PREFIX pq: <http://www.wikidata.org/prop/qualifier/>
PREFIX ps: <http://www.wikidata.org/prop/statement/>
PREFIX p: <http://www.wikidata.org/prop/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?org ?count ?year WHERE {
  ?org wdt:P6782 "024z2rq82" .
  ?org p:P2196 ?statement .
  ?statement ps:P2196 ?count .
  OPTIONAL {
    ?statement pq:P585 ?year .
  }
}
ORDER BY ?year

Got 31 rows and 3 columns, showing the first 5 and last 5 rows below:
| org                                   | count               | year                                |
| ------------------------------------- | ------------------- | ----------------------------------- |
| University of Düsseldorf (wd:Q317032) | 23997 (xsd:decimal) | 1998-01-01T00:00:00Z (xsd:dateTime) |
| University of Düsseldorf (wd:Q317032) | 24789 (xsd:decimal) | 1999-01-01T00:00:00Z (xsd:dateTime) |
| University of Düsseldorf (wd:Q317032) | 24868 (xsd:decimal) | 2000-01-01T00:00:00Z (xsd:dateTime) |
| University of Düsseldorf (wd:Q317032) | 25537 (xsd:decimal) | 2001-01-01T00:00:00Z (xsd:dateTime) |
| University of Düsseldorf (wd:Q317032) | 25220 (xsd:decimal) | 2002-01-01T00:00:00Z (xsd:dateTime) |
| ...                                   | ...                 | ...                                 |
| University of Düsseldorf (wd:Q317032) | 36571 (xsd:decimal) | 2018-01-01T00:00:00Z (xsd:dateTime) |
| University of Düsseldorf (wd:Q317032) | 37540 (xsd:decimal) | 2019-01-01T00:00:00Z (xsd:dateTime) |
| University of Düsseldorf (wd:Q317032) | 37473 (xsd:decimal) | 2019-01-01T00:00:00Z (xsd:dateTime) |
| University of Düsseldorf (wd:Q317032) | 36070 (xsd:decimal) | 2020-01-01T00:00:00Z (xsd:dateTime) |
| University of Düsseldorf (wd:Q317032) | 33942 (xsd:decimal) | 2021-01-01T00:00:00Z (xsd:dateTime) |

This query finds the educational organization with ROR ID '024z2rq82' (University of Düsseldorf), then retrieves the number of students for each year (if available), ordered by year. The results are robustly based on the ROR ID, not a hardcoded QID.

[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

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/
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. Use the functions to search for 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. Use the execute function to get feedback on intermediate queries. You can go back and forth between knowledge graph searches and SPARQL query executions to refine the query.
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 assume or make up any entities or properties without verifying them with the knowledge graphs and functions.
3. 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.
4. 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.
5. 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.
6. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
7. 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] How many students did the educational organization with the Research Organization Registry (ROR) ID "024z2rq82" have each year? Please include a count for each year (if available), and order results by year.

[Assistant]
Let's break down the question:

1. We need to identify the educational organization with the ROR ID "024z2rq82" in Wikidata.
2. Then, we need to find the property in Wikidata that links organizations to their ROR IDs.
3. Next, we need to find the property for the number of students (likely "number of students" or similar).
4. We also need to get the count for each year, so we should look for a qualifier property indicating the point in time (year).
5. Finally, we need to order the results by year.

Let's start by searching for the property in Wikidata that links organizations to their ROR ID.

[Tool]
Top 10 property alternatives:
1. ROR ID, also known as Research Organization Registry ID, ror.org ID (wd:P6782 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): identifier for the Research Organization Registry
2. Relations Ontology ID, also known as RO ID, Relation Ontology ID (wd:P3590 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): ID in the Relations Ontology
3. Rijksmuseum Research Library authority ID, also known as RRL ID (wd:P7444 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): authority control identifier for the Rijksmuseum Research Library
4. RBU person ID, also known as RBU ID (wd:P6387 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): identifier for a person at the Russian Biathlon Union site
5. Online Coins of the Roman Empire ID, also known as OCRE ID, Roman Imperial Coinage ID, RIC ID, RIC coin ID, OCRE coin ID (wd:P9645 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): identifier of a coin in the Online Coins of the Roman Empire pla...the Roman Imperial Coinage (RIC) series published by Spink & Son
6. Research Resource Identifier, also known as RRID, SciCrunch identifier (wd:P9712 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): identifier in the SciCrunch database of research resources
7. Australian Women's Register ID, also known as AWR ID, womenaustralia.info (wd:P4186 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): identifier for a person or organisation in the Australian Women's Register
8. Channel One Russia show ID, also known as 1tv.ru ID, Channel One Russia ID, COR ID (wd:P10170 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): identifier of TV program for Channel One Russia
9. French national research structure ID, also known as French national research structure identifier, RNSR ID, national research structure identifier (France) (wd:P3016 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): identifier in the French national research structure repertory
10. Russian Academy of Sciences person ID, also known as RAS ID, Russian Academy of Sciences ID (wd:P10133 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): identifier for a member of the Russian Academy of Sciences

[Assistant]
The property for ROR ID in Wikidata is `wd:P6782`.

Next, I will search for the educational organization in Wikidata that has the ROR ID "024z2rq82" using this property.

[Tool]
Failed to list triples with error:
failed to parse input: no matching token found from position 76: 'z2rq82 }
    ?s ?p ?o
} LIMIT 65536'

[Assistant] It seems there was an error, possibly due to the format of the ROR ID. Sometimes identifiers are stored as strings, and sometimes with a prefix or in a specific format. Let me try searching for the entity using the ROR ID as a string in the search function to find the corresponding Wikidata entity.

[Tool] No entity items found

[Assistant] The direct search for the ROR ID "024z2rq82" did not return any entity. Sometimes, ROR IDs are stored with a prefix, such as "https://ror.org/024z2rq82". I will try searching for the full ROR URL to see if the entity can be found that way.

[Tool] No entity items found

[Assistant] Searching for the full ROR URL also did not return any entity. To ensure we are not missing the organization due to formatting, I will search for the property value directly using the list function, but this time I will try with the full ROR URL as the object.

[Tool] Got no rows and 3 columns

[Assistant]
It appears that Wikidata does not have an entity with the ROR ID "024z2rq82" or it is not indexed in a way that is directly searchable via the ROR ID or its URL. Without being able to identify the organization entity in Wikidata, I cannot proceed to retrieve the number of students per year for it.

If you have the name of the organization, I could try searching by name. Otherwise, I am unable to construct a satisfactory SPARQL query for your request.

I will cancel and explain the issue.

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The system's initial attempt to find the organization by ROR ID was successful: the query returned University of Düsseldorf (wd:Q317032). However, the system failed to proceed to the next step, which is to retrieve the number of students per year for this organization. The next step should be to query for the number of students (likely using property P2196: student enrollment) with qualifiers for the year (P585: point in time), and order the results by year. The output should be refined to include this information.

[Assistant]
Thank you for the feedback and clarification. Now that we know the organization is University of Düsseldorf (wd:Q317032), the next steps are:

1. Find the property for "number of students" (likely P2196: student enrollment).
2. Find the qualifier for "point in time" (likely P585).
3. Query for all student enrollment statements for wd:Q317032, include the year (if available), and order results by year.

Let's confirm the property for "student enrollment" and "point in time" before constructing the query.

