PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?item ?line ?itemLabel ?lineLabel WHERE {
  ?item wdt:P81 ?line .
  ?line wdt:P31 wd:Q15079663 .
  FILTER NOT EXISTS {
    ?item wdt:P31 / wdt:P279 * wd:Q928830
  }
  FILTER NOT EXISTS {
    ?item wdt:P31 / wdt:P279 * wd:Q2175765
  }
  FILTER NOT EXISTS {
    ?item wdt:P31 / wdt:P279 * wd:Q63125083
  }
  OPTIONAL {
    ?item rdfs:label ?itemLabel FILTER ( LANG( ?itemLabel ) = "en" )
  }
  OPTIONAL {
    ?line rdfs:label ?lineLabel FILTER ( LANG( ?lineLabel ) = "en" )
  }
}
LIMIT 50

Got 50 rows and 4 columns, showing the first 5 and last 5 rows below:
| item                                                   | line                                         | itemLabel                                    | lineLabel                          |
| ------------------------------------------------------ | -------------------------------------------- | -------------------------------------------- | ---------------------------------- |
| wd:Q111738574                                          | Line 1 of the Salvador subway (wd:Q10318644) |                                              | Line 1 of the Salvador subway (en) |
| Nazarbekian (wd:Q2060834)                              | Line 1 (Yerevan Metro) (wd:Q10318696)        | Nazarbekian (en)                             | Line 1 (Yerevan Metro) (en)        |
| wd:Q19614659                                           | Line 1 (Yerevan Metro) (wd:Q10318696)        |                                              | Line 1 (Yerevan Metro) (en)        |
| Tuqiao depot (wd:Q10927801)                            | Batong line (wd:Q1039452)                    | Tuqiao depot (en)                            | Batong line (en)                   |
| Amara-Donostia train station (wd:Q12253308)            | Euskotren line E5 (wd:Q104233835)            | Amara-Donostia train station (en)            | Euskotren line E5 (en)             |
| ...                                                    | ...                                          | ...                                          | ...                                |
| PWTC LRT station (wd:Q4383723)                         | Sri Petaling line (wd:Q113297920)            | PWTC LRT station (en)                        | Sri Petaling line (en)             |
| Hang Tuah station (wd:Q27142)                          | Sri Petaling line (wd:Q113297920)            | Hang Tuah station (en)                       | Sri Petaling line (en)             |
| Sentul LRT station (wd:Q27140)                         | Sri Petaling line (wd:Q113297920)            | Sentul LRT station (en)                      | Sri Petaling line (en)             |
| Awan Besar LRT station (wd:Q21005945)                  | Sri Petaling line (wd:Q113297920)            | Awan Besar LRT station (en)                  | Sri Petaling line (en)             |
| Taman Perindustrian Puchong LRT station (wd:Q22674240) | Sri Petaling line (wd:Q113297920)            | Taman Perindustrian Puchong LRT station (en) | Sri Petaling line (en)             |

This refined query excludes all items that are instances (directly or indirectly) of 'metro station', 'tram stop' (including light rail stops), or 'monorail station'. For example, it returns:
- Nazarbekian (wd:Q2060834) with Line 1 (Yerevan Metro) (wd:Q10318696)
- Tuqiao depot (wd:Q10927801) with Batong line (wd:Q1039452)
- Amara-Donostia train station (wd:Q12253308) with Euskotren line E5 (wd:Q104233835)

The full query returns more such items and their connecting rapid transit railway lines, robustly excluding all major rapid transit station types.

[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 items that are not metro stations, but have a connecting line which is a rapid transit railway line? For each such item, return also the connecting line in your results.

[Assistant]
Let's break down the question:

1. We are looking for items that are not metro stations.
2. These items have a "connecting line".
3. The connecting line is a "rapid transit railway line".

First, I need to identify:
- The entity for "metro station".
- The property for "connecting line".
- The entity for "rapid transit railway line".

Let's start by searching for the entity "metro station".

[Tool]
Top 10 entity alternatives:
1. metro station, also known as metro stop, rapid transit station, rapid transit stop, subway station, subway stop (wd:Q928830): railway station of a rapid transit system
2. Metro Station (wd:Q864991): American pop rock band
3. Metro Station (wd:Q2570790): 2007 self-titled debut studio album by Metro Station
4. Athens Metro station, also known as metro station (wd:Q115792670): station served by the Athens Metro
5. Metro station (wd:Q103957766): encyclopedia article
6. Thessaloniki Metro station, also known as metro station (wd:Q133240803): station served by the Thessaloniki Metro
7. public transport stop, also known as transport stop nearby, metro station, transport station nearby, subway station, stop nearby (wd:P8453): general (e.g. nearest) public transport stop (bus, tram, train, subway)
8. metro station (wd:L427448-S1)
9. Town Hall, also known as Paris Metro station, Town Hall (wd:Q968939): Paris Metro station
10. Maelbeek/Maalbeek metro station (wd:Q2206139): metro station in Brussels, Belgium

[Assistant]
The main entity for "metro station" is wd:Q928830.

Next, I need to find the property for "connecting line". I'll search for "connecting line" as a property.

[Tool]
Top 10 property alternatives:
1. connecting line, also known as is on, railway line, rail line connected to, line connected to (wd:P81 as pq/prn/pqn/ps/p/wdt/psv/pr/wdtn/psn/prv/pqv): railway line(s) subject is directly connected to, part of
2. connecting service, also known as halt of, stop of (wd:P1192 as pq/prn/pqn/ps/p/wdt/psv/pr/wdtn/psn/prv/pqv): service stopping at a station
3. connector, also known as ports, electrical connector, port, has connector (wd:P2935 as pq/prn/pqn/ps/p/wdt/psv/pr/wdtn/psn/prv/pqv): connectors which the device has/supports, uses
4. connects with, also known as contacts, couples with, intersects at grade, links to, mates with (wd:P2789 as pq/prn/pqn/ps/p/wdt/psv/pr/wdtn/psn/prv/pqv): item with which the item is physically connected, physically interacts with
5. line(s), also known as line, lines, verse, verse(s), verses (wd:P7421 as pq/prn/pqn/ps/p/wdt/psv/pr/wdtn/psn/prv/pqv): line number(s) of reference for claim
6. route number, also known as line number, public transport line number (wd:P1671 as pq/prn/pqn/ps/p/wdt/psv/pr/wdtn/psn/prv/pqv): number of a rail or other public transport line, location code
7. last line, also known as closing line, ending, excipit, final line, final sentence (wd:P3132 as pq/prn/pqn/ps/p/wdt/psv/pr/wdtn/psn/prv/pqv): last line (excipit) of a poem, last sentence of a novel, etc.
8. electrical plug type, also known as electrical connector type, socket type, plug type, mains socket type, mains plug type (wd:P2853 as pq/prn/pqn/ps/p/wdt/psv/pr/wdtn/psn/prv/pqv): standard plug type for mains electricity in a country
9. applies to part, also known as when viewed as, valid for part, section, region, per (wd:P518 as pq/prn/pqn/ps/p/wdt/psv/pr/wdtn/psn/prv/pqv): part, aspect, or form of the item to which the claim applies
10. author name string, also known as short author name, writer named as, writer name, writer indicated as, songwriting credits string (wd:P2093 as pq/prn/pqn/ps/p/wdt/psv/pr/wdtn/psn/prv/pqv): stores unspecified author or editor name for publications; use i...or editor (P98) does not exist or is not known. Do not use both.

[Assistant]
The property "connecting line" is wd:P81.

Now, I need to find the entity for "rapid transit railway line". I'll search for this entity next.

[Tool]
Top 10 entity alternatives:
1. rapid transit railway line, also known as metro line, subway line, subway service, underground line (wd:Q15079663): type of railway line
2. automated rapid transit railway line, also known as driverless underground line, driverless subway line, automated subway service, driverless metro line, automated subway line (wd:Q107343049): railway line that doesn't need a driver
3. Cincinnati Subway, also known as Cincinnati Rapid Transit Railway (wd:Q1046992): incomplete city subway system
4. Kobe Rapid Transit Railway, also known as Kōbe Rapid Transit Railway (wd:Q847533): Japanese railway company
5. Saitama Rapid Railway Line, also known as Saitama Stadium Line (wd:Q1065949): railway line in Japan
6. Tōyō Rapid Railway Line, also known as Tōyō Rapid Line (wd:Q843148): railway line in Japan
7. Semboku Rapid Railway Line (wd:Q2758012): railway line in Japan
8. Syracuse Rapid Transit Railway (wd:Q7663055)
9. MRT Purple Line, also known as Metropolitan Rapid Transit Purple Line (wd:Q6584549): second line of Bangkok's underground metro system.
10. Nara Ikoma Rapid Transit Railway, also known as Nara Ikoma Rapid Railway Co., Ltd. (wd:Q10942268)

[Assistant]
The general entity for "rapid transit railway line" is wd:Q15079663.

Now, to summarize:
- Exclude items that are instances of "metro station" (wd:Q928830).
- Find items that have a "connecting line" (wd:P81).
- The connecting line should be an instance of "rapid transit railway line" (wd:Q15079663).

Let's construct a SPARQL query that finds items (?item) that are NOT instances of metro stations, but have a connecting line (?line) which is an instance of rapid transit railway line.

I'll also include optional labels for readability.

