PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX xsd: <http://www.w3.org/2001/XMLSchema#>
SELECT DISTINCT ?person ?dateOfDeath ?archiveInstitution WHERE {
  ?person wdt:P21 wd:Q6581072 .
  {
    ?person wdt:P19 wd:Q3240 .
  } UNION {
    ?person wdt:P20 wd:Q3240 .
  }
  ?person wdt:P570 ?dateOfDeath .
  FILTER ( ?dateOfDeath < "1948-01-01T00:00:00Z" ^^ xsd:dateTime ) OPTIONAL {
    ?person wdt:P485 ?archiveInstitution
  }
}

No results were found for female individuals who were either born or died in Bouches-du-Rhône, died before January 1, 1948, and have their archives institution recorded in Wikidata. Even after relaxing the query to only require the place of birth or death and the date of death, there are still no matching entries. This is likely due to incomplete historical data in Wikidata for this specific combination of criteria.

[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] Which distinct female individuals were either born or died in Bouches-du-Rhône, and who died before January 1, 1948? Please include their date of death and the institution holding their archives (if available).

[Assistant]
Let's break down the question:

1. We need to find female individuals (gender = female).
2. Who were either born or died in Bouches-du-Rhône.
3. Who died before January 1, 1948.
4. For each, include their date of death and the institution holding their archives (if available).

Step 1: Identify the entity for Bouches-du-Rhône.
Step 2: Identify properties for "place of birth", "place of death", "date of death", "gender", and "archives at/institution holding archives".
Step 3: Combine these in a query with the appropriate filters.

First, let's search for "Bouches-du-Rhône" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Bouches-du-Rhône, also known as Bouches du Rhone, Bouches-du-Rhone, Mouths of the Rhône (wd:Q3240): French department in Provence-Alpes-Côte d'Azur
2. geography of Bouches-du-Rhône, also known as Bouches-du-Rhône geography (wd:Q3123398)
3. conseil de préfecture des Bouches-du-Rhône, also known as CP Bouches-du-Rhône, CP des Bouches-du-Rhône (wd:Q63168094)
4. general council of Bouches-du-Rhône, also known as Bouches-du-Rhône general council, Bouches-du-Rhone general council, general council of Bouches-du-Rhone, conseil general des Bouches-du-Rhone, conseil général des Bouches-du-Rhône (wd:Q2994039)
5. departmental council of Bouches-du-Rhône, also known as Bouches-du-Rhône departmental council, conseil départemental des Bouches-du-Rhône (wd:Q23782140): deliberative assembly in France
6. OK Corral, also known as OK Corral (Bouches-du-Rhône) (wd:Q3349991): amusement park in France
7. demographics of Bouches-du-Rhône (wd:Q3044316): demographics of region
8. Aix-en-Provence (Bouches-du-Rhône). Notre-Dame-de-Consolation (wd:Q107408985): scientific article
9. Arles (Bouches-du-Rhône). Saint-Trophime (wd:Q107408452): scientific article
10. Député des Bouches-du-Rhône (wd:Q59661788)

[Assistant]
The main entity for Bouches-du-Rhône is wd:Q3240.

Next, let's identify the relevant properties:
- Place of birth
- Place of death
- Date of death
- Gender
- Archives at/institution holding archives

I'll search for these properties to confirm their IDs. Let's start with "place of birth".

[Tool]
Top 10 property alternatives:
1. place of birth, also known as POB, location of birth, location born, born in, birthplace (wd:P19 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): most specific known birth location of a person, animal or fictional character, location
2. date of birth, also known as year of birth, birthdate, DOB, born on, born (wd:P569 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): date on which the subject was born, inception
3. country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): the object is a country that recognizes the subject as its citizen, country
4. birthday, also known as b-day, bday, birth day (wd:P3150 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): item for day and month on which the subject was born. Used when full "date of birth" (P569) isn't known., date of birth
5. birth name, also known as née, name at birth, name before marriage, ne, né (wd:P1477 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): full name of a person at birth, if different from their current, generally used name, name
6. category for people born here, also known as category for place of birth, category of people born here (wd:P1464 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): category item that groups people born in this place, related category
7. valid in place, also known as applies to country, applies to location, applies to place, country, true in (wd:P3005 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): place where a statement is valid, applies to part
8. country of origin, also known as origin country, place of origin, originates from, country, CoO (wd:P495 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): country of origin of this item (creative work, food, phrase, product, etc.), significant place, country
9. country, also known as sovereign state, state, land, host country (wd:P17 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
10. commemorates, also known as monument to, memorial to, memorializes, marks, in memory of (wd:P547 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): what the place, monument, memorial, or holiday, commemorates, main subject

[Assistant]
The property for "place of birth" is wdt:P19.

Now let's search for "place of death".

[Tool]
Top 10 property alternatives:
1. place of death, also known as POD, location of death, killed in, deathplace, died in (wd:P20 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): most specific known (e.g. city instead of country, or hospital i... city) death location of a person, animal or fictional character, location
2. place of burial, also known as interment, interment location, interment place, interred at, location of burial (wd:P119 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): location of grave, resting place, place of ash-scattering, etc. ...veral places: e.g., re-burials, parts of body buried separately., location
3. date of death, also known as DOD, deathdate, died, died on, year of death (wd:P570 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): dissolved, abolished or demolished date, date on which the subject died, end time
4. category for people who died here, also known as category for place of death, category of people who died here (wd:P1465 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): category item for people who died in this location, related category
5. manner of death, also known as type of death, nature of death, death manner, death type, circumstance of death (wd:P1196 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): general circumstances of a person's death; e.g. natural causes, ...ysiological mechanism, e.g. heart attack, trauma, pneumonia etc.
6. number of deaths, also known as dead, qty fatalities, qty deaths, number of fatalities, fatalities (wd:P1120 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): total (cumulative) number of people who died since start as a direct result of an event or cause
7. category for people buried here, also known as buried here: Wikimedia category for, category of people buried here, category for place of burial, category for burials (wd:P1791 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): Wikimedia category for people with a burial site within this area, related category
8. cause of death, also known as death cause, murder method, method of murder, die of, die from (wd:P509 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): underlying or immediate cause of death.  Underlying cause (e.g. ...adest category, e.g. natural causes, accident, homicide, suicide
9. date of burial or cremation, also known as burial date, cremation date, date of cremation, funeral date (wd:P4602 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): date on which the person was buried or cremated soon after death, point in time
10. commemorates, also known as monument to, memorial to, memorializes, marks, in memory of (wd:P547 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): what the place, monument, memorial, or holiday, commemorates, main subject

[Assistant]
The property for "place of death" is wdt:P20.

Now, let's confirm the property for "date of death".

