date something took place, existed or a statement was true / time and date something took place, existed or a statement was true
- surface played on (wd:P765 as wdt), also known as playing surface, P765: the surface on which a sporting event is played

Execution result:
Got 39 rows and 8 columns, showing the first 5 and last 5 rows below:
| tournament                                                   | tLabel                                                  | country              | endTime                             | location                            | edition | pointInTime                         | surface                 |
| ------------------------------------------------------------ | ------------------------------------------------------- | -------------------- | ----------------------------------- | ----------------------------------- | ------- | ----------------------------------- | ----------------------- |
| 2018 Swedish Open (wd:Q55391498)                             | 2018 Swedish Open (lang:en)                             | Sweden (wd:Q34)      |                                     | Båstad Tennis Stadium (wd:Q5004953) | 71      | 2018-01-01T00:00:00Z (xsd:dateTime) |                         |
| 2018 Tata Open Maharashtra (wd:Q44318733)                    | 2018 Tata Open Maharashtra (lang:en)                    | 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 Brisbane International (men) (lang:en)             |                      | 2018-01-07T00:00:00Z (xsd:dateTime) |                                     | 10      | 2018-01-01T00:00:00Z (xsd:dateTime) |                         |
| 2018 Qatar ExxonMobil Open (wd:Q44318591)                    | 2018 Qatar ExxonMobil Open (lang:en)                    | 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 Sydney International (men) (lang:en)               |                      | 2018-01-13T00:00:00Z (xsd:dateTime) |                                     | 126     | 2018-01-01T00:00:00Z (xsd:dateTime) |                         |
| ...                                                          | ...                                                     | ...                  | ...                                 | ...                                 | ...     | ...                                 | ...                     |
| 2018 China Open (men) (wd:Q56819344)                         | 2018 China Open (men) (lang:en)                         |                      | 2018-10-07T00:00:00Z (xsd:dateTime) |                                     | 19      | 2018-01-01T00:00:00Z (xsd:dateTime) |                         |
| 2018 Stockholm Open (wd:Q57171456)                           | 2018 Stockholm Open (lang:en)                           | 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 Kremlin Cup (men) (lang:en)                        |                      | 2018-10-21T00:00:00Z (xsd:dateTime) |                                     | 29      |                                     |                         |
| 2018 Swiss Indoors (wd:Q57339856)                            | 2018 Swiss Indoors (lang:en)                            | 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 Oracle Challenger Series – Houston – Men (lang:en) |                      | 2018-11-18T00:00:00Z (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 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]
Plan:
1. Search Wikidata for the item that corresponds to "2018 ATP World Tour".
2. Inspect its properties to see how tournaments link to it (likely via P361 "part of" or P179 "part of the series").
3. Use the discovered property to find tournament items that are part of the 2018 ATP World Tour, and retrieve requested qualifiers/values: country (P17), end time (pq:P585 on population? No — for events, the tournament may have "end time" as end time qualifier on "start time"/"end time" properties or "end time" is P582?), location (P276 or P625?), edition number (P393? Actually "edition number" property is P393), point in time (P585), surface (P2596? Wait), and surface played on might be "surface" property P641? Need to search for relevant properties if necessary.

I'll start by searching for the entity "2018 ATP World Tour". I'll use the search_entity function constrained to wikidata.

Question: 2018 ATP World Tour

Top 10 entity alternatives:
1. 2018 ATP World Tour (wd:Q23039138): is instance of tennis tour edition / tennis circuit
2. 2018 ATP World Tour Masters 1000 (wd:Q50063551): is instance of tennis tour edition / tennis tour
3. ATP Finals (wd:Q270907, matched via ATP World Tour Finals), also known as ATP World Tour Finals, Tennis Masters Cup: is instance of recurring tennis tournament / tier of annual men's tennis tournaments / is subclass of ATP tennis tournament
4. ATP World Tour 500 series (wd:Q300018, matched via ATP World Tour 500), also known as ATP 500, ATP 500 Series, ATP Championship Series, ATP Championship Series, Double-Week, ATP Masters 500, etc.: is instance of tennis tour with multiple editions / tennis tournament category since 2009 / is subclass of tennis tour
5. ATP World Tour 250 series (wd:Q300017, matched via ATP World Tour 250), also known as ATP 250, ATP 250 Series, ATP Tour 250, ATP World Series, ATP World Tour 250, etc.: is instance of tennis tour with multiple editions / is subclass of tennis tour / tennis tournament category / tennis tournament / tennis tournament
6. 2018 UCI World Tour (wd:Q42317185): is instance of UCI World Tour / cycling races
7. ATP Tour (wd:Q300008, matched via ATP World Tour), also known as ATP World Tour: is instance of tennis tour with multiple editions / is instance of recurring sporting event / series of men's tennis tournaments / is subclass of tennis tour / tennis tournament / tennis tournament
8. 2011 ATP World Tour (wd:Q300013), also known as 2011 atp tour: is instance of tennis tour edition / men's tennis circuit / tennis tournament / tennis tournament
9. 2010 ATP World Tour (wd:Q300012), also known as 2010 atp tour: is instance of tennis tour edition / tennis tournament / tennis tournament / tennis circuit
10. 2009 ATP World Tour (wd:Q300011), also known as 2009 atp tour, 2009 ATP Tour, ATP Tour 2009, Juego 2000 Calendar, Tennis 2009 Calendare ATP ITF: is instance of tennis tour edition / tennis tournament / tennis tournament / tennis circuit