[Tool]
Top 10 property alternatives:
1. count of students, also known as count of pupils, count of students, enrollment, number of pupils, number of pupils or students (wd:P2196 as p/wdt): number of pupils or students of any type in an educational organ...evious years normal rank (not deprecated rank). Don't overwrite.
2. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as p/wdt): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
3. X (Twitter) username, also known as twitter.com/, X username, X handle, x.com/, X account (wd:P2002 as p/wdt): username on X (formerly Twitter); do not include the '@' symbol, website username or ID
4. category for employees of the organization, also known as Academic staff, category for employees of the organisation, Professor (wd:P4195 as p/wdt): Wikimedia category for people who work or worked at this organization
5. described by source, also known as mentioned in, source of item, reviewed in, mentioned in news article, talked about in (wd:P1343 as p/wdt): work where this item is described, attested in
6. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as p/wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
7. country, also known as sovereign state, state, land, host country (wd:P17 as p/wdt): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
8. Microsoft Academic ID, also known as MS Academic ID, Microsoft ID, Microsoft Academic Work ID, Microsoft Academic topic ID, Microsoft Academic Source ID (wd:P6366 as wdt/p/wdtn): identifier for an object or topic in the Microsoft Academic Graph (until 31 December 2021)
9. Instagram username, also known as IG username, www.instagram.com, urinsta, ufinsta, Insta ID (wd:P2003 as p/wdt): item's username on Instagram, website username or ID
10. member of, also known as band member of, membership, member of musical group, in musical group, be member of (wd:P463 as p/wdt): organization, club or musical group to which the subject belongs...ical position, such as a member of parliament (use P39 for that), part of

No other items found

[Tool]
Top 10 property alternatives:
1. point in time, also known as at time, as of, year, when, time of event (wd:P585 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): date something took place, existed or a statement was true; for providing time use the "refine date" property (P4241)
2. valid in period, also known as valid in season, valid for season, valid for period, valid for, time period (wd:P1264 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): time period when a statement is valid
3. set in period, also known as time period set in, time period of setting, time period, takes place in time, takes place during (wd:P2408 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): historical, contemporary, or future period, year, century or day...rk or genre is set in or event featured in the story of the work
4. time period, also known as oge (oge akụkọ ihe mere eme ma ọ...ụ mere ma ọ bụ nke ejikọtara ya. (wd:P2348 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): time period (historic period or era, sports season, theatre seas...c.) in which the subject occurred or with which it is associated
5. start time, also known as start date, since, valid, join time, joined (wd:P580 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): time an entity begins to exist or a statement starts being valid, point in time
6. date depicted, also known as depicted date, temporal coverage, shown as at date, depicts date, depicted time (wd:P2913 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): date represented in a work (for narrative works use P2408)
7. term length of position, also known as term length, time in position, term of position, position term, length of term (wd:P2097 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): length of time in years (unit: Q577) a person (usually a politician) is to serve in a particular position. Do not add bounds., duration
8. history of topic, also known as history of the topic, timeline of subject, timeline of the subject, timeline of the topic, timeline of topic (wd:P2184 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): item about the historical development of a subject's topic, exam... To list key events of the topic, use "significant event" (P793), studied in
9. latest date, also known as terminus ante quem, prior to, on or before this date, no later than, max date (wd:P1326 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): latest possible time that something could have occurred. Use as qualifier for other date properties
10. recording date, also known as recorded date, record date, recdate, rec. date, date of recording (wd:P10135 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): the date when a recording was made, inception

[Tool]
Got 31 rows and 2 columns, showing the first 5 and last 5 rows below:
| count               | year                                |
| ------------------- | ----------------------------------- |
| 23997 (xsd:decimal) | 1998-01-01T00:00:00Z (xsd:dateTime) |
| 24789 (xsd:decimal) | 1999-01-01T00:00:00Z (xsd:dateTime) |
| 24868 (xsd:decimal) | 2000-01-01T00:00:00Z (xsd:dateTime) |
| 25537 (xsd:decimal) | 2001-01-01T00:00:00Z (xsd:dateTime) |
| 25220 (xsd:decimal) | 2002-01-01T00:00:00Z (xsd:dateTime) |
| ...                 | ...                                 |
| 36571 (xsd:decimal) | 2018-01-01T00:00:00Z (xsd:dateTime) |
| 37540 (xsd:decimal) | 2019-01-01T00:00:00Z (xsd:dateTime) |
| 37473 (xsd:decimal) | 2019-01-01T00:00:00Z (xsd:dateTime) |
| 36070 (xsd:decimal) | 2020-01-01T00:00:00Z (xsd:dateTime) |
| 33942 (xsd:decimal) | 2021-01-01T00:00:00Z (xsd:dateTime) |

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The query retrieves the student counts by year for the University of Düsseldorf, which is correct based on the mapping from the ROR ID to the Wikidata entity (wd:Q317032). However, the query does not explicitly show how the ROR ID '024z2rq82' is mapped to this university. For completeness and robustness, the query should include a triple that connects the ROR ID (via property P6782) to the university entity, ensuring the answer is based on the ROR ID provided in the question. Additionally, the query should use an explicit BIND or FILTER for the ROR ID, rather than hardcoding the university QID. The rest of the query structure and ordering is correct.

[Assistant]
Thank you for the feedback. To make the query robust and fully based on the ROR ID, I will:

1. Start by finding the educational organization that has the ROR ID "024z2rq82" using property P6782.
2. Then, for that organization, retrieve all student enrollment (P2196) statements, with the year (P585) as a qualifier.
3. Order the results by year.
4. Use FILTER or BIND for the ROR ID, not a hardcoded QID.

Here is the refined SPARQL query:

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX xsd: <http://www.w3.org/2001/XMLSchema#>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?highway ?label ?number WHERE {
  ?highway wdt:P16 wd:Q1967342 .
  ?highway rdfs:label ?label .
  FILTER ( LANG( ?label ) = "en" ) FILTER ( CONTAINS( ?label , "National Highway " ) ) BIND( STRAFTER( ?label , "National Highway " ) AS ?numStr ) FILTER ( REGEX( ?numStr , "^[0-9]+$" ) ) BIND( xsd:integer ( ?numStr ) AS ?number ) FILTER ( ?number < 100 )
}
ORDER BY ?number

Got 80 rows and 3 columns, showing the first 5 and last 5 rows below:
| highway                            | label                    | number       |
| ---------------------------------- | ------------------------ | ------------ |
| National Highway 1 (wd:Q642922)    | National Highway 1 (en)  | 1 (xsd:int)  |
| National Highway 2 (wd:Q25203036)  | National Highway 2 (en)  | 2 (xsd:int)  |
| National Highway 3 (wd:Q25203039)  | National Highway 3 (en)  | 3 (xsd:int)  |
| National Highway 4 (wd:Q6973185)   | National Highway 4 (en)  | 4 (xsd:int)  |
| National Highway 5 (wd:Q25203045)  | National Highway 5 (en)  | 5 (xsd:int)  |
| ...                                | ...                      | ...          |
| National Highway 79 (wd:Q25203074) | National Highway 79 (en) | 79 (xsd:int) |
| National Highway 81 (wd:Q25352382) | National Highway 81 (en) | 81 (xsd:int) |
| National Highway 83 (wd:Q25212186) | National Highway 83 (en) | 83 (xsd:int) |
| National Highway 85 (wd:Q25207402) | National Highway 85 (en) | 85 (xsd:int) |
| National Highway 87 (wd:Q24238723) | National Highway 87 (en) | 87 (xsd:int) |

This query returns all Indian National Highways that are part of the national highways of India transport network, with English labels and highway numbers less than 100, ordered by highway number.

[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

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/
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. Use the functions to search for 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. Use the execute function to get feedback on intermediate queries. You can go back and forth between knowledge graph searches and SPARQL query executions to refine the query.
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 assume or make up any entities or properties without verifying them with the knowledge graphs and functions.
3. 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.
4. 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.
5. 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.
6. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
7. 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 Indian National Highways that are part of the national highways of India transport network? Return also their English labels and highway numbers (extracted from the labels), only include highways with numbers less than 100, and order by highway number.

[Assistant]
Let's break down the question:

1. We are looking for Indian National Highways that are part of the national highways of India transport network.
2. We need their English labels and highway numbers (extracted from the labels).
3. Only include highways with numbers less than 100.
4. Order the results by highway number.

Step 1: Identify the entity for "Indian National Highway" and "national highways of India transport network".
Step 2: Find the property that links highways to the network.
Step 3: Find how highway numbers are represented (likely in the label, e.g., "National Highway 44 (India)").
Step 4: Extract the number from the label using SPARQL string functions.
Step 5: Filter for numbers less than 100 and order by number.

First, let's search for the entity "Indian National Highway".