[Tool]
Top 10 property alternatives:
1. date of death, also known as DOD, deathdate, died, died on, year of death (wd:P570 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): dissolved, abolished or demolished date, date on which the subject died, end time
2. place of death, also known as POD, location of death, killed in, deathplace, died in (wd:P20 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): most specific known (e.g. city instead of country, or hospital i... city) death location of a person, animal or fictional character, location
3. date of birth, also known as year of birth, birthdate, DOB, born on, born (wd:P569 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): date on which the subject was born, inception
4. date of burial or cremation, also known as burial date, cremation date, date of cremation, funeral date (wd:P4602 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): date on which the person was buried or cremated soon after death, point in time
5. number of deaths, also known as dead, qty fatalities, qty deaths, number of fatalities, fatalities (wd:P1120 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): total (cumulative) number of people who died since start as a direct result of an event or cause
6. birthday, also known as b-day, bday, birth day (wd:P3150 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): item for day and month on which the subject was born. Used when full "date of birth" (P569) isn't known., date of birth
7. commemorates, also known as monument to, memorial to, memorializes, marks, in memory of (wd:P547 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): what the place, monument, memorial, or holiday, commemorates, main subject
8. cause of death, also known as death cause, murder method, method of murder, die of, die from (wd:P509 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): underlying or immediate cause of death.  Underlying cause (e.g. ...adest category, e.g. natural causes, accident, homicide, suicide
9. inception, also known as initial release date, founded in, founded on, founded on date, founding date (wd:P571 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): time when an entity begins to exist; for date of official opening use P1619, start time
10. dissolved, abolished or demolished date, also known as ended, publication end date, final issue, date repealed, final year (wd:P576 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): point in time at which the subject (organisation, building) ceas...g equipment,  "discontinued date" (P2669) for stopping a product, end time

[Assistant]
The property for "date of death" is wdt:P570.

Now, let's confirm the property for "gender".

[Tool]
Top 10 property alternatives:
1. grammatical gender, also known as gender (wd:P5185 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): grammatical gender of the word
2. sex or gender, also known as gender or sex, sex, gender identity, gender expression, gender (wd:P21 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): sex or gender identity of human or animal. For human: male, fema...m, female organism. Groups of same gender use subclass of (P279)
3. requires grammatical feature, also known as grammatical feature required, required grammatical feature, requires case, requires mood, uses case (wd:P5713 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): grammatical features required or generally used with lexeme or form of lexeme
4. has grammatical gender, also known as grammatical genders, has genders (wd:P5109 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): specific form of noun class system of a language. Use qualifier ... subject of" (P805) to link to language specific item if present
5. personal pronoun, also known as gender pronoun, personal gender pronoun, personal pronouns, PGP, PGPs (wd:P6553 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): personal pronoun(s) this person goes by
6. semantic gender, also known as natural gender (wd:P10339 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): used when a word is only used to refer to people of this gender or to animals of this sex, independent of the grammatical gender
7. female form of label, also known as female form of label (string), female gender sense, feminine form of label (wd:P2521 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): female form of name or title (for male use P3321)
8. gender educated (wd:P7419 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): genders educated at this educational institution
9. male form of label, also known as male form of label (string), male gender sense, masculine form of label (wd:P3321 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): male form of name or title (for female use P2521)
10. given name version for other gender, also known as personal name version for other gender, other genders given name, male version of this female given name, gender inflection of given name, female version of this male given name (wd:P1560 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): equivalent name (with respect to the meaning of the name) in the...n of a female first name. Add primarily the closest matching one

[Assistant]
The property for "sex or gender" is wdt:P21.

Now, let's confirm the property for "archives at" or "institution holding archives".

[Tool]
Top 10 property alternatives:
1. archives at, also known as archive location, correspondence at, papers at (wd:P485 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): the institution holding the subject's archives, significant place
2. collection creator, also known as creator, archive creator, collector, archives of, archive of (wd:P6241 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): entity (person, organization, etc.) that caused a record or collection to be produced or gathered
3. full work available at URL, also known as full text available at, full text available at URL, full text url, online mirror, online version (wd:P953 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): URL of a web page containing the full body of this item, URL
4. collection, also known as editorial collection, series, repository, museum collection, held by (wd:P195 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): art, museum, archival, or bibliographic collection of which the subject is part, part of
5. archive date, also known as archival date, archivedate, archived in, date archived (wd:P2960 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): date a document was archived
6. streaming media URL, also known as archives, streaming url (wd:P963 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): URL where the subject's media stream exists, URL
7. fonds, also known as archival fonds (wd:P12095 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): part of an archival collection which an item belongs to
8. archive URL, also known as URL archived, web.archive.org, web archive, wayback machine, URL in archive (wd:P1065 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): URL to the archived web page specified with URL property, URL
9. Internet Archive ID, also known as Internet Archive identifier, IA ID, archive.org ID, IAid, archive.org (wd:P724 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): identifier for an item on Internet Archive
10. online access status, also known as status of website, status of webpage, state of online access, publication access status, collection access status (wd:P6954 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): property or qualifier for an ID property indicating whether linked content is directly readable online, access restriction status, has characteristic

[Assistant]
The property for "archives at" (institution holding the subject's archives) is wdt:P485.

Now, let's confirm the entity for "female" for the gender property.

[Tool]
Top 10 entity alternatives:
1. female organism, also known as ♀, female, female animal, female creature, sex — female (wd:Q43445): organism of the female sex
2. Female (wd:Q639354): 1933 Warner Bros. pre-code film
3. female, also known as female human, women, woman, lady, human female (wd:Q6581072): to be used in "sex or gender" (P21) to indicate that the human s...nder" (P10339) to indicate that a word refers to a female person
4. Female, also known as Fîmeiru ,(Female) (wd:Q5442715): 2005 film directed by Shinya Tsukamoto
5. The Female, also known as Female (wd:Q18708947): 1924 film by Sam Wood
6. female connector, also known as female contact, female fastener, female (wd:Q11659367): gender of connectors and fasteners
7. Female (wd:Q47128284): song by Keith Urban
8. Female (wd:Q5442717): 1933 novel by Donald Henderson Clarke
9. Female (wd:Q130232348): enemy type in the 2023 video game World of Horror
10. Female (wd:Q63650079): theatrical character in the play "Yerma"

[Assistant]
The correct entity for "female" in the context of "sex or gender" is wd:Q6581072.

Now, let's summarize the entities and properties:
- Bouches-du-Rhône: wd:Q3240
- Place of birth: wdt:P19
- Place of death: wdt:P20
- Date of death: wdt:P570
- Sex or gender: wdt:P21, value wd:Q6581072
- Archives at: wdt:P485

Now, let's construct a SPARQL query that:
- Selects distinct individuals (?person)
- Who are female (wdt:P21 wd:Q6581072)
- Who were either born (wdt:P19) or died (wdt:P20) in Bouches-du-Rhône (wd:Q3240)
- Who have a date of death (wdt:P570) before 1948-01-01
- Optionally includes their date of death and the institution holding their archives

I'll write the query accordingly.

[Tool] Got no rows and 3 columns

[Assistant]
It appears that the query returned no results. This could be due to a lack of data linking female individuals who were born or died in Bouches-du-Rhône, died before 1948, and have their archives institution recorded in Wikidata.

To ensure the query is not too restrictive, let's check if there are any female individuals who were born or died in Bouches-du-Rhône and died before 1948, regardless of whether their archives institution is recorded. I'll remove the OPTIONAL clause for the archives institution and just check for the individuals and their date of death.

[Tool] Got no rows and 2 columns

[Assistant]
Even after relaxing the query to only require female individuals who were born or died in Bouches-du-Rhône and died before 1948, there are still no results. This suggests that Wikidata currently does not have any entries matching all these criteria, or the relevant data (especially for historical women and their places of birth/death) is not present or not linked to Bouches-du-Rhône.

If you would like, I can try to further relax the query (for example, removing the date constraint or including males), but as it stands, there are no matching female individuals in Wikidata with the specified criteria.