[Tool]
Got 50 rows and 4 columns, showing the first 5 and last 5 rows below:
| item                                               | line                                         | itemLabel                               | lineLabel                          |
| -------------------------------------------------- | -------------------------------------------- | --------------------------------------- | ---------------------------------- |
| wd:Q111738574                                      | Line 1 of the Salvador subway (wd:Q10318644) |                                         | Line 1 of the Salvador subway (en) |
| wd:Q19614659                                       | Line 1 (Yerevan Metro) (wd:Q10318696)        |                                         | Line 1 (Yerevan Metro) (en)        |
| Nazarbekian (wd:Q2060834)                          | Line 1 (Yerevan Metro) (wd:Q10318696)        | Nazarbekian (en)                        | Line 1 (Yerevan Metro) (en)        |
| Fukuoka City Subway Hakata Station (wd:Q124368779) | Nanakuma Line (wd:Q1039166)                  | Fukuoka City Subway Hakata Station (en) | Nanakuma Line (en)                 |
| Tuqiao depot (wd:Q10927801)                        | Batong line (wd:Q1039452)                    | Tuqiao depot (en)                       | Batong line (en)                   |
| ...                                                | ...                                          | ...                                     | ...                                |
| Meiji-Jingūmae Station (wd:Q80429)                 | Chiyoda Line (wd:Q1075089)                   | Meiji-Jingūmae Station (en)             | Chiyoda Line (en)                  |
| Shin-Ochanomizu Station (wd:Q80433)                | Chiyoda Line (wd:Q1075089)                   | Shin-Ochanomizu Station (en)            | Chiyoda Line (en)                  |
| Kamiiida Station (wd:Q6357803)                     | Kamiiida Line (wd:Q1078347)                  | Kamiiida Station (en)                   | Kamiiida Line (en)                 |
| Heian-dōri Station (wd:Q853241)                    | Kamiiida Line (wd:Q1078347)                  | Heian-dōri Station (en)                 | Kamiiida Line (en)                 |
| Sanshanxinchengnan station (wd:Q110994058)         | Foshan Metro Line 4 (wd:Q10886734)           | Sanshanxinchengnan station (en)         | Foshan Metro Line 4 (en)           |

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The query is mostly correct and follows the requirements: it finds items (?item) that are not metro stations (not instance of wd:Q928830) but have a connecting line (?line) that is a rapid transit railway line (instance of wd:Q15079663). It also returns the IRIs for both the item and the line, with optional labels.

However, there is a potential issue: some items returned (e.g., Meiji-Jingūmae Station, Shin-Ochanomizu Station, Kamiiida Station, Heian-dōri Station, Sanshanxinchengnan station) appear to be stations, which may indicate that they are not properly excluded as metro stations. This could be due to items being instances of subclasses of 'metro station' (wd:Q928830), rather than direct instances. The current FILTER NOT EXISTS only excludes direct instances.

To refine the query, you should exclude all items that are instances of subclasses of 'metro station' as well. This can be done by using a property path: ?item wdt:P31/wdt:P279* wd:Q928830. So, the FILTER NOT EXISTS should be:
FILTER NOT EXISTS { ?item wdt:P31/wdt:P279* wd:Q928830 }

Please update the query accordingly to ensure all metro stations, including those that are subclasses, are excluded.

[Assistant]
Thank you for the feedback. You are correct: to fully exclude all metro stations, including those that are instances of subclasses of "metro station" (wd:Q928830), we need to use a property path in the FILTER NOT EXISTS clause: ?item wdt:P31/wdt:P279* wd:Q928830.

I will update the query accordingly and ensure that all such items are excluded. Here is the refined query.

[Tool]
Got 50 rows and 4 columns, showing the first 5 and last 5 rows below:
| item                                        | line                                         | itemLabel                         | lineLabel                          |
| ------------------------------------------- | -------------------------------------------- | --------------------------------- | ---------------------------------- |
| wd:Q111738574                               | Line 1 of the Salvador subway (wd:Q10318644) |                                   | Line 1 of the Salvador subway (en) |
| wd:Q19614659                                | Line 1 (Yerevan Metro) (wd:Q10318696)        |                                   | Line 1 (Yerevan Metro) (en)        |
| Nazarbekian (wd:Q2060834)                   | Line 1 (Yerevan Metro) (wd:Q10318696)        | Nazarbekian (en)                  | Line 1 (Yerevan Metro) (en)        |
| Tuqiao depot (wd:Q10927801)                 | Batong line (wd:Q1039452)                    | Tuqiao depot (en)                 | Batong line (en)                   |
| Amara-Donostia train station (wd:Q12253308) | Euskotren line E5 (wd:Q104233835)            | Amara-Donostia train station (en) | Euskotren line E5 (en)             |
| ...                                         | ...                                          | ...                               | ...                                |
| Alam Sutera LRT station (wd:Q23763025)      | Sri Petaling line (wd:Q113297920)            | Alam Sutera LRT station (en)      | Sri Petaling line (en)             |
| Muhibbah LRT station (wd:Q25109920)         | Sri Petaling line (wd:Q113297920)            | Muhibbah LRT station (en)         | Sri Petaling line (en)             |
| Kinrara BK5 LRT station (wd:Q25038320)      | Sri Petaling line (wd:Q113297920)            | Kinrara BK5 LRT station (en)      | Sri Petaling line (en)             |
| IOI Puchong Jaya LRT station (wd:Q24806750) | Sri Petaling line (wd:Q113297920)            | IOI Puchong Jaya LRT station (en) | Sri Petaling line (en)             |
| PWTC LRT station (wd:Q4383723)              | Sri Petaling line (wd:Q113297920)            | PWTC LRT station (en)             | Sri Petaling line (en)             |

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The query is mostly correct and well-constructed: it finds items that are not metro stations (nor their subclasses) but have a connecting line that is a rapid transit railway line, and returns both the item and the connecting line. However, there is a minor issue: some of the returned items (such as 'Alam Sutera LRT station', 'Muhibbah LRT station', etc.) are actually LRT (Light Rail Transit) stations, which may themselves be subclasses of metro stations or at least conceptually similar. If the user's intent is to exclude all types of rapid transit stations (not just those strictly subclassed under 'metro station'), the query might need to be refined to exclude other relevant subclasses (like LRT station, monorail station, etc.) as well.

Suggestion: Double-check the subclass hierarchy for 'metro station' (wd:Q928830) and consider excluding other types of rapid transit stations if needed. Otherwise, the query is correct as per the current specification.

[Assistant]
Thank you for the detailed feedback. You are correct: if the user's intent is to exclude all types of rapid transit stations (not just those strictly subclassed under 'metro station'), we should broaden the exclusion criteria.

Step-by-step, here's how to refine further:

1. Identify other relevant station types that are conceptually rapid transit stations, such as:
   - Light rail station (LRT station)
   - Monorail station
   - Subway station (sometimes a synonym, but sometimes a separate class)
   - Urban rail transit station

2. Check the subclass hierarchy for 'metro station' (wd:Q928830) to see if these are already covered, or if they need to be explicitly excluded.

Let's search for entities like "light rail station", "monorail station", and "urban rail transit station" to get their Q-IDs.

[Tool]
Top 10 entity alternatives:
1. tram stop, also known as light rail stop, streetcar station, streetcar stop, tram station, trolley station (wd:Q2175765): place designated for a tram to stop so passengers can board or leave
2. Hamasen Station, also known as Hamasen light rail station (wd:Q10922186): light rail station in Kaohsiung, Taiwan
3. Ganzhenlin Station, also known as Ganzhenlin light rail station (wd:Q40095032): light rail station in New Taipei, Taiwan
4. Kanding Station, also known as Kanding light rail station (wd:Q59326193): light rail station in New Taipei, Taiwan
5. Shalun light rail station (wd:Q86725565): light rail station in New Taipei, Taiwan
6. BWI Marshall Airport, also known as BWI station, BWI Marshall Airport station, BWI light rail station (wd:Q4836842): Baltimore Light Rail station at Baltimore-Washington International Airport in Maryland
7. Cold Spring Lane, also known as Cold Spring Lane station, Cold Spring station, Coldspring station, Coldspring light rail station, Cold Spring light rail station (wd:Q5142551): light rail station in Baltimore, Maryland, US
8. Arlozorov Light Rail Station (wd:Q41992304): railway station in Tel Aviv
9. Allenby Light Rail Station, also known as Allenby, Light Rail Station, Tel Aviv (wd:Q50275914): railway station in Tel Aviv
10. Bialik Light Rail Station (wd:Q41991555): railway station in Ramat Gan

[Tool]
Top 10 entity alternatives:
1. monorail station, also known as monorail stop (wd:Q63125083): location where monorails unload and load passengers
2. Imbi Monorail station (wd:Q31321): monorail station in Kuala Lumpur
3. Maharajalela Monorail station (wd:Q3133573): monorail station in Kuala Lumpur
4. Medan Tuanku Monorail station, also known as Wawasan Monorail station (wd:Q31544): monorail station in Malaysia
5. Monorail Hamamatsuchō Station, also known as Hamamatsuchō Station (wd:Q124863397): monorail station in Minato, Tokyo, Japan
6. Chembur monorail station (wd:Q17050476): train station in Maharashtra, India
7. Naigaon monorail station (wd:Q63346704): Mumbai Monorail Station
8. Resorts World Monorail Station, also known as Waterfront Monorail Station (wd:Q7974085)
9. VivoCity Monorail Station (wd:Q124337043)
10. Shonan Monorail Ōfuna Station, also known as Monorail Ōfuna Station, Ōfuna Station (wd:Q124719338): part of Ōfuna Station, operating by Shonan Monorail, in Japan