[Tool]
Top 10 entity alternatives:
1. Indian Oil Fuel Filling Station ...ay (Jay Jalaram Krupa Petroleum), also known as Indian Oil Petrol Pump Old National Highway (wd:Q131950634): fuel station of IndianOil in Ankleshwar District, Gujarat, India
2. Indian Oil Fuel Filling Station ...al Highway (Rameshwar Petroleum), also known as Indian Oil Petrol Pump Old National Highway (wd:Q131950636): fuel station of IndianOil in Ankleshwar District, Gujarat, India
3. Indian Oil Fuel Filling Station ...onal Highway (Dwrakesh Agencies), also known as Indian Oil Petrol Pump Labbaikudikadu National Highway (wd:Q131964834): fuel station of IndianOil in Perambalur District, Tamil Nadu, India
4. Indian Oil Fuel Filling Station ...way 128B (Janta Service Station), also known as Indian Oil Petrol Pump National Highway 128B (wd:Q131945545): fuel station of IndianOil in Azamgarh District, Uttar Pradesh, India
5. Indian Oil Fuel Filling Station ...y 130 (Pitambar Filling Station), also known as Indian Oil Petrol Pump National Highway 130 (wd:Q131957322): fuel station of IndianOil in Ambikapur District, Chhattisgarh, India
6. Indian Oil Fuel Filling Station ... Highway 130CD (Srinivasa Fuels), also known as Indian Oil Petrol Pump National Highway 130CD (wd:Q131971088): fuel station of IndianOil in Nabarangapur District, Odisha, India
7. Indian Oil Fuel Filling Station ...y 129A (Jalukie Filling Station), also known as Indian Oil Petrol Pump National Highway 129A (wd:Q131972847): fuel station of IndianOil in Peren District, Nagaland, India
8. Indian Oil Fuel Filling Station ...al Highway 128B (Usha Petroleum), also known as Indian Oil Petrol Pump National Highway 128B (wd:Q131945575): fuel station of IndianOil in Ballia District, Uttar Pradesh, India
9. Indian Oil Fuel Filling Station ...hway 128B (Shiv Filling Station), also known as Indian Oil Petrol Pump National Highway 128B (wd:Q131945465): fuel station of IndianOil in Azamgarh District, Uttar Pradesh, India
10. Indian Oil Fuel Filling Station ...8B (Saubhagya Sumitra Petroleum), also known as Indian Oil Petrol Pump National Highway 128B (wd:Q131945546): fuel station of IndianOil in Azamgarh District, Uttar Pradesh, India

[Tool]
Top 10 entity alternatives:
1. National Highway 544, also known as National Highway 47 (India)(old numbering), Salem - Kochi Highway, NH 544 (India), NH544, National Highway 544 (India) (wd:Q765630): national highway in South India connecting Salem and Kochi
2. National Highway 47, also known as Bamanbore - Nagpur Highway, National Highway 47 (India), NH 47 (wd:Q25203064): national highway in India running through Gujarat and Madhya Pradesh
3. National Highway 32 (India) (wd:Q12450079)
4. National Highway 505, also known as National Highway 505 (India) (wd:Q50409103): National Highway in Himachal Pradesh, India
5. National Highway 8C (India) (wd:Q12450142)
6. National Highway 179A, also known as National Highway 179A (India) (wd:Q39573809): national highway in India
7. National Highway 161E, also known as National Highway 161E (India) (wd:Q56289412): national highway in India
8. National Highway 251 (India) (wd:Q55473647): national highway in India
9. National Highway 352A (India) (wd:Q55876664): National Highway in India
10. National Highway 148A (India) (wd:Q111337703): National Highway of India

[Tool]
Top 10 entity alternatives:
1. national highways of India, also known as India's National Highways, National Highway, National Highways of India (wd:Q1967342): network of highways owned by the Government of India
2. National Highways Authority of India, also known as NHAI (wd:Q282114): Agency responsible for Road Construction and It's Management in India
3. National Highways Authority of India Act, 1988 (wd:Q95338787): Act of the Parliament of India
4. Ministry of Road Transport and Highways, also known as Ministry of Road Transport and Highways, Government of India, MoRTH (wd:Q167156): government ministry in India
5. National Highways Authority of India (Amendment) Act, 2013 (wd:Q79471774): Act of the Parliament of India
6. Roadkill animals on national highways of Karnataka, India (wd:Q125952091): scientific article published in 2012
7. transport in India, also known as transport of India, transport (India), transportation of India, transportation (India), India transport (wd:Q2065643): methods of transportation in India
8. National Library of India (wd:Q619913): national library located in Kolkata
9. national park of India, also known as Indian National Parks and Wildlife Sanctuaries (wd:Q1125269): IUCN (International union of conservation of Nature)
10. National Museum, also known as National Museum, New Delhi, National Museum of India (wd:Q1356138): National and art museum in New Delhi, India

[Tool]
Top 10 property alternatives:
1. original broadcaster, also known as TV channel, television channel, radio station, radio network, original network (wd:P449 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): network(s) or service(s) that originally broadcast a radio or television program, broadcast by
2. transport network, also known as transport network, transit network, tram network, trail system, system of routes (wd:P16 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): network the infrastructure is a part of, part of
3. broadcast by, also known as streamed by, TV station, TV network, TV channel, radio station (wd:P3301 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): channel, network, website or service that broadcast this item over radio, television or the Internet
4. IPv4 routing prefix, also known as CIDR, IPv4 CIDR, IPv4 range, IPv4 subnetwork, routing prefix (wd:P3761 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): range of IPv4 addresses
5. IPv6 routing prefix, also known as CIDR, subnetwork, routing prefix, IPv6 range, IPv6 CIDR (wd:P3793 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): range of IPv6 addresses
6. card network, also known as card association (wd:P4443 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): credit or debit card network
7. multi-channel network (wd:P6540 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): multi-channel network of which this YouTube channel is a member
8. network bands (wd:P8097 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): network bands supported by the device
9. connects with, also known as contacts, couples with, intersects at grade, links to, mates with (wd:P2789 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): item with which the item is physically connected, physically interacts with
10. Indigenous Corporation Number, also known as ICN (wd:P10024 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): registration number assigned to an Aboriginal and Torres Strait Islander corporation

[Tool]
Got 652 rows and 3 columns, showing the first 10 rows below:
| subject                            | property                    | object                                   |
| ---------------------------------- | --------------------------- | ---------------------------------------- |
| National Highway 66 (wd:Q3520609)  | transport network (wdt:P16) | national highways of India (wd:Q1967342) |
| National Highway 11 (wd:Q765649)   | transport network (wdt:P16) | national highways of India (wd:Q1967342) |
| National Highway 2 (wd:Q25203036)  | transport network (wdt:P16) | national highways of India (wd:Q1967342) |
| National Highway 19 (wd:Q25209307) | transport network (wdt:P16) | national highways of India (wd:Q1967342) |
| National Highway 16 (wd:Q643140)   | transport network (wdt:P16) | national highways of India (wd:Q1967342) |
| National Highway 44 (wd:Q643144)   | transport network (wdt:P16) | national highways of India (wd:Q1967342) |
| National Highway 5 (wd:Q25203045)  | transport network (wdt:P16) | national highways of India (wd:Q1967342) |
| National Highway 48 (wd:Q28178832) | transport network (wdt:P16) | national highways of India (wd:Q1967342) |
| National Highway 1 (wd:Q642922)    | transport network (wdt:P16) | national highways of India (wd:Q1967342) |
| National Highway 51 (wd:Q1757346)  | transport network (wdt:P16) | national highways of India (wd:Q1967342) |
| ...                                | ...                         | ...                                      |

[Tool]
Got 100 rows and 2 columns, showing the first 5 and last 5 rows below:
| highway                                         | label                                |
| ----------------------------------------------- | ------------------------------------ |
| Raipur–Visakhapatnam Expressway (wd:Q104848629) | Raipur–Visakhapatnam Expressway (en) |
| National Highway 109K (wd:Q105759673)           | National Highway 109K (en)           |
| National Highway 148A (wd:Q106647823)           | National Highway 148A (en)           |
| National Highway 229 (wd:Q106652354)            | National Highway 229 (en)            |
| National Highway 753AB (wd:Q106668254)          | National Highway 753AB (en)          |
| ...                                             | ...                                  |
| National Highway 302 (wd:Q18619662)             | National Highway 302 (en)            |
| National Highway 306 (wd:Q18619663)             | National Highway 306 (en)            |
| National Highway 307 (wd:Q18619664)             | National Highway 307 (en)            |
| National Highway 325 (wd:Q18619665)             | National Highway 325 (en)            |
| National Highway 502 (wd:Q18619667)             | National Highway 502 (en)            |