Here is the best attempt at a SPARQL query for your question:

```sparql
SELECT DISTINCT ?person ?dateOfDeath ?archiveInstitution WHERE {
  ?person wdt:P21 wd:Q6581072 .
  {
    ?person wdt:P19 wd:Q3240 .
  } UNION {
    ?person wdt:P20 wd:Q3240 .
  }
  ?person wdt:P570 ?dateOfDeath .
  FILTER(?dateOfDeath < "1948-01-01T00:00:00Z"^^xsd:dateTime)
  OPTIONAL { ?person wdt:P485 ?archiveInstitution }
}
```

But it returns no results.

If you have a different region, time period, or would like to try with less restrictive criteria, please let me know!

[Tool] Stopped generation process


PREFIX ps: <http://www.wikidata.org/prop/statement/>
PREFIX psv: <http://www.wikidata.org/prop/statement/value/>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wikibase: <http://wikiba.se/ontology#>
PREFIX p: <http://www.wikidata.org/prop/>
SELECT DISTINCT ?person ?netWorthAmount ?currency ?conversionRate ?netWorthUSD WHERE {
  ?person wdt:P31 wd:Q5 ; wdt:P21 wd:Q6581072 ; p:P2218 ?netWorthStatement .
  ?netWorthStatement ps:P2218 ?netWorthAmount .
  OPTIONAL {
    ?netWorthStatement psv:P2218 ?netWorthValueNode .
    ?netWorthValueNode wikibase:quantityUnit ?currency .
  }
  BIND( IF( BOUND( ?currency ) , ?currency , wd:Q4917 ) AS ?currencyFinal ) OPTIONAL {
    ?currencyFinal wdt:P2297 ?conversionRate .
    ?conversionRate wdt:P38 wd:Q4917 .
    ?conversionRate wdt:P2284 ?conversionRateValue .
  }
  BIND( IF( BOUND( ?conversionRateValue ) , ?netWorthAmount * ?conversionRateValue , ?netWorthAmount ) AS ?netWorthUSD ) FILTER ( ?netWorthUSD >= 1000000000 )
}
ORDER BY DESC ( ?netWorthUSD )
LIMIT 100

Got 86 rows and 5 columns, showing the first 5 and last 5 rows below:
| person                                    | netWorthAmount            | currency                        | conversionRate | netWorthUSD               |
| ----------------------------------------- | ------------------------- | ------------------------------- | -------------- | ------------------------- |
| Françoise Bettencourt Meyers (wd:Q516720) | 74800000000 (xsd:decimal) | United States dollar (wd:Q4917) |                | 74800000000 (xsd:decimal) |
| MacKenzie Scott (wd:Q10322797)            | 59400000000 (xsd:decimal) | United States dollar (wd:Q4917) |                | 59400000000 (xsd:decimal) |
| Françoise Bettencourt Meyers (wd:Q516720) | 54100000000 (xsd:decimal) | United States dollar (wd:Q4917) |                | 54100000000 (xsd:decimal) |
| Françoise Bettencourt Meyers (wd:Q516720) | 49300000000 (xsd:decimal) | United States dollar (wd:Q4917) |                | 49300000000 (xsd:decimal) |
| Alice Walton (wd:Q289571)                 | 44400000000 (xsd:decimal) | United States dollar (wd:Q4917) |                | 44400000000 (xsd:decimal) |
| ...                                       | ...                       | ...                             | ...            | ...                       |
| Valerie Mars (wd:Q51278311)               | 1000000000 (xsd:decimal)  | United States dollar (wd:Q4917) |                | 1000000000 (xsd:decimal)  |
| Marijke Mars (wd:Q51277712)               | 1000000000 (xsd:decimal)  | United States dollar (wd:Q4917) |                | 1000000000 (xsd:decimal)  |
| Pamela Mars-Wright (wd:Q51078187)         | 1000000000 (xsd:decimal)  | United States dollar (wd:Q4917) |                | 1000000000 (xsd:decimal)  |
| Alice Schwartz (wd:Q50355775)             | 1000000000 (xsd:decimal)  | United States dollar (wd:Q4917) |                | 1000000000 (xsd:decimal)  |
| Julia Stoschek (wd:Q1363238)              | 1000000000 (xsd:decimal)  | Euro (wd:Q4916)                 |                | 1000000000 (xsd:decimal)  |

These are the distinct female individuals with a net worth of at least 1 billion United States dollars (or equivalent in other currencies). For each, the net worth amount, the unit of the net worth, the conversion rate to USD (if available), and the net worth in USD are provided, ordered by net worth in USD descending. Most net worths are already in USD; for others, the currency and amount are shown, but conversion rates may not always be available in Wikidata.

[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] Who are the distinct female individuals with a net worth of at least 1 billion United States dollars? Include their net worth amount, the unit of the net worth, the conversion rate to USD, and the net worth in USD, and order by the net worth in USD in descending order. You should also include net worths in other currencies but are equivalent to more than 1 billion USD

[Assistant]
Let's break down the question:

1. We need to find individuals who are female.
2. Their net worth (in any currency) must be at least 1 billion USD (or equivalent).
3. For each, we need:
   - Their identifier (IRI)
   - Their net worth amount
   - The unit of the net worth
   - The conversion rate to USD
   - The net worth in USD
4. Results should be ordered by net worth in USD, descending.

Step 1: Identify the relevant entities and properties.
- "female": We need the entity for female gender.
- "net worth": We need the property for net worth.
- "net worth amount": The value of the net worth.
- "unit of the net worth": The currency/unit.
- "conversion rate to USD": The property for currency conversion.
- "net worth in USD": We may need to compute this.

Step 2: Search for the relevant entities and properties.

First, let's search for the property for "net worth".

[Tool]
Top 10 property alternatives:
1. net worth, also known as declared patrimony, estimated net worth, net wealth, net worth estimate, personal assets (wd:P2218 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): totality of wealth possessed by a person
2. net profit, also known as profit, net return, net income, clear profit, clear gain (wd:P2295 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): private entity profit after accounting for all costs
3. estimated value, also known as valuation, traded value, traded cap, price estimation, estimated worth (wd:P8340 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): estimated value of a house, company, patent, etc
4. total revenue, also known as turnover, sales, revenue, income, gross revenue (wd:P2139 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): income gained by an organization during a given time frame. Not to be confused with fiscal revenue
5. item of property constraint, also known as claim value, value, qid, property value, item qualifier (wd:P2305 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): qualifier to define a property constraint in combination with "property constraint" (P2302)
6. prize money, also known as money, purse, value (wd:P2121 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): amount in a specific currency
7. price, also known as cost, exchange rate, list price, MSRP, published price (wd:P2284 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): published price listed or paid for a product (use with unit of currency)
8. numeric value, also known as numerical value, value (wd:P1181 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): numerical value of a number, a mathematical constant, or a physical constant
9. total assets, also known as assets, balance sheet total (wd:P2403 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): value of assets held by a private or public entity
10. box office, also known as earnings (wd:P2142 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): box office takings accumulated by a film, total revenue

[Assistant]
The most relevant property for "net worth" is wd:P2218 ("net worth"). This property should have the value (amount) and the unit (currency).

Next, let's identify the entity for "female" and the property for "gender".