[Tool]
Top 10 entity alternatives:
1. Attraction Area Model for Urban Rail Transit Stations (wd:Q66875537): article published in 2014
2. Optimization model of emergency ... location for urban rail transit (wd:Q128978261): scholarly article
3. Noise evaluation method for urba...it underground station platforms (wd:Q118385892)
4. Urban Rail Transit (wd:Q50810900): Academic journal published by Springer , covering the subjects: ...engineering | Social Sciences: Transportation and communications
5. urban rail transit system (wd:Q3491904): term for various types of local rail systems
6. Exploring urban rail transit sta...ip growth with network expansion (wd:Q129989209): scholarly article published in August 2019
7. urban rail transit engineering (wd:Q132532060): engineering of rail systems and local passenger trains in urban areas
8. urban rail transit in India, also known as urban rail transport in India (wd:Q112061565): overview of the urban rail transit system in India
9. Taizhou railway station, also known as Category:Taizhou Railway Station (Taizhou Rail Transit), Taizhou Central railway station (wd:Q104872928): railway station in Jiaojiang, Taizhou, Zhejiang, China
10. Ningbo Railway Station (Ningbo Rail Transit) (wd:Q21079308): metro station in Ningbo, China

[Tool]
Top 10 entity alternatives:
1. Lviv Suburban railway station (wd:Q4271107): railway station in Lviv, Ukraine
2. Yenikapı railway station, also known as Yenikapı (Suburban) railway station (wd:Q15136731): railway station in Istanbul, Turkey
3. Former suburban railways station, Málaga, also known as Centro de Estudios Portuarios (wd:Q2889984): building in Málaga City, Spain
4. Bandra suburban railway station building (wd:Q98828607): building in Mumbai, India
5. Suburban railway station in Gdynia (wd:Q30620802)
6. Driving to Suburban Rail Stations (wd:Q59149794)
7. railway station, also known as railroad station, rail station, rail stop, railway stop, train station (wd:Q55488): railway facility where trains regularly stop to load or unload passengers and/or freight
8. commuter rail, also known as urban rail system, suburban rail service, commuter train service, suburban rail (wd:Q1412403): passenger rail transport services primarily within metropolitan areas
9. urban rail, also known as suburban railway system, suburban railways, suburban rail (wd:Q109072382)
10. Suburban Station, also known as Penn Center Station (wd:Q1531481): commuter rail station in Center City, Philadelphia

[Tool]
Top 10 entity alternatives:
1. railway station, also known as railroad station, rail station, rail stop, railway stop, train station (wd:Q55488): railway facility where trains regularly stop to load or unload passengers and/or freight
2. railway platform, also known as platform, railway station, subway platform, train platform (wd:Q325358): fixed structure to allow people to board or alight trains
3. Railway station (wd:Q3096773): railway station in La Chaux-de-Fonds in the canton of Neuchâtel, Switzerland
4. Hyvinkää railway station, also known as Hyvinge railway station, Railway station (wd:Q4348424): railway station in Hyvinkää, Finland
5. Railway Station, also known as Dworzec (wd:Q9213261): 1980 film by Krzysztof Kieślowski
6. Railway Station (wd:Q38876707): station of Changsha Metro
7. Railway Station (wd:Q7284210): village in Semnan, Iran
8. Railway Station (wd:Q111995385): metro station in Shaoxing
9. Thames railway station, also known as Railway Station (wd:Q24189731): railway station in New Zealand
10. railway station (wd:Q7075475): Metrorail station on the Southern Line

[Tool]
Top 10 entity alternatives:
1. tram stop, also known as light rail stop, streetcar station, streetcar stop, tram station, trolley station (wd:Q2175765): place designated for a tram to stop so passengers can board or leave
2. Straßenbahnhaltestelle, also known as Tram Stop, Tram-Stop (wd:Q2354756): installation artwork by Joseph Beuys
3. Tram Stop (wd:Q29911466): drawing by Max Beckmann
4. Tram Stop (wd:Q20776191): painting by Gunvor Grönvik
5. Tram stop Westwijk, also known as Tram stop on route 25R (wd:Q2044925): tram stop in Amstelveen, Netherlands
6. Kronenburg, also known as Tram stop Kronenburg (wd:Q2109813): tram stop in Amstelveen, Netherlands
7. Onderuit, also known as Onderuit metro station, Tram stop Onderuit (wd:Q13922931): tram stop in Amstelveen, Netherlands
8. Miyanomae tram stop, also known as Miyanomae Station (wd:Q11453134): tram station in Arakawa, Tokyo, Japan
9. Uilenstede, also known as Tram stop Uilenstede (wd:Q2457557): tram stop in Amstelveen, Netherlands
10. Tram stop Sacharovlaan, also known as Sacharovlaan metro station (wd:Q2218736): tram stop in Amstelveen, Netherlands

[Tool]
Top 10 entity alternatives:
1. metro station, also known as metro stop, rapid transit station, rapid transit stop, subway station, subway stop (wd:Q928830): railway station of a rapid transit system
2. Subway Station (wd:Q76440820): print in the National Gallery of Art (NGA 144112)
3. Subway Station (wd:Q76551461): print in the National Gallery of Art (NGA 149118)
4. public transport stop, also known as transport stop nearby, metro station, transport station nearby, subway station, stop nearby (wd:P8453): general (e.g. nearest) public transport stop (bus, tram, train, subway)
5. Ottakring subway station, also known as U3 Ottakring (wd:Q15264665): metro station in Vienna, Austria
6. Hillhead subway station (wd:Q3269432): subway station in Glasgow, Scotland, UK
7. Kelvinbridge subway station (wd:Q1804645): subway station in Glasgow, Scotland, UK
8. Cowcaddens subway station (wd:Q1802437): subway station in Glasgow, Scotland, UK
9. Ibrox subway station (wd:Q2397220): subway station in Glasgow, Scotland, UK
10. Kelvinhall subway station (wd:Q1804611): subway station in Glasgow, Scotland, UK

[Assistant]
Based on the searches, here are the relevant station types and their Q-IDs:
- Metro station (wd:Q928830)
- Tram stop / light rail stop (wd:Q2175765)
- Monorail station (wd:Q63125083)
- Railway station (wd:Q55488) (very broad, may include all types)
- Subway station is an alias for metro station (wd:Q928830)

To exclude all rapid transit station types, we should use a FILTER NOT EXISTS with a property path for all these types:
- ?item wdt:P31/wdt:P279* wd:Q928830 (metro station)
- ?item wdt:P31/wdt:P279* wd:Q2175765 (tram stop / light rail stop)
- ?item wdt:P31/wdt:P279* wd:Q63125083 (monorail station)

We should not exclude all railway stations (wd:Q55488), as this would remove too much.

Let's update the query to exclude items that are instances (direct or indirect) of any of these three types.

[Tool]
Got 50 rows and 4 columns, showing the first 5 and last 5 rows below:
| item                                                   | line                                         | itemLabel                                    | lineLabel                          |
| ------------------------------------------------------ | -------------------------------------------- | -------------------------------------------- | ---------------------------------- |
| wd:Q111738574                                          | Line 1 of the Salvador subway (wd:Q10318644) |                                              | Line 1 of the Salvador subway (en) |
| Nazarbekian (wd:Q2060834)                              | Line 1 (Yerevan Metro) (wd:Q10318696)        | Nazarbekian (en)                             | Line 1 (Yerevan Metro) (en)        |
| wd:Q19614659                                           | Line 1 (Yerevan Metro) (wd:Q10318696)        |                                              | Line 1 (Yerevan Metro) (en)        |
| Tuqiao depot (wd:Q10927801)                            | Batong line (wd:Q1039452)                    | Tuqiao depot (en)                            | Batong line (en)                   |
| Amara-Donostia train station (wd:Q12253308)            | Euskotren line E5 (wd:Q104233835)            | Amara-Donostia train station (en)            | Euskotren line E5 (en)             |
| ...                                                    | ...                                          | ...                                          | ...                                |
| PWTC LRT station (wd:Q4383723)                         | Sri Petaling line (wd:Q113297920)            | PWTC LRT station (en)                        | Sri Petaling line (en)             |
| Hang Tuah station (wd:Q27142)                          | Sri Petaling line (wd:Q113297920)            | Hang Tuah station (en)                       | Sri Petaling line (en)             |
| Sentul LRT station (wd:Q27140)                         | Sri Petaling line (wd:Q113297920)            | Sentul LRT station (en)                      | Sri Petaling line (en)             |
| Awan Besar LRT station (wd:Q21005945)                  | Sri Petaling line (wd:Q113297920)            | Awan Besar LRT station (en)                  | Sri Petaling line (en)             |
| Taman Perindustrian Puchong LRT station (wd:Q22674240) | Sri Petaling line (wd:Q113297920)            | Taman Perindustrian Puchong LRT station (en) | Sri Petaling line (en)             |

[Tool]
Got 17,031 rows and 3 columns, showing the first 10 rows below:
| subject                                 | property              | object                     |
| --------------------------------------- | --------------------- | -------------------------- |
| Amsterdam Central station (wd:Q50719)   | instance of (wdt:P31) | metro station (wd:Q928830) |
| La Défense (wd:Q140277)                 | instance of (wdt:P31) | metro station (wd:Q928830) |
| Châtelet (wd:Q601484)                   | instance of (wdt:P31) | metro station (wd:Q928830) |
| Charles de Gaulle - Étoile (wd:Q800624) | instance of (wdt:P31) | metro station (wd:Q928830) |
| Komsomolskaya (wd:Q1200275)             | instance of (wdt:P31) | metro station (wd:Q928830) |
| Novoslobodskaya (wd:Q1200389)           | instance of (wdt:P31) | metro station (wd:Q928830) |
| Esplanade de La Défense (wd:Q1368326)   | instance of (wdt:P31) | metro station (wd:Q928830) |
| Town Hall (wd:Q968939)                  | instance of (wdt:P31) | metro station (wd:Q928830) |
| République (wd:Q1341849)                | instance of (wdt:P31) | metro station (wd:Q928830) |
| Nation (wd:Q1418711)                    | instance of (wdt:P31) | metro station (wd:Q928830) |
| ...                                     | ...                   | ...                        |

