PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?industryLabel WHERE {
  wd:Q806191 wdt:P452 ?industry .
  ?industry rdfs:label ?industryLabel
  FILTER ( LANG( ?industryLabel ) = 'en' )
}

Using entities:
- Medici Bank (wd:Q806191), also known as Medici bank: is instance of bank / is instance of Bank / is instance of business / bank of the Medici family

Using properties:
- industry (wd:P452 as wdt), also known as branch, economic branch, field of action, field of exercise, sector, etc.: is subproperty of part of / specific industry of company or organization

Got 1 row and 1 column:
| industryLabel                |
| ---------------------------- |
| financial services (lang:en) |

Answer: The House of Medici owned a business in the financial services industry.

The House of Medici owned a business in the financial services industry.

SPARQL query over wikidata:
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?industryLabel WHERE {
  wd:Q806191 wdt:P452 ?industry .
  ?industry rdfs:label ?industryLabel
  FILTER ( LANG( ?industryLabel ) = 'en' )
}

Using entities:
- Medici Bank (wd:Q806191), also known as Medici bank: is instance of bank / is instance of Bank / is instance of business / bank of the Medici family

Using properties:
- industry (wd:P452 as wdt), also known as branch, economic branch, field of action, field of exercise, sector, etc.: is subproperty of part of / specific industry of company or organization

Execution result:
Got 1 row and 1 column:
| industryLabel                |
| ---------------------------- |
| financial services (lang:en) |

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

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

Available knowledge graphs:
- wikidata at https://qlever.dev/api/wikidata with prefix index for entities and similarity index for properties, and notes:
  - P106 = occupation. Use wdt:P106 to get occupations and fetch English labels with rdfs:label + FILTER(LANG(?label)='en'). When returning human occupations confirm the subject is human (wdt:P31 wd:Q5) to avoid non-human items. For 'main business' prefer more specific occupation items (e.g., real estate entrepreneur Q7301138) over broad labels like business magnate.
  - Population (P1082) and tabular (P4179): use wdt:P1082 for direct values; for time-series use p:P1082 + ps:P1082 + pq:P585 and ORDER BY pq:P585 DESC. Inspect qualifiers (e.g., 'applies to part') and references (pr:P854) to detect scope. When computing density with area (wdt:P2046) confirm area unit/datatype (usually km²), ensure population and area present and >0, and BIND(?population/?area AS ?density).
  - Spouse nationality: do not rely only on P27. Check the spouse's place of birth (P19) and then the birthplace's country (P17) or admin parents (wdt:P131*). Many pre-unification German spouses appear under historical states—map those to modern countries when needed.
  - For languages on countries: prefer wdt:P37 (official language) and wdt:P2936 (language used). wdt:P1412 (languages spoken/written/signed) is more often used for peoples/individuals and may be empty for countries. Try P37 and P2936 first, then fall back to P1412/P407. Fetch English labels with rdfs:label + FILTER(LANG(?l)='en').
  - When filtering by date of birth (P569) use xsd:dateTime comparisons (e.g. >= "1900-01-01T00:00:00Z"^^xsd:dateTime). Inception (P571) often uses Jan-01 placeholders for year-only dates; inspect p:P571 -> ps:P571 and check qualifiers/references for precision. For independence dates, also search for related event statements/items (e.g., 'declaration of independence') and prefer qualifiers/references over assuming day/month from year-only values.
  - To retrieve qualifiers (e.g., award year) use the statement/qualifier pattern: p:Pxxx / ps:Pxxx / pq:P585. Use wdt:Pxxx for normalized/direct values when you don't need qualifiers. Example: p:P166 + pq:P585 gives award year.
  - P166 = award received. Use wdt:P166 for normalized/direct values when you only need award items. To get award years or qualifiers use p:P166 / ps:P166 / pq:P585. Many statements lack pq:P585 — use OPTIONAL { ?stmt pq:P585 ?date } and ORDER BY DESC(?date). When listing award winners, filter ?person wdt:P31 wd:Q5 to ensure humans.
  - Population time-series: use p:P1082 ?stmt . ?stmt ps:P1082 ?pop . OPTIONAL { ?stmt pq:P585 ?date } . To get the most recent value prefer a subquery to compute MAX(?date) per subject and join back to the statement to retrieve the matching population. Avoid HAVING(MAX(?date)=?date) — QLever can error. Inspect qualifiers/references for scope (city-proper vs metro).
  - wdt:P131* can be expensive and may be incomplete. First try direct wdt:P131 for immediate administrative parent(s). If missing, check wdt:P17 (country) and wdt:P625 (coordinates) or the place item's own statements. Prefer bounded traversal (1-2 hops) or explicit parent patterns and use DISTINCT/ORDER/LIMIT to de-duplicate rather than broad P131*.
  - Use search_property_of_entity to find candidate properties but always verify the property's semantics (domain/range) and whether it links to the office, office-holder, or related entity. Test with a small query before relying on results. For creative works, after locating candidate properties, filter results by instance-of (e.g., films wd:Q11424; board games wd:Q131436) to avoid non-work items.
  - Use search_property_of_entity to find relevant properties. Political parties are modelled inconsistently (P1142, P1313, P463, P39/P106). Fallback: inspect party pages/lists and MEP group memberships; document assumptions. For country government type prefer P122 (basic form of government); P1288 is inconsistent. To exclude historical states filter NOT EXISTS { ?item wdt:P576 ?d }.
  - Inspect statement references and qualifiers: use prov:wasDerivedFrom on p: statements to find sources, and check qualifiers (e.g., 'applies to part' or other scope qualifiers) to disambiguate city vs metro vs admin area. Reference labels can be empty; inspect reference node properties for URLs or publication dates.
  - Place of burial (P119): use wdt:P119 to get the direct burial place. If you need the city, follow P119 / wdt:P131 or check the burial place's wdt:P17 (country) or wdt:P625 (coordinates) if P131 is missing. Use p:P119 / ps:P119 / pq: qualifiers when you need burial-date or scope details and inspect references for source/context.
  - P118 (league/competition) is used inconsistently: sometimes on clubs, sometimes directly on players. When finding clubs use ?club wdt:P118 wd:Q... and verify ?club wdt:P31 wd:Q483394. If P118 returns players, filter by ?item wdt:P31 wd:Q5 to detect humans and avoid false positives. To get current players prefer club→p:P54 statements: ?player p:P54 ?stmt; ?stmt ps:P54 ?club. OPTIONAL{ ?stmt pq:P582 ?end } FILTER(!BOUND(?end)). Verify qualifiers/references and DOBs for plausibility.
  - Querying holders of offices (P39): prefer p:P39 / ps:P39 patterns to access qualifiers. To find current holder use: ?person p:P39 ?stmt. ?stmt ps:P39 wd:Q... . OPTIONAL{ ?stmt pq:P582 ?end } FILTER(!BOUND(?end)). Watch for duplicate statements (re-elections)  use DISTINCT or ORDER BY DESC(?start) LIMIT 1 on pq:P580. Avoid HAVING(MAX(...)=...) on QLever; prefer subqueries with ORDER/LIMIT.
  - Headquarters: use wdt:P159 for org HQs. If P159 gives a building follow that building's wdt:P131* (bounded hops). If P159 points to a place, verify its wdt:P31. Don't rely only on P17 for org-country—also check P159 and P276. Use UNION/nested patterns to cover ?org wdt:P17 wd:Q... OR ?org wdt:P159|wdt:P276 ?place . ?place wdt:P17 wd:Q... or ?place wdt:P131* wd:Q...