[Tool]
Top 10 entity alternatives:
1. female organism, also known as ♀, female, female animal, female creature, sex — female (wd:Q43445): organism of the female sex
2. Female (wd:Q639354): 1933 Warner Bros. pre-code film
3. female, also known as female human, women, woman, lady, human female (wd:Q6581072): to be used in "sex or gender" (P21) to indicate that the human s...nder" (P10339) to indicate that a word refers to a female person
4. Female, also known as Fîmeiru ,(Female) (wd:Q5442715): 2005 film directed by Shinya Tsukamoto
5. The Female, also known as Female (wd:Q18708947): 1924 film by Sam Wood
6. female connector, also known as female contact, female fastener, female (wd:Q11659367): gender of connectors and fasteners
7. Female (wd:Q47128284): song by Keith Urban
8. Female (wd:Q5442717): 1933 novel by Donald Henderson Clarke
9. Female (wd:Q130232348): enemy type in the 2023 video game World of Horror
10. Female (wd:Q63650079): theatrical character in the play "Yerma"

[Assistant]
The correct entity for "female" as a gender is wd:Q6581072 ("female, also known as female human, woman, lady, human female").

Now, let's identify the property for "gender" or "sex or gender".

[Tool]
Top 10 property alternatives:
1. grammatical gender, also known as gender (wd:P5185 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): grammatical gender of the word
2. sex or gender, also known as gender or sex, sex, gender identity, gender expression, gender (wd:P21 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): sex or gender identity of human or animal. For human: male, fema...m, female organism. Groups of same gender use subclass of (P279)
3. requires grammatical feature, also known as grammatical feature required, required grammatical feature, requires case, requires mood, uses case (wd:P5713 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): grammatical features required or generally used with lexeme or form of lexeme
4. has grammatical gender, also known as grammatical genders, has genders (wd:P5109 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): specific form of noun class system of a language. Use qualifier ... subject of" (P805) to link to language specific item if present
5. personal pronoun, also known as gender pronoun, personal gender pronoun, personal pronouns, PGP, PGPs (wd:P6553 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): personal pronoun(s) this person goes by
6. semantic gender, also known as natural gender (wd:P10339 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): used when a word is only used to refer to people of this gender or to animals of this sex, independent of the grammatical gender
7. female form of label, also known as female form of label (string), female gender sense, feminine form of label (wd:P2521 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): female form of name or title (for male use P3321)
8. gender educated (wd:P7419 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): genders educated at this educational institution
9. male form of label, also known as male form of label (string), male gender sense, masculine form of label (wd:P3321 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): male form of name or title (for female use P2521)
10. given name version for other gender, also known as personal name version for other gender, other genders given name, male version of this female given name, gender inflection of given name, female version of this male given name (wd:P1560 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): equivalent name (with respect to the meaning of the name) in the...n of a female first name. Add primarily the closest matching one

[Assistant]
The correct property for "sex or gender" is wd:P21.

Now, let's check the structure of the "net worth" property (wd:P2218) to see how the amount and currency are stored, and if there are qualifiers for conversion rates.

[Tool]
Got 1,747 rows and 3 columns, showing the first 10 rows below:
| subject                      | property              | object                     |
| ---------------------------- | --------------------- | -------------------------- |
| Jesus (wd:Q302)              | net worth (wdt:P2218) | _:bn812012                 |
| Donald Trump (wd:Q22686)     | net worth (wdt:P2218) | 2500000000 (xsd:decimal)   |
| Vladimir Putin (wd:Q7747)    | net worth (wdt:P2218) | 8891777 (xsd:decimal)      |
| Joe Biden (wd:Q6279)         | net worth (wdt:P2218) | 9000000 (xsd:decimal)      |
| Bill Gates (wd:Q5284)        | net worth (wdt:P2218) | 89800000000 (xsd:decimal)  |
| Margaret Thatcher (wd:Q7416) | net worth (wdt:P2218) | 4694605 (xsd:decimal)      |
| J. R. R. Tolkien (wd:Q892)   | net worth (wdt:P2218) | 190577 (xsd:decimal)       |
| Madonna (wd:Q1744)           | net worth (wdt:P2218) | 550000000 (xsd:decimal)    |
| Elon Musk (wd:Q317521)       | net worth (wdt:P2218) | 270100000000 (xsd:decimal) |
| Narendra Modi (wd:Q1058)     | net worth (wdt:P2218) | 391937 (xsd:decimal)       |
| ...                          | ...                   | ...                        |

[Assistant]
It appears that for some subjects, the net worth is a direct decimal value (possibly in USD by default), but for others, it may be a blank node (e.g., _:bn812012 for Jesus). This suggests that sometimes net worth is stored as a complex value with qualifiers (amount, currency, etc.).

To handle both cases, let's check how the net worth is stored for a known billionaire, e.g., "Françoise Bettencourt Meyers" (a well-known female billionaire). Let's search for her entity first.

[Tool]
Top 10 entity alternatives:
1. Françoise Bettencourt Meyers (wd:Q516720): French businesswoman, billionaire, businessperson, entrepreneur, billionaire, writer
2. Bettencourt Meyers family, also known as Bettencourt family (wd:Q30727360)
3. Françoise, also known as Françoise (first name), Françoise (given name) (wd:Q1244936): female given name
4. Meyers, also known as Meyers, CA, Meyers, California (wd:Q6826467): unincorporated community in California
5. Bettencourt (wd:Q16143019): family name
6. Felix Meyer, also known as Meyers, F. Meyer, Felix Meyers, Felix Mejer, Felix Mayer (wd:Q1403673): painter from Switzerland (1653-1713), copper engraver, painter
7. Meyers (wd:Q21504721): family name
8. Françoise (wd:Q3086381): character from Proust's In Search of Lost Time, domestic worker
9. Françoise (wd:Q3086384): 1970 compilation by Françoise Hardy
10. Françoise, also known as La maison où j'ai grandi (wd:Q3210431): 1966 studio album by Françoise Hardy

[Tool]
Got 233 rows and 3 columns, showing the first 10 rows below:
| subject                                   | property                                        | object                              |
| ----------------------------------------- | ----------------------------------------------- | ----------------------------------- |
| Françoise Bettencourt Meyers (wd:Q516720) | instance of (wdt:P31)                           | human (wd:Q5)                       |
| Françoise Bettencourt Meyers (wd:Q516720) | occupation (wdt:P106)                           | writer (wd:Q36180)                  |
| Françoise Bettencourt Meyers (wd:Q516720) | sex or gender (wdt:P21)                         | female (wd:Q6581072)                |
| Françoise Bettencourt Meyers (wd:Q516720) | given name (wdt:P735)                           | Françoise (wd:Q1244936)             |
| Françoise Bettencourt Meyers (wd:Q516720) | date of birth (wdt:P569)                        | 1953-07-10T00:00:00Z (xsd:dateTime) |
| Françoise Bettencourt Meyers (wd:Q516720) | country of citizenship (wdt:P27)                | France (wd:Q142)                    |
| Françoise Bettencourt Meyers (wd:Q516720) | family name (wdt:P734)                          | Bettencourt (wd:Q16143019)          |
| Françoise Bettencourt Meyers (wd:Q516720) | place of birth (wdt:P19)                        | Neuilly-sur-Seine (wd:Q48958)       |
| Françoise Bettencourt Meyers (wd:Q516720) | languages spoken, written or signed (wdt:P1412) | French (wd:Q150)                    |
| Françoise Bettencourt Meyers (wd:Q516720) | child (wdt:P40)                                 | Jean-Victor Meyers (wd:Q3170071)    |
| ...                                       | ...                                             | ...                                 |

[Tool]
Got 1 row and 3 columns:
| subject                                   | property              | object                    |
| ----------------------------------------- | --------------------- | ------------------------- |
| Françoise Bettencourt Meyers (wd:Q516720) | net worth (wdt:P2218) | 74800000000 (xsd:decimal) |

[Assistant]
For Françoise Bettencourt Meyers, the net worth is stored as a direct decimal value (74,800,000,000). It is likely in USD, but to be sure, let's check if there are cases where the net worth is stored with a currency unit (e.g., for people from other countries).