[Tool]
Got 16,069 rows and 3 columns, showing the first 10 rows below:
| subject                                            | property              | object                  |
| -------------------------------------------------- | --------------------- | ----------------------- |
| Den Haag Centraal railway station (wd:Q200704)     | instance of (wdt:P31) | tram stop (wd:Q2175765) |
| Amsterdam Zuid (wd:Q49872)                         | instance of (wdt:P31) | tram stop (wd:Q2175765) |
| Den Haag HS railway station (wd:Q800657)           | instance of (wdt:P31) | tram stop (wd:Q2175765) |
| Hakodate Station (wd:Q1151274)                     | instance of (wdt:P31) | tram stop (wd:Q2175765) |
| Amsterdam Amstel (wd:Q50720)                       | instance of (wdt:P31) | tram stop (wd:Q2175765) |
| Newark Penn Station (wd:Q1745642)                  | instance of (wdt:P31) | tram stop (wd:Q2175765) |
| Amsterdam Lelylaan (wd:Q50722)                     | instance of (wdt:P31) | tram stop (wd:Q2175765) |
| Delft railway station (wd:Q800653)                 | instance of (wdt:P31) | tram stop (wd:Q2175765) |
| Den Haag Laan van NOI railway station (wd:Q800656) | instance of (wdt:P31) | tram stop (wd:Q2175765) |
| 7th Street/Metro Center (wd:Q3093639)              | instance of (wdt:P31) | tram stop (wd:Q2175765) |
| ...                                                | ...                   | ...                     |

[Tool]
Got 206 rows and 3 columns, showing the first 10 rows below:
| subject                                       | property              | object                          |
| --------------------------------------------- | --------------------- | ------------------------------- |
| Bologna Centrale railway station (wd:Q800557) | instance of (wdt:P31) | monorail station (wd:Q63125083) |
| Timiryazevskaya (wd:Q3031151)                 | instance of (wdt:P31) | monorail station (wd:Q63125083) |
| Ulitsa Sergeya Eyzenshteyna (wd:Q3031255)     | instance of (wdt:P31) | monorail station (wd:Q63125083) |
| Ulitsa Milashenkova (wd:Q3031179)             | instance of (wdt:P31) | monorail station (wd:Q63125083) |
| Teletsentr (wd:Q3031207)                      | instance of (wdt:P31) | monorail station (wd:Q63125083) |
| Ulitsa Akademika Korolyova (wd:Q3031244)      | instance of (wdt:P31) | monorail station (wd:Q63125083) |
| Vystavochny Tsentr (wd:Q3031250)              | instance of (wdt:P31) | monorail station (wd:Q63125083) |
| Dainichi Station (wd:Q681742)                 | instance of (wdt:P31) | monorail station (wd:Q63125083) |
| Bampaku-kinen-kōen Station (wd:Q1002726)      | instance of (wdt:P31) | monorail station (wd:Q63125083) |
| Senri-chuo Station (wd:Q2056658)              | instance of (wdt:P31) | monorail station (wd:Q63125083) |
| ...                                           | ...                   | ...                             |

[Tool]
Top 10 entity alternatives:
1. LRT station (wd:Q31727016): LRT station in Indonesia
2. KL Gateway–Universiti LRT station, also known as KL Gateway Universiti, KL Gateway-Universiti LRT station, KL Gateway-Universiti LRT Station, KL Gateway–Universiti LRT Station, KL Gateway-Universiti station (wd:Q6131847): light rail station serving the University of Malaya, in Kuala Lumpur
3. Ampang LRT station, also known as AG8 (wd:Q4748041): railway station in Selangor, Malaysia
4. Bandaraya LRT station (wd:Q4854452): Rapid transit station in Malaysia
5. Damai LRT station (wd:Q5211926): elevated rapid transit station in Kuala Lumpur, Malaysia
6. KLCC LRT station (wd:Q1054307): LRT station in Kuala Lumpur
7. Maluri station, also known as AEON-Maluri MRT station, Maluri LRT station, Maluri LRT Station, Maluri MRT station (wd:Q6744979): railway station in Miharja, Malaysia
8. PWTC LRT station, also known as ST8 (wd:Q4383723): an LRT station in Kuala Lumpur
9. Kerinchi LRT station (wd:Q6131677): railway station in Pantai, Malaysia
10. Pudu LRT station (wd:Q6150815): railway station in Pudu, Kuala Lumpur, Malaysia

[Tool]
Top 10 entity alternatives:
1. tram stop, also known as light rail stop, streetcar station, streetcar stop, tram station, trolley station (wd:Q2175765): place designated for a tram to stop so passengers can board or leave
2. Hamasen Station, also known as Hamasen light rail station (wd:Q10922186): light rail station in Kaohsiung, Taiwan
3. Ganzhenlin Station, also known as Ganzhenlin light rail station (wd:Q40095032): light rail station in New Taipei, Taiwan
4. Kanding Station, also known as Kanding light rail station (wd:Q59326193): light rail station in New Taipei, Taiwan
5. Shalun light rail station (wd:Q86725565): light rail station in New Taipei, Taiwan
6. BWI Marshall Airport, also known as BWI station, BWI Marshall Airport station, BWI light rail station (wd:Q4836842): Baltimore Light Rail station at Baltimore-Washington International Airport in Maryland
7. Cold Spring Lane, also known as Cold Spring Lane station, Cold Spring station, Coldspring station, Coldspring light rail station, Cold Spring light rail station (wd:Q5142551): light rail station in Baltimore, Maryland, US
8. Arlozorov Light Rail Station (wd:Q41992304): railway station in Tel Aviv
9. Allenby Light Rail Station, also known as Allenby, Light Rail Station, Tel Aviv (wd:Q50275914): railway station in Tel Aviv
10. Bialik Light Rail Station (wd:Q41991555): railway station in Ramat Gan

[Assistant]
From the searches, it appears that "LRT station" is not a distinct class in Wikidata, but is often modeled as a "tram stop" (wd:Q2175765) or "light rail stop". Therefore, our previous exclusions already cover most rapid transit station types except for possible edge cases.

If we want to be even more robust, we could also exclude items that are instances of any subclass of "railway station" (wd:Q55488) that is itself a subclass of "rapid transit station" (if such a class exists). However, Wikidata's modeling often uses "metro station", "tram stop", and "monorail station" for rapid transit.

Given this, our current query is as robust as possible for the available Wikidata structure. If the user wants to exclude all possible rapid transit station types, the current exclusions for:
- metro station (wd:Q928830)
- tram stop (wd:Q2175765)
- monorail station (wd:Q63125083)

are the best approach.

Here is the final refined query and answer.

[Tool] Stopped generation process


SELECT ?item ?population ?areaRaw ?unit ?areaKm2 WHERE {
  VALUES ?item { wd:Q1781 wd:Q43296 wd:Q183 }
  OPTIONAL { ?item wdt:P1082 ?population }
  OPTIONAL {
    ?item p:P2046 ?areaStatement .
    ?areaStatement ps:P2046 ?areaNode .
    ?areaNode wikibase:quantityAmount ?areaRaw .
    ?areaNode wikibase:quantityUnit ?unit .
    OPTIONAL { ?areaStatement pq:P518 ?appliesToPart }
    FILTER(!EXISTS { ?areaStatement pq:P518 wd:Q187223 }) # exclude lagoon
    BIND(
      IF(?unit = wd:Q712226, ?areaRaw, IF(?unit = wd:Q35852, ?areaRaw * 0.01, IF(?unit = wd:Q25343, ?areaRaw / 1000000, ?areaRaw)))
      AS ?areaKm2
    )
  }
}
ORDER BY ?item ?areaKm2 DESC

This query retrieves all area statements for Budapest, Wake Island, and Germany, excluding those that apply to lagoons, and converts the area to square kilometres where possible. It also returns the raw value and unit for transparency. This should ensure that valid area values are returned for all three entities.

[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 item IDs, populations (if available), and land areas in square kilometers (if available) for Budapest, Wake Island, and Germany, excluding any area measurements that apply to lagoons?

[Assistant]
Let's break down the question:

1. **Entities to find**: Budapest, Wake Island, Germany.
2. **Properties to retrieve**:
   - Item IDs (IRIs).
   - Population (if available).
   - Land area in square kilometers (if available), but **exclude any area measurements that apply to lagoons**.

**Step 1: Find the correct entities for Budapest, Wake Island, and Germany.**

I'll search for each entity in Wikidata to get their Q-IDs.

Let's start with "Budapest".

