PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?event WHERE {
  wd:Q5577 wdt:P793 ?event
}

The key event related to Salvador Dalí is his exhumation (wd:Q1898510).

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

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

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

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

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

[User] What was the key event related to Salvador Dalí?

[Assistant] To identify the key event related to Salvador Dalí, we need to first find the entity for Salvador Dalí and then look for significant events associated with him. Let's start by searching for Salvador Dalí in the knowledge graph.

[Tool]
Top 10 entity alternatives:
1. Salvador Dalí (wd:Q5577): Spanish artist (1904–1989), jewelry designer, graphic artist, film director, screenwriter, scenographer, photographer, illustrator, holographer, film actor, sculptor, painter, writer, actor
2. Salvador Dalí, also known as Salvador Dali (wd:Q3945890): 1966 short film by Andy Warhol
3. Salvador Dalí, also known as Salvador Dali, Salvador Dalì (wd:Q28669534): 2016 song by Marracash and Guè Pequeno
4. Salvador Dalí (wd:Q3945892): 1970 film
5. Salvador Dalí (wd:Q76627906): photograph by Man Ray
6. Salvador Dalí (wd:Q110890669): 1941 exhibition at Museum of Modern Art
7. Salvador Dalí (wd:Q104633152): exhibition in 1970
8. Salvador Dali (wd:Q76456803): print in the National Gallery of Art (NGA 147625)
9. Salvador Dali (wd:Q103927804): painting by Otto Duecker
10. Salvador Dalí Desert, also known as Dali Desert, Dalí Desert, Desierto Dali, Salvador Dali Desert (wd:Q1382079): desert in Bolivia

[Assistant] The top result for Salvador Dalí is the Spanish artist (wd:Q5577). Now, let's list the triples where Salvador Dalí is the subject to find significant events or notable achievements associated with him.

[Tool]
Got 1,904 rows and 3 columns, showing the first 10 rows below:
| subject                  | property                         | object                                                                               |
| ------------------------ | -------------------------------- | ------------------------------------------------------------------------------------ |
| Salvador Dalí (wd:Q5577) | instance of (wdt:P31)            | human (wd:Q5)                                                                        |
| Salvador Dalí (wd:Q5577) | occupation (wdt:P106)            | actor (wd:Q33999)                                                                    |
| Salvador Dalí (wd:Q5577) | sex or gender (wdt:P21)          | male (wd:Q6581097)                                                                   |
| Salvador Dalí (wd:Q5577) | given name (wdt:P735)            | Salvador (wd:Q18220463)                                                              |
| Salvador Dalí (wd:Q5577) | date of birth (wdt:P569)         | 1904-05-11T00:00:00Z                                                                 |
| Salvador Dalí (wd:Q5577) | Commons category (wdt:P373)      | Salvador Dalí                                                                        |
| Salvador Dalí (wd:Q5577) | image (wdt:P18)                  | <http://commons.wikimedia.org/wiki/Special:FilePath/Salvador%20Dal%C3%AD%201939.jpg> |
| Salvador Dalí (wd:Q5577) | country of citizenship (wdt:P27) | Spain (wd:Q29)                                                                       |
| Salvador Dalí (wd:Q5577) | family name (wdt:P734)           | Dali (wd:Q37534724)                                                                  |
| Salvador Dalí (wd:Q5577) | part of (wdt:P361)               | Salvador Dalí & Louise Bourgeois (wd:Q55236369)                                      |
| ...                      | ...                              | ...                                                                                |

[Assistant]
From the list of triples, we can see various details about Salvador Dalí, such as his occupation, date of birth, and citizenship. However, we need to focus on significant events or notable achievements. Let's look for properties that might indicate important events, such as awards, exhibitions, or notable works.

I will search for properties related to events or notable achievements.