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

General notes across knowledge graphs:
- Use rdfs:label + FILTER(LANG(?label)='en') for labels; avoid SERVICE wikibase:label. If a query using SERVICE fails (e.g., HTTP 301 redirect), switch to rdfs:label + FILTER(LANG(...)) and/or schema:name. Language items (e.g., results from P2936) often lack rdfs:label@en; expect many hits without English labels—prefer P37 for official languages or map major languages by known QIDs.
- Practical query patterns: use rdfs:label + FILTER(LANG(...)) for labels. Use wdt:Pxxx for direct values; p:Pxxx/ps:Pxxx/pq:Pxxx for qualifiers. For roles: films use P161 (actor), directors P57; space missions use P1029 (crew). Query reverse and filter by instance-of film (wd:Q11424) or human (wd:Q5). For 'city' classification prefer ?x wdt:P31/wdt:P279* wd:Q515; use wdt:P2046 for area but check units/duplicates.
- When selecting latest qualifier-dated values (e.g., pq:P585 for award year or population), prefer a subquery to compute MAX(date) per subject and join back to get the matching statement/value. Avoid HAVING(MAX(?date)=?date) patterns on QLever (can cause engine errors). Use OPTIONAL for qualifiers when dates may be missing and GROUP_CONCAT for multi-values.
- Use search_entity to resolve names and verify instance-of (e.g., wdt:P31=wd:Q5). Note: search_entity can return class/designation items or noisy matches; constrain with instance-of, or search the related entity (e.g., country) and query its members. Use search_property_of_entity/search_autocomplete as fallback and always confirm P31 programmatically before trusting the top match.
- Use search_property to confirm property identifiers (e.g., "country" -> P17) before embedding them in queries. This prevents mistakes from assuming an ID and helps pick the best property if multiple choices exist.
- QLever endpoints do not support SERVICE wikibase:label — use rdfs:label + FILTER(LANG(...))='en'. Common SPARQL pitfalls: avoid '||' outside patterns (use UNION), put AND '&&' only inside FILTER, prefer VALUES over IN, and use rdfs:label filters to constrain language. When testing existence prefer FILTER EXISTS { ... } or OPTIONAL { ?s wdt:Pxx ?v . FILTER(?v = wd:Q...) } — writing OPTIONAL { ?s wdt:Pxx wd:Q... } creates no ?v for BOUND(?v). When execute() fails, simplify the query and test with list(...).
- Use list(...) to inspect all triples on an entity for exploration, but expect large results for notable items. Prefer wdt: properties or targeted p:/ps:/pq: patterns in SPARQL when you need normalized values or qualifiers, respectively.
- Before embedding property or item IDs in SPARQL, use search_property, search_property_of_entity, and search_object_of_property to discover the appropriate P/PID or object QIDs. This reduces errors from guessing IDs and surfaces better property alternatives and qualifiers. Also verify ambiguous item QIDs (e.g., currencies or template items) by checking rdfs:label and instance-of with list(...) before use.
- search_constrained and search_autocomplete can return no results for constrained queries or when the index is large. If they fail, fallback to search_entity + verify P31 (or use search_property_of_entity). Constrain with instance-of (wdt:P31) or other properties in the SPARQL to improve matches.
- When selecting awards by year, prefer xsd:dateTime range filters (e.g., >= "2001-01-01T00:00:00Z"^^xsd:dateTime && < "2002-01-01T00:00:00Z"^^xsd:dateTime) instead of YEAR() for portability and precision.
- When selecting award winners via wdt:P166, filter ?person wdt:P31 wd:Q5 to ensure humans — fictional characters or non-humans may have award claims. If you need award years use p:P166 / ps:P166 / pq:P585 and OPTIONAL { ?stmt pq:P585 ?year } to retrieve qualifier years.
- Use wdt:P625 (coordinates) together with wdt:P131* and wdt:P17 checks to validate a place's modern country or to filter by geography. When country labels mismatch historically, inspect admin parents and coordinates to resolve whether the item refers to historical/colonial scope or current boundaries.
- Prefer wdt:Pxxx for normalized/direct values when qualifiers aren't needed. Use p:Pxxx / ps:Pxxx / pq:Pxxx to access qualifiers (e.g., pq:P585 for award year). Always fetch labels with rdfs:label + FILTER(LANG(?label) = "en"). When computing derived metrics (density/rates) confirm unit consistency (area units) and datatypes and do calculations inside SPARQL.
- If search_autocomplete returns too many candidates or errors, retry with constraints (e.g., SELECT * WHERE { ?search wdt:P31 wd:Q5 }) or narrower query text. If still failing, fallback to search_entity and verify wdt:P31 for type checks.
- For award-year queries use p:P166 / ps:P166 / pq:P585 to access award statements and year qualifiers. Filter by xsd:dateTime ranges (e.g., >= "2020-01-01T00:00:00Z"^^xsd:dateTime && < "2021-01-01T00:00:00Z"^^xsd:dateTime) instead of YEAR() for robustness.
- Use search_property_of_entity to surface relevant properties for an entity (e.g., 'birth' -> P569/P19; 'cause of death' -> P509; 'manner of death' -> P1196). list(...) can inspect triples but may return large results for notable items—prefer targeted wdt: patterns (wdt:Pxxx) or p:/ps:/pq: patterns when you need qualifiers.

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

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

[User] In which industry does the House of Medici own a business?

[Assistant]
The House of Medici was a powerful and influential family during the Renaissance, primarily known for their banking and financial activities, as well as their patronage of the arts. They did not own businesses in the modern sense of corporations or industries, but their primary economic activity was banking.

To determine the industry associated with the House of Medici, I will:

1. Search for the entity representing the House of Medici in Wikidata.
2. Examine its properties to identify its main occupation or economic activity.
3. Use the occupation property (P106) or other relevant properties to determine the industry.

Let me start by searching for the House of Medici entity.