[Tool]
Top 10 entity alternatives:
1. Budapest, also known as Pešta, Pešť, Pest, Ofen, Budon (wd:Q1781): capital and largest city of Hungary
2. Budapest (wd:Q16467392): 2013 single by George Ezra
3. Budapest (wd:Q55420238): 2018 film directed by Xavier Gens
4. Budapest, also known as Budapest, MO (wd:Q825871): unincorporated community in Missouri
5. Budapest, also known as Budapest, GA, Budapest, Georgia (wd:Q603551): human settlement in Haralson County, Georgia, United States of America
6. Budapest, also known as AKENA VERANDAS, ELA, Fondation Océan Vital, FRA 77, Livie, Livie, CND 77 (wd:Q109017715): IMOCA 60 (1996 Fa)
7. .budapest, also known as dot budapest (wd:Q20571386): top-level domain
8. Budapest (wd:Q3646355): song performed by Jethro Tull
9. Budapest (wd:Q221191): band
10. Budapest (wd:Q850941): 1992 studio album by Deborah Henson-Conant

[Tool]
Top 10 entity alternatives:
1. Wake Island, also known as Wake Atoll, St Francois, St Francis Island, St Francis, San Francisco Island (wd:Q43296): coral atoll in the North Pacific Ocean administered by the US and also claimed by the Marshall Islands
2. Wake Island (wd:Q1581633): 1942 film directed by John Farrow
3. Wake Island, also known as Wake Islet (wd:Q32040976): island in the territory Wake Island, United States of America
4. Wake Island (wd:Q32040970)
5. Wake Island (wd:L254522-F1)
6. Wake Island (wd:L254522)
7. Wake Island Rail, also known as Gallirallus wakensis (wd:Q541492): species of bird
8. Wake Island Airfield, also known as AWK, PWAK (wd:Q7960943): airport in United States Minor Outlying Islands, United States of America
9. USS Wake Island (wd:Q7875218): 1943 Casablanca-class escort carrier
10. Wake Island Conference (wd:Q7960939): 1950 conference between US President Harry S. Truman and General Douglas MacArthur to confer about the progress of the Korean War

[Tool]
Top 10 entity alternatives:
1. Germany, also known as BR Deutschland, Bundesrepublik Deutschland, Deutschland, Federal Republic of Germany (wd:Q183): country in Central Europe
2. Weimar Republic, also known as German Republic, Weimar Germany, Republic of Germany, Germany, German Reich (wd:Q41304): Germany in the years 1918/1919–1933
3. German Reich, also known as Deutsches Reich, German Empire, German Realm, Germany, Imperial Germany (wd:Q1206012): official name for the German nation state from 1871 to 1945, and name of Germany until 1949
4. Burg Drachenfels, also known as Germany (wd:Q1011486): castle
5. Germany (wd:Q5552078): European Parliament constituency
6. Geilenkirchen-Heinsberg, also known as Germany (wd:Q2268218)
7. Germany, also known as Germany, IN, Germany, Indiana (wd:Q18151573): unincorporated community in Clark County, Indiana
8. Germany (wd:Q19147844): poem by Vladimir Mayakovsky
9. Germany, also known as Ludwig, West (wd:Q3839160): Hetalia character
10. Germany, also known as Germany, Texas, Germany, TX (wd:Q15221573): unincorporated community in Houston County, Texas, United States

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

[Tool]
Top 10 property alternatives:
1. area, also known as total area, surface area, surface, size, resolution (wd:P2046 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): area occupied by an object
2. country, also known as sovereign state, state, land, host country (wd:P17 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
3. applies to part, also known as when viewed as, valid for part, section, region, per (wd:P518 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): part, aspect, or form of the item to which the claim applies
4. field of work, also known as scientific discipline, scientific area, responsible for, research on, research fields (wd:P101 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): specialization of a person or organization; see P106 for the occupation, interested in
5. water area (wd:P8887 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): area/surface of a geographical entity that is covered by water, area
6. located in/on physical feature, also known as located on the terrain feature, location (terrain feature), loc (terr), on, on geographical feature (wd:P706 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): located on the specified (geo)physical feature. Should not be us...nly political/administrative (P131) or a mountain range (P4552)., location, part of
7. applies to jurisdiction, also known as belongs to jurisdiction, applies to territorial jurisdiction, applies to region, applies to place, applies to geographic place (wd:P1001 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): the item (institution, law, public office, public register...) o...a territorial jurisdiction: a country, state, municipality, ...), significant place, characteristic of, operating area
8. water as percent of area, also known as H₂O%, percent of area that is water (wd:P2927 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): which percentage of the territory of this item inside coast line...ternational bounderies is water. Use "percent" (Q11229)  as unit
9. land acknowledgement, also known as land acknowledgement (wd:P13282 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): acknowledgement of indigenous or native people who live and whose ancestors lived at a location, URL
10. territory overlaps, also known as partially overlaps, partially coincident with, partly coincident with, partly located in territorial entity, partly overlaps (wd:P3179 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): part or all of the area associated with (this) entity overlaps part or all of the area associated with that entity, partially coincident with

[Tool]
No entity items found

No other items found

No literal items found

[Tool]
Got 1,523 rows and 3 columns, showing the first 10 rows below:
| subject             | property                                                    | object                                                                                |
| ------------------- | ----------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------- |
| Budapest (wd:Q1781) | instance of (wdt:P31)                                       | enclave (wd:Q171441)                                                                                |
| Budapest (wd:Q1781) | country (wdt:P17)                                           | Hungary (wd:Q28)                                                                                |
| Budapest (wd:Q1781) | located in the administrative territorial entity (wdt:P131) | Hungary (wd:Q28)                                                                                |
| Budapest (wd:Q1781) | coordinate location (wdt:P625)                              | POINT(19.040833 47.498333) (geo:wktLiteral)                                                                         |
| Budapest (wd:Q1781) | Commons category (wdt:P373)                                 | Budapest                                                                                |
| Budapest (wd:Q1781) | image (wdt:P18)                                             | <http://commons.wikimedia.org/wiki/Special:FilePath/Budapest%2C%20Hungary%20%28explored%29%20%2814995308504%29.jpg> |
| Budapest (wd:Q1781) | part of (wdt:P361)                                          | Central Hungary (wd:Q852742)                                                                                |
| Budapest (wd:Q1781) | population (wdt:P1082)                                      | 1686222 (xsd:decimal)                                                                                |
| Budapest (wd:Q1781) | inception (wdt:P571)                                        | 1873-11-17T00:00:00Z (xsd:dateTime)                                                                                |
| Budapest (wd:Q1781) | described by source (wdt:P1343)                             | Brockhaus and Efron Encyclopedic Dictionary (wd:Q602358)                                                            |
| ...                 | ...                                                         | ...                                                                                |

[Tool]
Got 680 rows and 3 columns, showing the first 10 rows below:
| subject                 | property                                                    | object                                                                                |
| ----------------------- | ----------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------- |
| Wake Island (wd:Q43296) | instance of (wdt:P31)                                       | atoll (wd:Q42523)                                                                                |
| Wake Island (wd:Q43296) | country (wdt:P17)                                           | United States (wd:Q30)                                                                                |
| Wake Island (wd:Q43296) | located in the administrative territorial entity (wdt:P131) | United States Minor Outlying Islands (wd:Q16645)                                                               |
| Wake Island (wd:Q43296) | coordinate location (wdt:P625)                              | POINT(166.633333 19.300000) (geo:wktLiteral)                                                                   |
| Wake Island (wd:Q43296) | Commons category (wdt:P373)                                 | Wake Island                                                                                |
| Wake Island (wd:Q43296) | image (wdt:P18)                                             | <http://commons.wikimedia.org/wiki/Special:FilePath/Aerial%20view%20of%20Wake%20Island%20in%20July%202014.JPG> |
| Wake Island (wd:Q43296) | population (wdt:P1082)                                      | 100 (xsd:decimal)                                                                                |
| Wake Island (wd:Q43296) | heritage designation (wdt:P1435)                            | National Register of Historic Places listed place (wd:Q19558910)                                               |
| Wake Island (wd:Q43296) | has part(s) (wdt:P527)                                      | Peale Island (wd:Q31985226)                                                                                |
| Wake Island (wd:Q43296) | described by source (wdt:P1343)                             | wd:Q2041543                                                                                |
| ...                     | ...                                                         | ...                                                                                |

[Tool]
Got 3,661 rows and 3 columns, showing the first 10 rows below:
| subject           | property                        | object                                                                                |
| ----------------- | ------------------------------- | -------------------------------------------------------------------------------------------------------- |
| Germany (wd:Q183) | instance of (wdt:P31)           | country (wd:Q6256)                                                                                |
| Germany (wd:Q183) | country (wdt:P17)               | Germany (wd:Q183)                                                                                |
| Germany (wd:Q183) | coordinate location (wdt:P625)  | POINT(10.000000 51.000000) (geo:wktLiteral)                                                              |
| Germany (wd:Q183) | Commons category (wdt:P373)     | Germany                                                                                |
| Germany (wd:Q183) | image (wdt:P18)                 | <http://commons.wikimedia.org/wiki/Special:FilePath/Aerial%20view%20of%20Berlin%20%2832881394137%29.jpg> |
| Germany (wd:Q183) | population (wdt:P1082)          | 84358845 (xsd:decimal)                                                                                |
| Germany (wd:Q183) | inception (wdt:P571)            | 1949-05-23T00:00:00Z (xsd:dateTime)                                                                      |
| Germany (wd:Q183) | described at URL (wdt:P973)     | <https://wikispooks.com/wiki/Germany>                                                                    |
| Germany (wd:Q183) | short name (wdt:P1813)          | Deutschland (de)                                                                                |
| Germany (wd:Q183) | described by source (wdt:P1343) | Brockhaus and Efron Encyclopedic Dictionary (wd:Q602358)                                                 |
| ...               | ...                             | ...                                                                                |

[Tool]
Got 1 row and 3 columns:
| subject             | property         | object              |
| ------------------- | ---------------- | ------------------- |
| Budapest (wd:Q1781) | area (wdt:P2046) | 52514 (xsd:decimal) |

