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 ?periodical ?periodicalLabel WHERE {
  ?periodical wdt:P31 wd:Q1002697 ; wdt:P407 wd:Q143 .
  OPTIONAL {
    ?periodical rdfs:label ?periodicalLabel FILTER ( LANG( ?periodicalLabel ) = "en" )
  }
}

Got 89 rows and 2 columns, showing the first 5 and last 5 rows below:
| periodical                                                                         | periodicalLabel                                                          |
| ---------------------------------------------------------------------------------- | ------------------------------------------------------------------------ |
| Momenton! (wd:Q10331627)                                                           | Momenton! (en)                                                           |
| Pola Esperantisto (wd:Q11821362)                                                   | Pola Esperantisto (en)                                                   |
| El Popola Ĉinio (wd:Q119633)                                                       | El Popola Ĉinio (en)                                                     |
| Beletra Almanako N-ro 4 (februaro 2009) (wd:Q12345463)                             | Beletra Almanako N-ro 4 (februaro 2009) (en)                             |
| Bohema Revuo Esperantista (wd:Q12345746)                                           | Bohema Revuo Esperantista (en)                                           |
| ...                                                                                | ...                                                                      |
| Mondano (wd:Q80452320)                                                             | Mondano (en)                                                             |
| Norda prismo : kultura, socia, literatura, revuo, dumonata (wd:Q80452629)          | Norda prismo : kultura, socia, literatura, revuo, dumonata (en)          |
| Paco : oficiala organo de Mondpaca esperantista movado (MEM) (wd:Q80452991)        | Paco : oficiala organo de Mondpaca esperantista movado (MEM) (en)        |
| UABO : (antaǔe Ligilo por vidant...la asocio de blindul-organizaĵoj (wd:Q80454504) | UABO : (antaǔe Ligilo por vidant...la asocio de blindul-organizaĵoj (en) |
| Lingvo Internacia (wd:Q844150)                                                     | Lingvo Internacia (en)                                                   |

There are at least 89 periodicals whose primary language is Esperanto. Examples include 'Momenton!', 'Pola Esperantisto', 'El Popola Ĉinio', 'Beletra Almanako N-ro 4 (februaro 2009)', 'Bohema Revuo Esperantista', and 'Lingvo Internacia'. The full list can be retrieved using the provided SPARQL query.

Which periodicals have a primary language of Esperanto?

[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] Which periodicals have a primary language of Esperanto?

[Assistant]
Let's break down the question:

1. We are looking for periodicals (magazines, journals, newspapers, etc.).
2. These periodicals should have Esperanto as their primary language.

Step 1: Identify the entity for "Esperanto" and for "periodical".
Step 2: Identify the property for "primary language" or "language of work or name".

Let's start by searching for the entity "Esperanto".

[Tool]
Top 10 entity alternatives:
1. Esperanto, also known as epo, Esperanto language, eo (wd:Q143): international auxiliary language designed by L. L. Zamenhof, instance of international auxiliary language, instance of a posteriori language, instance of constructed language, instance of planned language, instance of modern language
2. Esperanto (wd:Q608836): official magazine of the World Esperanto Association (UEA), instance of periodical
3. Esperanto (wd:Q5398868): instance of rock band, Belgo-English band
4. Esperanto, also known as Esperanto.4733 (wd:Q15734339): instance of computer virus, computer virus
5. Esperanto (wd:Q3733094): 1993 debut studio album by Elektric Music, instance of album
6. Esperanto (wd:Q10489150): instance of Zamenhof-Esperanto object, restaurant in Stockholm, Sweden, instance of restaurant
7. Esperanto (wd:Q5398858): US-American fishing schooner, instance of schooner
8. Esperanto (wd:Q23012159): album by Freundeskreis, instance of album
9. Esperanto (wd:Q12347414): instance of ship, Spanish ship
10. Esperanto (wd:Q11290111): album by Ryuichi Sakamoto, instance of album

[Assistant]
The entity for the Esperanto language is wd:Q143.

Next, let's identify the entity for "periodical". I'll search for "periodical" to find the appropriate class.