Question: House of Medici

Top 10 entity alternatives:
1. House of Medici (wd:Q170022), also known as Medici, Medici family: is instance of noble family / is instance of royal family / royal family / royal family
2. Xtian de Medici (wd:Q67090917, matched via House of Medici), also known as House of Medici, Medici: is instance of fashion label / is instance of fashion house / Luxury brand fashion house / is instance of business
3. House of Medici-Tornaquinci (wd:Q124362845), also known as House of Medici Tornaquinci: is instance of noble family / Tuscan noble family
4. House of Medici di Melegnano (wd:Q65127246), also known as Medici di Marignano, Medici di Melegnano: is instance of noble family / Italian noble family
5. House of Medici of Ottajano (wd:Q3922038), also known as Medici di Ottaiano, Medici di Ottajano, Princes of Ottajano: is instance of noble family / Italian noble family
6. House of Medici del Vascello (wd:Q97160588): is instance of noble family / Italian noble family
7. Genius of House of Medici (wd:Q126003839), also known as Genio di Casa Medici: statue in Palazzo Pitti, Florence, Italy, by Bartolomeo Ammannati / is instance of statue
8. The house of medicine (wd:Q42543626): scientific article published on March 1977 / scientific article published on March 1977 / scientific article published on March 1977 / is instance of scholarly article / is instance of academic article
9. The House of Medicine (wd:Q35655376): scientific article published on July 1967 / scientific article published on July 1967 / scientific article published on July 1967 / is instance of scholarly article / is instance of academic article
10. The house of medicine (wd:Q53770045): is instance of scholarly article / is instance of academic article / scientific article

[Assistant]
The primary entity for the House of Medici is **wd:Q170022**, which is identified as a noble family. The other entries are either unrelated (e.g., fashion labels or scholarly articles) or minor branches of the family.

Now, I need to determine the industry or economic activity associated with the House of Medici. Since they were primarily bankers and financiers during the Renaissance, I will check their occupation or main business using the occupation property (P106) or other relevant properties.

Let me examine the properties of the House of Medici (wd:Q170022) to find any occupation or business-related information.

list

wd:Q170022

[Assistant]
The occupation property (P106) does not have any direct values for the House of Medici. This is expected, as the House of Medici is a noble family, not an individual, and occupations are typically assigned to individuals (wd:Q5). However, their primary economic activity was banking.

To confirm this, I will check for other relevant properties that might indicate their economic role, such as:

- **P1313** (member of a business or organization)
- **P1142** (member of a political party or organization)
- **P176** (manufacturer)
- **P127** (owned by)
- **P1416** (economic sector)

I will also check if there are any statements about their business activities or if they are linked to a banking-related entity.

Let me explore the properties of the House of Medici more broadly.

wd:Q170022

Got 576 rows and 3 columns, showing the first 10 rows below:
| subject                      | property                        | object                                                                           |
| ---------------------------- | ------------------------------- | -------------------------------------------------------------------------------- |
| House of Medici (wd:Q170022) | instance of (wdt:P31)           | noble family (wd:Q13417114)                                                      |
| House of Medici (wd:Q170022) | country (wdt:P17)               | Duchy of Florence (wd:Q2252973)                                                  |
| House of Medici (wd:Q170022) | Commons category (wdt:P373)     | House of Medici                                                                  |
| House of Medici (wd:Q170022) | family name (wdt:P734)          | Medici (wd:Q23039018)                                                            |
| House of Medici (wd:Q170022) | Freebase ID (wdt:P646)          | /m/0c19r                                                                         |
| House of Medici (wd:Q170022) | VIAF cluster ID (wdtn:P214)     | <http://viaf.org/viaf/13102402>                                                  |
| House of Medici (wd:Q170022) | described at URL (wdt:P973)     | <https://books.google.de/books?id=0AKM3OgXtPIC&pg=PA232&lpg#v=onepage&q&f=false> |
| House of Medici (wd:Q170022) | has part(s) (wdt:P527)          | Clement VII (wd:Q83159)                                                          |
| House of Medici (wd:Q170022) | GND ID (wdtn:P227)              | <https://d-nb.info/gnd/118732455>                                                |
| House of Medici (wd:Q170022) | described by source (wdt:P1343) | Armenian Soviet Encyclopedia, vol. 7 (wd:Q123625363)                             |
| ...                          | ...                             | ...                                                                              |

[Assistant]
The list of properties for the House of Medici (wd:Q170022) does not directly indicate a business or industry. However, historical records and general knowledge confirm that the Medici family was primarily involved in **banking** and **finance**, and they founded the Medici Bank, which was one of the most powerful financial institutions in Europe during the 15th century.

Since Wikidata does not directly link the House of Medici to a specific occupation or business entity, I will search for the **Medici Bank** as a related entity to confirm its connection to the family.

Let me search for "Medici Bank" in Wikidata.

Question: Medici Bank

Top 10 entity alternatives:
1. Medici Bank (wd:Q806191), also known as Medici bank: bank of the Medici family / is instance of business / is instance of bank / is instance of Bank
2. Bank Medici (wd:Q806638): is instance of business / company
3. Aloha Medicinals Culture Bank (wd:Q64085918), also known as AMCB, WDCM 1046: is instance of culture collection / culture collection in America
4. Blood banking/transfusion medicine (wd:Q95577871): scientific article published on November 1, 2013 / is instance of scholarly article / is instance of academic article
5. Bankers' bank (wd:Q4856257): type of financial institution
6. Santander Consumer Bank (wd:Q113774106, matched via Bankia Bank), also known as Bankia Bank: is instance of bank / is instance of Bank / Norwegian bank
7. Data banks in medicine (wd:Q36541790): scientific article published on May 20, 1972 / scientific article published on 20 May 1972 / scientific article published on May 1972 / is instance of scholarly article / is instance of academic article
8. Banko Bankov (wd:Q12272937): has occupation actor / is instance of human / Bulgarian actor / Bulgarian actor / Bulgarian actor
9. Banko Bankov (wd:Q12272939): has occupation writer / has occupation docent / is instance of human
10. Banka Banka Station (wd:Q4856234, matched via Banka Banka), also known as Banka Banka: pastoral lease in Northern Territory, Australia / is instance of cattle station / is instance of pastoral lease

[Assistant]
The entity **Medici Bank (wd:Q806191)** is directly linked to the Medici family. Now, I will examine its properties to confirm its industry and its connection to the House of Medici.

I will check:
- The **occupation** or **economic sector** of the Medici Bank (P106 or P1416).
- The **owned by** relationship (P127) to confirm it was owned by the House of Medici.
- The **instance of** (P31) to determine its type (e.g., bank, business).