[Tool]
Top 10 property alternatives:
1. significant event, also known as significant occurrence, significant incident, significant achievment, sign. event, outcome (wd:P793 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): significant or notable events associated with the subject
2. competition won, also known as won event, won, winner of, victory (wd:P2522 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): competition or sports event won by the subject, participant in
3. qualifies for event, also known as league this event qualifies for (wd:P3085 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): this event qualifies for that event
4. participant, also known as suspect, player, party, participants, has participant (wd:P710 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): person, group of people or organization (object) that actively t...ct has role" (P3831). Use P1923 for participants that are teams., significant person
5. MusicBrainz event ID, also known as event ID, event MBID, MBE, MB event ID, MBID event (wd:P6423 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): identifier for an event in the MusicBrainz open music encyclopedia
6. final event (wd:P3967 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): final event of a competition
7. participant in, also known as participated in, present at, takes part, took part, took part in (wd:P1344 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): event in which a person or organization was/is a participant; inverse of P710 or P1923, significant event, part of
8. edition number, also known as number of event, software version number, version number (wd:P393 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): number of an edition (first, second, ... as 1, 2, ...) or event, series ordinal
9. set in period, also known as time period set in, time period of setting, time period, takes place in time, takes place during (wd:P2408 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): historical, contemporary, or future period, year, century or day...rk or genre is set in or event featured in the story of the work
10. X moment ID, also known as Twitter event ID, Twitter moment ID, Twitter Moments ID, twt moment ID, X event ID (wd:P10767 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): identifier of a moment feed on X (formerly Twitter)

[Assistant]
The property "significant event" (wdt:P793) seems to be the most relevant for finding notable events associated with Salvador Dalí. Let's use this property to find the significant events in his life.

I will execute a SPARQL query to find the significant events related to Salvador Dalí.

[Tool]
Got 1 row and 1 column:
| ?event      |
| ----------- |
| wd:Q1898510 |

[Assistant]
The significant event related to Salvador Dalí is represented by the entity wd:Q1898510. To understand what this event is, let's fetch the label and description of this entity.

I will execute a SPARQL query to get the label and description of the event.

[Tool]
Got 1 row and 2 columns:
| ?eventLabel | ?eventDescription                                                   |
| ----------- | ------------------------------------------------------------------- |
| exhumation  | excavation of a buried corpse; a... digging up, especially a corpse |

[Assistant]
The significant event related to Salvador Dalí is his exhumation. This event refers to the excavation of his buried corpse, which is a notable and unusual occurrence in his life.

Here is the final SPARQL query and answer:

```sparql
SELECT ?event WHERE { wd:Q5577 wdt:P793 ?event }
```

The key event related to Salvador Dalí is his exhumation (wd:Q1898510).

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
ASK WHERE {
  wd:Q3616 wdt:P1082 ?tehranPopulation .
  wd:Q64 wdt:P1082 ?berlinPopulation .
  FILTER ( ?tehranPopulation > ?berlinPopulation )
}

True

[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] Is the capital of Iran bigger than that of Germany?

[Assistant]
To answer this question, we need to identify the capitals of Iran and Germany, and then compare their population sizes. Let's start by finding the capitals of these countries.

First, I will search for the entities representing Iran and Germany.

[Tool]
Top 10 entity alternatives:
1. Iran, also known as ir, IRI, IRN, Islamic Rep. Iran, Islamic Republic of Iran (wd:Q794): country in Western Asia
2. Qajar Iran, also known as Guarded Domains of Persia, Sublime State of Persia, Qajar Persia, Persia, Iran (wd:Q63158027): country in Western Asia (1789–1925)
3. Iran (wd:Q2043606): village in North Ossetia, Russia
4. Iran, also known as Īrān (wd:Q10859757): Iranian newspaper
5. IRAN, also known as Iran: Journal of the British Institute of Persian Studies (wd:Q5973372): academic journal
6. Irane Man, also known as Iran (wd:Q100939484): 2018 studio by Homayoun Shajarian & Sohrab Pournazeri
7. IRAN (wd:Q108434787): herbarium
8. Iran, also known as Iran (first name), Iran (given name) (wd:Q21286079): male given name
9. Iran, also known as IMO 5327817 (wd:Q101778560): ship built in 1941
10. Iran (wd:Q96382820): About Iran

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

[Assistant]
From the search results, we can see that the correct entities for Iran and Germany are:

- Iran: `wd:Q794`
- Germany: `wd:Q183`

Next, we need to find the capitals of these countries. I will look for the property that represents the capital of a country.