[Assistant]
I'll list triples for the item 2018 ATP World Tour (wd:Q23039138) to see how tournaments are connected to it and which properties are used. I'll look for properties like "has part" (P527), "has part(s)" or "part of" (P361), "contains event" etc. Then I'll refine the query to retrieve tournaments and requested attributes.

list

wd:Q23039138

Got 84 rows and 3 columns, showing the first 10 rows below:
| subject                            | property                                           | object                                           |
| ---------------------------------- | -------------------------------------------------- | ------------------------------------------------ |
| 2018 ATP World Tour (wd:Q23039138) | instance of (wdt:P31)                              | tennis tour edition (wd:Q47358534)               |
| 2018 ATP World Tour (wd:Q23039138) | Google Knowledge Graph ID (wdtn:P2671)             | <http://g.co/kg/g/11clgfhqnp>                    |
| 2018 ATP World Tour (wd:Q23039138) | sport (wdt:P641)                                   | tennis (wd:Q847)                                 |
| 2018 ATP World Tour (wd:Q23039138) | point in time (wdt:P585)                           | 2018-01-01T00:00:00Z (xsd:dateTime)              |
| 2018 ATP World Tour (wd:Q23039138) | topic's main category (wdt:P910)                   | wd:Q41205628                                     |
| 2018 ATP World Tour (wd:Q23039138) | sports season of league or competition (wdt:P3450) | ATP Tour (wd:Q300008)                            |
| 2018 ATP World Tour (wd:Q23039138) | topic's main template (wdt:P1424)                  | wd:Q46995157                                     |
| 2018 ATP World Tour (wd:Q23039138) | schema:description                                 | ATP-toernooikalender van het jaar 2018 (lang:nl) |
| 2018 ATP World Tour (wd:Q23039138) | schema:name                                        | 2018 ATP World Tour (lang:en)                    |
| 2018 ATP World Tour (wd:Q23039138) | rdf:type                                           | wikibase:Item                                    |
| ...                                | ...                                                | ...                                              |

[Assistant]
Now I'll check if the 2018 ATP World Tour item uses a property like "has part" (P527) to list tournaments. I'll list triples with property wdt:P527 for the subject.

wd:Q23039138

[Assistant]
I'll run a SPARQL query to find items that have property "part of" (wdt:P361) pointing to the 2018 ATP World Tour (wd:Q23039138). I'll retrieve the item and its English label and check a sample to confirm the pattern.

execute

SELECT ?tournament ?tLabel WHERE {
  ?tournament wdt:P361 wd:Q23039138 .
  ?tournament rdfs:label ?tLabel . FILTER(LANG(?tLabel) = "en")
} LIMIT 200

Got 39 rows and 2 columns, showing the first 5 and last 5 rows below:
| tournament                                                   | tLabel                                                  |
| ------------------------------------------------------------ | ------------------------------------------------------- |
| 2018 Queen's Club Championships (wd:Q12299856)               | 2018 Queen's Club Championships (lang:en)               |
| 2018 Monte-Carlo Rolex Masters (wd:Q29477409)                | 2018 Monte-Carlo Rolex Masters (lang:en)                |
| 2018 Qatar ExxonMobil Open (wd:Q44318591)                    | 2018 Qatar ExxonMobil Open (lang:en)                    |
| 2018 Tata Open Maharashtra (wd:Q44318733)                    | 2018 Tata Open Maharashtra (lang:en)                    |
| 2018 Brisbane International (men) (wd:Q46911399)             | 2018 Brisbane International (men) (lang:en)             |
| ...                                                          | ...                                                     |
| 2018 Swiss Indoors (wd:Q57339856)                            | 2018 Swiss Indoors (lang:en)                            |
| 2018 Oracle Challenger Series – Houston – Men (wd:Q59994545) | 2018 Oracle Challenger Series – Houston – Men (lang:en) |
| 2018 BNP Paribas Open (men) (wd:Q61953108)                   | 2018 BNP Paribas Open (men) (lang:en)                   |
| 2018 Rogers Cup (wd:Q66310546)                               | 2018 Rogers Cup (lang:en)                               |
| 2018 Kunming Open (men) (wd:Q96251157)                       | 2018 Kunming Open (men) (lang:en)                       |

[Assistant]
I'll search for relevant properties: "end time", "location", "country", "edition number", "point in time", and "surface". I'll use search_property for each keyword to confirm property IDs.