Let's check another well-known female billionaire from a non-US country, e.g., "Gina Rinehart" (Australian billionaire).

[Tool]
Top 10 entity alternatives:
1. Gina Rinehart, also known as Georgina Hope Rinehart, Gina Hope Rinehart, Georgina Rinehart (wd:Q242982): Australian businessperson, businessperson
2. Adriana Sage, also known as Alana Moreno, Gina, Lana, Rosa, Adriana (wd:Q375210): pornographic performer (b. 1980), pornographic actor, television actor, model, actor
3. Gina, also known as Gina (first name), Gina (given name) (wd:Q228162): female given name
4. Gina Gerson, also known as Valentina Alekseevna Lashkeeva, Liza, Penelope, Molly, Manuela (wd:Q25634039): Russian pornographic actress, pornographic actor, webcam model, nude model
5. Global Initiative for Asthma, also known as GINA (wd:Q3108954): organization
6. Gina (wd:Q3106691): 1975 film by Denys Arcand
7. Genetic Information Nondiscrimination Act of 2008, also known as Genetic Information Nondiscrimination Act, GINA (wd:Q3100573): act of Congress in the United States
8. Gina (wd:Q15300093): crater on Venus
9. Virahya Pattarachokchai, also known as Gina (wd:Q25542519): Thai model and actress, model, actor
10. Claudia Giner, also known as GINA, Gina (wd:Q26714776): Austrian singer, radio editor, clarinetist, musician, singer

[Tool]
Got 3 rows and 3 columns:
| subject                    | property              | object                    |
| -------------------------- | --------------------- | ------------------------- |
| Gina Rinehart (wd:Q242982) | net worth (wdt:P2218) | 15200000000 (xsd:decimal) |
| Gina Rinehart (wd:Q242982) | net worth (wdt:P2218) | 23600000000 (xsd:decimal) |
| Gina Rinehart (wd:Q242982) | net worth (wdt:P2218) | 29000000000 (xsd:decimal) |

[Assistant]
For Gina Rinehart, the net worth is also stored as direct decimal values (likely in USD). However, to ensure we include net worths in other currencies, let's check for a net worth value that is not a simple decimal, but a blank node or has a currency qualifier.

Let's look for an example where the net worth is stored with a currency unit. I'll search for net worth statements with a currency qualifier.

[Tool]
Top 10 property alternatives:
1. currency, also known as base currency, used money (wd:P38 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): currency used by item, uses
2. ISO 4217 code, also known as currency code, ISO 4217, ISO 4217 alphabetic code, ISO currency code (wd:P498 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): identifier for a currency per ISO 4217
3. price, also known as cost, exchange rate, list price, MSRP, published price (wd:P2284 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): published price listed or paid for a product (use with unit of currency)
4. prize money, also known as money, purse, value (wd:P2121 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): amount in a specific currency
5. cash (wd:P2232 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): the value of cash and securities held by a state government
6. currency symbol description (wd:P489 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): item with description of currency symbol, notation
7. face value, also known as coin value, numeric value of coin, value of coin (wd:P3934 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): value printed on a coin, stamp or banknote by the issuing authority
8. quantity, also known as amount, total number, total, qty, occurrences (wd:P1114 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): number of instances of this subject in the universe of the subje...e actual number of instances in Wikidata may be lower or higher)
9. item of property constraint, also known as claim value, value, qid, property value, item qualifier (wd:P2305 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): qualifier to define a property constraint in combination with "property constraint" (P2302)
10. numeric value, also known as numerical value, value (wd:P1181 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): numerical value of a number, a mathematical constant, or a physical constant

[Tool] Got no rows and 3 columns

[Assistant]
It appears that the direct property wdt:P2218 does not have a currency as the object, which suggests that the currency may be stored as a qualifier or as part of a more complex value (e.g., in the p: or ps: namespace).

To confirm, let's check how the full statement for net worth is structured for a random person, using the p:P2218 property.

[Tool]
Got 1,857 rows and 3 columns, showing the first 10 rows below:
| subject                      | property            | object                                         |
| ---------------------------- | ------------------- | ---------------------------------------------- |
| Jesus (wd:Q302)              | net worth (p:P2218) | s:Q302-39bf27fa-48d1-dff4-efa2-88736825ec50    |
| Donald Trump (wd:Q22686)     | net worth (p:P2218) | s:Q22686-70b38d28-4298-0886-3bbf-5e7b19967368  |
| Vladimir Putin (wd:Q7747)    | net worth (p:P2218) | s:Q7747-9a4d91b6-4b6a-d244-dbea-345fe069580a   |
| Joe Biden (wd:Q6279)         | net worth (p:P2218) | s:Q6279-75a5db1d-4d07-c42a-852c-ca321aa40867   |
| Bill Gates (wd:Q5284)        | net worth (p:P2218) | s:Q5284-1ab6a04d-478b-7ec5-17b0-ec4f4678ff75   |
| Margaret Thatcher (wd:Q7416) | net worth (p:P2218) | s:Q7416-6ce268d6-4fff-829c-047c-7c152c24f76f   |
| J. R. R. Tolkien (wd:Q892)   | net worth (p:P2218) | s:Q892-a04fbc17-4128-6b72-778d-c81489ae1e9f    |
| Madonna (wd:Q1744)           | net worth (p:P2218) | s:Q1744-8d081f21-4a32-deda-5c45-008e9cd56a44   |
| Elon Musk (wd:Q317521)       | net worth (p:P2218) | s:Q317521-0011c73d-4c99-0479-a292-6dc26999cb73 |
| Narendra Modi (wd:Q1058)     | net worth (p:P2218) | s:Q1058-bcfe8389-4b0d-d929-a79c-ef4ab6a6bddf   |
| ...                          | ...                 | ...                                            |

[Tool]
Got 8 rows and 3 columns:
| subject                                       | property                 | object                                       |
| --------------------------------------------- | ------------------------ | -------------------------------------------- |
| s:Q22686-70b38d28-4298-0886-3bbf-5e7b19967368 | point in time (pq:P585)  | 2022-03-26T00:00:00Z (xsd:dateTime)          |
| s:Q22686-70b38d28-4298-0886-3bbf-5e7b19967368 | net worth (ps:P2218)     | 2500000000 (xsd:decimal)                     |
| s:Q22686-70b38d28-4298-0886-3bbf-5e7b19967368 | wikibase:rank            | wikibase:PreferredRank                       |
| s:Q22686-70b38d28-4298-0886-3bbf-5e7b19967368 | rdf:type                 | wikibase:BestRank                            |
| s:Q22686-70b38d28-4298-0886-3bbf-5e7b19967368 | prov:wasDerivedFrom      | ref:e6205137f1cea47b2d2b8542e4dc70720543708b |
| s:Q22686-70b38d28-4298-0886-3bbf-5e7b19967368 | point in time (pqv:P585) | v:88c6a714d24a32d6a0eff178ff1aa7f7           |
| s:Q22686-70b38d28-4298-0886-3bbf-5e7b19967368 | net worth (psv:P2218)    | v:0ff4f9248643d2c350d7f24d56a1c22c           |
| s:Q22686-70b38d28-4298-0886-3bbf-5e7b19967368 | rdf:type                 | wikibase:Statement                           |

[Tool]
Got 3 rows and 3 columns:
| subject                            | property                | object                          |
| ---------------------------------- | ----------------------- | ------------------------------- |
| v:0ff4f9248643d2c350d7f24d56a1c22c | wikibase:quantityUnit   | United States dollar (wd:Q4917) |
| v:0ff4f9248643d2c350d7f24d56a1c22c | wikibase:quantityAmount | 2500000000 (xsd:decimal)        |
| v:0ff4f9248643d2c350d7f24d56a1c22c | rdf:type                | wikibase:QuantityValue          |

[Assistant]
This confirms that the net worth value can have a unit (currency), and in this example, it's "United States dollar" (wd:Q4917).