[Tool]
Top 10 entity alternatives:
1. periodical, also known as periodical literature, periodicals, periodical publication (wd:Q1002697)
2. Periodical (wd:Q103961464): instance of encyclopedia article, encyclopedia article
3. Periodical, also known as Journal, Magazine, Publication, Cartoon mag, Cartoon Magazine (wd:Q67520005): a monthly cartoon publication, instance of publication, instance of magazine, instance of project, instance of ebook
4. periodicals, also known as periodical, periodicals as topic (wd:Q131470059)
5. periodical (wd:L727823-S1)
6. periodical (wd:L339209-F1)
7. periodical (wd:L339209)
8. periodical (wd:L325294-F1)
9. periodical (wd:L325294)
10. article, also known as journal article, serial article, periodical article (wd:Q191067)

[Assistant]
The main class for periodicals is wd:Q1002697.

Now, let's find the property for "primary language" or "language of work or name". I'll search for properties related to "language".

[Tool]
Top 10 property alternatives:
1. programmed in, also known as language, programming language, written in (wd:P277 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): the programming language(s) in which the software is developed
2. languages spoken, written or signed, also known as language written, wrote language, writes language, uses language, used language (wd:P1412 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): language(s) that a person or a people speaks, writes or signs, including the native language(s)
3. language of work or name, also known as used language, named in language, language of work, language of website, language of URL (wd:P407 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): language associated with this creative work (such as books, show...guage" (P103) and "languages spoken, written or signed" (P1412))
4. official language, also known as language official, language spoken, speaking, spoken in (wd:P37 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): language designated as official by this item, subproperty of language used
5. language used, also known as working languages, working language, used language, uses language, medium of instruction (wd:P2936 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): language widely used (spoken or written) in this place or at this event or organisation
6. language style, also known as obsolete, register, sense register, sense usage, style (wd:P6191 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): to denote of the way a sense of a word is used, e.g., slang, vulgarism, babytalk, colloquialism, etc.
7. native language, also known as first language, mother tongue, language native, L1 speaker of (wd:P103 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): language or languages a person has learned from early childhood, subproperty of languages spoken, written or signed
8. writing language, also known as languages for writing, writing languages, language written, languages written, languages of writings (wd:P6886 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): language in which the writer has written their work, subproperty of languages spoken, written or signed
9. Ethnologue language status, also known as EGIDS, language status (wd:P3823 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): language status identifier by Ethnologue.com using EGIDS scale
10. pronunciation variety, also known as dialect, accent, with pronunciation, with dialect, language variant (wd:P5237 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): qualifier for IPA transcription (P898), pronunciation audio (P44... audio (P989) to indicate the associated spoken language variant

[Assistant]
The property "language of work or name" (wd:P407) is the most appropriate for specifying the language of a periodical.

Now, let's summarize:
- Periodical: wd:Q1002697
- Esperanto: wd:Q143
- Language of work or name: wdt:P407

We want to find all items that are instances of (wdt:P31) periodical (wd:Q1002697) and have language of work or name (wdt:P407) Esperanto (wd:Q143).

Let's construct a SPARQL query to retrieve these periodicals, including their QIDs and optionally their English labels.

[Tool]
Got 89 rows and 2 columns, showing the first 5 and last 5 rows below:
| periodical                                                                         | periodicalLabel                                                          |
| ---------------------------------------------------------------------------------- | ------------------------------------------------------------------------ |
| Momenton! (wd:Q10331627)                                                           | Momenton! (en)                                                           |
| Pola Esperantisto (wd:Q11821362)                                                   | Pola Esperantisto (en)                                                   |
| El Popola Ĉinio (wd:Q119633)                                                       | El Popola Ĉinio (en)                                                     |
| Beletra Almanako N-ro 4 (februaro 2009) (wd:Q12345463)                             | Beletra Almanako N-ro 4 (februaro 2009) (en)                             |
| Bohema Revuo Esperantista (wd:Q12345746)                                           | Bohema Revuo Esperantista (en)                                           |
| ...                                                                                | ...                                                                      |
| Mondano (wd:Q80452320)                                                             | Mondano (en)                                                             |
| Norda prismo : kultura, socia, literatura, revuo, dumonata (wd:Q80452629)          | Norda prismo : kultura, socia, literatura, revuo, dumonata (en)          |
| Paco : oficiala organo de Mondpaca esperantista movado (MEM) (wd:Q80452991)        | Paco : oficiala organo de Mondpaca esperantista movado (MEM) (en)        |
| UABO : (antaǔe Ligilo por vidant...la asocio de blindul-organizaĵoj (wd:Q80454504) | UABO : (antaǔe Ligilo por vidant...la asocio de blindul-organizaĵoj (en) |
| Lingvo Internacia (wd:Q844150)                                                     | Lingvo Internacia (en)                                                   |

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?city ?pop ?coord WHERE {
  ?city wdt:P31 wd:Q515 ; wdt:P17 wd:Q159 ; wdt:P1082 ?pop ; wdt:P625 ?coord .
  FILTER ( ?pop > 100000 )
}

These are cities in Russia with a population exceeding 100,000, along with their coordinates. The query returns the city entity, its population, and its coordinates as a geo:wktLiteral. Example results include Tolyatti, Obninsk, Murino, Maykop, Orsk, Kemerovo, Irkutsk, Abakan, Chelyabinsk, and Vladivostok. The full list can be obtained by running the query.