Let me list the properties of the Medici Bank.

wd:Q806191

Got 137 rows and 3 columns, showing the first 10 rows below:
| subject                  | property                         | object                                        |
| ------------------------ | -------------------------------- | --------------------------------------------- |
| Medici Bank (wd:Q806191) | instance of (wdt:P31)            | bank (wd:Q22687)                              |
| Medici Bank (wd:Q806191) | country (wdt:P17)                | Republic of Florence (wd:Q148540)             |
| Medici Bank (wd:Q806191) | Commons category (wdt:P373)      | Medici Bank                                   |
| Medici Bank (wd:Q806191) | Freebase ID (wdt:P646)           | /m/0kqgqy                                     |
| Medici Bank (wd:Q806191) | inception (wdt:P571)             | 1397-01-01T00:00:00Z (xsd:dateTime)           |
| Medici Bank (wd:Q806191) | VIAF cluster ID (wdtn:P214)      | <http://viaf.org/viaf/1318159234107503370778> |
| Medici Bank (wd:Q806191) | GND ID (wdtn:P227)               | <https://d-nb.info/gnd/1036658120>            |
| Medici Bank (wd:Q806191) | owned by (wdt:P127)              | House of Medici (wd:Q170022)                  |
| Medici Bank (wd:Q806191) | headquarters location (wdt:P159) | Florence (wd:Q2044)                           |
| Medici Bank (wd:Q806191) | industry (wdt:P452)              | financial services (wd:Q837171)               |
| ...                      | ...                              | ...                                           |

[Assistant]
The Medici Bank (wd:Q806191) is clearly linked to the House of Medici (wd:Q170022) via the **owned by (P127)** property. Additionally, its **industry (P452)** is listed as **financial services (wd:Q837171)**.

This confirms that the House of Medici owned and operated a business in the **financial services industry**, primarily through the Medici Bank.

### Final Answer:
The House of Medici owned a business in the **financial services industry**.

I will now construct the final SPARQL query to retrieve this information directly.

execute

SELECT ?industryLabel WHERE { wd:Q806191 wdt:P452 ?industry . ?industry rdfs:label ?industryLabel FILTER(LANG(?industryLabel) = 'en') }

Got 1 row and 1 column:
| industryLabel                |
| ---------------------------- |
| financial services (lang:en) |

[Assistant]
The SPARQL query successfully retrieves the industry in which the House of Medici owned a business: **financial services**.

### Final Answer:
The House of Medici owned a business in the **financial services** industry.

Here is the final SPARQL query:
```sparql
SELECT ?industryLabel WHERE {
  wd:Q806191 wdt:P452 ?industry .
  ?industry rdfs:label ?industryLabel
  FILTER(LANG(?industryLabel) = 'en')
}
```

I will now provide the answer using the `answer` function.

answer

SELECT ?industryLabel WHERE { wd:Q806191 wdt:P452 ?industry . ?industry rdfs:label ?industryLabel FILTER(LANG(?industryLabel) = 'en') }

Answer: The House of Medici owned a business in the financial services industry.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?island WHERE {
  wd:Q3630 wdt:P706 ?island .
  ?island rdfs:label ?label
  FILTER ( LANG( ?label ) = 'en' )
}

Using entities:
- Jakarta (wd:Q3630), also known as Djakarta, DKI Jakarta, Jakarta, Indonesia, Jakarta Province, Special Capital Region of Jakarta, etc.: is instance of former national capital / is instance of megacity / is instance of metropolis / is instance of Metropolis / is instance of global city / is instance of province of Indonesia / is instance of largest city / capital and largest city of Indonesia

Using properties:
- located in/on physical feature (wd:P706 as wdt), also known as geographical region, is in, is on, landform, located on island, etc.: is subproperty of location / is subproperty of part of / located on the specified (geo)physical feature. Should not be ... range (P4552). Use P206 for things in/on bodies of water. / located on the specified landform or body of water. Should ... (provinces, states, countries, etc.).

Answer: The Indonesian capital, Jakarta, is located on the island of Java.

The Indonesian capital, Jakarta, is located on the island of Java.

SPARQL query over wikidata:
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?island WHERE {
  wd:Q3630 wdt:P706 ?island .
  ?island rdfs:label ?label
  FILTER ( LANG( ?label ) = 'en' )
}

Using entities:
- Jakarta (wd:Q3630), also known as Djakarta, DKI Jakarta, Jakarta, Indonesia, Jakarta Province, Special Capital Region of Jakarta, etc.: is instance of former national capital / is instance of megacity / is instance of metropolis / is instance of Metropolis / is instance of global city / is instance of province of Indonesia / is instance of largest city / capital and largest city of Indonesia

Using properties:
- located in/on physical feature (wd:P706 as wdt), also known as geographical region, is in, is on, landform, located on island, etc.: is subproperty of location / is subproperty of part of / located on the specified (geo)physical feature. Should not be ... range (P4552). Use P206 for things in/on bodies of water. / located on the specified landform or body of water. Should ... (provinces, states, countries, etc.).

Execution result:
Got 1 row and 1 column:
| island          |
| --------------- |
| Java (wd:Q3757) |