[Tool]
Got 200 rows and 2 columns, showing the first 5 and last 5 rows below:
| highway                                | label                       |
| -------------------------------------- | --------------------------- |
| National Highway 109K (wd:Q105759673)  | National Highway 109K (en)  |
| National Highway 148A (wd:Q106647823)  | National Highway 148A (en)  |
| National Highway 229 (wd:Q106652354)   | National Highway 229 (en)   |
| National Highway 753AB (wd:Q106668254) | National Highway 753AB (en) |
| National Highway 744A (wd:Q106668587)  | National Highway 744A (en)  |
| ...                                    | ...                         |
| National Highway 319 (wd:Q25352210)    | National Highway 319 (en)   |
| National Highway 519 (wd:Q25352212)    | National Highway 519 (en)   |
| National Highway 719 (wd:Q25352214)    | National Highway 719 (en)   |
| National Highway 919 (wd:Q25352215)    | National Highway 919 (en)   |
| National Highway 320 (wd:Q25352216)    | National Highway 320 (en)   |

[Assistant]
Now that we have a list of highways with English labels, the next step is to extract the highway number from the label. The labels are in the format "National Highway X" or "National Highway XX", sometimes with suffixes (e.g., "National Highway 44", "National Highway 44A"). We only want those with numbers less than 100 and without suffixes (since "44A" is not less than 100 as a number).

We can use SPARQL string functions to extract the number from the label, filter out those with non-numeric suffixes, and only include those less than 100. We will also order the results by the extracted highway number.

Here is the final SPARQL query to achieve this.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves Indian National Highways that are part of the national highways of India transport network, extracts their English labels, parses the highway numbers from the labels, filters for numbers less than 100, and orders the results by highway number. The query returns the actual IRIs, and all computation is performed within SPARQL. The output matches the user's requirements. No further refinement is necessary.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?institution ?memobaseID ( GROUP_CONCAT( DISTINCT ?type ; separator = ", " ) AS ?types ) ?streetAddress ?municipality ?municipalityLabel ?canton ?cantonLabel WHERE {
  ?institution wdt:P9657 ?memobaseID .
  ?institution wdt:P31 / wdt:P279 * wd:Q43229 .
  OPTIONAL {
    ?institution wdt:P31 ?type .
  }
  OPTIONAL {
    ?institution wdt:P6375 ?streetAddress .
  }
  OPTIONAL {
    ?institution wdt:P131 ?municipality .
    ?municipality wdt:P31 wd:Q70208 .
    OPTIONAL {
      ?municipality rdfs:label ?municipalityLabel FILTER ( LANG( ?municipalityLabel ) = "en" )
    }
  }
  OPTIONAL {
    ?institution wdt:P131 ?canton .
    ?canton wdt:P31 wd:Q23058 .
    OPTIONAL {
      ?canton rdfs:label ?cantonLabel FILTER ( LANG( ?cantonLabel ) = "en" )
    }
  }
  FILTER NOT EXISTS {
    ?institution wdt:P576 | wdt:P582 ?end .
  }
  FILTER ( ( BOUND( ?municipality ) && ! BOUND( ?canton ) ) || ( ! BOUND( ?municipality ) && BOUND( ?canton ) ) )
}
GROUP BY ?institution ?memobaseID ?streetAddress ?municipality ?municipalityLabel ?canton ?cantonLabel
ORDER BY ?institution

The refined results for institutions located in municipalities or cantons of Switzerland described in Memobase (excluding those where the municipality is within the canton and those that no longer exist) are:

- Aargauer Kunsthaus (wd:Q301250), Memobase ID: kha, types: memory institution, art museum, museum collection; street address: Aargauerplatz 1, 5001 Aarau; municipality: Aarau.

Each institution appears only once, with all types aggregated, and the exclusion logic is clarified and enforced.

[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

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/
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. Use the functions to search for 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. Use the execute function to get feedback on intermediate queries. You can go back and forth between knowledge graph searches and SPARQL query executions to refine the query.
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 assume or make up any entities or properties without verifying them with the knowledge graphs and functions.
3. 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.
4. 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.
5. 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.
6. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
7. 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 institutions located in municipalities or cantons of Switzerland that are described in Memobase? Include their types (if available), street addresses (if available), municipalities (if available), and cantons (if available). Exclude any institutions where the municipality is within the canton, as well as institutions that no longer exist. Order results by item ID.

[Assistant]
Let's break down the question:

1. **Entities:** We are looking for "institutions" (likely organizations or buildings) that are:
   - Located in municipalities or cantons of Switzerland.
   - Described in Memobase (likely a property or external identifier).
   - Still existing (not dissolved or defunct).
2. **Properties:** We need to retrieve:
   - Institution type (if available).
   - Street address (if available).
   - Municipality (if available).
   - Canton (if available).
3. **Exclusions:**
   - Exclude institutions where the municipality is within the canton (so, only those located in a municipality OR a canton, but not both, or where the municipality is not within the canton).
   - Exclude institutions that no longer exist.
4. **Ordering:** By item ID.

First, I need to identify:
- The entity for "institution".
- The property for "described in Memobase".
- The properties for location (municipality, canton), type, street address, and existence status.

Let's start by searching for "Memobase" to find the relevant property.

[Tool]
Top 10 property alternatives:
1. Memobase ID, also known as Memobase identifier, Memobase Object ID (wd:P9657 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): identifier in the Memobase database of Swiss audiovisual heritage
2. base Mémoire reference (wd:P3480 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): reference in the base Mémoire for a French iconographic heritage element
3. criterion used, also known as reason for distinction, with respect to, with reference to, respectively to, on the basis of (wd:P1013 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): property by which a distinction or classification is made
4. radix, also known as base (wd:P3264 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): number of distinct digits in a positional numeral system
5. base (wd:P3263 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): configuration of a polytop vertices around the symmetry axis
6. US Congress Bio ID, also known as Biographical Directory of the United States Congress identifier, bioguide.congress.gov, Bioguide US Congress, congbio, US Congress Bio ID (wd:P1157 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): identifier for a person on the Biographical Directory of the United States Congress
7. applicable 'stated in' value, also known as stated in value, 'stated in' value, stated in database, corresponding P248 value, applicable stated in value (wd:P9073 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): value suitable for "stated in" (P248) when property is used in r...rimary publication/website/database associated with the property
8. documentation files at, also known as clipping files at, documentary records at, documentary records held at, documentary records held by, documentation at (wd:P10527 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): institution that holds documentation files about the subject
9. Freebase ID, also known as Freebase, MID, Freebase identifier, FID (wd:P646 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): identifier for a page in the Freebase database. Format: "/m/0" f...r IDs starting with "/g/", use Google Knowledge Graph ID (P2671)
10. Wine AppDB ID, also known as Wine AppDB-ID, Wine AppDB identifier, AppDB (wd:P600 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): identifier for an application in the AppDB of WineHQ

[Assistant]
The relevant property for "described in Memobase" is likely "Memobase ID" (wd:P9657), which is an identifier in the Memobase database of Swiss audiovisual heritage.

Next, I need to identify:
- The entity or class for "institution".
- The properties for location (municipality, canton), type, street address, and existence status.

I'll search for the entity "institution" to find the relevant class or classes.

[Tool]
Top 10 entity alternatives:
1. organization, also known as organizations, organization in sociology, organisation, institution, organisations (wd:Q43229): social entity established to meet needs or pursue goals
2. institution, also known as social institution, social institutions (wd:Q178706): structure or mechanism of social order and cooperation governing the behaviour of a set of individuals within a given community
3. institution (wd:Q3917196): non-profit organization founded for managerial, socio-cultural or other functions, either by state, municipality or private party
4. Institution (wd:Q6041045): notion in computer science
5. Institution (wd:Q59507540): painting by Christopher Pratt
6. institution (wd:L25381-S1)
7. institution (wd:L641275-S1)
8. institution (wd:L1374974-S1)
9. institution (wd:L1359751-S1)
10. institution (wd:L1147-F1)

[Assistant]
There are several relevant entities:
- "organization" (wd:Q43229): general, includes institutions.
- "institution" (wd:Q178706): social institution, more abstract.
- "institution" (wd:Q3917196): non-profit organization founded for managerial, socio-cultural or other functions, either by state, municipality or private party.

For our purposes, wd:Q3917196 seems most appropriate, as it refers to actual organizations/institutions, not just the abstract concept.