Question: surface

Top 10 property alternatives:
1. area (wd:P2046 as pr/psn/wdtn/ps/prn/p/pq/pqv/wdt/prv/psv/pqn, matched via surface), also known as acreage, camera resolution, die area, die size, image resolution, etc.: area occupied by an object / area occupied by an object
2. has surface (wd:P10614 as pr/psn/wdtn/ps/prn/p/pq/pqv/wdt/prv/psv/pqn), also known as P10614: the object is the 2-dimensional surface that partly or completely surrounds the subject in 3-dimensional space
3. home venue (wd:P115 as pr/psn/wdtn/ps/prn/p/pq/pqv/wdt/prv/psv/pqn, matched via ground), also known as arena, ballpark, ground, home field, home ground, etc.: home stadium or venue of a sports team or applicable performing arts organization / home stadium or venue of a sports team or applicable performing arts organization / home stadium or venue of a sports team or applicable performing arts organization / is subproperty of location
4. orientation (wd:P7469 as pr/psn/wdtn/ps/prn/p/pq/pqv/wdt/prv/psv/pqn, matched via faces), also known as alignment, direction, face, faces, facing, etc.: axis of alignment of an item, or direction perpendicular to its primary face (specify with P518 if necessary)
5. surface played on (wd:P765 as pr/psn/wdtn/ps/prn/p/pq/pqv/wdt/prv/psv/pqn), also known as playing surface, P765: the surface on which a sporting event is played
6. surface gravity (wd:P7015 as pr/psn/wdtn/ps/prn/p/pq/pqv/wdt/prv/psv/pqn), also known as P7015: gravitational acceleration experienced at the equator of an astronomical body surface
7. house publication (wd:P2813 as pr/psn/wdtn/ps/prn/p/pq/pqv/wdt/prv/psv/pqn, matched via manifest), also known as has mouthpiece, house journal, house magazine, house organ, house periodical, etc.: media that speaks for an organization or a movement, and that is usually edited by its members
8. country (wd:P17 as pr/psn/wdtn/ps/prn/p/pq/pqv/wdt/prv/psv/pqn, matched via land), also known as host country, land, sovereign state, state, P17: sovereign state that this item is in (not to be used for human beings) / sovereign state that this item is in (not to be used for human beings) / sovereign state that this item is in (not to be used for human beings) / sovereign state that this item is in (not to be used for human beings) / is subproperty of located in the administrative territorial entity
9. located on street (wd:P669 as pr/psn/wdtn/ps/prn/p/pq/pqv/wdt/prv/psv/pqn, matched via square), also known as address street, is on, located at street (item), on street, road, etc.: street, road, or square, where the item is located. To add ... P6375 "street address", if there is no item for the street / street, or road, where the item is located. To add the ... Use property P6375 if there is no item for the street / is subproperty of location / is subproperty of part of
10. field of work (wd:P101 as pr/psn/wdtn/ps/prn/p/pq/pqv/wdt/prv/psv/pqn, matched via fields), also known as academic area, academic discipline, academic subject, activity, activity domain, etc.: specialisation of a person or organisation; see P106 for the occupation / specialization of a person or organization; see P106 for the occupation / specialization of a person or organization; see P106 for the occupation / specialization of a person or organization; see P106 for the occupation / is subproperty of interested in

[Assistant]
I'll search for "end time" and "location", "edition number", "point in time", and "country" properties to confirm their IDs.

Question: end time

Top 10 property alternatives:
1. end time (wd:P582 as pr/psn/wdtn/ps/prn/p/pq/pqv/wdt/prv/psv/pqn), also known as abolished, cease date, cease operation, cease time, closed, etc.: moment when an entity ceases to exist and a statement stops being entirely valid or no longer be true / indicates the time an item ceases to exist or a statement stops being valid / indicates the time an item ceases to exist or a statement stops being valid / is subproperty of point in time
2. start time (wd:P580 as pr/psn/wdtn/ps/prn/p/pq/pqv/wdt/prv/psv/pqn), also known as began, beginning, building date, effective, effectivity, etc.: indicates the time an item begins to exist or a statement starts being valid / indicates the time an item begins to exist or a statement starts being valid / time an entity begins to exist or a statement starts being valid / is subproperty of point in time
3. work period (end) (wd:P2032 as pr/psn/wdtn/ps/prn/p/pq/pqv/wdt/prv/psv/pqn, matched via end time for work), also known as active until, date of activity (end), end date of activity, end time for work, fl. (end), etc.: end of period during which a person or group flourished (fl. = "floruit") in their professional activity / end of period during which a person or group flourished (fl. = "floruit") in their professional activity / is subproperty of end time / is subproperty of floruit
4. duration (wd:P2047 as pr/psn/wdtn/ps/prn/p/pq/pqv/wdt/prv/psv/pqn, matched via time interval), also known as cook time, era, interval, length, length of time, etc.: length of time of an event or process / length of time of an event or process / length of time of an event or process
5. time played (wd:P9140 as pr/psn/wdtn/ps/prn/p/pq/pqv/wdt/prv/psv/pqn), also known as minutes played, P9140: time (usually minutes) played by a participant in a sporting event
6. dissolved, abolished or demolished date (wd:P576 as pr/psn/wdtn/ps/prn/p/pq/pqv/wdt/prv/psv/pqn, matched via time abolished), 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. end period (wd:P3416 as pr/psn/wdtn/ps/prn/p/pq/pqv/wdt/prv/psv/pqn), also known as until period, P3416: last period in which the statement is still valid (including the period-value)
8. point in time (wd:P585 as pr/psn/wdtn/ps/prn/p/pq/pqv/wdt/prv/psv/pqn, matched via at time), also known as as of, at time, by date, date, during, etc.: date something took place, existed or a statement was true; for providing time use the "refine date" property (P4241) / time and date something took place, existed or a statement was true / time and date something took place, existed or a statement was true / time and date something took place, existed or a statement was true
9. refine date (wd:P4241 as pr/psn/wdtn/ps/prn/p/pq/pqv/wdt/prv/psv/pqn, matched via specific time), also known as date refinement, exact time, hour, local time, quarter, etc.: qualifier to narrow down the precision of a date not fully specified by the Wikidata time datatype precision field / qualifier to narrow down the precision of a date not fully specified by the Wikidata time datatype precision field
10. time gap (wd:P2911 as pr/psn/wdtn/ps/prn/p/pq/pqv/wdt/prv/psv/pqn), also known as gap, P2911: time gap to winner time (P2781)

[Assistant]
I'll search for the property "location" (likely P276) and "edition number" (likely P393), and confirm "country" is P17 and "point in time" is P585.