What are the cities in Russia with a population exceeding 100,000? For each one also return their coordinates

[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 cities in Russia with a population exceeding 100,000? For each one also return their coordinates

[Assistant]
Let's break down the question:

1. We need to find entities that are cities in Russia.
2. For each city, we need to check if its population exceeds 100,000.
3. For each qualifying city, we need to return its coordinates.

Step 1: Identify the entity for "city" and "Russia".
- "city" is likely Q515.
- "Russia" is likely Q159.

Step 2: Find the relevant properties:
- "instance of" (P31) for city.
- "country" (P17) for Russia.
- "population" (P1082).
- "coordinates" (P625).

Let me verify these assumptions by searching for the entities and properties.

[Tool]
Top 10 entity alternatives:
1. city, also known as cities (wd:Q515)
2. Manchester City F.C., also known as Citizens, The Sky Blues, The Citizens, The Blues, Sky Blues (wd:Q50602): association football club in Manchester, England, instance of association football club
3. Leicester City F.C., also known as The Foxes, Leicester Fosse Football Club, Leicester Fosse FC, Leicester Fosse, Leicester (wd:Q19481): association football club in Leicester, England, instance of association football club
4. Swansea City A.F.C., also known as Swansea City Association Football Club, The Swans, The Jacks, Swansea City AFC, Swansea City (wd:Q18659): association football club in Swansea, Wales, instance of association football club
5. Stoke City F.C., also known as The Potters, Stoke City Football Club, Stoke City FC, Stoke, Stoke City (wd:Q18736): association football club in Stoke-on-Trent, England, instance of association football club
6. Birmingham City F.C., also known as City, BCFC, Blues, Birmingham City Football Club, Birmingham City FC (wd:Q19444): association football club in Birmingham, England, instance of association football club
7. Norwich City F.C., also known as City, The Canaries, Norwich City Football Club, Norwich City FC, Norwich City (wd:Q18721): association football club in Norwich, England, instance of association football club
8. Cardiff City F.C., also known as CCFC, City, The Bluebirds, Cardiff City FC, Cardiff City Football Club (wd:Q18662): association football club in Cardiff, Wales, instance of association football club
9. Hull City A.F.C., also known as Hull, The Tigers, Hull City Association Football Club, Hull City AFC, Hull City (wd:Q19477): association football club in Hull, England, instance of association football club
10. Coventry City F.C., also known as Sky Blues, Coventry City Football Club, Coventry City FC, Coventry City, Coventry (wd:Q19580): association football club in Coventry, England, instance of association football club

[Tool]
Top 10 entity alternatives:
1. Russia, also known as RU, ru, RUS, Russian Federation, ISO 3166-1:RU (wd:Q159): country in Eastern Europe and Northern Asia, instance of transcontinental country, instance of sovereign state, instance of successor state, instance of secular state, instance of federation, instance of country
2. Russian Empire, also known as Tsarist Russia, Russia or Moscovy, Russia, Rusia, Rossia (wd:Q34266): former empire in Eurasia and North America (1721–1917), instance of historical country
3. Russia, also known as Russia, OH (wd:Q2477732): instance of village of Ohio, town in Ohio
4. Russia, also known as Russia, NY (wd:Q3708651): instance of town in the United States, instance of town of New York, town in New York
5. Russia in the Junior Eurovision Song Contest 2006, also known as Russia (wd:Q12739658): instance of nation at competition
6. Russia (wd:Q4339657): annual international documentary film festival in Yekaterinburg, instance of film festival
7. Intelligence and Security Committee Russia report, also known as The Russia report, Russia Report, Russia (wd:Q97577701): UK government investigation into allegations of Russian interference in British politics, instance of report
8. Russia (wd:Q19149694): instance of literary work, poem by Alexander Blok
9. Russia, also known as Russia, New Jersey, Russia, NJ (wd:Q20657737): instance of unincorporated community in the United States, township in Morris County, New Jersey
10. Russia, also known as Rossiya (wd:Q109806507): cast iron sculpture by Nikolay Laveretsky, instance of sculpture