[Tool]
Got 2 rows and 3 columns:
| subject                 | property         | object            |
| ----------------------- | ---------------- | ----------------- |
| Wake Island (wd:Q43296) | area (wdt:P2046) | 6 (xsd:decimal)   |
| Wake Island (wd:Q43296) | area (wdt:P2046) | 7.1 (xsd:decimal) |

[Tool]
Got 1 row and 3 columns:
| subject           | property         | object               |
| ----------------- | ---------------- | -------------------- |
| Germany (wd:Q183) | area (wdt:P2046) | 357588 (xsd:decimal) |

[Tool]
Got 2 rows and 3 columns:
| subject                 | property       | object                                        |
| ----------------------- | -------------- | --------------------------------------------- |
| Wake Island (wd:Q43296) | area (p:P2046) | s:Q43296-b0a74143-4214-3ec6-af13-3c0a0b4f5511 |
| Wake Island (wd:Q43296) | area (p:P2046) | s:Q43296-d0f59de0-4bbf-ac68-02f9-eee102c462e6 |

[Tool]
Got 7 rows and 3 columns:
| subject                                       | property                  | object                             |
| --------------------------------------------- | ------------------------- | ---------------------------------- |
| s:Q43296-b0a74143-4214-3ec6-af13-3c0a0b4f5511 | area (ps:P2046)           | 6 (xsd:decimal)                    |
| s:Q43296-b0a74143-4214-3ec6-af13-3c0a0b4f5511 | applies to part (pq:P518) | lagoon (wd:Q187223)                |
| s:Q43296-b0a74143-4214-3ec6-af13-3c0a0b4f5511 | wikibase:rank             | wikibase:NormalRank                |
| s:Q43296-b0a74143-4214-3ec6-af13-3c0a0b4f5511 | rdf:type                  | wikibase:BestRank                  |
| s:Q43296-b0a74143-4214-3ec6-af13-3c0a0b4f5511 | area (psn:P2046)          | v:1d1927789299eb5f52f1161d504dc4af |
| s:Q43296-b0a74143-4214-3ec6-af13-3c0a0b4f5511 | area (psv:P2046)          | v:af2f0a4729c89142c2c15d42ceecc5af |
| s:Q43296-b0a74143-4214-3ec6-af13-3c0a0b4f5511 | rdf:type                  | wikibase:Statement                 |

[Tool]
Got 7 rows and 3 columns:
| subject                                       | property                  | object                             |
| --------------------------------------------- | ------------------------- | ---------------------------------- |
| s:Q43296-d0f59de0-4bbf-ac68-02f9-eee102c462e6 | area (ps:P2046)           | 7.1 (xsd:decimal)                  |
| s:Q43296-d0f59de0-4bbf-ac68-02f9-eee102c462e6 | applies to part (pq:P518) | land (wd:Q11081619)                |
| s:Q43296-d0f59de0-4bbf-ac68-02f9-eee102c462e6 | wikibase:rank             | wikibase:NormalRank                |
| s:Q43296-d0f59de0-4bbf-ac68-02f9-eee102c462e6 | rdf:type                  | wikibase:BestRank                  |
| s:Q43296-d0f59de0-4bbf-ac68-02f9-eee102c462e6 | area (psn:P2046)          | v:e692f5931d922693b20edc1d0086541a |
| s:Q43296-d0f59de0-4bbf-ac68-02f9-eee102c462e6 | area (psv:P2046)          | v:3918715902b0e0e7a0e4b533fa07c806 |
| s:Q43296-d0f59de0-4bbf-ac68-02f9-eee102c462e6 | rdf:type                  | wikibase:Statement                 |

[Assistant]
Here's what I've found so far:

- **Budapest (wd:Q1781)**
  - Population: 1,686,222
  - Area: 525.14 km² (no indication of lagoon, so it's valid)

- **Wake Island (wd:Q43296)**
  - Population: 100
  - Area: There are two area values:
    - 6 km² (applies to part: lagoon)
    - 7.1 km² (applies to part: land) ← **this is the one to use, as requested**

- **Germany (wd:Q183)**
  - Population: 84,358,845
  - Area: 357,588 km² (no indication of lagoon, so it's valid)

Now, I'll construct a SPARQL query that returns the item IRIs, population, and land area (excluding lagoon areas) for these three entities, with the correct filtering for Wake Island. I'll also include the area qualifier for Wake Island to ensure only the "land" area is returned.

Here is the final SPARQL query:

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The SPARQL query is mostly correct and well-constructed, especially in its handling of Wake Island to exclude lagoon area by filtering for land (wd:Q11081619). However, there are a few points for refinement:

1. Area Units: The query does not explicitly ensure that the area values are in square kilometers. Wikidata may store area values in different units, so it is important to check the unit (P2046 with qualifier P518 for part, and P2046 with qualifier P1889 for unit) and convert if necessary. The query should filter or convert to square kilometers where possible.
2. Area for Budapest and Germany: The query retrieves the area for these entities without checking if the measurement applies to land only or if it might include water bodies. While this is less likely to be an issue for these entities, for completeness and consistency, the query should also check for 'applies to part' qualifiers for these items, similar to what is done for Wake Island, to ensure only land area is considered if available.
3. Labels: The query does not include labels, but since the question only asks for IDs, this is acceptable.

In summary, refine the query to ensure all area values are in square kilometers and, where possible, only land area is considered for all entities, not just Wake Island.

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

**1. Area Units:**
Wikidata stores area values with units, accessible via the value node (psv:P2046) and the unit property (wikibase:quantityUnit). The standard unit for area is square kilometre (wd:Q712226). I will ensure the query only returns area values in square kilometres, or converts them if necessary.

**2. Land Area for All Entities:**
For all three entities, I will check if there is a 'land' qualifier (wd:Q11081619) via 'applies to part' (P518). If such a statement exists, I will use it; otherwise, I will fall back to the unqualified area value, but only if it is in square kilometres.

**3. Labels:**
Since only IDs are required, I will not add labels.

**Approach:**
- For each entity, check for area statements with 'applies to part' = 'land' (wd:Q11081619) and unit = square kilometre (wd:Q712226).
- If not found, check for unqualified area statements with unit = square kilometre.
- Only return area values in square kilometres.
- Exclude any area statements with 'applies to part' = 'lagoon' (wd:Q187223).

Now, I will construct the refined SPARQL query.

[Tool]
Got 3 rows and 3 columns:
| item                    | population             | areaValue |
| ----------------------- | ---------------------- | --------- |
| Budapest (wd:Q1781)     | 1686222 (xsd:decimal)  |           |
| Germany (wd:Q183)       | 84358845 (xsd:decimal) |           |
| Wake Island (wd:Q43296) | 100 (xsd:decimal)      |           |

[Tool]
Got 3 rows and 3 columns:
| item                    | population             | areaValue |
| ----------------------- | ---------------------- | --------- |
| Budapest (wd:Q1781)     | 1686222 (xsd:decimal)  |           |
| Germany (wd:Q183)       | 84358845 (xsd:decimal) |           |
| Wake Island (wd:Q43296) | 100 (xsd:decimal)      |           |

[Tool]
Got 1 row and 3 columns:
| subject             | property       | object                                       |
| ------------------- | -------------- | -------------------------------------------- |
| Budapest (wd:Q1781) | area (p:P2046) | s:Q1781-7b05a645-47bd-b4de-0542-77e91131216f |

[Tool]
Got 9 rows and 3 columns:
| subject                                      | property                 | object                                       |
| -------------------------------------------- | ------------------------ | -------------------------------------------- |
| s:Q1781-7b05a645-47bd-b4de-0542-77e91131216f | point in time (pq:P585)  | 2017-01-01T00:00:00Z (xsd:dateTime)          |
| s:Q1781-7b05a645-47bd-b4de-0542-77e91131216f | area (ps:P2046)          | 52514 (xsd:decimal)                          |
| s:Q1781-7b05a645-47bd-b4de-0542-77e91131216f | wikibase:rank            | wikibase:NormalRank                          |
| s:Q1781-7b05a645-47bd-b4de-0542-77e91131216f | rdf:type                 | wikibase:BestRank                            |
| s:Q1781-7b05a645-47bd-b4de-0542-77e91131216f | prov:wasDerivedFrom      | ref:bfe8f4dfb7460fdc0e720d0ae09911070b5aa100 |
| s:Q1781-7b05a645-47bd-b4de-0542-77e91131216f | point in time (pqv:P585) | v:8bf14fd5c6dc0f5de433b8fe86c3f6eb           |
| s:Q1781-7b05a645-47bd-b4de-0542-77e91131216f | area (psn:P2046)         | v:def2025c75581f199cfd6985e8b2f685           |
| s:Q1781-7b05a645-47bd-b4de-0542-77e91131216f | area (psv:P2046)         | v:efe4f2fc0749364c5c02d42e7196aec4           |
| s:Q1781-7b05a645-47bd-b4de-0542-77e91131216f | rdf:type                 | wikibase:Statement                           |

[Tool]
Got 4 rows and 3 columns:
| subject                            | property                    | object                             |
| ---------------------------------- | --------------------------- | ---------------------------------- |
| v:efe4f2fc0749364c5c02d42e7196aec4 | wikibase:quantityUnit       | hectare (wd:Q35852)                |
| v:efe4f2fc0749364c5c02d42e7196aec4 | wikibase:quantityAmount     | 52514 (xsd:decimal)                |
| v:efe4f2fc0749364c5c02d42e7196aec4 | wikibase:quantityNormalized | v:def2025c75581f199cfd6985e8b2f685 |
| v:efe4f2fc0749364c5c02d42e7196aec4 | rdf:type                    | wikibase:QuantityValue             |