[Tool]
Top 10 property alternatives:
1. capital of, also known as national capital of, parish seat of, provincial capital of, seat of, state capital (wd:P1376 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): country, state, department, canton or other administrative division of which the municipality is the governmental seat, located in the administrative territorial entity
2. capital, also known as administrative seat, seat of government, seat, principal place, location of capital (wd:P36 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): seat of government of a country, province, state or other type of administrative territorial entity
3. capital cost, also known as budget, cost, unit cost (wd:P2130 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): amount of money spent on building or producing an object
4. authorised capital, also known as authorized capital (wd:P12651 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): maximum amount of share capital that the company is authorised to issue to shareholders
5. number of matches played/races/starts, also known as gp, starts, races, number of games played, mp (wd:P1350 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): matches or games a player or a team played during an event. Also...matches a player officially appeared in during the whole career.
6. uses capitalization for, also known as capitalises, capitalizes, uses capitalisation for (wd:P6106 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): lexical classes and subclasses of words as well as other uses in the language where the first letter is written as a capital letter
7. market capitalization, also known as market cap, market capitalisation (wd:P2226 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): total value of issued shares by a publicly traded company
8. location, also known as neighbourhood, whereabouts, vilage, venue, town (wd:P276 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): location of the object, structure or event. In the case of an ad...ity use P706. Use P7153 for locations associated with the object
9. located in the administrative territorial entity, also known as is in the settlement of, is in the voivodeship of, is in the shire of, is in the state of, is in the territory of (wd:P131 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): the item is located on the territory of the following administra...if the item falls only partially into the administrative entity., location, part of
10. nominal share capital (wd:P8247 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): total of the nominal values of the issued ordinary and preference shares of the entity

[Assistant]
The correct property for the capital of a country is `wdt:P36`. Now, I will use this property to find the capitals of Iran and Germany.

Let's execute a SPARQL query to get the capitals of Iran and Germany.

[Tool]
Got 1 row and 2 columns:
| ?iranCapital      | ?germanyCapital |
| ----------------- | --------------- |
| Tehran (wd:Q3616) | Berlin (wd:Q64) |

[Assistant]
We have found that the capital of Iran is Tehran (`wd:Q3616`) and the capital of Germany is Berlin (`wd:Q64`). Next, we need to find the population of these cities to compare them.

I will now search for the property that represents the population of a city.

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

[Assistant]
The correct property for the population of a city is `wdt:P1082`. Now, I will use this property to find the populations of Tehran and Berlin.

Let's execute a SPARQL query to get the populations of these cities.

[Tool]
Got 1 row and 2 columns:
| ?tehranPopulation | ?berlinPopulation |
| ----------------- | ----------------- |
| 8693706           | 3782202           |

[Assistant]
We have found that the population of Tehran is 8,693,706 and the population of Berlin is 3,782,202.

Now, we can compare these populations to answer the question. Since 8,693,706 is greater than 3,782,202, the capital of Iran (Tehran) is indeed bigger than the capital of Germany (Berlin).

Let's confirm this with an ASK query to ensure the result is accurate.

[Tool] True

[Assistant]
The ASK query confirms that the population of Tehran is indeed greater than the population of Berlin.

Therefore, the answer to the question "Is the capital of Iran bigger than that of Germany?" is **True**.

Here is the final SPARQL query and answer:

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ( COUNT( ?language ) AS ?count ) WHERE {
  wd:Q30 wdt:P37 ?language .
}

Got 1 row and 1 column:
| ?count |
| ------ |
| 1      |

[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 official languages does the united states of america have?

[Assistant] To answer the question about the number of official languages in the United States of America, we need to identify the relevant entities and properties in the knowledge graph. Let's start by searching for the entity representing the United States of America.

[Tool]
Top 10 entity alternatives:
1. United States, also known as the U.S. of A, United States of America, the US of America, United States of North America, U. S. (wd:Q30): country primarily located in North America
2. Istadus Unidus the America, also known as United States of America (wd:Q29045433): Wikimedia permanent duplicate item
3. United States of America (wd:Q100270731): scholarly article
4. United States of America (wd:Q103971355): encyclopedic article; Grove Art Online
5. United States of America (wd:Q105870683): vocal track by Kikki Danielsson; 1980 studio recording
6. United States of America (wd:Q105870692): song written and composed by Donna Fargo, originally recorded by Donna Fargo and released in 1974
7. United States of America (wd:Q106315054): vocal track by Donna Fargo; 1974 studio recording
8. United States of America, also known as Star Trek USA, USA (wd:Q99281400): country of the United States of America as depicted in Star Trek
9. United States of America (wd:L350484-S1)
10. United States (of America) (wd:L399000-S1)

[Assistant] The correct entity for the United States of America is `wd:Q30`. Next, we need to find the property that represents the official language(s) of a country. Let's search for a property related to "official language".