[Tool]
Top 10 property alternatives:
1. tabular population, also known as population (wd:P4179 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): same as population (P1082); used when there is data for many different points in time
2. population, also known as human population, inhabitants (wd:P1082 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): number of people inhabiting the place; number of people of subject
3. has census, also known as has human population census (wd:P8701 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): general population census of the country or region
4. urban population (wd:P6343 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): number of people living within the territorial entity who live in its urban parts, subproperty of population
5. birth rate (wd:P8763 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): the total number of live births per 1,000 population
6. category populated by, also known as wikimedia entity populating this category, populated by, component adding into the category, category has template, category filled by (wd:P4329 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): software component (template, module, extension, MediaWiki core) populating the category
7. rural population (wd:P6344 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): number of people living within the territorial entity who live in its rural parts, subproperty of population
8. female population (wd:P1539 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): number of female people inhabiting the place; number of female people of subject, subproperty of population
9. male population, also known as number of males, male inhabitants (wd:P1540 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): number of male people inhabiting the place; number of male people of subject, subproperty of population
10. number of households, also known as dwellings, households (wd:P1538 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): total number of households in this place, includes dwellings of all types

[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]
Top 10 property alternatives:
1. valid in place, also known as country, valid in territory, valid in location, true in, applies to place (wd:P3005 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): place where a statement is valid, subproperty of applies to part
2. country of origin, also known as comes from, place of origin, origin country, originates from, country (wd:P495 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): country of origin of this item (creative work, food, phrase, product, etc.), subproperty of significant place, subproperty of country
3. country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): the object is a country that recognizes the subject as its citizen, subproperty of country
4. country, also known as state, sovereign state, land, host country (wd:P17 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): sovereign state that this item is in (not to be used for human beings), subproperty of located in the administrative territorial entity
5. applies to jurisdiction, also known as country of jurisdiction, of, jurisdiction linked, jurisdiction, belongs to jurisdiction (wd:P1001 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): the item (institution, law, public office, public register...) o...a territorial jurisdiction: a country, state, municipality, ...), subproperty of characteristic of, subproperty of significant place, subproperty of operating area
6. place of publication, also known as country (published in), where published, release region, released in, published in (place) (wd:P291 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): geographical place of publication of the edition (use 1st edition when referring to works), subproperty of significant place
7. operating area, also known as operating region, serves geographic region, serves geographic area, serves area, region served (wd:P2541 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): geographic area or jurisdiction an organisation or industry operates in, serves, or has responsibility for, subproperty of location
8. place of birth, also known as location born, POB, location of birth, born in, born at (wd:P19 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): most specific known birth location of a person, animal or fictional character, subproperty of location
9. continent (wd:P30 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): subproperty of located in/on physical feature, continent of which the subject is a part
10. located in the administrative territorial entity, also known as is in the shire of, is in the voivodeship of, is in the state of, is in the territory of, is in the town of (wd:P131 as pqv/prv/psn/pqn/wdt/pr/p/psv/wdtn/prn/ps/pq): the item is located on the territory of the following administra...if the item falls only partially into the administrative entity., subproperty of location, subproperty of part of

[Tool]
Got 5 rows and 1 column:
| city                  |
| --------------------- |
| Abaza (wd:Q102469)    |
| Abdulino (wd:Q102682) |
| Agidel (wd:Q102737)   |
| Kursk (wd:Q13140191)  |
| Tolyatti (wd:Q1341)   |

[Tool]
Got 1,129 rows and 3 columns, showing the first 10 rows below:
| subject             | property                                                    | object                                                                                |
| ------------------- | ----------------------------------------------------------- | --------------------------------------------------------------------------------------------------------- |
| Tolyatti (wd:Q1341) | instance of (wdt:P31)                                       | city (wd:Q515)                                                                                |
| Tolyatti (wd:Q1341) | country (wdt:P17)                                           | Russia (wd:Q159)                                                                                |
| Tolyatti (wd:Q1341) | located in the administrative territorial entity (wdt:P131) | Tolyatti Urban Okrug (wd:Q27577216)                                                                       |
| Tolyatti (wd:Q1341) | coordinate location (wdt:P625)                              | POINT(49.416667 53.516667) (geo:wktLiteral)                                                               |
| Tolyatti (wd:Q1341) | Commons category (wdt:P373)                                 | Tolyatti                                                                                |
| Tolyatti (wd:Q1341) | image (wdt:P18)                                             | <http://commons.wikimedia.org/wiki/Special:FilePath/Komsomolsky%20district%2C%20Tolyatti%2C%20Russia.JPG> |
| Tolyatti (wd:Q1341) | population (wdt:P1082)                                      | 667956 (xsd:decimal)                                                                                |
| Tolyatti (wd:Q1341) | inception (wdt:P571)                                        | 1737-07-01T00:00:00Z (xsd:dateTime)                                                                       |
| Tolyatti (wd:Q1341) | described by source (wdt:P1343)                             | Armenian Soviet Encyclopedia, vol. 12 (wd:Q124737664)                                                     |
| Tolyatti (wd:Q1341) | official name (wdt:P1448)                                   | Тольятти (ru)                                                                                |
| ...                 | ...                                                         | ...                                                                                |