Question: location

Top 10 property alternatives:
1. work location (wd:P937 as pr/psn/wdtn/ps/prn/p/pq/pqv/wdt/prv/psv/pqn, matched via location), also known as active in, conducts business at, conducts business in, did work at, did work from, etc.: location where persons or organisations were actively participating in employment, business or other work / is subproperty of significant place / location where persons were active / is subproperty of location
2. location (wd:P276 as pr/psn/wdtn/ps/prn/p/pq/pqv/wdt/prv/psv/pqn), also known as based in, city, from, held by, in, etc.: location of the object, structure or event. In the case of an ... use P706. Use P7153 for locations associated with the object / location of the item, physical object or event is within. In ... use P131. In case of a distinct terrain feature use P706. / location of the item, physical object or event is within. In ... use P131. In case of a distinct terrain feature use P706.
3. coordinate location (wd:P625 as pr/psn/wdtn/ps/prn/p/pq/pqv/wdt/prv/psv/pqn, matched via location), also known as co-ordinate location, co-ordinates, coordinates, co-ords, coords, etc.: geocoordinates of the subject. For Earth, please note that only WGS84 coordinating system is supported at the moment / coordinates of the subject / coordinates of the subject
4. ranking (wd:P1352 as pr/psn/wdtn/ps/prn/p/pq/pqv/wdt/prv/psv/pqn, matched via place), also known as peak position, place, placing, position, rank, etc.: subject's ordinal position as qualitatively evaluated relative to other members of a group / the subject's position in the specified rank
5. occupant (wd:P466 as pr/psn/wdtn/ps/prn/p/pq/pqv/wdt/prv/psv/pqn, matched via location of), also known as home team, houses, inhabitant, lessee, location of, etc.: person or organization occupying a building or facility / person or organization occupying property / is subproperty of used by
6. applies to jurisdiction (wd:P1001 as pr/psn/wdtn/ps/prn/p/pq/pqv/wdt/prv/psv/pqn, matched via of location), also known as applicable area, applicable country, applicable geographic place, applicable jurisdiction, applicable location, etc.: the item (institution, law, public office, public ... jurisdiction: a country, state, municipality, ...) / the item (an institution, law, public office ...) or ... jurisdiction: a country, state, municipality, ...) / is subproperty of characteristic of / is subproperty of significant place / is subproperty of operating area
7. directions (wd:P2795 as pr/psn/wdtn/ps/prn/p/pq/pqv/wdt/prv/psv/pqn, matched via locality or place), also known as locality or place, P2795: describe how to find the subject - directions, objects along way, comments / describe how to find the subject - directions, objects along way, comments
8. located in the present-day administrative territorial entity (wd:P3842 as pr/psn/wdtn/ps/prn/p/pq/pqv/wdt/prv/psv/pqn, matched via current location), also known as current administrative territorial entity, current location, currently in, located in present day administrative territorial entity, located in present-day administrative territorial entity, etc.: the item was located in the territory of this present-day ... unit; however the two did not at any point coexist in time / the item was located in the territory of this present-day ... unit; however the two did not at any point coexist in time / is subproperty of location / is subproperty of part of
9. located in the administrative territorial entity (wd:P131 as pr/psn/wdtn/ps/prn/p/pq/pqv/wdt/prv/psv/pqn, matched via locality), also known as administrative territorial entity, administrative territory, city, happens in, in, etc.: the item is located on the territory of the following ... the item falls only partially into the administrative entity. / the item is located on the territory of the following ... the item falls only partially into the administrative entity. / the item is located on the territory of the following administrative entity / the item is located on the territory of the following administrative entity / is subproperty of location / is subproperty of part of
10. operating area (wd:P2541 as pr/psn/wdtn/ps/prn/p/pq/pqv/wdt/prv/psv/pqn, matched via location served), also known as area of operations, area of responsibility, area operated, area served, areas served, etc.: geographic area or jurisdiction an organisation or industry operates in, serves, or has responsibility for / geographic area or jurisdiction an organisation or industry operates in, serves, or has responsibility for / geographic area or jurisdiction an organization or industry operates in, serves, or has responsibility for / is subproperty of location

[Assistant]
I'll search for "edition number" and confirm its property id (I expect P393).