Next, I need to find properties for:
- Location (municipality, canton)
- Type
- Street address
- Existence status (to filter out dissolved/defunct institutions)

I'll search for properties related to "location" for institutions.

[Tool]
Top 10 property alternatives:
1. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as p/wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
2. subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as p/wdt): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain
3. topic's main category, also known as article's main category, category, category for this topic, catmain, has category (wd:P910 as p/wdt): main Wikimedia category
4. Google Knowledge Graph ID, also known as MREID, Google Knowledge Panel ID, Google knowledge panel, kgmid (wd:P2671 as wdt/p/wdtn): identifier for Google Knowledge Graph API, starting with "/g/". For IDs starting with "/m/", use Freebase ID (P646)

No other items found

[Tool]
Top 10 property alternatives:
1. located in the administrative territorial entity, also known as is in the settlement of, is in the voivodeship of, is in the shire of, is in the state of, is in the territory of (wd:P131 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): the item is located on the territory of the following administra...if the item falls only partially into the administrative entity., location, part of
2. contains the administrative territorial entity, also known as has shires, has rural cities, has regions, has municipalities, has members (wd:P150 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): (list of) direct subdivisions of an administrative territorial entity, has part(s)
3. LAU, also known as local administrative unit (wd:P782 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): identifier for a local administrative unit, renamed from NUTS 4 and NUTS 5. Format: 2 letters followed by digits
4. location, also known as neighbourhood, whereabouts, vilage, venue, town (wd:P276 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): location of the object, structure or event. In the case of an ad...ity use P706. Use P7153 for locations associated with the object
5. associated cadastral district, also known as cadastral community, cadastral district, cadastral districts, cadastral municipality, Katastralgemeinde (wd:P10254 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): cadastral district in which a place is located or is part of. Us...inct from administrative entities (P131) in predefined countries
6. capital, also known as administrative seat, seat of government, seat, principal place, location of capital (wd:P36 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): seat of government of a country, province, state or other type of administrative territorial entity
7. legislative body, also known as aboriginal council, Zila, Tehsil, rural council, representative body (wd:P194 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): legislative body governing this entity; political institution wi...ted representatives, such as a parliament/legislature or council
8. German municipality key, also known as Gemeindeschlüssel, municipality key (Germany) (wd:P439 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): identifier for municipalities and independent towns in Germany
9. head of government, also known as head of national government, mayor, premier, president, prime minister (wd:P6 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): head of the executive power of this town, city, municipality, state, country, or other governmental body, director / manager, chairperson
10. capital of, also known as national capital of, parish seat of, provincial capital of, seat of, state capital (wd:P1376 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): country, state, department, canton or other administrative division of which the municipality is the governmental seat, located in the administrative territorial entity

[Assistant]
The property "located in the administrative territorial entity" (wd:P131) is used to specify the administrative unit (such as municipality or canton) where an institution is located.

Now, let's search for properties for "type", "street address", and "existence status" (to filter out dissolved/defunct institutions).

I'll start by searching for "type".

[Tool]
Top 10 property alternatives:
1. class, also known as type (wd:P2308 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): qualifier to define a property constraint in combination with "property constraint" (P2302)
2. taxonomic type, also known as genotype, species typica, type, type genus, type species (wd:P427 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): type genus or species: [in zoology:] nominal genus or species th...t is the name-bearing type of this nominal species or subspecies
3. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
4. script style, also known as handwriting style, type style, style of writing, style of script (wd:P9302 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): style of script of a document or typeface
5. subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain
6. typing discipline, also known as typing, type system (wd:P7078 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): specifies the typing discipline implemented, used, or mandated in a programming language, manifestation of
7. Vox-ATypI classification, also known as font type, typeface variety (wd:P1878 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): classification for typefaces
8. character type, also known as -dere, stock character, stereotype, dere, character stereotype (wd:P9071 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): generic character type that this fictional character represents, manifestation of
9. typeface/font used, also known as is sample of, typeface used, typeface, lettering, font used (wd:P2739 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): style of type used in a work
10. manner of, also known as imitator of, style of (wd:P1777 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): for unknown artists who worked in a similar style as the named author, but not necessary from the same period, significant person

[Assistant]
The property "instance of" (wd:P31) is commonly used to specify the type or class of an entity in Wikidata.

Next, I'll search for "street address".

[Tool]
Top 10 property alternatives:
1. located on street, also known as on street, street address, street, square, road (wd:P669 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): street, road, or square, where the item is located. To add the n...perty P6375 "street address", if there is no item for the street, location, part of
2. street address, also known as postal address, physical address, mailing address, located at street address, full address (wd:P6375 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): full street address where subject is located. Include building n...t country; use also P669 if the street has its own separate item
3. house number, also known as housenumber, street number, house number, address number (wd:P670 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): number in the street address. To be used as a qualifier of Property:P669 "located on street", series ordinal
4. residence, also known as living in, place of residence, resided at, resided in, resident in (wd:P551 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): the place where the person is or has been, resident, location
5. street key, also known as street ID (wd:P1945 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): identification number for a specific street within the street cadastre of a municipality
6. Unique Street Reference Number, also known as street identifier (United Kingdom), USRN (wd:P8447 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): unique 8 digit number assigned to streets, roads, footpaths or public rights of way in the United Kingdom, street key
7. route map, also known as schema, street map, railway map, subway map, transit map (wd:P15 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): image of route map at Wikimedia Commons, locator map image
8. road number, also known as shield number, route number, highway number (wd:P1824 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): number assigned to a stretch of public roadway; omit any prefix or suffix indicated by a road number formatter (P8498), location code
9. post office box, also known as PO Box, Post Office Box, P.O. Box, P. O. Box, P O Box (wd:P2918 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): post office box number, as part of an address
10. Dresden Street ID, also known as street identifier (Dresden) (wd:P8710 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): official identifier for streets in Dresden, Saxony, Germany; format: 5 digits, street key

[Assistant]
The property "street address" (wd:P6375) is the most direct for retrieving the full street address.

Now, I'll search for a property related to "existence status" to filter out institutions that no longer exist (e.g., dissolved, defunct, etc.).

[Tool]
Top 10 property alternatives:
1. end time, also known as ends, stop time, endtime, fall date, ineffective (wd:P582 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): moment when an entity ceases to exist and a statement stops being entirely valid or no longer be true, point in time
2. dissolved, abolished or demolished date, also known as ended, publication end date, final issue, date repealed, final year (wd:P576 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): point in time at which the subject (organisation, building) ceas...g equipment,  "discontinued date" (P2669) for stopping a product, end time
3. merged into, also known as absorbed in, acquired by, annexed to, bought by, dissolved into (wd:P7888 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): the subject was dissolved and merged into the object, that existed previously
4. discharge (wd:P2225 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): volume rate of water flow which is transported through a given cross-sectional area
5. destroyed, also known as ihe anụ ahụ nke ihe omume a mebiri (wd:P3082 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): physical items destroyed by this event
6. announcement date, also known as released, date teased, made public on, public announcement date, published (wd:P6949 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): time of the first public presentation of a subject by the creator, of information by the media, point in time
7. publication date, also known as launched, published, publication time, publication, pubdate (wd:P577 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): date or point in time when a work was first published or released, point in time
8. separated from, also known as branched from, broke from, forked from, schism from, seceded from (wd:P807 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): subject was founded or started by separating from identified object
9. stage reached, also known as eliminated at, point achieved, round reached (wd:P2443 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): ultimate point in an event or competition reached by a participant
10. follows, also known as prev, successor to, succeeds to, succeeds, split from (wd:P155 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): immediately prior item in a series of which the subject is a par... preceding item, e.g. political offices, use "replaces" (P1365)]

[Assistant]
The properties "dissolved, abolished or demolished date" (wd:P576) and "end time" (wd:P582) are both relevant for filtering out institutions that no longer exist. If either is present, the institution should be considered dissolved/defunct.

Now, I need to ensure that the location is in a municipality or canton of Switzerland, and to distinguish between municipality and canton. Let's search for the entities for "municipality of Switzerland" and "canton of Switzerland" to use as filters.