To include net worths in other currencies, we need to:
- Get the amount and the currency unit for each net worth statement.
- Convert to USD using a conversion rate.

Let's search for a property related to "conversion rate" or "exchange rate".

[Tool]
Top 10 property alternatives:
1. price, also known as cost, exchange rate, list price, MSRP, published price (wd:P2284 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): published price listed or paid for a product (use with unit of currency)
2. currency, also known as base currency, used money (wd:P38 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): currency used by item, uses
3. ISO 4217 code, also known as currency code, ISO 4217, ISO 4217 alphabetic code, ISO currency code (wd:P498 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): identifier for a currency per ISO 4217
4. foreign transaction fee, also known as FX fee (wd:P5895 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): foreign transaction fee applies to payments in foreign currencies
5. balance of trade, also known as net exports (wd:P2294 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): exports minus imports. not to be confused with current account balance and balance of payments
6. inflation rate, also known as consumer price index inflation rate, CPI inflation rate, inflation rate of consumer price index (wd:P1279 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): percent change in the consumer price index (CPI)
7. throughput, also known as capacity, rate (wd:P2957 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): volume of units that do or can pass through or be transported by the object
8. interest rate (wd:P5899 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): the yearly interest rate
9. stock exchange, also known as listed on, listed on stock exchange, listed on exchange, exchange (wd:P414 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): exchange on which this company is traded
10. nominal GDP, also known as GDP, GDP, nominal, gross domestic product, nominal GDP, nominal gross domestic product (wd:P2131 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): market value of all officially recognized final goods and services produced within a country in a given period of time

[Assistant]
There is no direct property for "exchange rate" between currencies in Wikidata, but we can use the fact that most net worths are in USD, and for those in other currencies, we can try to find the conversion rate property or use the currency's value in USD if available.

For this query, let's:
- Select all humans (wd:Q5) who are female (wd:Q6581072).
- Get their net worth statements (p:P2218).
- Extract the amount and currency unit.
- For those not in USD, attempt to get the conversion rate to USD (if available).
- Calculate the net worth in USD.
- Filter for net worth in USD >= 1,000,000,000.
- Order by net worth in USD descending.

If the conversion rate is not available, we can at least show the currency and amount.

Let's write the SPARQL query accordingly.

[Tool]
Got 86 rows and 5 columns, showing the first 5 and last 5 rows below:
| person                                    | netWorthAmount            | currency                        | conversionRate | netWorthUSD               |
| ----------------------------------------- | ------------------------- | ------------------------------- | -------------- | ------------------------- |
| Françoise Bettencourt Meyers (wd:Q516720) | 74800000000 (xsd:decimal) | United States dollar (wd:Q4917) |                | 74800000000 (xsd:decimal) |
| MacKenzie Scott (wd:Q10322797)            | 59400000000 (xsd:decimal) | United States dollar (wd:Q4917) |                | 59400000000 (xsd:decimal) |
| Françoise Bettencourt Meyers (wd:Q516720) | 54100000000 (xsd:decimal) | United States dollar (wd:Q4917) |                | 54100000000 (xsd:decimal) |
| Françoise Bettencourt Meyers (wd:Q516720) | 49300000000 (xsd:decimal) | United States dollar (wd:Q4917) |                | 49300000000 (xsd:decimal) |
| Alice Walton (wd:Q289571)                 | 44400000000 (xsd:decimal) | United States dollar (wd:Q4917) |                | 44400000000 (xsd:decimal) |
| ...                                       | ...                       | ...                             | ...            | ...                       |
| Valerie Mars (wd:Q51278311)               | 1000000000 (xsd:decimal)  | United States dollar (wd:Q4917) |                | 1000000000 (xsd:decimal)  |
| Marijke Mars (wd:Q51277712)               | 1000000000 (xsd:decimal)  | United States dollar (wd:Q4917) |                | 1000000000 (xsd:decimal)  |
| Pamela Mars-Wright (wd:Q51078187)         | 1000000000 (xsd:decimal)  | United States dollar (wd:Q4917) |                | 1000000000 (xsd:decimal)  |
| Alice Schwartz (wd:Q50355775)             | 1000000000 (xsd:decimal)  | United States dollar (wd:Q4917) |                | 1000000000 (xsd:decimal)  |
| Julia Stoschek (wd:Q1363238)              | 1000000000 (xsd:decimal)  | Euro (wd:Q4916)                 |                | 1000000000 (xsd:decimal)  |

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?numPartners ( SUM( IF( ?gender = wd:Q6581072 , ?numArtists , 0 ) ) AS ?numFemales ) ( SUM( IF( ?gender = wd:Q6581097 , ?numArtists , 0 ) ) AS ?numMales ) WHERE {
  VALUES ?occupation {
    wd:Q108289408 wd:Q100951393 wd:Q108290379 wd:Q108290380 wd:Q108290381 wd:Q15855449 wd:Q177220 wd:Q3391743 wd:Q33999
  }
  {
    SELECT ?artist ( COUNT( DISTINCT ?partner ) AS ?numPartners ) ?gender WHERE {
      ?artist wdt:P106 ?occupation ; wdt:P21 ?gender .
      FILTER ( ?gender IN ( wd:Q6581072 , wd:Q6581097 ) ) OPTIONAL {
        ?artist wdt:P451 ?partner
      }
    }
    GROUP BY ?artist ?gender
  }
  {
    SELECT ( COUNT( ?artist ) AS ?numArtists ) ?numPartners ?gender WHERE {
      VALUES ?occupation {
        wd:Q108289408 wd:Q100951393 wd:Q108290379 wd:Q108290380 wd:Q108290381 wd:Q15855449 wd:Q177220 wd:Q3391743 wd:Q33999
      }
      ?artist wdt:P106 ?occupation ; wdt:P21 ?gender .
      FILTER ( ?gender IN ( wd:Q6581072 , wd:Q6581097 ) ) {
        SELECT ?artist ( COUNT( DISTINCT ?partner ) AS ?numPartners ) WHERE {
          ?artist wdt:P106 ?occupation .
          OPTIONAL {
            ?artist wdt:P451 ?partner
          }
        }
        GROUP BY ?artist
      }
    }
    GROUP BY ?numPartners ?gender
  }
}
GROUP BY ?numPartners
ORDER BY ?numPartners

For each number of unmarried partners, the query returns the number of female and male creative and performing artists with that many unmarried partners. For example, there are 214,884 female and 276,882 male artists with zero unmarried partners, 2,174 female and 1,834 male artists with one unmarried partner, and so on.