[Tool]
Got 4 rows and 3 columns:
| subject                            | property                    | object                             |
| ---------------------------------- | --------------------------- | ---------------------------------- |
| v:def2025c75581f199cfd6985e8b2f685 | wikibase:quantityUnit       | square metre (wd:Q25343)           |
| v:def2025c75581f199cfd6985e8b2f685 | wikibase:quantityAmount     | 525140000 (xsd:decimal)            |
| v:def2025c75581f199cfd6985e8b2f685 | wikibase:quantityNormalized | v:def2025c75581f199cfd6985e8b2f685 |
| v:def2025c75581f199cfd6985e8b2f685 | rdf:type                    | wikibase:QuantityValue             |

[Tool]
Got 3 rows and 3 columns:
| subject           | property       | object                                      |
| ----------------- | -------------- | ------------------------------------------- |
| Germany (wd:Q183) | area (p:P2046) | s:Q183-248801f0-4066-92c7-5a50-c5f7c4c7d5b7 |
| Germany (wd:Q183) | area (p:P2046) | s:Q183-595e1726-4ffa-d997-a38f-d6055767ad72 |
| Germany (wd:Q183) | area (p:P2046) | s:Q183-e7ed88a3-487d-9467-13a1-9e02764207d4 |

[Tool]
Got 6 rows and 3 columns:
| subject                                     | property            | object                                       |
| ------------------------------------------- | ------------------- | -------------------------------------------- |
| s:Q183-248801f0-4066-92c7-5a50-c5f7c4c7d5b7 | area (ps:P2046)     | 357170 (xsd:decimal)                         |
| s:Q183-248801f0-4066-92c7-5a50-c5f7c4c7d5b7 | wikibase:rank       | wikibase:NormalRank                          |
| s:Q183-248801f0-4066-92c7-5a50-c5f7c4c7d5b7 | rdf:type            | wikibase:Statement                           |
| s:Q183-248801f0-4066-92c7-5a50-c5f7c4c7d5b7 | prov:wasDerivedFrom | ref:897540258fb27553c6e28d72bda786efe8231ee6 |
| s:Q183-248801f0-4066-92c7-5a50-c5f7c4c7d5b7 | area (psn:P2046)    | v:fb256141af69168d2c277c8b60d41055           |
| s:Q183-248801f0-4066-92c7-5a50-c5f7c4c7d5b7 | area (psv:P2046)    | v:34680adf3298df6beb59abd8d7169461           |

[Tool]
Got 4 rows and 3 columns:
| subject                            | property                    | object                             |
| ---------------------------------- | --------------------------- | ---------------------------------- |
| v:34680adf3298df6beb59abd8d7169461 | wikibase:quantityUnit       | square kilometre (wd:Q712226)      |
| v:34680adf3298df6beb59abd8d7169461 | wikibase:quantityAmount     | 357170 (xsd:decimal)               |
| v:34680adf3298df6beb59abd8d7169461 | wikibase:quantityNormalized | v:fb256141af69168d2c277c8b60d41055 |
| v:34680adf3298df6beb59abd8d7169461 | rdf:type                    | wikibase:QuantityValue             |

[Tool]
Got 7 rows and 3 columns:
| subject                                     | property                  | object                                       |
| ------------------------------------------- | ------------------------- | -------------------------------------------- |
| s:Q183-595e1726-4ffa-d997-a38f-d6055767ad72 | area (ps:P2046)           | 349390 (xsd:decimal)                         |
| s:Q183-595e1726-4ffa-d997-a38f-d6055767ad72 | applies to part (pq:P518) | landmass (wd:Q205895)                        |
| s:Q183-595e1726-4ffa-d997-a38f-d6055767ad72 | wikibase:rank             | wikibase:NormalRank                          |
| s:Q183-595e1726-4ffa-d997-a38f-d6055767ad72 | rdf:type                  | wikibase:Statement                           |
| s:Q183-595e1726-4ffa-d997-a38f-d6055767ad72 | prov:wasDerivedFrom       | ref:897540258fb27553c6e28d72bda786efe8231ee6 |
| s:Q183-595e1726-4ffa-d997-a38f-d6055767ad72 | area (psn:P2046)          | v:15e3fc267affe7e4888917bbddf08e27           |
| s:Q183-595e1726-4ffa-d997-a38f-d6055767ad72 | area (psv:P2046)          | v:3498f9e32c5237b1ce8ab37775abaed7           |

[Tool]
Got 4 rows and 3 columns:
| subject                            | property                    | object                             |
| ---------------------------------- | --------------------------- | ---------------------------------- |
| v:3498f9e32c5237b1ce8ab37775abaed7 | wikibase:quantityUnit       | square kilometre (wd:Q712226)      |
| v:3498f9e32c5237b1ce8ab37775abaed7 | wikibase:quantityAmount     | 349390 (xsd:decimal)               |
| v:3498f9e32c5237b1ce8ab37775abaed7 | wikibase:quantityNormalized | v:15e3fc267affe7e4888917bbddf08e27 |
| v:3498f9e32c5237b1ce8ab37775abaed7 | rdf:type                    | wikibase:QuantityValue             |

[Tool]
Got 7 rows and 3 columns:
| subject                                     | property            | object                                       |
| ------------------------------------------- | ------------------- | -------------------------------------------- |
| s:Q183-e7ed88a3-487d-9467-13a1-9e02764207d4 | area (ps:P2046)     | 357588 (xsd:decimal)                         |
| s:Q183-e7ed88a3-487d-9467-13a1-9e02764207d4 | wikibase:rank       | wikibase:PreferredRank                       |
| s:Q183-e7ed88a3-487d-9467-13a1-9e02764207d4 | rdf:type            | wikibase:BestRank                            |
| s:Q183-e7ed88a3-487d-9467-13a1-9e02764207d4 | prov:wasDerivedFrom | ref:31852f0babbfeaca4e49f7640b666fd9f66222a8 |
| s:Q183-e7ed88a3-487d-9467-13a1-9e02764207d4 | area (psn:P2046)    | v:e646d85b8afd9a166f8acba431c15128           |
| s:Q183-e7ed88a3-487d-9467-13a1-9e02764207d4 | area (psv:P2046)    | v:e73b11bf9422673e6213e984de6581bf           |
| s:Q183-e7ed88a3-487d-9467-13a1-9e02764207d4 | rdf:type            | wikibase:Statement                           |

[Tool]
Got 4 rows and 3 columns:
| subject                            | property                    | object                             |
| ---------------------------------- | --------------------------- | ---------------------------------- |
| v:e73b11bf9422673e6213e984de6581bf | wikibase:quantityUnit       | square kilometre (wd:Q712226)      |
| v:e73b11bf9422673e6213e984de6581bf | wikibase:quantityAmount     | 357588 (xsd:decimal)               |
| v:e73b11bf9422673e6213e984de6581bf | wikibase:quantityNormalized | v:e646d85b8afd9a166f8acba431c15128 |
| v:e73b11bf9422673e6213e984de6581bf | rdf:type                    | wikibase:QuantityValue             |

[Tool]
Got 7 rows and 3 columns:
| subject                                       | property                  | object                             |
| --------------------------------------------- | ------------------------- | ---------------------------------- |
| s:Q43296-d0f59de0-4bbf-ac68-02f9-eee102c462e6 | area (ps:P2046)           | 7.1 (xsd:decimal)                  |
| s:Q43296-d0f59de0-4bbf-ac68-02f9-eee102c462e6 | applies to part (pq:P518) | land (wd:Q11081619)                |
| s:Q43296-d0f59de0-4bbf-ac68-02f9-eee102c462e6 | wikibase:rank             | wikibase:NormalRank                |
| s:Q43296-d0f59de0-4bbf-ac68-02f9-eee102c462e6 | rdf:type                  | wikibase:BestRank                  |
| s:Q43296-d0f59de0-4bbf-ac68-02f9-eee102c462e6 | area (psn:P2046)          | v:e692f5931d922693b20edc1d0086541a |
| s:Q43296-d0f59de0-4bbf-ac68-02f9-eee102c462e6 | area (psv:P2046)          | v:3918715902b0e0e7a0e4b533fa07c806 |
| s:Q43296-d0f59de0-4bbf-ac68-02f9-eee102c462e6 | rdf:type                  | wikibase:Statement                 |

[Tool]
Got 4 rows and 3 columns:
| subject                            | property                    | object                             |
| ---------------------------------- | --------------------------- | ---------------------------------- |
| v:3918715902b0e0e7a0e4b533fa07c806 | wikibase:quantityUnit       | square kilometre (wd:Q712226)      |
| v:3918715902b0e0e7a0e4b533fa07c806 | wikibase:quantityAmount     | 7.1 (xsd:decimal)                  |
| v:3918715902b0e0e7a0e4b533fa07c806 | wikibase:quantityNormalized | v:e692f5931d922693b20edc1d0086541a |
| v:3918715902b0e0e7a0e4b533fa07c806 | rdf:type                    | wikibase:QuantityValue             |

[Assistant]
I have now verified the following:
- All area values for the three entities can be retrieved in square kilometres (wd:Q712226).
- For Wake Island, the land area (7.1 km²) is properly qualified.
- For Germany, the preferred area value is 357,588 km², and for Budapest, the area is stored in hectares (52514 ha), which is 525.14 km².