[Tool]
Top 10 entity alternatives:
1. municipality of Switzerland, also known as commune of Switzerland, communes of Switzerland, politische Gemeinde (wd:Q70208): smallest government division in Switzerland
2. municipality of Switzerland (wd:L25865-S1)
3. former municipality of Switzerland (wd:Q685309): type of municipality of Switzerland
4. former municipality of Switzerland (wd:L25883-S1)
5. former municipality of Switzerland (wd:L26070-S1)
6. former municipality of Switzerland in Fribourg (wd:L25882-S1)
7. former municipality of Switzerland in Jura (wd:L26411-S1)
8. former municipality of Switzerland in Neuchâtel (wd:L26818-S1)
9. former municipality of Switzerland in Valais (wd:L25923-S1)
10. former municipality of Switzerland in Valais (wd:L27156-S1)

[Tool]
Top 10 entity alternatives:
1. canton of Switzerland, also known as canton, Canton of Switzerland, Swiss canton (wd:Q23058): administrative divisions of the Swiss Confederation
2. Glarus, also known as Glaris, Glarus (Switzerland), Glarus GL, Glaris Centre, Glarus, Canton of Glarus, Switzerland (wd:Q63912): municipality and capital of the Canton of Glarus in Switzerland
3. Villeneuve, also known as Villeneuve, Canton of Vaud, Switzerland, Villeneuve, Vaud, Villeneuve VD (wd:Q69972): municipality in Switzerland
4. Reinach, also known as Reinach, Basel-Country, Reinach BL, Reinach, Canton of Basel-Land, Switzerland (wd:Q69747): municipality in the canton of Basel-Country, Switzerland
5. Romont, also known as Romont, Canton of Fribourg, Switzerland, Romont FR (wd:Q67103): municipality in the canton of Fribourg, Switzerland
6. Aesch, also known as Aesch, Basel-Country, Aesch, Baselland, Aesch BL, Aesch, Canton of Basel-Land, Switzerland (wd:Q68367): municipality in the canton of Basel-Country, Switzerland
7. Kilchberg, also known as Kilchberg, Canton of Zürich, Switzerland, Kilchberg ZH (wd:Q66633): municipality in the canton of Zürich, Switzerland
8. Ecublens, also known as Ecublens VD, Écublens VD, Ecublens (VD), Écublens, Vaud, Ecublens (Vaud) (wd:Q69716): municipality in the canton of Vaud, Switzerland
9. Oberdorf, also known as Oberdorf, Canton of Basel-Land, Switzerland, Oberdorf BL (wd:Q64821): municipality in the canton Basel-Landschaft, Switzerland
10. Buchs, also known as Buchs AG, Buchs, Canton of Aargau, Switzerland (wd:Q64512): municipality in the canton of Aargau, Switzerland

[Assistant]
The relevant entities are:
- "municipality of Switzerland" (wd:Q70208)
- "canton of Switzerland" (wd:Q23058)

To ensure the location is in Switzerland, we can check that the administrative entity (via P131) is an instance of either of these.

Now, to address the exclusion: "Exclude any institutions where the municipality is within the canton." This means, if both a municipality and a canton are given, and the municipality is located within the canton, exclude that institution.

To summarize, the query will:
- Select institutions (wd:Q3917196) with a Memobase ID (wd:P9657)
- Located in a municipality (P131 → wd:Q70208) or canton (P131 → wd:Q23058) of Switzerland
- Optionally retrieve type (P31), street address (P6375), municipality, and canton
- Exclude institutions with a dissolved/abolished/demolished date (P576) or end time (P582)
- Exclude institutions where the municipality is within the canton
- Order by item ID

Let's draft the SPARQL query.

[Tool] Got no rows and 8 columns

[Assistant]
The query returned no results, which suggests that either the data is sparse, or the constraints are too restrictive. Let's analyze and adjust:

- The main constraints are:
  - Must have Memobase ID (wd:P9657)
  - Must be an institution (wd:Q3917196)
  - Must be located in a municipality (wd:Q70208) or canton (wd:Q23058) of Switzerland
  - Must not be dissolved (no P576 or P582)
  - Exclude cases where both municipality and canton are given and the municipality is within the canton

Possible issues:
- The class wd:Q3917196 might be too restrictive; perhaps institutions are typed as "organization" (wd:Q43229) or another class.
- The location property (P131) might not always point directly to a municipality/canton, but perhaps to a city or other administrative entity.
- The Memobase ID might be attached to organizations of broader types.

Let's try broadening the institution type to "organization" (wd:Q43229) and see if that yields results.

[Tool]
Got 7 rows and 8 columns:
| institution                                   | memobaseID                            | type                             | streetAddress                    | municipality      | municipalityLabel | canton | cantonLabel |
| --------------------------------------------- | ------------------------------------- | -------------------------------- | -------------------------------- | ----------------- | ----------------- | ------ | ----------- |
| Michèle Roten, Miss Universum (wd:Q107134571) | rxb-003-DE3D4EAE6BBA21251422F100F_MPG | radio program (wd:Q1555508)      |                                  |                   |                   |        |             |
| Aargauer Kunsthaus (wd:Q301250)               | kha                                   | memory institution (wd:Q1497649) | Aargauerplatz 1, 5001 Aarau (de) | Aarau (wd:Q14274) | Aarau (en)        |        |             |
| Aargauer Kunsthaus (wd:Q301250)               | kha                                   | art museum (wd:Q207694)          | Aargauerplatz 1, 5001 Aarau (de) | Aarau (wd:Q14274) | Aarau (en)        |        |             |
| Aargauer Kunsthaus (wd:Q301250)               | kha                                   | museum collection (wd:Q27699276) | Aargauerplatz 1, 5001 Aarau (de) | Aarau (wd:Q14274) | Aarau (en)        |        |             |
| Aargauer Kunsthaus (wd:Q301250)               | kha                                   | memory institution (wd:Q1497649) | Aargauerplatz 1, 5001 Aarau (de) | Aarau (wd:Q14274) | Aarau (en)        |        |             |
| Aargauer Kunsthaus (wd:Q301250)               | kha                                   | art museum (wd:Q207694)          | Aargauerplatz 1, 5001 Aarau (de) | Aarau (wd:Q14274) | Aarau (en)        |        |             |
| Aargauer Kunsthaus (wd:Q301250)               | kha                                   | museum collection (wd:Q27699276) | Aargauerplatz 1, 5001 Aarau (de) | Aarau (wd:Q14274) | Aarau (en)        |        |             |

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The SPARQL query is mostly correct and returns relevant institutions described in Memobase, including their types, street addresses, municipalities, and cantons. However, there are some issues that need refinement:

1. Duplicate Rows: The result contains duplicate rows for Aargauer Kunsthaus with the same type. This is likely due to multiple OPTIONAL clauses and should be deduplicated using SELECT DISTINCT or GROUP BY.
2. Exclusion Logic: The exclusion of institutions where the municipality is within the canton is not entirely clear in the FILTER NOT EXISTS clause. It should be clarified and tested to ensure that only institutions located directly in a canton (not in a municipality within that canton) are included, and vice versa.
3. Label Retrieval: The use of rdfs:label for municipalityLabel and cantonLabel is correct, but the query should ensure that labels are only retrieved if available and not required for the main result.
4. ASK queries are not relevant here, but the query correctly returns IRIs as required.

Suggested improvements:
- Use SELECT DISTINCT to remove duplicate rows.
- Double-check the FILTER NOT EXISTS logic for municipality/canton relationships to ensure correct exclusion.
- Optionally, use GROUP BY if you want to aggregate types or addresses per institution.

Overall, the query is close to correct but needs refinement for deduplication and exclusion logic.

[Assistant]
Thank you for the detailed feedback. Here’s how I’ll refine the query:

1. **Deduplication:** I will use SELECT DISTINCT to remove duplicate rows.
2. **Exclusion Logic:** I will clarify and enforce the exclusion so that:
   - Institutions located in both a municipality and a canton are only included if the municipality is NOT within the canton.
   - Institutions located directly in a municipality (with no canton) or directly in a canton (with no municipality) are included.
   - This will be achieved by:
     - Including institutions with only a municipality (no canton).
     - Including institutions with only a canton (no municipality).
     - Excluding institutions where both are present and the municipality is within the canton.
3. **Label Retrieval:** Labels will remain OPTIONAL.

Let’s implement these improvements in the query.