[Tool]
Top 10 property alternatives:
1. official language, also known as language spoken, spoken in, speaking, language official (wd:P37 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): language designated as official by this item, language used
2. native label, also known as official title, original label, original language label, original language name, original language title (wd:P1705 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): label for the items in their official language  or their original language, name
3. Ethnologue language status, also known as EGIDS, language status (wd:P3823 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): language status identifier by Ethnologue.com using EGIDS scale
4. language regulatory body, also known as language authority, regulatory body (wd:P1018 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): regulatory body of a language
5. languages spoken, written or signed, also known as language of expression, language, wrote language, writes language, uses language (wd:P1412 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): language(s) that a person or a people speaks, writes or signs, including the native language(s)
6. native language, also known as first language, L1 speaker of, language native, mother tongue (wd:P103 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): language or languages a person has learned from early childhood, languages spoken, written or signed
7. language used, also known as languages used, medium of instruction, used language, uses language, working language (wd:P2936 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): language widely used (spoken or written) in this place or at this event or organisation
8. language of work or name, also known as language of the reference, language of URL, language of website, language of work, named in language (wd:P407 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): language associated with this creative work (such as books, show...guage" (P103) and "languages spoken, written or signed" (P1412))
9. programmed in, also known as language, programming language, written in (wd:P277 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): the programming language(s) in which the software is developed
10. writing language, also known as languages of writings, languages written, language written, writing languages, language of works (wd:P6886 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): language in which the writer has written their work, languages spoken, written or signed

[Assistant]
The correct property for "official language" is `wdt:P37`. Now, let's construct a SPARQL query to find the official languages of the United States of America (`wd:Q30`).

We will start with a simple query to list the official languages and then count them.

```sparql
SELECT ?language
WHERE {
  wd:Q30 wdt:P37 ?language .
}
```

Let's execute this query to see the results.

[Tool]
Got 1 row and 1 column:
| ?language          |
| ------------------ |
| English (wd:Q1860) |

[Assistant]
The query returned one official language for the United States of America, which is English (`wd:Q1860`). To answer the question, we need to count the number of official languages. We can modify the query to count the results.

```sparql
SELECT (COUNT(?language) AS ?count)
WHERE {
  wd:Q30 wdt:P37 ?language .
}
```

Let's execute this query to get the count.

[Tool]
Got 1 row and 1 column:
| ?count |
| ------ |
| 1      |

[Assistant]
The query returned that the United States of America has 1 official language.

Therefore, the answer to the question "How many official languages does the United States of America have?" is:

**1**

Here is the final SPARQL query and answer:

```sparql
SELECT (COUNT(?language) AS ?count)
WHERE {
  wd:Q30 wdt:P37 ?language .
}
```

Answer: 1

Now, I will provide the final answer using the `answer` function.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
ASK WHERE {
  wd:Q183 wdt:P2046 ?germanyArea .
  wd:Q36 wdt:P2046 ?polandArea .
  FILTER ( ?germanyArea > ?polandArea )
}

True

[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] Is Germany bigger than Poland?

[Assistant] To determine if Germany is bigger than Poland, we need to compare their areas. Let's start by searching for the entities representing Germany and Poland in the knowledge graph.

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

[Assistant] The top result for Germany is `wd:Q183`, which represents the current Federal Republic of Germany. Now let's search for Poland.

[Tool]
Top 10 entity alternatives:
1. Poland, also known as Republic of Poland (wd:Q36): country in Central Europe
2. Polish–Lithuanian Commonwealth, also known as Commonwealth of Poland, First Republic of Poland, Poland, Poland-Lithuania, Poland–Lithuania (wd:Q172107): historical multinational monarchist state in Central Europe (Crown of the Kingdom of Poland and the Grand Duchy of Lithuania)
3. Crown of the Kingdom of Poland, also known as Kingdom of Poland, Poland (wd:Q171348): 1385–1795 territorial possessions of the King of Poland
4. Poland, also known as Poland, OH, Poland, Ohio (wd:Q2300093): village in Ohio, United States
5. Poland, also known as Poland, Maine, Poland, ME (wd:Q1572109): town in Androscoggin County, Maine, United States
6. Polish, also known as Poland (wd:Q385059): breed of chicken
7. Poland, also known as Boran (wd:Q5763870): village in Kiribati
8. Poland, also known as Poland, Chautauqua County, New York, Poland, New York, Poland, NY (wd:Q7208883): town in Chautauqua County, New York, United States
9. Poland, also known as Poland, Herkimer County, New York, Poland, NY (wd:Q7208887): village in Herkimer County, New York, United States
10. Poland - The Warsaw Concert, also known as Poland (wd:Q599300): album by Tangerine Dream

[Assistant] The top result for Poland is `wd:Q36`, which represents the current Republic of Poland. Next, we need to find the property that represents the area of a country. Let's search for the property "area" in the knowledge graph.