I will now write a final SPARQL query that:
- For each entity, prefers area statements with 'applies to part' = 'land' (wd:Q11081619) and unit = square kilometre.
- If not available, falls back to any area statement in square kilometre.
- For Budapest, if only hectare is available, converts it to km² (1 ha = 0.01 km²).
- Excludes any area statement with 'applies to part' = 'lagoon' (wd:Q187223).
- Returns the item, population, and area in square kilometres.

Here is the final SPARQL query:

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The SPARQL query is on the right track: it selects the correct items, retrieves population, and attempts to filter for land area in km², excluding lagoon areas. However, the execution result shows that the areaKm2 column is empty for all three items, which means the area values were not successfully retrieved. This could be due to overly restrictive filters or issues with how area statements are structured in Wikidata.

Suggestions for refinement:
- Double-check the use of qualifiers and units in the area retrieval part. Some area statements may not have the 'applies to part' qualifier at all, so the filter should allow for unqualified area statements as well as those explicitly marked as land.
- Consider relaxing the filter to include area statements without any 'applies to part' qualifier, as these often refer to total or land area.
- Ensure that the unit conversion logic covers all possible units used for area (km², ha, m²).
- Optionally, retrieve the raw area value and its unit for debugging purposes.

In summary, the query logic is good, but it needs to be refined to actually return the area values as intended.

[Assistant]
Thank you for the feedback. Here’s my revised plan:

**Diagnosis:**
- The previous query may have excluded valid area statements by requiring either no 'applies to part' qualifier or an explicit 'land' qualifier, but some area statements may lack any qualifier.
- Some area statements may use units like hectare (ha, wd:Q35852) or square metre (m², wd:Q25343), so conversion logic must be robust.
- To debug, I will also retrieve the raw area value and its unit.

**Refined Approach:**
- For each entity, retrieve all area statements (P2046).
- Exclude only those with 'applies to part' = 'lagoon' (wd:Q187223).
- For each area statement, get the value and unit, and convert to km² if possible.
- Prefer area statements with 'applies to part' = 'land' (wd:Q11081619) or 'landmass' (wd:Q205895), but also allow unqualified statements.
- Return the item, population, area in km², raw area value, and unit for transparency.

Here is the refined query:

[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 ?item ?itemLabel WHERE {
  {
    ?item wdt:P403 wd:Q2155719 .
  } UNION {
    ?item wdt:P974 ?river .
    ?river wdt:P403 wd:Q2155719 .
  }
  OPTIONAL {
    ?item rdfs:label ?itemLabel FILTER ( LANG( ?itemLabel ) = "en" )
  }
}

Got 9 rows and 2 columns:
| item                                 | itemLabel                  |
| ------------------------------------ | -------------------------- |
| Rivière Mégiscane (wd:Q2155719)      | Rivière Mégiscane (en)     |
| Rivière Achepabanca (wd:Q22402791)   | Rivière Achepabanca (en)   |
| Rivière Assup (wd:Q22403780)         | Rivière Assup (en)         |
| Rivière Attic (wd:Q22403929)         | Rivière Attic (en)         |
| Rivière Capousacataca (wd:Q22410355) | Rivière Capousacataca (en) |
| Rivière Collin (wd:Q22411694)        | Rivière Collin (en)        |
| Rivière Kekek (wd:Q22424844)         | Rivière Kekek (en)         |
| Rivière Tavernier (wd:Q22438550)     | Rivière Tavernier (en)     |
| Rivière Whitegoose (wd:Q22440754)    | Rivière Whitegoose (en)    |

The distinct items that either have the Rivière Mégiscane as their mouth of the watercourse or are tributaries of watercourses that have the Rivière Mégiscane as their mouth are:
- wd:Q2155719 (Rivière Mégiscane)
- wd:Q22402791 (Rivière Achepabanca)
- wd:Q22403780 (Rivière Assup)
- wd:Q22403929 (Rivière Attic)
- wd:Q22410355 (Rivière Capousacataca)
- wd:Q22411694 (Rivière Collin)
- wd:Q22424844 (Rivière Kekek)
- wd:Q22438550 (Rivière Tavernier)
- wd:Q22440754 (Rivière Whitegoose)

[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 distinct items that either have the Rivière Mégiscane as their mouth of the watercourse or are tributaries of watercourses that have the Rivière Mégiscane as their mouth of the watercourse?

[Assistant]
Let's break down the question:

1. We need to find items that have the Rivière Mégiscane as their "mouth of the watercourse".
2. We also need to find items that are tributaries of watercourses that themselves have the Rivière Mégiscane as their mouth.

First, I need to identify:
- The entity for "Rivière Mégiscane".
- The property for "mouth of the watercourse".
- The property for "tributary".

Let's start by searching for "Rivière Mégiscane" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Rivière Mégiscane (wd:Q2155719): watercourse in Quebec, Canada
2. Rivière (wd:Q1023491): commune in Pas-de-Calais, France
3. Rivière (wd:Q1170903): commune in Indre-et-Loire, France
4. Auguste Rivière, also known as Rivière, Marie Auguste Riviere (birthname), Riviere (wd:Q5851435): French horticulturalist (1821-1877), horticulturist, agronomist, botanist
5. Rivière, also known as Riviere (wd:Q3071663): section of Profondeville, Belgium
6. William Riviere, also known as William Rivière, Rivière (wd:Q18577229): English drawing-master, draftsperson, painter
7. Rivière (wd:Q112340485): Type of necklace, type of necklace
8. rivière (wd:Q112340485): type of necklace, Type of necklace
9. Rivière (wd:Q131680870)
10. Riviere (wd:Q37055601): family name

[Assistant]
The entity for "Rivière Mégiscane" is wd:Q2155719.

Next, I need to find the property for "mouth of the watercourse". I'll search for relevant properties.

[Tool]
Top 10 property alternatives:
1. mouth of the watercourse, also known as flows into, watercourse outflow, watercourse ends in, watercourse drain, tributary of (wd:P403 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): the body of water to which the watercourse drains
2. origin of the watercourse, also known as headwaters, water source, water origin, water body origin, stream source (wd:P885 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): main source of a river, stream or lake
3. located in or next to body of water, also known as located on body of water, ocean, on bay, next to lake, on coast of (wd:P206 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): body of water on or next to which a place is located, location
4. tributary, also known as has inflow of, affluent, receives tributary, receives river, has river inflow (wd:P974 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): watercourse that flows into an other one (for lake inflows use P200)
5. distance from river mouth, also known as river kilometer, river mile, river kilometre (wd:P2148 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): qualifier for P974 statements on streams, length
6. inflows, also known as inflow, lake inflow, river inflows (wd:P200 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): major inflow sources — rivers, aquifers, glacial runoff, etc. Some terms may not be place names, e.g. none
7. lake on watercourse, also known as reservoir on this river, lakes on river, lake on stream, lake on river, lake on this river (wd:P469 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): lake or reservoir through which the river or stream flows
8. tributary orientation, also known as orientation of tributary (wd:P3871 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): specify if the stream confluence is a left bank or right bank tributary
9. 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
10. next crossing downstream, also known as downstream crossing adjacent (wd:P2674 as pqv/psn/psv/p/prn/prv/ps/wdtn/pq/pqn/pr/wdt): next crossing of this river, canal, etc. downstream of this subject, followed by

[Assistant]
The property for "mouth of the watercourse" is wd:P403, and the property for "tributary" is wd:P974.

Now, let's clarify the two parts of the query:
1. Items (?item) such that ?item wdt:P403 wd:Q2155719 (mouth of the watercourse is Rivière Mégiscane).
2. Items (?item) such that ?item wdt:P974 ?river and ?river wdt:P403 wd:Q2155719 (item is a tributary of a river that has Rivière Mégiscane as its mouth).

We want the distinct union of these two sets.

I'll now construct a SPARQL query that returns the distinct items matching either of these criteria, along with their labels (optionally).

[Tool]
Got 9 rows and 1 column:
| item                                 |
| ------------------------------------ |
| Rivière Mégiscane (wd:Q2155719)      |
| Rivière Achepabanca (wd:Q22402791)   |
| Rivière Assup (wd:Q22403780)         |
| Rivière Attic (wd:Q22403929)         |
| Rivière Capousacataca (wd:Q22410355) |
| Rivière Collin (wd:Q22411694)        |
| Rivière Kekek (wd:Q22424844)         |
| Rivière Tavernier (wd:Q22438550)     |
| Rivière Whitegoose (wd:Q22440754)    |

[Tool]
Got 9 rows and 2 columns:
| item                                 | itemLabel                  |
| ------------------------------------ | -------------------------- |
| Rivière Mégiscane (wd:Q2155719)      | Rivière Mégiscane (en)     |
| Rivière Achepabanca (wd:Q22402791)   | Rivière Achepabanca (en)   |
| Rivière Assup (wd:Q22403780)         | Rivière Assup (en)         |
| Rivière Attic (wd:Q22403929)         | Rivière Attic (en)         |
| Rivière Capousacataca (wd:Q22410355) | Rivière Capousacataca (en) |
| Rivière Collin (wd:Q22411694)        | Rivière Collin (en)        |
| Rivière Kekek (wd:Q22424844)         | Rivière Kekek (en)         |
| Rivière Tavernier (wd:Q22438550)     | Rivière Tavernier (en)     |
| Rivière Whitegoose (wd:Q22440754)    | Rivière Whitegoose (en)    |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly implements the logic described in the question: it retrieves all items that either have Rivière Mégiscane as their mouth (wdt:P403 wd:Q2155719) or are tributaries (wdt:P974) of watercourses that have Rivière Mégiscane as their mouth. The query returns the IRIs as required, and the labels are included optionally. The answer matches the query result. No further refinement is needed.