[Tool]
Got 3 rows and 8 columns:
| institution                     | memobaseID | type                             | streetAddress                    | municipality      | municipalityLabel | canton | cantonLabel |
| ------------------------------- | ---------- | -------------------------------- | -------------------------------- | ----------------- | ----------------- | ------ | ----------- |
| Aargauer Kunsthaus (wd:Q301250) | kha        | memory institution (wd:Q1497649) | Aargauerplatz 1, 5001 Aarau (de) | Aarau (wd:Q14274) | Aarau (en)        |        |             |
| Aargauer Kunsthaus (wd:Q301250) | kha        | art museum (wd:Q207694)          | Aargauerplatz 1, 5001 Aarau (de) | Aarau (wd:Q14274) | Aarau (en)        |        |             |
| Aargauer Kunsthaus (wd:Q301250) | kha        | museum collection (wd:Q27699276) | Aargauerplatz 1, 5001 Aarau (de) | Aarau (wd:Q14274) | Aarau (en)        |        |             |

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The SPARQL query is mostly correct and follows the requirements well, but there are a few issues to refine:

1. The query currently returns multiple rows for the same institution due to multiple types. To avoid duplicate rows for the same institution, consider grouping types into a list using GROUP_CONCAT or similar SPARQL aggregation, unless the user explicitly wants one row per type.
2. The query does not strictly ensure that the institution is located in either a municipality or a canton, but not both. The logic in the FILTER clause is complex and may not fully exclude cases where both are present. Consider simplifying and clarifying the logic to ensure only institutions located in either a municipality or a canton (but not both) are included.
3. The query does not explicitly exclude institutions where the municipality is within the canton, but the user wants to exclude those. The current FILTER NOT EXISTS block attempts this, but double-check that it works as intended for all cases.
4. The query returns labels within OPTIONALs, which is good, but make sure all labels are always within OPTIONALs.

Overall, the query is close, but a bit of refinement is needed for deduplication and clarity of the exclusion logic.

[Assistant]
Thank you for the feedback. Here’s how I’ll address the issues:

1. **Deduplication:** I will use GROUP_CONCAT to aggregate all types for each institution into a single row, so each institution appears only once.
2. **Exclusion Logic:** I will simplify the logic so that only institutions located in either a municipality or a canton (but not both) are included. This means:
   - Include institutions with a municipality and no canton.
   - Include institutions with a canton and no municipality.
   - Exclude institutions with both a municipality and a canton.
3. **Municipality-in-Canton Exclusion:** Since we are now excluding all institutions with both a municipality and a canton, the case where the municipality is within the canton is automatically excluded.
4. **Labels:** All labels will remain within OPTIONALs.

Let’s implement these refinements in the query.

[Tool]
Got 1 row and 8 columns:
| institution                     | memobaseID | types                                                               | streetAddress                    | municipality      | municipalityLabel | canton | cantonLabel |
| ------------------------------- | ---------- | ------------------------------------------------------------------- | -------------------------------- | ----------------- | ----------------- | ------ | ----------- |
| Aargauer Kunsthaus (wd:Q301250) | kha        | http://www.wikidata.org/entity/Q...ww.wikidata.org/entity/Q27699276 | Aargauerplatz 1, 5001 Aarau (de) | Aarau (wd:Q14274) | Aarau (en)        |        |             |

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT DISTINCT ?language ?languageLabel WHERE {
  ?wiki_edition wdt:P31 wd:Q10876391 ; wdt:P407 ?language .
  FILTER ( ?language != wd:Q1860 ) ?language wdt:P1098 ?speakers .
  FILTER ( ?speakers > 3000000 ) ?language wdt:P31 wd:Q34770 .
  OPTIONAL {
    ?language rdfs:label ?languageLabel FILTER ( LANG( ?languageLabel ) = "en" )
  }
}
ORDER BY ?languageLabel

Got 57 rows and 2 columns, showing the first 5 and last 5 rows below:
| language               | languageLabel  |
| ---------------------- | -------------- |
| Acehnese (wd:Q27683)   | Acehnese (en)  |
| Akan (wd:Q28026)       | Akan (en)      |
| Alemannic (wd:Q131339) | Alemannic (en) |
| Awadhi (wd:Q29579)     | Awadhi (en)    |
| Bambara (wd:Q33243)    | Bambara (en)   |
| ...                    | ...            |
| Tok Pisin (wd:Q34159)  | Tok Pisin (en) |
| Tsonga (wd:Q34327)     | Tsonga (en)    |
| Tswana (wd:Q34137)     | Tswana (en)    |
| Waray (wd:Q34279)      | Waray (en)     |
| Zulu (wd:Q10179)       | Zulu (en)      |

This query returns all human languages (excluding English) that have a Wikipedia language edition and more than 3,000,000 speakers. The result includes the Wikidata IRIs for each language and their English labels (if available).

[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

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/
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. Use the functions to search for 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. Use the execute function to get feedback on intermediate queries. You can go back and forth between knowledge graph searches and SPARQL query executions to refine the query.
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 assume or make up any entities or properties without verifying them with the knowledge graphs and functions.
3. 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.
4. 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.
5. 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.
6. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
7. 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 languages, other than English, that have a Wikipedia language edition and more than 3,000,000 speakers?

[Assistant]
Let's break down the question:

1. We need to find languages that have a Wikipedia language edition. Wikidata has items for Wikipedia language editions, and these are linked to the language they represent.
2. We need to exclude English.
3. We need to find the number of speakers for each language and filter for those with more than 3,000,000 speakers.

Step 1: Find the property that links a Wikipedia language edition to its language.
Step 2: Find the property for the number of speakers of a language.
Step 3: Exclude English.
Step 4: Combine these to get the desired list.

First, let's search for the property that links a Wikipedia language edition to its language.

[Tool]
Top 10 property alternatives:
1. spoken text audio, also known as audio description, spoken Wikipedia, spoken Wikipedia text audio, Wikipedia audio, Wikipedia spoken text audio (wd:P989 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): audio file for the spoken work or Wikipedia article, including audio descriptions, audio
2. language used, also known as languages used, medium of instruction, used language, uses language, working language (wd:P2936 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): language widely used (spoken or written) in this place or at this event or organisation
3. languages spoken, written or signed, also known as language of expression, language, wrote language, writes language, uses language (wd:P1412 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): language(s) that a person or a people speaks, writes or signs, including the native language(s)
4. language of work or name, also known as language of the reference, language of URL, language of website, language of work, named in language (wd:P407 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): language associated with this creative work (such as books, show...guage" (P103) and "languages spoken, written or signed" (P1412))
5. programmed in, also known as language, programming language, written in (wd:P277 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): the programming language(s) in which the software is developed
6. Wikilengua article (wd:P8257 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): name of an article on Wikilengua wiki
7. Wikidata language code, also known as Wikidata language identifier, Wikidata language ID, Wikidata language codes, term language code, termbox language code (wd:P9753 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): identifier for a language or variant at Wikidata (use P424 (Wikimedia language code) to identify the language of a Wikimedia wiki), Wikimedia language code
8. has edition or translation, also known as version, translation(s), released as, modified as, has version (wd:P747 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): item that is an edition or translation of this item
9. official language, also known as language spoken, spoken in, speaking, language official (wd:P37 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): language designated as official by this item, language used
10. writing language, also known as languages of writings, languages written, language written, writing languages, language of works (wd:P6886 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): language in which the writer has written their work, languages spoken, written or signed

[Assistant]
From the search, the most relevant property for linking a Wikipedia language edition to its language is likely "language of work or name" (wd:P407), which is used for creative works and websites.

Next, let's search for the property that gives the number of speakers for a language.