Question: edition number

Top 10 property alternatives:
1. edition number (wd:P393 as pr/psn/wdtn/ps/prn/p/pq/pqv/wdt/prv/psv/pqn), also known as number of event, software version number, version number, P393: number of this edition (first, second, ... as 1, 2, ...) of a book or event / number of an edition (first, second, ... as 1, 2, ...) or event / is subproperty of series ordinal
2. edition/version (wd:P9767 as pr/psn/wdtn/ps/prn/p/pq/pqv/wdt/prv/psv/pqn, matched via edition designation), also known as designation of edition, designation of version, edition, edition designation, edition or version, etc.: the official edition or version name of a resource; this name is not considered part of the title or subtitle of the resource
3. catalog code (wd:P528 as pr/psn/wdtn/ps/prn/p/pq/pqv/wdt/prv/psv/pqn, matched via catalog number), also known as astronomical catalog, cat#, catalog number, catalogue code, catalogue number, etc.: catalogue name of an object, use with qualifier P972 / catalog name of an object, use with qualifier P972
4. inventory number (wd:P217 as pr/psn/wdtn/ps/prn/p/pq/pqv/wdt/prv/psv/pqn, matched via catalog number), also known as accession number, call number, catalog number, catalogue number, collection number, etc.: identifier for a physical object or a set of physical objects in a collection / identifier for a physical object or a set of physical objects in a collection
5. has edition or translation (wd:P747 as pr/psn/wdtn/ps/prn/p/pq/pqv/wdt/prv/psv/pqn, matched via has edition), also known as arranged as, arrangement, edition, edition or translation, editions, etc.: item that is an edition or translation of this item
6. article ID (wd:P2322 as pr/psn/wdtn/ps/prn/p/pq/pqv/wdt/prv/psv/pqn, matched via article number), also known as article number, P2322: identifier for an article in an online publication
7. edition or translation of (wd:P629 as pr/psn/wdtn/ps/prn/p/pq/pqv/wdt/prv/psv/pqn, matched via edition of), also known as edition of, edition, version, or translation of, is an edition of, is an edition or translation of, is a translation of, etc.: is an edition or translation of this entity / is an edition or translation of this entity / is an edition or translation of this entity
8. distribution format (wd:P437 as pr/psn/wdtn/ps/prn/p/pq/pqv/wdt/prv/psv/pqn, matched via edition), also known as book format, distribution, distribution method, edition, format, etc.: method (or type) of distribution for the subject / method (or type) of distribution for the subject
9. sport number (wd:P1618 as pr/psn/wdtn/ps/prn/p/pq/pqv/wdt/prv/psv/pqn, matched via entry number), also known as bib, car number, entry number, guernsey number, jersey number, etc.: number worn on a player's (competitor's) uniform, equipment, etc / number worn on a player's (competitor's) uniform, equipment, etc / number worn on a player's (competitor's) uniform, equipment, etc / is subproperty of series ordinal
10. Library of Congress Classification (works and editions) (wd:P8360 as pr/psn/wdtn/ps/prn/p/pq/pqv/wdt/prv/psv/pqn, matched via Library of Congress Class Number (works and editions)), also known as LC Classification and Shelflisting Number, LC Classification (works and editions), LC Class Number (works and editions), LCC (works and editions), Library of Congress Class Number (works and editions), etc.: Library of Congress Classification number assigned to a ... the subject portion and the shelflisting portion of a number

[Assistant]
I'll run a SPARQL query that selects all items with wdt:P361 wd:Q23039138 (members of the 2018 ATP World Tour), retrieving optional properties: country (P17), end time (P582), location (P276), edition number (P393), point in time (P585), and surface played on (P765). I'll also fetch English labels for readability. Results will be ordered by end time ascending. Now executing the query to verify results.

SELECT DISTINCT ?tournament ?tLabel ?country ?countryLabel ?endTime ?location ?locationLabel ?edition ?pointInTime ?surface ?surfaceLabel WHERE {
  ?tournament wdt:P361 wd:Q23039138 .
  OPTIONAL { ?tournament rdfs:label ?tLabel . FILTER(LANG(?tLabel) = "en") }
  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 . }
  OPTIONAL { ?country rdfs:label ?countryLabel . FILTER(LANG(?countryLabel) = "en") }
  OPTIONAL { ?location rdfs:label ?locationLabel . FILTER(LANG(?locationLabel) = "en") }
  OPTIONAL { ?surface rdfs:label ?surfaceLabel . FILTER(LANG(?surfaceLabel) = "en") }
} ORDER BY ?endTime
LIMIT 500

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

[Assistant]
I'll first retrieve the list of tournaments (just their IRIs) that have P361 pointing to the 2018 ATP World Tour. Then I'll query details for that fixed list using VALUES to reduce complexity and avoid timeouts.

SELECT DISTINCT ?tournament WHERE { ?tournament wdt:P361 wd:Q23039138 . } LIMIT 500

Got 39 rows and 1 column, showing the first 5 and last 5 rows below:
| tournament                                                   |
| ------------------------------------------------------------ |
| 2018 Queen's Club Championships (wd:Q12299856)               |
| 2018 Monte-Carlo Rolex Masters (wd:Q29477409)                |
| 2018 Qatar ExxonMobil Open (wd:Q44318591)                    |
| 2018 Tata Open Maharashtra (wd:Q44318733)                    |
| 2018 Brisbane International (men) (wd:Q46911399)             |
| ...                                                          |
| 2018 Swiss Indoors (wd:Q57339856)                            |
| 2018 Oracle Challenger Series – Houston – Men (wd:Q59994545) |
| 2018 BNP Paribas Open (men) (wd:Q61953108)                   |
| 2018 Rogers Cup (wd:Q66310546)                               |
| 2018 Kunming Open (men) (wd:Q96251157)                       |

[Assistant]
Now I'll retry the full query retrieving all requested properties and English labels, ordered by end time ascending. If it times out again, I'll fall back to a two-step approach.