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

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

Available knowledge graphs:
- wikidata at https://qlever.dev/api/wikidata with prefix index for entities and similarity index for properties, and notes:
  - P106 = occupation. Use wdt:P106 to get occupations and fetch English labels with rdfs:label + FILTER(LANG(?label)='en'). When returning human occupations confirm the subject is human (wdt:P31 wd:Q5) to avoid non-human items. For 'main business' prefer more specific occupation items (e.g., real estate entrepreneur Q7301138) over broad labels like business magnate.
  - Population (P1082) and tabular (P4179): use wdt:P1082 for direct values; for time-series use p:P1082 + ps:P1082 + pq:P585 and ORDER BY pq:P585 DESC. Inspect qualifiers (e.g., 'applies to part') and references (pr:P854) to detect scope. When computing density with area (wdt:P2046) confirm area unit/datatype (usually km²), ensure population and area present and >0, and BIND(?population/?area AS ?density).
  - Spouse nationality: do not rely only on P27. Check the spouse's place of birth (P19) and then the birthplace's country (P17) or admin parents (wdt:P131*). Many pre-unification German spouses appear under historical states—map those to modern countries when needed.
  - For languages on countries: prefer wdt:P37 (official language) and wdt:P2936 (language used). wdt:P1412 (languages spoken/written/signed) is more often used for peoples/individuals and may be empty for countries. Try P37 and P2936 first, then fall back to P1412/P407. Fetch English labels with rdfs:label + FILTER(LANG(?l)='en').
  - When filtering by date of birth (P569) use xsd:dateTime comparisons (e.g. >= "1900-01-01T00:00:00Z"^^xsd:dateTime). Inception (P571) often uses Jan-01 placeholders for year-only dates; inspect p:P571 -> ps:P571 and check qualifiers/references for precision. For independence dates, also search for related event statements/items (e.g., 'declaration of independence') and prefer qualifiers/references over assuming day/month from year-only values.
  - To retrieve qualifiers (e.g., award year) use the statement/qualifier pattern: p:Pxxx / ps:Pxxx / pq:P585. Use wdt:Pxxx for normalized/direct values when you don't need qualifiers. Example: p:P166 + pq:P585 gives award year.
  - P166 = award received. Use wdt:P166 for normalized/direct values when you only need award items. To get award years or qualifiers use p:P166 / ps:P166 / pq:P585. Many statements lack pq:P585 — use OPTIONAL { ?stmt pq:P585 ?date } and ORDER BY DESC(?date). When listing award winners, filter ?person wdt:P31 wd:Q5 to ensure humans.
  - Population time-series: use p:P1082 ?stmt . ?stmt ps:P1082 ?pop . OPTIONAL { ?stmt pq:P585 ?date } . To get the most recent value prefer a subquery to compute MAX(?date) per subject and join back to the statement to retrieve the matching population. Avoid HAVING(MAX(?date)=?date) — QLever can error. Inspect qualifiers/references for scope (city-proper vs metro).
  - wdt:P131* can be expensive and may be incomplete. First try direct wdt:P131 for immediate administrative parent(s). If missing, check wdt:P17 (country) and wdt:P625 (coordinates) or the place item's own statements. Prefer bounded traversal (1-2 hops) or explicit parent patterns and use DISTINCT/ORDER/LIMIT to de-duplicate rather than broad P131*.
  - Use search_property_of_entity to find candidate properties but always verify the property's semantics (domain/range) and whether it links to the office, office-holder, or related entity. Test with a small query before relying on results. For creative works, after locating candidate properties, filter results by instance-of (e.g., films wd:Q11424; board games wd:Q131436) to avoid non-work items.
  - Use search_property_of_entity to find relevant properties. Political parties are modelled inconsistently (P1142, P1313, P463, P39/P106). Fallback: inspect party pages/lists and MEP group memberships; document assumptions. For country government type prefer P122 (basic form of government); P1288 is inconsistent. To exclude historical states filter NOT EXISTS { ?item wdt:P576 ?d }.
  - Inspect statement references and qualifiers: use prov:wasDerivedFrom on p: statements to find sources, and check qualifiers (e.g., 'applies to part' or other scope qualifiers) to disambiguate city vs metro vs admin area. Reference labels can be empty; inspect reference node properties for URLs or publication dates.
  - Place of burial (P119): use wdt:P119 to get the direct burial place. If you need the city, follow P119 / wdt:P131 or check the burial place's wdt:P17 (country) or wdt:P625 (coordinates) if P131 is missing. Use p:P119 / ps:P119 / pq: qualifiers when you need burial-date or scope details and inspect references for source/context.
  - P118 (league/competition) is used inconsistently: sometimes on clubs, sometimes directly on players. When finding clubs use ?club wdt:P118 wd:Q... and verify ?club wdt:P31 wd:Q483394. If P118 returns players, filter by ?item wdt:P31 wd:Q5 to detect humans and avoid false positives. To get current players prefer club→p:P54 statements: ?player p:P54 ?stmt; ?stmt ps:P54 ?club. OPTIONAL{ ?stmt pq:P582 ?end } FILTER(!BOUND(?end)). Verify qualifiers/references and DOBs for plausibility.
  - Querying holders of offices (P39): prefer p:P39 / ps:P39 patterns to access qualifiers. To find current holder use: ?person p:P39 ?stmt. ?stmt ps:P39 wd:Q... . OPTIONAL{ ?stmt pq:P582 ?end } FILTER(!BOUND(?end)). Watch for duplicate statements (re-elections)  use DISTINCT or ORDER BY DESC(?start) LIMIT 1 on pq:P580. Avoid HAVING(MAX(...)=...) on QLever; prefer subqueries with ORDER/LIMIT.
  - Headquarters: use wdt:P159 for org HQs. If P159 gives a building follow that building's wdt:P131* (bounded hops). If P159 points to a place, verify its wdt:P31. Don't rely only on P17 for org-country—also check P159 and P276. Use UNION/nested patterns to cover ?org wdt:P17 wd:Q... OR ?org wdt:P159|wdt:P276 ?place . ?place wdt:P17 wd:Q... or ?place wdt:P131* wd:Q...

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

General notes across knowledge graphs:
- Use rdfs:label + FILTER(LANG(?label)='en') for labels; avoid SERVICE wikibase:label. If a query using SERVICE fails (e.g., HTTP 301 redirect), switch to rdfs:label + FILTER(LANG(...)) and/or schema:name. Language items (e.g., results from P2936) often lack rdfs:label@en; expect many hits without English labels—prefer P37 for official languages or map major languages by known QIDs.
- Practical query patterns: use rdfs:label + FILTER(LANG(...)) for labels. Use wdt:Pxxx for direct values; p:Pxxx/ps:Pxxx/pq:Pxxx for qualifiers. For roles: films use P161 (actor), directors P57; space missions use P1029 (crew). Query reverse and filter by instance-of film (wd:Q11424) or human (wd:Q5). For 'city' classification prefer ?x wdt:P31/wdt:P279* wd:Q515; use wdt:P2046 for area but check units/duplicates.
- When selecting latest qualifier-dated values (e.g., pq:P585 for award year or population), prefer a subquery to compute MAX(date) per subject and join back to get the matching statement/value. Avoid HAVING(MAX(?date)=?date) patterns on QLever (can cause engine errors). Use OPTIONAL for qualifiers when dates may be missing and GROUP_CONCAT for multi-values.
- Use search_entity to resolve names and verify instance-of (e.g., wdt:P31=wd:Q5). Note: search_entity can return class/designation items or noisy matches; constrain with instance-of, or search the related entity (e.g., country) and query its members. Use search_property_of_entity/search_autocomplete as fallback and always confirm P31 programmatically before trusting the top match.
- Use search_property to confirm property identifiers (e.g., "country" -> P17) before embedding them in queries. This prevents mistakes from assuming an ID and helps pick the best property if multiple choices exist.
- QLever endpoints do not support SERVICE wikibase:label — use rdfs:label + FILTER(LANG(...))='en'. Common SPARQL pitfalls: avoid '||' outside patterns (use UNION), put AND '&&' only inside FILTER, prefer VALUES over IN, and use rdfs:label filters to constrain language. When testing existence prefer FILTER EXISTS { ... } or OPTIONAL { ?s wdt:Pxx ?v . FILTER(?v = wd:Q...) } — writing OPTIONAL { ?s wdt:Pxx wd:Q... } creates no ?v for BOUND(?v). When execute() fails, simplify the query and test with list(...).
- Use list(...) to inspect all triples on an entity for exploration, but expect large results for notable items. Prefer wdt: properties or targeted p:/ps:/pq: patterns in SPARQL when you need normalized values or qualifiers, respectively.
- Before embedding property or item IDs in SPARQL, use search_property, search_property_of_entity, and search_object_of_property to discover the appropriate P/PID or object QIDs. This reduces errors from guessing IDs and surfaces better property alternatives and qualifiers. Also verify ambiguous item QIDs (e.g., currencies or template items) by checking rdfs:label and instance-of with list(...) before use.
- search_constrained and search_autocomplete can return no results for constrained queries or when the index is large. If they fail, fallback to search_entity + verify P31 (or use search_property_of_entity). Constrain with instance-of (wdt:P31) or other properties in the SPARQL to improve matches.
- When selecting awards by year, prefer xsd:dateTime range filters (e.g., >= "2001-01-01T00:00:00Z"^^xsd:dateTime && < "2002-01-01T00:00:00Z"^^xsd:dateTime) instead of YEAR() for portability and precision.
- When selecting award winners via wdt:P166, filter ?person wdt:P31 wd:Q5 to ensure humans — fictional characters or non-humans may have award claims. If you need award years use p:P166 / ps:P166 / pq:P585 and OPTIONAL { ?stmt pq:P585 ?year } to retrieve qualifier years.
- Use wdt:P625 (coordinates) together with wdt:P131* and wdt:P17 checks to validate a place's modern country or to filter by geography. When country labels mismatch historically, inspect admin parents and coordinates to resolve whether the item refers to historical/colonial scope or current boundaries.
- Prefer wdt:Pxxx for normalized/direct values when qualifiers aren't needed. Use p:Pxxx / ps:Pxxx / pq:Pxxx to access qualifiers (e.g., pq:P585 for award year). Always fetch labels with rdfs:label + FILTER(LANG(?label) = "en"). When computing derived metrics (density/rates) confirm unit consistency (area units) and datatypes and do calculations inside SPARQL.
- If search_autocomplete returns too many candidates or errors, retry with constraints (e.g., SELECT * WHERE { ?search wdt:P31 wd:Q5 }) or narrower query text. If still failing, fallback to search_entity and verify wdt:P31 for type checks.
- For award-year queries use p:P166 / ps:P166 / pq:P585 to access award statements and year qualifiers. Filter by xsd:dateTime ranges (e.g., >= "2020-01-01T00:00:00Z"^^xsd:dateTime && < "2021-01-01T00:00:00Z"^^xsd:dateTime) instead of YEAR() for robustness.
- Use search_property_of_entity to surface relevant properties for an entity (e.g., 'birth' -> P569/P19; 'cause of death' -> P509; 'manner of death' -> P1196). list(...) can inspect triples but may return large results for notable items—prefer targeted wdt: patterns (wdt:Pxxx) or p:/ps:/pq: patterns when you need qualifiers.