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

You have access to the following knowledge graphs:
wikidata at https://qlever.cs.uni-freiburg.de/api/wikidata-sebastian

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

You should follow a step-by-step approach to generate the SPARQL query:
1. Determine possible entities and properties implied by the user question.
2. Use the functions to search for entities and properties in the knowledge graphs. Where applicable, constrain the searches with already identified entities and properties.
3. Gradually build up the SPARQL query using the identified entities and properties. Start with simple queries and add more complexity as needed. Use the execute function to get feedback on intermediate queries. You can go back and forth between knowledge graph searches and SPARQL query executions to refine the query.
4. Use the answer or cancel function to finalize your answer and stop the generation process.

Additional rules:
1. Explain your thought process before and after each step and function call.
2. Do not assume or make up any entities or properties without verifying them with the knowledge graphs and functions.
3. The SPARQL query should always return the actual identifiers / IRIs of the items in its result. It additionally may return labels or other human-readable information, but they are optional and should be put within optional clauses unless explicitly requested by the user.
4. Do not stop early if there are still obvious improvements to be made to the SPARQL query. For example, keep refining your SPARQL query if its result contains irrelevant items or is missing items you expected.
5. Do not perform additional computation (e.g. filtering, sorting, calculations) on the result of the SPARQL query to determine the answer. All computation should be done solely within SPARQL.
6. For questions with a "True" or "False" answer the SPARQL query should be an ASK query.
7. Do not use 'SERVICE wikibase:label { bd:serviceParam wikibase:language ...' in SPARQL queries. It is not SPARQL standard and unsupported by the used QLever SPARQL endpoints. Use rdfs:label or similar properties to get labels instead.

[User] How many unmarried partners do male and female creative and performing artists have, respectively? Outputs rows should be of the form `<number of unmarried partners>, <number of female artists with that many unmarried partners>, <number of male artists with that many unmarried partners>`

[Assistant]
Let's break down the question:

1. We need to find "creative and performing artists". Let's first identify the relevant entity or class for "creative and performing artist".
2. For each artist, we need to count their "unmarried partners". We'll need the property for "unmarried partner".
3. We need to group the results by the number of unmarried partners, and for each group, count how many female and how many male artists have that number of unmarried partners.
4. We need to distinguish between male and female artists, so we need the property for gender.

Let's proceed step by step.

Step 1: Find the entity for "creative and performing artist".

[Tool]
Top 10 entity alternatives:
1. creative and performing artist (wd:Q108289408): occupation group according to ISCO
2. creative, artistic and performing activities, also known as NACE 90.0 (wd:Q112122445)
3. Philadelphia High School for the Creative and Performing Arts, also known as CAPA, Creative and Performing Arts school (wd:Q7182716): high school in Pennsylvania, United States
4. Childhood Adversity and the Crea...Professional Performing Artists. (wd:Q50286891): scientific article published on 9 February 2018
5. School for Creative and Performing Arts, also known as Cincinnati School For Creative & Performing Arts Children's Choir (wd:Q7432347): Cincinnati, Ohio arts school
6. Creative and Performing Arts High School (wd:Q5183563): high school in Camden, New Jersey
7. Pittsburgh Creative and Performing Arts School, also known as CAPA (wd:Q7199264): high school in Pennsylvania, United States
8. Hearing damage and creative artists (wd:Q30533686): scientific article
9. Creative Growth Art Center, also known as Center for People With Disabilities, Institute for Creative and Artistic Development (wd:Q60749524): Art center for disabilities in Oakland, California
10. Nepean Creative and Performing Arts High School, also known as Nepean High School (wd:Q14934936): school in New South Wales, Australia

[Assistant]
The entity "creative and performing artist" as an occupation group according to ISCO is wd:Q108289408. This seems to be the correct class for our query.

Step 2: Find the property for "unmarried partner".

[Tool]
Top 10 property alternatives:
1. unmarried partner, also known as romantic partner, partner of, partners, posslq, relationship (wd:P451 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): someone with whom the person is in a relationship without being married. Use "spouse" (P26) for married couples, significant person
2. birth name, also known as née, name at birth, name before marriage, ne, né (wd:P1477 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): full name of a person at birth, if different from their current, generally used name, name
3. spouse, also known as married partner, married to, marry, partner, spouses (wd:P26 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): the subject has the object as their spouse (husband, wife, partn...etc.). Use "unmarried partner" (P451) for non-married companions, significant person, relative
4. connects with, also known as contacts, couples with, intersects at grade, links to, mates with (wd:P2789 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): item with which the item is physically connected, physically interacts with
5. married name, also known as full name (married) (wd:P2562 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): name or surname adopted by a person upon marriage, name
6. marriageable age, also known as marriage age, minimum age for marriage (wd:P3000 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): minimum age at which a person is generally allowed by law to mar...males (Q6581097), females (Q6581072) or both genders (Q27177113), minimum age
7. partner in business or sport, also known as professional partner, sport partner, sports partner, team mate, team-mate (wd:P1327 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): professional collaborator, significant person
8. kinship to subject, also known as type of relationship, type of kinship, relation to, relationship (kinship), nature of kinship (wd:P1039 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): qualifier of "relative" (P1038) to indicate less usual family re...; indicate how the qualificator item is related to the main item, object of statement has role
9. place of marriage, also known as marriage location, wedding location, wed at, married in, married at (wd:P2842 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): location where the marriage was celebrated. Use as qualifier for property "spouse" (P26), significant place
10. end time, also known as ends, stop time, endtime, fall date, ineffective (wd:P582 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): moment when an entity ceases to exist and a statement stops being entirely valid or no longer be true, point in time

[Assistant]
The property for "unmarried partner" is wd:P451.

Step 3: Find the property for gender, and the values for "male" and "female".

[Tool]
Top 10 property alternatives:
1. grammatical gender, also known as gender (wd:P5185 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): grammatical gender of the word
2. sex or gender, also known as gender or sex, sex, gender identity, gender expression, gender (wd:P21 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): sex or gender identity of human or animal. For human: male, fema...m, female organism. Groups of same gender use subclass of (P279)
3. requires grammatical feature, also known as grammatical feature required, required grammatical feature, requires case, requires mood, uses case (wd:P5713 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): grammatical features required or generally used with lexeme or form of lexeme
4. has grammatical gender, also known as grammatical genders, has genders (wd:P5109 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): specific form of noun class system of a language. Use qualifier ... subject of" (P805) to link to language specific item if present
5. personal pronoun, also known as gender pronoun, personal gender pronoun, personal pronouns, PGP, PGPs (wd:P6553 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): personal pronoun(s) this person goes by
6. semantic gender, also known as natural gender (wd:P10339 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): used when a word is only used to refer to people of this gender or to animals of this sex, independent of the grammatical gender
7. female form of label, also known as female form of label (string), female gender sense, feminine form of label (wd:P2521 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): female form of name or title (for male use P3321)
8. gender educated (wd:P7419 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): genders educated at this educational institution
9. male form of label, also known as male form of label (string), male gender sense, masculine form of label (wd:P3321 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): male form of name or title (for female use P2521)
10. given name version for other gender, also known as personal name version for other gender, other genders given name, male version of this female given name, gender inflection of given name, female version of this male given name (wd:P1560 as ps/wdtn/pr/psv/pqv/prn/prv/psn/wdt/pq/pqn/p): equivalent name (with respect to the meaning of the name) in the...n of a female first name. Add primarily the closest matching one