[Tool]
Got 5 rows and 1 column:
| city                 |
| -------------------- |
| Tolyatti (wd:Q1341)  |
| Obninsk (wd:Q175651) |
| Murino (wd:Q1978797) |
| Maykop (wd:Q3752)    |
| Orsk (wd:Q47166)     |

[Tool]
Got 441 rows and 3 columns, showing the first 10 rows below:
| subject              | property                                                    | object                                                               |
| -------------------- | ----------------------------------------------------------- | -------------------------------------------------------------------- |
| Obninsk (wd:Q175651) | instance of (wdt:P31)                                       | city (wd:Q515)                                                       |
| Obninsk (wd:Q175651) | country (wdt:P17)                                           | Russia (wd:Q159)                                                     |
| Obninsk (wd:Q175651) | located in the administrative territorial entity (wdt:P131) | Obninsk Urban Okrug (wd:Q27558920)                                   |
| Obninsk (wd:Q175651) | coordinate location (wdt:P625)                              | POINT(36.616667 55.100000) (geo:wktLiteral)                          |
| Obninsk (wd:Q175651) | Commons category (wdt:P373)                                 | Obninsk                                                              |
| Obninsk (wd:Q175651) | image (wdt:P18)                                             | <http://commons.wikimedia.org/wiki/Special:FilePath/Obninsk2016.jpg> |
| Obninsk (wd:Q175651) | population (wdt:P1082)                                      | 132477 (xsd:decimal)                                                 |
| Obninsk (wd:Q175651) | inception (wdt:P571)                                        | 1946-01-01T00:00:00Z (xsd:dateTime)                                  |
| Obninsk (wd:Q175651) | official website (wdt:P856)                                 | <http://www.admobninsk.ru/>                                          |
| Obninsk (wd:Q175651) | postal code (wdt:P281)                                      | 249030–249040                                                        |
| ...                  | ...                                                         | ...                                                                  |

[Tool]
Got 11 rows and 3 columns, showing the first 5 and last 5 rows below:
| city                  | pop                   | coord                                        |
| --------------------- | --------------------- | -------------------------------------------- |
| Tolyatti (wd:Q1341)   | 667956 (xsd:decimal)  | POINT(49.416667 53.516667) (geo:wktLiteral)  |
| Obninsk (wd:Q175651)  | 132477 (xsd:decimal)  | POINT(36.616667 55.100000) (geo:wktLiteral)  |
| Murino (wd:Q1978797)  | 112536 (xsd:decimal)  | POINT(30.438611 60.051389) (geo:wktLiteral)  |
| Maykop (wd:Q3752)     | 139084 (xsd:decimal)  | POINT(40.083333 44.600000) (geo:wktLiteral)  |
| Orsk (wd:Q47166)      | 185362 (xsd:decimal)  | POINT(58.468100 51.229000) (geo:wktLiteral)  |
| ...                   | ...                   | ...                                          |
| Kemerovo (wd:Q6066)   | 542928 (xsd:decimal)  | POINT(86.066667 55.333333) (geo:wktLiteral)  |
| Irkutsk (wd:Q6576)    | 605708 (xsd:decimal)  | POINT(104.280000 52.289167) (geo:wktLiteral) |
| Abakan (wd:Q875)      | 181709 (xsd:decimal)  | POINT(91.416667 53.716667) (geo:wktLiteral)  |
| Chelyabinsk (wd:Q906) | 1176770 (xsd:decimal) | POINT(61.400000 55.150000) (geo:wktLiteral)  |
| Vladivostok (wd:Q959) | 591628 (xsd:decimal)  | POINT(131.885278 43.115000) (geo:wktLiteral) |

[Tool] Stopped generation process