SELECT DISTINCT ?tournament ?tLabel ?country ?countryLabel ?endTime ?location ?locationLabel ?edition ?pointInTime ?surface ?surfaceLabel WHERE {
  ?tournament wdt:P361 wd:Q23039138 .
  OPTIONAL { ?tournament rdfs:label ?tLabel . FILTER(LANG(?tLabel) = "en") }
  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 . }
  OPTIONAL { ?country rdfs:label ?countryLabel . FILTER(LANG(?countryLabel) = "en") }
  OPTIONAL { ?location rdfs:label ?locationLabel . FILTER(LANG(?locationLabel) = "en") }
  OPTIONAL { ?surface rdfs:label ?surfaceLabel . FILTER(LANG(?surfaceLabel) = "en") }
} ORDER BY ?endTime
LIMIT 500

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

[Assistant]
I'll run a simplified query returning tournament and tournament label plus IRIs for country, location and surface, and the requested time/edition values. This reduces label lookups to improve performance.

SELECT DISTINCT ?tournament ?tLabel ?country ?endTime ?location ?edition ?pointInTime ?surface WHERE {
  ?tournament wdt:P361 wd:Q23039138 .
  OPTIONAL { ?tournament rdfs:label ?tLabel . FILTER(LANG(?tLabel) = "en") }
  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 ?endTime
LIMIT 500

[Assistant]
answer

SELECT DISTINCT ?tournament ?tLabel ?country ?endTime ?location ?edition ?pointInTime ?surface WHERE {
  ?tournament wdt:P361 wd:Q23039138 .
  OPTIONAL { ?tournament rdfs:label ?tLabel . FILTER(LANG(?tLabel) = "en") }
  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 ?endTime
LIMIT 500

Answer:
I ran a query to retrieve all tournaments that are part of the 2018 ATP World Tour (items with wdt:P361 wd:Q23039138). The query returns one row per tournament with these columns: tournament (IRI), tLabel (English label of the tournament item), country (IRI, if available), endTime (if available), location (IRI, if available), edition (P393, if available), pointInTime (P585, if available), and surface (P765, IRI, if available). Results are sorted in ascending order by endTime.

Query results: the query returned 39 tournament items. Some fields are missing for some tournaments (they are optional and not present on every item). If you would like, I can present the full result table here, or export it as CSV/JSON for easier inspection.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX xsd: <http://www.w3.org/2001/XMLSchema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?place1 ?place2 ?lat ?lon WHERE {
  VALUES ( ?place1 ?place2 ) {
    ( wd:Q90 wd:Q240798 )
  }
  ?place1 wdt:P625 ?c1 .
  ?place2 wdt:P625 ?c2 .
  BIND( REPLACE( STR( ?c1 ) , "POINT\\(" , "" ) AS ?t1 ) .
  BIND( REPLACE( ?t1 , "\\)" , "" ) AS ?coords1 ) .
  BIND( STRBEFORE( ?coords1 , " " ) AS ?lon1s ) .
  BIND( STRAFTER( ?coords1 , " " ) AS ?lat1s ) .
  BIND( REPLACE( STR( ?c2 ) , "POINT\\(" , "" ) AS ?t2 ) .
  BIND( REPLACE( ?t2 , "\\)" , "" ) AS ?coords2 ) .
  BIND( STRBEFORE( ?coords2 , " " ) AS ?lon2s ) .
  BIND( STRAFTER( ?coords2 , " " ) AS ?lat2s ) .
  BIND( xsd:decimal ( ?lat1s ) AS ?lat1 ) .
  BIND( xsd:decimal ( ?lon1s ) AS ?lon1 ) .
  BIND( xsd:decimal ( ?lat2s ) AS ?lat2 ) .
  BIND( xsd:decimal ( ?lon2s ) AS ?lon2 ) .
  BIND( ( ( ?lat1 + ?lat2 ) / 2 ) AS ?lat ) .
  BIND( ( ( ?lon1 + ?lon2 ) / 2 ) AS ?lon ) .
}

Using entities:
- Montigny-le-Bretonneux (wd:Q240798): is instance of commune of France / commune in Yvelines, France
- Paris (wd:Q90), also known as City of Light, City of Love, Lutetia: is instance of megacity / is instance of metropolis / is instance of Metropolis / is instance of global city / is instance of territorial collectivity of France with special status / is instance of largest city / is instance of department of France / capital city and largest city of France / capital city of France / capital city of France

Using properties:
- 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

Answer: The query returns midpoint latitude = 48.8136 and midpoint longitude = 2.19236 (these are the averages of the coordinates of Paris (wd:Q90) and Montigny-le-Bretonneux (wd:Q240798)).

The query returns midpoint latitude = 48.8136 and midpoint longitude = 2.19236 (these are the averages of the coordinates of Paris (wd:Q90) and Montigny-le-Bretonneux (wd:Q240798)).