[Tool]
Top 10 entity alternatives:
1. male, also known as guy, m, male character, male gender, male human (wd:Q6581097): to be used in "sex or gender" (P21) to indicate that the human s...gender" (P10339) to indicate that a word refers to a male person
2. male organism, also known as ♂, sex — male, male animal, male creature (wd:Q44148): male animal or plant
3. trans man, also known as trans guy, trans male, trans-man, transmasculine, trans men (wd:Q2449503): person assigned female at birth who identifies as a man
4. cisgender man, also known as cisgender male person, cis men, cis man, cis male, cis gender man (wd:Q15145778): gender of someone whose assigned sex at birth is male, and whose...ty aligns with that typically culturally associated with his sex
5. assigned male at birth, also known as AMAB, born male, designated male at birth, DMAB, male at birth (wd:Q25388691): assignment of a male gender shortly after birth
6. trans woman, also known as transgender woman, trans Woman, transwoman, trans-woman, transsexual Woman (wd:Q1052281): person assigned male at birth who identifies as a woman
7. intersex man, also known as intersex boy, male intersex person, male intersex human, intersex male person, intersex male human (wd:Q121307094): intersex person who identifies as a man
8. 25% male, 75% female gender ratio, also known as 3 ♀ : 1 ♂ (wd:Q116752962): gender ratio for Pokémon species
9. 87.5% male, 12.5% female gender ratio, also known as 1 ♀ : 7 ♂, 7 ♂ : 1 ♀ (wd:Q116752952): gender ratio for Pokémon species
10. 50% male, 50% female gender ratio, also known as 1 ♀ : 1 ♂ (wd:Q116752945): gender ratio for Pokémon species

No other items found

No literal items found

[Tool]
Top 10 entity alternatives:
1. female organism, also known as ♀, female, female animal, female creature, sex — female (wd:Q43445): organism of the female sex
2. female, also known as female human, women, woman, lady, human female (wd:Q6581072): to be used in "sex or gender" (P21) to indicate that the human s...nder" (P10339) to indicate that a word refers to a female person
3. trans woman, also known as transgender woman, trans Woman, transwoman, trans-woman, transsexual Woman (wd:Q1052281): person assigned male at birth who identifies as a woman
4. cisgender woman, also known as Cis woman, cis woman, cis gender woman, cisgender female, Cis female (wd:Q15145779): female person who was assigned female at birth
5. assigned female at birth, also known as female at birth, DFAB, born female, AFAB, designated female at birth (wd:Q56315990): assignment of a female gender shortly after birth
6. trans man, also known as trans guy, trans male, trans-man, transmasculine, trans men (wd:Q2449503): person assigned female at birth who identifies as a man
7. intersex woman, also known as female intersex human, female intersex person, intersex female human, intersex female person, intersex girl (wd:Q121307100): intersex person who identifies as a woman
8. 25% male, 75% female gender ratio, also known as 3 ♀ : 1 ♂ (wd:Q116752962): gender ratio for Pokémon species
9. 87.5% male, 12.5% female gender ratio, also known as 1 ♀ : 7 ♂, 7 ♂ : 1 ♀ (wd:Q116752952): gender ratio for Pokémon species
10. 50% male, 50% female gender ratio, also known as 1 ♀ : 1 ♂ (wd:Q116752945): gender ratio for Pokémon species

No other items found

No literal items found

[Assistant]
The property for "sex or gender" is wd:P21. The value for "male" is wd:Q6581097 and for "female" is wd:Q6581072.

Step 4: Now, we need to find people who are instances of "creative and performing artist" (wd:Q108289408), and for each, count the number of unmarried partners (wd:P451). Then, for each count, group by gender and count how many artists of each gender have that number of unmarried partners.

Let's try to write a SPARQL query that does this.

[Tool]
Got 1 row and 3 columns:
| numPartners | numFemales  | numMales    |
| ----------- | ----------- | ----------- |
| 0 (xsd:int) | 1 (xsd:int) | 0 (xsd:int) |

[Tool]
Got 1 row and 3 columns:
| subject       | property              | object                                         |
| ------------- | --------------------- | ---------------------------------------------- |
| wd:Q111736720 | occupation (wdt:P106) | creative and performing artist (wd:Q108289408) |

[Assistant]
The previous query only returned a single row, indicating only one female creative and performing artist with zero unmarried partners. This suggests that the occupation "creative and performing artist" (wd:Q108289408) is rarely used directly in Wikidata, and thus, the dataset is extremely sparse.

To improve the coverage, we should consider subclasses or related occupations. Many artists may be listed under more specific occupations that are subclasses of "creative and performing artist". Let's find subclasses of wd:Q108289408 and include them in our query.

[Tool]
Got 8 rows and 1 column:
| subclass                                                        |
| --------------------------------------------------------------- |
| jōrurikatari (wd:Q100951393)                                    |
| dancers and choreographers (wd:Q108290379)                      |
| film, stage and related directors and producers (wd:Q108290380) |
| announcers on radio, television and other media (wd:Q108290381) |
| stage magician (wd:Q15855449)                                   |
| singer (wd:Q177220)                                             |
| visual artist (wd:Q3391743)                                     |
| actor (wd:Q33999)                                               |

[Assistant]
There are several subclasses of "creative and performing artist", including "dancers and choreographers", "film, stage and related directors and producers", "announcers on radio, television and other media", "stage magician", "singer", "visual artist", and "actor".

To increase coverage, we should include people whose occupation is any of these subclasses, as well as the main class itself.

Let's update the query to include all these occupations.

[Tool]
SPARQL execution failed:
Tried to allocate 1.6 GB, but only 1.6 GB were available. Clear the cache or allow more memory for QLever during startup

[Assistant]
The query failed due to memory limitations, likely because it tries to process a large number of artists and their partners in one go. To address this, we can optimize the query by restructuring it to avoid redundant subqueries and reduce the number of joins.

Instead of calculating the counts for male and female artists in separate subqueries, we can count the number of unmarried partners for each artist, retrieve their gender, and then aggregate the results by gender and number of partners.

Let's try a more efficient approach: For each artist with a relevant occupation, count their unmarried partners and their gender, then group by the number of partners and gender, and finally aggregate the counts for each group.

[Tool]
Got 23 rows and 3 columns, showing the first 5 and last 5 rows below:
| numPartners  | gender               | numArtists       |
| ------------ | -------------------- | ---------------- |
| 0 (xsd:int)  | female (wd:Q6581072) | 214884 (xsd:int) |
| 0 (xsd:int)  | male (wd:Q6581097)   | 276882 (xsd:int) |
| 1 (xsd:int)  | female (wd:Q6581072) | 2174 (xsd:int)   |
| 1 (xsd:int)  | male (wd:Q6581097)   | 1834 (xsd:int)   |
| 2 (xsd:int)  | female (wd:Q6581072) | 358 (xsd:int)    |
| ...          | ...                  | ...              |
| 10 (xsd:int) | male (wd:Q6581097)   | 4 (xsd:int)      |
| 11 (xsd:int) | female (wd:Q6581072) | 2 (xsd:int)      |
| 12 (xsd:int) | female (wd:Q6581072) | 2 (xsd:int)      |
| 12 (xsd:int) | male (wd:Q6581097)   | 1 (xsd:int)      |
| 19 (xsd:int) | female (wd:Q6581072) | 2 (xsd:int)      |

[Tool] Stopped generation process