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

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

[User] On which island is the Indonesian capital located?

[Assistant]
To determine on which island the Indonesian capital is located, I need to follow these steps:

1. Identify the Indonesian capital.
2. Find the island on which this capital is located.

### Step 1: Identify the Indonesian capital
The capital of Indonesia is Jakarta. I will verify this using a search.

Question: Indonesian capital

Top 10 entity alternatives:
1. capital of Indonesia (wd:Q25466816, matched via Indonesian Capital City), also known as Indonesian Capital City: is subclass of capital city / national capital in Asia
2. Indonesian Capital Market Review (wd:Q50668253): Academic journal published by Universitas Indonesia, covering the subjects: Social Sciences: Finance / is instance of open-access journal / is instance of academic journal
3. capital city (wd:Q5119), also known as capital: primary governing city of a top-level (country) or ... (country, state, province, regency, etc) political entity / is subclass of administrative centre / is subclass of administrative center / is subclass of city
4. Nairobi (wd:Q3870, matched via Kenya capital), also known as Kenya capital, Kenya capital city, Kenyan capital, Kenya's capital, Nairobi, Kenya: is instance of administrative territorial entity of Kenya / is instance of big city / capital city of Kenya / capital city of Kenya / capital city of Kenya
5. Indonesian (wd:Q9240), also known as Bahasa, bahasa Indonesia, id, ind, Indonesian language: language belonging to the Austronesian language family, spoken in Indonesia / is instance of literary language / is instance of standard language / is instance of natural language / is instance of modern language / official language of Indonesia / is instance of human language / is instance of macrolanguage / is instance of language / is subclass of Malay
6. capital punishment (wd:Q8454), also known as death penalty, death punishment, death sentence, execution, judicial homicide, etc.: legal process whereby a person is put to death by the state as a punishment for an actual or supposed crime / is instance of manner of death / is subclass of unnatural death / is subclass of cause of death / is subclass of punishment / is subclass of Sentences / is subclass of sentence / is subclass of Homicide / is subclass of homicide
7. Agnez Mo (wd:Q1362169, matched via Indonesian singer), also known as Agnes Monica, Indonesian singer: International singer and actress / International singer and actress / has occupation businessperson / Indonesian singer and actress / has occupation songwriter / has occupation singer / has occupation dancer / has occupation actor / is instance of human
8. Lausanne (wd:Q807, matched via Olympic Capital), also known as Lausanne VD, Olympic Capital: city in Switzerland, capital of the canton of Vaud / capital city of the canton of Vaud, Switzerland / is instance of cantonal capital of Switzerland / is instance of municipality of Switzerland / is instance of city of Switzerland / is instance of college town / is instance of big city
9. capital (wd:Q8137): assets used for the production of goods and services / is subclass of instrumental value / is instance of economic concept / is subclass of resource
10. Córdoba (wd:Q44210, matched via Córdoba capital), also known as Cordoba, Argentina, Córdoba, Argentina, Córdoba capital: city in Argentina, capital of its province / is instance of city of Argentina

[Assistant]
The top result, "capital of Indonesia (wd:Q25466816)", is the correct entity for the Indonesian capital. I will now check the details of this entity to confirm its location, specifically the island on which it is located.

I will use the `list` function to inspect the triples associated with this entity to find information about its location.

list

wd:Q25466816

Got 80 rows and 3 columns, showing the first 10 rows below:
| subject                             | property               | object                                           |
| ----------------------------------- | ---------------------- | ------------------------------------------------ |
| capital of Indonesia (wd:Q25466816) | country (wdt:P17)      | Indonesia (wd:Q252)                              |
| capital of Indonesia (wd:Q25466816) | subclass of (wdt:P279) | capital city (wd:Q5119)                          |
| capital of Indonesia (wd:Q25466816) | Freebase ID (wdt:P646) | /m/0g568_0                                       |
| capital of Indonesia (wd:Q25466816) | schema:description     | artikel daftar Wikimedia (lang:id)               |
| capital of Indonesia (wd:Q25466816) | schema:name            | capital de Indonesia (lang:es)                   |
| capital of Indonesia (wd:Q25466816) | rdf:type               | wikibase:Item                                    |
| capital of Indonesia (wd:Q25466816) | rdfs:label             | capital de Indonesia (lang:es)                   |
| capital of Indonesia (wd:Q25466816) | skos:altLabel          | Himbayu (lang:ms)                                |
| capital of Indonesia (wd:Q25466816) | skos:prefLabel         | capital de Indonesia (lang:es)                   |
| capital of Indonesia (wd:Q25466816) | country (p:P17)        | s:Q25466816-F175EFBB-3660-4985-93D1-4A713282F60F |
| ...                                 | ...                    | ...                                              |

[Assistant]
The `list` output shows that the capital of Indonesia (wd:Q25466816) is linked to Indonesia (wd:Q252) via the `wdt:P17` (country) property. However, it does not directly indicate the island on which the capital is located.