SPARQL query over wikidata:
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX xsd: <http://www.w3.org/2001/XMLSchema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?place1 ?place2 ?lat ?lon WHERE {
  VALUES ( ?place1 ?place2 ) {
    ( wd:Q90 wd:Q240798 )
  }
  ?place1 wdt:P625 ?c1 .
  ?place2 wdt:P625 ?c2 .
  BIND( REPLACE( STR( ?c1 ) , "POINT\\(" , "" ) AS ?t1 ) .
  BIND( REPLACE( ?t1 , "\\)" , "" ) AS ?coords1 ) .
  BIND( STRBEFORE( ?coords1 , " " ) AS ?lon1s ) .
  BIND( STRAFTER( ?coords1 , " " ) AS ?lat1s ) .
  BIND( REPLACE( STR( ?c2 ) , "POINT\\(" , "" ) AS ?t2 ) .
  BIND( REPLACE( ?t2 , "\\)" , "" ) AS ?coords2 ) .
  BIND( STRBEFORE( ?coords2 , " " ) AS ?lon2s ) .
  BIND( STRAFTER( ?coords2 , " " ) AS ?lat2s ) .
  BIND( xsd:decimal ( ?lat1s ) AS ?lat1 ) .
  BIND( xsd:decimal ( ?lon1s ) AS ?lon1 ) .
  BIND( xsd:decimal ( ?lat2s ) AS ?lat2 ) .
  BIND( xsd:decimal ( ?lon2s ) AS ?lon2 ) .
  BIND( ( ( ?lat1 + ?lat2 ) / 2 ) AS ?lat ) .
  BIND( ( ( ?lon1 + ?lon2 ) / 2 ) AS ?lon ) .
}

Using entities:
- Montigny-le-Bretonneux (wd:Q240798): is instance of commune of France / commune in Yvelines, France
- Paris (wd:Q90), also known as City of Light, City of Love, Lutetia: is instance of megacity / is instance of metropolis / is instance of Metropolis / is instance of global city / is instance of territorial collectivity of France with special status / is instance of largest city / is instance of department of France / capital city and largest city of France / capital city of France / capital city of France

Using properties:
- 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 row and 4 columns:
| place1         | place2                              | lat                   | lon                   |
| -------------- | ----------------------------------- | --------------------- | --------------------- |
| Paris (wd:Q90) | Montigny-le-Bretonneux (wd:Q240798) | 48.8136 (xsd:decimal) | 2.19236 (xsd:decimal) |

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

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

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

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

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

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

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

[User] What is the 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]
Step 1 — I will resolve the two place names to Wikidata QIDs so I don't guess identifiers. I'll search Wikidata for "Paris" (to get the capital of France) and "Montigny-le-Bretonneux". I will verify the returned items are the expected places. I'll call the search function for "Paris" first.

Question: Paris

Top 10 entity alternatives:
1. Paris (wd:Q90), also known as City of Light, City of Love, Lutetia: is instance of territorial collectivity of France with special status / capital city and largest city of France / is instance of department of France / is instance of largest city / is instance of global city / is instance of Metropolis / is instance of metropolis / is instance of megacity / capital city of France / capital city of France
2. Paris Saint-Germain FC (wd:Q483020, matched via Paris), also known as Paris, Paris Saint-Germain, Paris Saint-Germain F.C., Paris Saint-Germain Football Club, Paris SG, etc.: association football club in Paris, France / is instance of association football club / is instance of soccer club
3. Paris (wd:Q167646), also known as Alexander, Alexandros: is instance of mythological Greek character / mythological son of Priam, king of Troy / has occupation herder / has occupation Herder
4. Paris (wd:Q830149), also known as Paris, Texas, Paris, TX: city in and county seat of Lamar County, Texas, United States / is instance of city in the United States / is instance of city of the United States / is instance of county seat
5. Paris (wd:Q984459), also known as Paris, ID, Paris, Idaho: is instance of city of the United States / is instance of city in the United States / city in Idaho, United States
6. Paris (wd:Q162121): is instance of taxon / genus of plants
7. Paris (wd:Q576584), also known as Paris, IL, Paris Illinois, Paris, Illinois: is instance of city in the United States / is instance of city of the United States / city in Illinois
8. Paris (wd:Q3181341), also known as Paris, Kentucky, Paris, KY: county seat of Bourbon County, Kentucky, United States / is instance of city in the United States / is instance of city of the United States / is instance of county seat
9. Paris (wd:Q79917), also known as Paris, AR, Paris, Arkansas: is instance of city of the United States / is instance of city in the United States / city in Arkansas, United States
10. Paris (wd:Q1018504), also known as Paris, Tennessee, Paris, TN: city in and the county seat of Henry County, Tennessee, United States / is instance of city in the United States / is instance of city of the United States

[Assistant]
Now I'll search Wikidata for "Montigny-le-Bretonneux" to get its QID.

Question: Montigny-le-Bretonneux

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

[Assistant]
I'll run a SPARQL query that fetches the P625 coordinates for Paris (wd:Q90) and Montigny-le-Bretonneux (wd:Q240798), extracts numeric latitude and longitude from the WKT "Point(lon lat)" strings, computes the midpoint as the average of the latitudes and the average of the longitudes, and returns the two items' IRIs plus the midpoint latitude and longitude. Now I'll execute that query.

execute

PREFIX xsd: <http://www.w3.org/2001/XMLSchema#>
SELECT ?place1 ?place2 ?lat ?lon WHERE {
  VALUES (?place1 ?place2) { (wd:Q90 wd:Q240798) }
  ?place1 wdt:P625 ?c1 .
  ?place2 wdt:P625 ?c2 .

  BIND(STR(?c1) AS ?s1) .
  BIND(STRAFTER(?s1, "Point(") AS ?t1) .
  BIND(STRBEFORE(?t1, ")") AS ?coords1) .
  BIND(STRBEFORE(?coords1, " ") AS ?lon1s) .
  BIND(STRAFTER(?coords1, " ") AS ?lat1s) .