[Tool]
Top 10 property alternatives:
1. number of speakers, writers, or signers, also known as signers of a language, speakers of language, writers of a language (wd:P1098 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): number of people who use a language
2. number of viewers/listeners, also known as plays, watches, watch count, views, view number (wd:P5436 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): number of viewers of a television or broadcasting program; web traffic on websites
3. number of words, also known as word count, words (number of) (wd:P6570 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): number of words in text
4. official language, also known as language spoken, spoken in, speaking, language official (wd:P37 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): language designated as official by this item, language used
5. speaker, also known as speech by, spoken by (wd:P823 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): person who is speaker for this event, ceremony, keynote, presentation or in a literary work, participant, spoken by
6. spoken by, also known as speaker (wd:P10894 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): the person who is speaking in this audio or video file
7. number of aid beneficiaries, also known as number of aid recipients, number of beneficiaries, number of people reached, people reached (wd:P9077 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): number of people reached with international aid programmes, acti...ctivities. Qualify with "point in time" (P585) where appropriate
8. intended public, also known as for, user group, target market, target group, target demographic (wd:P2360 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): this work, product, object or event is intended for, or has been designed to that person or group of people, animals, plants, etc
9. number of registered users/contributors, also known as number of contributors, number of registered users, number of users, users (wd:P1833 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): number of registered users on a website
10. member count, also known as total members, number of members, count of members, amount of members, membership (wd:P2124 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): number of entities that are part of an organization at a particular time

[Assistant]
The property "number of speakers, writers, or signers" (wd:P1098) is the correct one for the number of speakers of a language.

Now, let's identify how Wikipedia language editions are represented in Wikidata. Usually, each edition is an item (e.g., "English Wikipedia" is wd:Q328), and these are instances of "Wikimedia project" or "Wikipedia".

Let's search for the entity representing "Wikipedia" as a project to find its subclasses or instances.

[Tool]
Top 10 entity alternatives:
1. Wikipedia, also known as Wikipedia, the free encyclopedia, The Free Encyclopedia, Wikipedia, the free encyclopedia that anyone can edit, WP, Wikipaedia (wd:Q52): free multilingual online encyclopedia
2. Wikipedia, also known as WP, Wikipedia, the free encyclopedia that anyone can edit, Wikipaedia, Wikipedia, the free encyclopedia, The Free Encyclopedia (wd:Q52): free multilingual online encyclopedia
3. Wikipedia, also known as Wikipedia Android app (wd:Q4390943): Wikimedia's official app for Wikipedia
4. Wikipedia (wd:Q3890886): Wikimedia permanent duplicate item
5. Sylheti Wikipedia, also known as Wp/syl, Wikipedia Sylheti, Wikipedia (Sylheti), Wikipedia, SYLWP (wd:Q118646488): Sylheti-language edition of Wikipedia
6. Wikipedia:Chinese Wikipedia (wd:Q133054809)
7. Arco de la Federación, also known as Wikipedia (wd:Q35163184): Buenísima
8. Cruz de San Clemente, also known as Wikipedia (wd:Q43585281): Bien
9. Wikipedia (wd:Q42495628): 2017 single by Hanan Ben Ari
10. @Wikipedia, also known as @wikipedia@wikis.world (wd:Q125203171)

[Assistant]
The main entity for Wikipedia as a project is wd:Q52. Language editions like "English Wikipedia" are separate items and are instances of "Wikimedia project" or "Wikipedia edition".

Let's check what class "English Wikipedia" (wd:Q328) is an instance of, to find the right class for all Wikipedia language editions.

[Tool]
Got 959 rows and 3 columns, showing the first 10 rows below:
| subject                     | property                            | object                                                                                |
| --------------------------- | ----------------------------------- | ----------------------------------------------------------------------------------------- |
| English Wikipedia (wd:Q328) | instance of (wdt:P31)               | Wikipedia language edition (wd:Q10876391)                                                 |
| English Wikipedia (wd:Q328) | title (wdt:P1476)                   | Wikipedia (en)                                                                            |
| English Wikipedia (wd:Q328) | author (wdt:P50)                    | English Wikipedia community (wd:Q112669601)                                               |
| English Wikipedia (wd:Q328) | language of work or name (wdt:P407) | English (wd:Q1860)                                                                        |
| English Wikipedia (wd:Q328) | Commons category (wdt:P373)         | English Wikipedia                                                                         |
| English Wikipedia (wd:Q328) | image (wdt:P18)                     | <http://commons.wikimedia.org/wiki/Special:FilePath/English%20Wikipedia%20screenshot.png> |
| English Wikipedia (wd:Q328) | copyright status (wdt:P6216)        | copyrighted (wd:Q50423863)                                                                |
| English Wikipedia (wd:Q328) | inception (wdt:P571)                | 2001-01-15T00:00:00Z (xsd:dateTime)                                                       |
| English Wikipedia (wd:Q328) | has part(s) (wdt:P527)              | English Wikipedia article (wd:Q105770631)                                                 |
| English Wikipedia (wd:Q328) | copyright license (wdt:P275)        | Creative Commons Attribution-ShareAlike 3.0 Unported (wd:Q14946043)                       |
| ...                         | ...                                 | ...                                                                                |

[Assistant]
"English Wikipedia" (wd:Q328) is an instance of "Wikipedia language edition" (wd:Q10876391). So, all Wikipedia language editions are instances of wd:Q10876391.

Now, let's summarize the plan for the SPARQL query:

- Find all items that are instances of wd:Q10876391 (Wikipedia language edition).
- For each, get the language (wdt:P407).
- Exclude English (wd:Q1860).
- For each language, get the number of speakers (wdt:P1098).
- Filter for languages with more than 3,000,000 speakers.
- Return the language IRI and optionally its label.

Let's write and execute a query to check if this works as expected.

[Tool]
Got 151 rows and 1 column, showing the first 5 and last 5 rows below:
| language                  |
| ------------------------- |
| Zulu (wd:Q10179)          |
| Alemannic (wd:Q131339)    |
| Romani (wd:Q13201)        |
| Spanish (wd:Q1321)        |
| Zhuang (wd:Q13216)        |
| ...                       |
| Azerbaijani (wd:Q9292)    |
| Serbian (wd:Q9299)        |
| Serbo-Croatian (wd:Q9301) |
| Bosnian (wd:Q9303)        |
| Bangla (wd:Q9610)         |

[Tool]
Got 151 rows and 2 columns, showing the first 5 and last 5 rows below:
| language               | languageLabel   |
| ---------------------- | --------------- |
| Acehnese (wd:Q27683)   | Acehnese (en)   |
| Afrikaans (wd:Q14196)  | Afrikaans (en)  |
| Akan (wd:Q28026)       | Akan (en)       |
| Albanian (wd:Q8748)    | Albanian (en)   |
| Alemannic (wd:Q131339) | Alemannic (en)  |
| ...                    | ...             |
| Wu Chinese (wd:Q34290) | Wu Chinese (en) |
| Xhosa (wd:Q13218)      | Xhosa (en)      |
| Yoruba (wd:Q34311)     | Yoruba (en)     |
| Zhuang (wd:Q13216)     | Zhuang (en)     |
| Zulu (wd:Q10179)       | Zulu (en)       |

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The query is mostly correct, but it could be improved for clarity and completeness. Specifically:

1. The query should ensure that the Wikipedia edition is an actual Wikipedia language edition (wd:Q10876391) and not another Wikimedia project. The current query does this correctly.
2. The query excludes English (wd:Q1860), which is correct.
3. The query uses the number of speakers (wd:P1098), which is appropriate.
4. However, the query does not ensure that the language is a human language (instance of wd:Q34770), which would filter out constructed or non-human languages if any are present.
5. The query does not return labels, but since the question did not explicitly request them, this is acceptable.

Suggestion: Add an OPTIONAL clause for rdfs:label if labels are desired, and consider filtering for human languages for more precise results.

[Assistant]
Thank you for the feedback. To refine the query for clarity and completeness:

- I will ensure that the language is a human language (instance of wd:Q34770).
- I will add an OPTIONAL clause to return the English label for each language, for easier interpretation (but keep it optional, as labels were not explicitly requested).

Here is the improved SPARQL query:

```sparql
SELECT DISTINCT ?language ?languageLabel WHERE {
  ?wiki_edition wdt:P31 wd:Q10876391 ;
                wdt:P407 ?language .
  FILTER(?language != wd:Q1860)
  ?language wdt:P1098 ?speakers .
  FILTER(?speakers > 3000000)
  ?language wdt:P31 wd:Q34770 .
  OPTIONAL { ?language rdfs:label ?languageLabel FILTER(LANG(?languageLabel) = "en") }
}
ORDER BY ?languageLabel
```

This query ensures that only human languages are included, excludes English, and provides optional English labels for clarity. I will now submit this as the final answer.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves all human languages (excluding English) that have a Wikipedia language edition and more than 3,000,000 speakers. It returns the required IRIs and optionally their English labels, as requested. The use of filters and the structure of the query are appropriate for the question. No further refinement is needed.