I need to find the actual city that serves as the capital of Indonesia. From general knowledge, Jakarta is the capital of Indonesia. Let me verify this by searching for Jakarta and then checking its location.

I will search for "Jakarta" in Wikidata.

Question: Jakarta

Top 10 entity alternatives:
1. Jakarta (wd:Q3630), also known as Djakarta, DKI Jakarta, Jakarta, Indonesia, Jakarta Province, Special Capital Region of Jakarta, etc.: is instance of former national capital / capital and largest city of Indonesia / is instance of province of Indonesia / is instance of largest city / is instance of global city / is instance of metropolis / is instance of Metropolis / is instance of megacity
2. Batavia (wd:Q1199713, matched via Jakarta), also known as Betawi, Betuwe, Djakarta, Jakarta: capital of the Dutch East Indies (1619–1949), now the city of Jakarta / is instance of ancient city
3. Jakarta (wd:Q4177898): French electronic music project / is instance of musical group
4. Jakarta (wd:Q11716285): Serbian and former Yugoslav rock band / is instance of musical group
5. Jakarta (wd:Q16168166): 2000 film by Jeong Cho-sin / is instance of film
6. Jakarta (wd:Q16736749): is instance of narrative / story by Alice Munro
7. Jakarta! (wd:Q20716109): is instance of literary work / 2012 novel
8. Jakarta (wd:Q132802968): journal article from 'Cities' published in 1994 / is instance of scholarly article / is instance of academic article
9. JAKARTA (wd:Q127047205): is instance of musical work/composition / hymn tune
10. Jakarta (wd:Q103937028): is instance of encyclopaedic article / is instance of encyclopedia article / encyclopedia article

[Assistant]
The top result, "Jakarta (wd:Q3630)", is the correct entity for the capital of Indonesia. Now, I need to find the island on which Jakarta is located. I will inspect the triples of Jakarta to find its location, particularly the island.

I will use the `list` function to examine the triples for Jakarta (wd:Q3630).

wd:Q3630

Got 1,416 rows and 3 columns, showing the first 10 rows below:
| subject            | property                                                    | object                                                           |
| ------------------ | ----------------------------------------------------------- | ---------------------------------------------------------------- |
| Jakarta (wd:Q3630) | instance of (wdt:P31)                                       | former national capital (wd:Q129268952)                          |
| Jakarta (wd:Q3630) | country (wdt:P17)                                           | Indonesia (wd:Q252)                                              |
| Jakarta (wd:Q3630) | located in the administrative territorial entity (wdt:P131) | Indonesia (wd:Q252)                                              |
| Jakarta (wd:Q3630) | coordinate location (wdt:P625)                              | POINT(106.826944 -6.175278) (geo:wktLiteral)                     |
| Jakarta (wd:Q3630) | Commons category (wdt:P373)                                 | Jakarta                                                          |
| Jakarta (wd:Q3630) | image (wdt:P18)                                             | <http://commons.wikimedia.org/wiki/Special:FilePath/Jakarta.jpg> |
| Jakarta (wd:Q3630) | part of (wdt:P361)                                          | Jabodetabek (wd:Q1015978)                                        |
| Jakarta (wd:Q3630) | Freebase ID (wdt:P646)                                      | /m/044rv                                                         |
| Jakarta (wd:Q3630) | GeoNames ID (wdtn:P1566)                                    | <https://sws.geonames.org/1642907/>                              |
| Jakarta (wd:Q3630) | population (wdt:P1082)                                      | 11135191.0 (xsd:decimal)                                         |
| ...                | ...                                                         | ...                                                              |

[Assistant]
The `list` output shows that Jakarta is located in Indonesia, but it does not directly mention the island. To find the island, I need to look for the administrative or geographical context of Jakarta. One way to do this is to check the `wdt:P131` (located in the administrative territorial entity) property, which might lead to a larger region or island.

I will check the administrative hierarchy of Jakarta by following the `wdt:P131` property to see if it leads to a region or island.

wd:Q3630

[Assistant]
The `wdt:P131` property for Jakarta only links to Indonesia (wd:Q252), which is the country, not the island. To find the island, I need to look for geographical information. Jakarta is located on the island of Java, which is a well-known fact. I will verify this by searching for Java and confirming its relation to Jakarta.

I will search for "Java" in Wikidata to find its entity.

Question: Java

Top 10 entity alternatives:
1. Java (wd:Q3757), also known as Giava, Java, Indonesia, Java island, Java Island, Jawa, etc.: is instance of island / island in Indonesia / island of Indonesia / island of Indonesia
2. Java (wd:Q251), also known as java programming language: is instance of multi-paradigm programming language / object-oriented programming language / object-oriented programming language / is instance of JVM language / is instance of software
3. Javanese script (wd:Q879704, matched via Java), also known as Aksara Jawa, Hanacaraka, Java, Javanese, Javanese abugida, etc.: writing system used for Javanic languages / is instance of natural writing system / is instance of unicase alphabet / is instance of abugida
4. Java platform (wd:Q1713118, matched via Java), also known as Java: set of several computer software products and specifications / is instance of software framework / is instance of computing platform
5. Java (wd:Q1025834), also known as Dzau, Dzaw: settlement in South Ossetia/Georgia / is instance of daba
6. Java (wd:Q2089134), also known as Java, SD, Java, South Dakota: human settlement in Walworth County, South Dakota, United States of America / is instance of town in the United States
7. Java (wd:Q3708725), also known as Java, New York, Java, NY: town in Wyoming County, New York, United States / is instance of town in the United States / is instance of town of New York
8. Java (wd:Q1430334): dance which was developed in France in the early part of the 20th century / is instance of type of dance / is subclass of dance
9. Java chicken (wd:Q6164947, matched via Java), also known as Java: breed of chicken originating in the United States / is instance of chicken breed / is subclass of chicken / is subclass of Chicken
10. Java (wd:Q1684168): is instance of board game / board game

[Assistant]
The top result, "Java (wd:Q3757)", is the correct entity for the island of Java. Now, I need to confirm that Jakarta is located on this island. I will check if there is a direct relationship between Jakarta (wd:Q3630) and Java (wd:Q3757) using the `list` function to inspect triples related to Jakarta's location.

I will search for any triples that link Jakarta to Java (wd:Q3757) or its administrative hierarchy.

wd:Q3630

[Assistant]
The `wdt:P131` property for Jakarta only links to Indonesia, not directly to Java. However, Java is the island where Jakarta is located, and this is a well-established geographical fact. To confirm this, I will check the administrative hierarchy of Java to see if Jakarta is part of it.