  BIND(STR(?c2) AS ?s2) .
  BIND(STRAFTER(?s2, "Point(") AS ?t2) .
  BIND(STRBEFORE(?t2, ")") AS ?coords2) .
  BIND(STRBEFORE(?coords2, " ") AS ?lon2s) .
  BIND(STRAFTER(?coords2, " ") AS ?lat2s) .

  BIND(xsd:decimal(?lat1s) AS ?lat1) .
  BIND(xsd:decimal(?lon1s) AS ?lon1) .
  BIND(xsd:decimal(?lat2s) AS ?lat2) .
  BIND(xsd:decimal(?lon2s) AS ?lon2) .

  BIND(((?lat1 + ?lat2) / 2) AS ?lat) .
  BIND(((?lon1 + ?lon2) / 2) AS ?lon) .
}

[Assistant]
The result returned an empty latitude/longitude — I'll debug by returning the intermediate extracted strings (the raw P625 string and the parsed coordinate substrings) to see why numeric casting failed. I'll run a diagnostic query that shows STR(?c1), STR(?c2), the coordinate substrings, and the numeric casts for each place.

PREFIX xsd: <http://www.w3.org/2001/XMLSchema#>
SELECT ?place ?cstr ?coords ?lonStr ?latStr ?latVal ?lonVal WHERE {
  VALUES ?place { wd:Q90 wd:Q240798 }
  ?place wdt:P625 ?c .
  BIND(STR(?c) AS ?cstr) .
  BIND(STRAFTER(?cstr, "Point(") AS ?t) .
  BIND(STRBEFORE(?t, ")") AS ?coords) .
  BIND(STRBEFORE(?coords, " ") AS ?lonStr) .
  BIND(STRAFTER(?coords, " ") AS ?latStr) .
  BIND(xsd:decimal(?latStr) AS ?latVal) .
  BIND(xsd:decimal(?lonStr) AS ?lonVal) .
}

[Assistant]
I see the P625 strings use uppercase "POINT(...)" so my previous STRAFTER("Point(") failed. I'll remove the leading "POINT(" and trailing ")" by using REPLACE(), then split on the space to get lon/lat, cast to decimal, and compute the midpoint. I'll run the corrected query now.

PREFIX xsd: <http://www.w3.org/2001/XMLSchema#>
SELECT ?place1 ?place2 ?lat ?lon WHERE {
  VALUES (?place1 ?place2) { (wd:Q90 wd:Q240798) }
  ?place1 wdt:P625 ?c1 .
  ?place2 wdt:P625 ?c2 .

  # remove leading 'POINT(' and trailing ')'
  BIND(REPLACE(STR(?c1), "POINT\\(", "") AS ?t1) .
  BIND(REPLACE(?t1, "\\)", "") AS ?coords1) .
  BIND(STRBEFORE(?coords1, " ") AS ?lon1s) .
  BIND(STRAFTER(?coords1, " ") AS ?lat1s) .

  BIND(REPLACE(STR(?c2), "POINT\\(", "") AS ?t2) .
  BIND(REPLACE(?t2, "\\)", "") AS ?coords2) .
  BIND(STRBEFORE(?coords2, " ") AS ?lon2s) .
  BIND(STRAFTER(?coords2, " ") AS ?lat2s) .

  BIND(xsd:decimal(?lat1s) AS ?lat1) .
  BIND(xsd:decimal(?lon1s) AS ?lon1) .
  BIND(xsd:decimal(?lat2s) AS ?lat2) .
  BIND(xsd:decimal(?lon2s) AS ?lon2) .

  BIND(((?lat1 + ?lat2) / 2) AS ?lat) .
  BIND(((?lon1 + ?lon2) / 2) AS ?lon) .
}

[Assistant]
answer

PREFIX xsd: <http://www.w3.org/2001/XMLSchema#>
SELECT ?place1 ?place2 ?lat ?lon WHERE {
  VALUES (?place1 ?place2) { (wd:Q90 wd:Q240798) }
  ?place1 wdt:P625 ?c1 .
  ?place2 wdt:P625 ?c2 .

  # remove leading 'POINT(' and trailing ')'
  BIND(REPLACE(STR(?c1), "POINT\\(", "") AS ?t1) .
  BIND(REPLACE(?t1, "\\)", "") AS ?coords1) .
  BIND(STRBEFORE(?coords1, " ") AS ?lon1s) .
  BIND(STRAFTER(?coords1, " ") AS ?lat1s) .

  BIND(REPLACE(STR(?c2), "POINT\\(", "") AS ?t2) .
  BIND(REPLACE(?t2, "\\)", "") AS ?coords2) .
  BIND(STRBEFORE(?coords2, " ") AS ?lon2s) .
  BIND(STRAFTER(?coords2, " ") AS ?lat2s) .

  BIND(xsd:decimal(?lat1s) AS ?lat1) .
  BIND(xsd:decimal(?lon1s) AS ?lon1) .
  BIND(xsd:decimal(?lat2s) AS ?lat2) .
  BIND(xsd:decimal(?lon2s) AS ?lon2) .

  BIND(((?lat1 + ?lat2) / 2) AS ?lat) .
  BIND(((?lon1 + ?lon2) / 2) AS ?lon) .
}

Answer: The query returns midpoint latitude = 48.8136 and midpoint longitude = 2.19236 (these are the averages of the coordinates of Paris (wd:Q90) and Montigny-le-Bretonneux (wd:Q240798)).