[Tool]
Top 10 property alternatives:
1. area, also known as total area, surface area, surface, size, resolution (wd:P2046 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): area occupied by an object
2. field of work, also known as scientific discipline, scientific area, responsible for, research on, research fields (wd:P101 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): specialization of a person or organization; see P106 for the occupation, interested in
3. applies to part, also known as when viewed as, valid for part, section, region, per (wd:P518 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): part, aspect, or form of the item to which the claim applies
4. applies to jurisdiction, also known as belongs to jurisdiction, applies to territorial jurisdiction, applies to region, applies to place, applies to geographic place (wd:P1001 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): the item (institution, law, public office, public register...) o...a territorial jurisdiction: a country, state, municipality, ...), significant place, characteristic of, operating area
5. operating area, also known as province served, serves jurisdiction, serves geographic region, serves geographic area, serves area (wd:P2541 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): geographic area or jurisdiction an organisation or industry operates in, serves, or has responsibility for, location
6. water area (wd:P8887 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): area/surface of a geographical entity that is covered by water, area
7. interested in, also known as area of interest, area of research, field of interest, field of research, field of study (wd:P2650 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): item of special or vested interest to this person or organisation
8. location, also known as neighbourhood, whereabouts, vilage, venue, town (wd:P276 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): location of the object, structure or event. In the case of an ad...ity use P706. Use P7153 for locations associated with the object
9. located in the administrative territorial entity, also known as is in the settlement of, is in the voivodeship of, is in the shire of, is in the state of, is in the territory of (wd:P131 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): the item is located on the territory of the following administra...if the item falls only partially into the administrative entity., location, part of
10. electoral district, also known as riding, seat, ward, electoral area, electorate (wd:P768 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): electoral district this person is representing, or of the office... or "office contested" (P541) or "candidacy in election" (P3602)

[Assistant]
The top result for the property "area" is `wd:P2046`. Now we can construct a SPARQL query to retrieve the areas of Germany and Poland and compare them.

Let's write a SPARQL query to get the areas of both countries and then compare them.

[Tool]
Got 1 row and 2 columns:
| ?germanyArea | ?polandArea |
| ------------ | ----------- |
| 357588       | 312683      |

[Assistant]
The area of Germany is 357,588 square kilometers, and the area of Poland is 312,683 square kilometers. Therefore, Germany is indeed bigger than Poland.

To confirm this with an ASK query, we can check if the area of Germany is greater than the area of Poland.

Let's write the ASK query.

[Tool] True

[Assistant]
The ASK query confirms that Germany is indeed bigger than Poland.

Therefore, the answer to the question "Is Germany bigger than Poland?" is **True**.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ( COUNT( DISTINCT ?occupation ) AS ?count ) WHERE {
  wd:Q7245 wdt:P106 ?occupation .
}

Got 1 row and 1 column:
| ?count |
| ------ |
| 12     |

Mark Twain had 12 occupations.

[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 occupations did Mark Twain have?

[Assistant] To answer the question about how many occupations Mark Twain had, we need to identify the entity for Mark Twain and the property for occupation. Let's start by searching for the entity "Mark Twain" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Mark Twain, also known as Samuel L. Clemens, Samuel Langhorne Clemens, Quintus Curtius Snodgrass, Samuel Clemens (wd:Q7245): American author and humorist (1835–1910), science fiction writer, opinion journalist, children's writer, autobiographer, travel writer, prose writer, journalist, humorist, novelist, aphorist, teacher, writer
2. 2362 Mark Twain, also known as Mark Twain (wd:Q959983): asteroid
3. Mark Twain (wd:Q6770075): crater on Mercury
4. Mark Twain (wd:Q6770076): 2001 documentary film on the life of Mark Twain directed by Ken Burns
5. Mark Twain (wd:Q66716403): 1873 article in Cartoon portraits and biographical sketches of men of the day
6. Mark Twain, also known as Mark Twain, St. Louis (wd:Q6770071): neighborhood of St. Louis, Missouri, United States
7. Rosa 'Mark Twain', also known as Mark Twain (wd:Q83668756): rose cultivar
8. Mark Twain (wd:Q116958637): bronze sculpture by unidentified artist
9. Mark Twain (wd:Q20174185): painting by Charles Noel Flagg
10. Mark Twain (wd:Q79493007): print by Samuel Johnson Woolf (American, 1880-1948) (1920.11)

[Assistant] The top result for "Mark Twain" is the correct entity, which is `wd:Q7245`. Next, we need to find the property that represents occupations. Let's search for the property "occupation" in Wikidata.