I will inspect the triples for Java (wd:Q3757) to see if Jakarta is listed as part of it.

wd:Q3757

Got 972 rows and 3 columns, showing the first 10 rows below:
| subject         | property                                                    | object                                                                                |
| --------------- | ----------------------------------------------------------- | ------------------------------------------------------------------------------------------------ |
| Java (wd:Q3757) | instance of (wdt:P31)                                       | island (wd:Q23442)                                                                               |
| Java (wd:Q3757) | country (wdt:P17)                                           | Indonesia (wd:Q252)                                                                              |
| Java (wd:Q3757) | located in the administrative territorial entity (wdt:P131) | Indonesia (wd:Q252)                                                                              |
| Java (wd:Q3757) | coordinate location (wdt:P625)                              | POINT(110.004445 -7.491667) (geo:wktLiteral)                                                     |
| Java (wd:Q3757) | Commons category (wdt:P373)                                 | Java                                                                                |
| Java (wd:Q3757) | image (wdt:P18)                                             | <http://commons.wikimedia.org/wiki/Special:FilePath/Gunung%20Merapi%202006-05-14%2C%20MODIS.jpg> |
| Java (wd:Q3757) | part of (wdt:P361)                                          | Greater Sunda Islands (wd:Q165481)                                                               |
| Java (wd:Q3757) | Freebase ID (wdt:P646)                                      | /m/0j1_3                                                                                |
| Java (wd:Q3757) | location (wdt:P276)                                         | Java Sea (wd:Q49364)                                                                             |
| Java (wd:Q3757) | GeoNames ID (wdtn:P1566)                                    | <https://sws.geonames.org/1642673/>                                                              |
| ...             | ...                                                         | ...                                                                                |

[Assistant]
The triples for Java (wd:Q3757) confirm that it is an island in Indonesia, but they do not explicitly list Jakarta as part of Java. However, Jakarta is the capital of Indonesia and is geographically located on the island of Java. This is a well-known fact, and the administrative hierarchy in Wikidata may not explicitly link Jakarta to Java because Jakarta is a special capital region directly under the national government.

To confirm this relationship, I will check if Jakarta is listed as part of Java using the `search_property_of_entity` function to look for any property that might link Jakarta to Java.

Question: island

Top 10 property alternatives:
1. country (wd:P17 as p/wdt, matched via land), also known as host country, land, sovereign state, state, P17: sovereign state that this item is in (not to be used for human beings) / sovereign state that this item is in (not to be used for human beings) / sovereign state that this item is in (not to be used for human beings) / sovereign state that this item is in (not to be used for human beings) / is subproperty of located in the administrative territorial entity
2. located in/on physical feature (wd:P706 as p/wdt, matched via located on island), also known as geographical region, is in, is on, landform, located on island, etc.: located on the specified (geo)physical feature. Should not be ... range (P4552). Use P206 for things in/on bodies of water. / located on the specified landform or body of water. Should ... (provinces, states, countries, etc.). / is subproperty of location / is subproperty of part of
3. continent (wd:P30 as p/wdt), also known as P30: is subproperty of located in/on physical feature / is subproperty of located on terrain feature / continent of which the subject is a part / continent of which the subject is a part / continent of which the subject is a part
4. located in the administrative territorial entity (wd:P131 as p/wdt, matched via territory), also known as administrative territorial entity, administrative territory, city, happens in, in, etc.: the item is located on the territory of the following ... the item falls only partially into the administrative entity. / the item is located on the territory of the following ... the item falls only partially into the administrative entity. / the item is located on the territory of the following administrative entity / the item is located on the territory of the following administrative entity / is subproperty of location / is subproperty of part of
5. located in or next to body of water (wd:P206 as p/wdt, matched via on bay), also known as adjacent water body, along river, bay, body of water, borders body of water, etc.: body of water on or next to which a place is located / is subproperty of located in/on physical feature / is subproperty of located on terrain feature / sea, lake or river
6. coordinate location (wd:P625 as p/wdt, matched via location), also known as co-ordinate location, co-ordinates, coordinates, co-ords, coords, etc.: geocoordinates of the subject. For Earth, please note that only the WGS84 geodetic datum is currently supported / coordinates of the subject / coordinates of the subject
7. MusicBrainz area ID (wd:P982 as p/wdtn/wdt, matched via MBarea), also known as area MBID, MBarea, MBID area, P982: identifier for an area in the MusicBrainz open music database
8. area (wd:P2046 as p/wdt), also known as acreage, camera resolution, die area, die size, image resolution, etc.: area occupied by an object / area occupied by an object
9. part of (wd:P361 as p/wdt, matched via of), also known as assembly of, branch of, chain, collateral branch of, component of, etc.: object of which the subject is a part (if this subject is ... "has part" (P527, see also "has parts of the class" (P2670)) / object of which the subject is a part (if this subject is ... "has part" (P527, see also "has parts of the class" (P2670)) / object of which the subject is a part (if this subject is ... "has part" (P527, see also "has parts of the class" (P2670)) / object of which the subject is a part (if this subject is ... "has part" (P527, see also "has parts of the class" (P2670))
10. contains the administrative territorial entity (wd:P150 as p/wdt, matched via has countries), also known as contains, contains administrative territorial entity, divided into, divides into, has administrative divisions, etc.: (list of) direct subdivisions of an administrative territorial entity / (list of) direct subdivisions of an administrative division / (list of) direct subdivisions of an administrative division / is subproperty of has part(s) / is subproperty of has part

No other items found

[Assistant]
The property "located in/on physical feature (wdt:P706)" is relevant here, as it is used to indicate that an item is located on a physical feature such as an island. I will now check if Jakarta is linked to Java via this property.

I will execute a SPARQL query to check if Jakarta (wd:Q3630) is located on Java (wd:Q3757) using the `wdt:P706` property.

execute

SELECT ?island WHERE { wd:Q3630 wdt:P706 ?island . ?island rdfs:label ?label FILTER(LANG(?label)='en') }

[Assistant]
The SPARQL query confirms that Jakarta (wd:Q3630) is located on the island of Java (wd:Q3757) via the `wdt:P706` (located in/on physical feature) property.

Thus, the Indonesian capital, Jakarta, is located on the island of Java.

### Final Answer:
The Indonesian capital, Jakarta, is located on the island of Java.

### SPARQL Query:
```sparql
SELECT ?island WHERE {
  wd:Q3630 wdt:P706 ?island .
  ?island rdfs:label ?label FILTER(LANG(?label)='en')
}
```

This query returns the island (Java) on which Jakarta is located.

answer

SELECT ?island WHERE { wd:Q3630 wdt:P706 ?island . ?island rdfs:label ?label FILTER(LANG(?label)='en') }

Answer: The Indonesian capital, Jakarta, is located on the island of Java.