[Tool]
Top 10 property alternatives:
1. occupation, also known as job, work, vocation, profession, employment (wd:P106 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): occupation of a person; see also "field of work" (Property:P101), "position held" (Property:P39)
2. field of this occupation, also known as practice, works in, profession's field, practices, field of this profession (wd:P425 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): field corresponding to this occupation or profession (use only f...fessions - for people use Property:P101, for companies use P452)
3. members have occupation, also known as profession of members, organization of, organization for, organisation of, organisation for (wd:P3989 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): some or all members of this group share the occupation
4. practiced by, also known as proponent, studied by, practitioners, practioner, occupation of this field (wd:P3095 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): type of agents that study this subject or work in this field
5. position held, also known as function, held position, holds position, job, office held (wd:P39 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): subject currently or formerly holds the object position or public office
6. employer, also known as working at, working for, working place, works at, works for (wd:P108 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): person or organization for which the subject works or worked, affiliation
7. country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): the object is a country that recognizes the subject as its citizen, country
8. occupant, also known as tenant, resident, renter, occupiers, lessee (wd:P466 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): person or organization occupying property, used by
9. field of work, also known as scientific discipline, scientific area, responsible for, research on, research fields (wd:P101 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): specialization of a person or organization; see P106 for the occupation, interested in
10. work location, also known as work place, working from, working at, worked from, worked at (wd:P937 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): location where persons or organisations were actively participating in employment, business or other work, significant place, location

[Assistant]
The property for occupation is `wdt:P106`. Now, let's construct a SPARQL query to count the number of distinct occupations that Mark Twain (`wd:Q7245`) had.

Here is the initial SPARQL query:

```sparql
SELECT (COUNT(DISTINCT ?occupation) AS ?count)
WHERE {
  wd:Q7245 wdt:P106 ?occupation .
}
```

Let's execute this query to get the result.

[Tool]
Got 1 row and 1 column:
| ?count |
| ------ |
| 12     |

[Assistant]
The SPARQL query returned a count of 12 distinct occupations for Mark Twain. Therefore, the answer to the question "How many occupations did Mark Twain have?" is 12.

Here is the final SPARQL query and answer:

```sparql
SELECT (COUNT(DISTINCT ?occupation) AS ?count)
WHERE {
  wd:Q7245 wdt:P106 ?occupation .
}
```

Answer: Mark Twain had 12 occupations.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?birthPlace ?birthPlaceLabel WHERE {
  wd:Q79904 wdt:P19 ?birthPlace .
  OPTIONAL {
    ?birthPlace rdfs:label ?birthPlaceLabel .
    FILTER ( LANG( ?birthPlaceLabel ) = 'en' )
  }
}

Got 1 row and 2 columns:
| ?birthPlace            | ?birthPlaceLabel |
| ---------------------- | ---------------- |
| New York City (wd:Q60) | New York City    |

New York City

[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] Where was the author of The Catcher in the Rye born ?

[Assistant]
To answer the question "Where was the author of The Catcher in the Rye born?", we need to identify the following:

1. The author of "The Catcher in the Rye".
2. The place of birth of the author.

Let's start by finding the entity for "The Catcher in the Rye" and then identify its author.

[Tool]
Top 10 entity alternatives:
1. The Catcher in the Rye, also known as Catcher in the Rye (wd:Q183883): 1951 novel by J. D. Salinger
2. Catcher in the Rye (wd:Q5051738): Chinese punk rock band
3. Catcher In the Rye (wd:Q16184712): 2011 EP by Datarock
4. Catcher in the Rye (wd:Q110065569): 2021 single by Ross Jennings
5. Catcher in the Rye (wd:Q10443835): song by Guns N' Roses
6. The Catcher in the Rye (wd:Q16689546): 2012 debut studio album by Ann
7. The Catcher in the Rye (wd:Q125291968): 2001 Back Bay edition
8. Catchers in the rye (wd:Q68693473): scientific article published on 01 January 1990
9. The Catcher in the Rye in popular culture (wd:Q7721703): Influence of J.D. Salinger's 1951 novel
10. The Catcher in the Rye in popular culture (wd:Q7721703): Influence of J.D. Salinger's 1951 novel

[Assistant] The top result for "The Catcher in the Rye" is the correct one, which is `wd:Q183883`. Now, let's find the author of this novel.

[Tool]
Got 1 row and 3 columns:
| subject                             | property         | object                     |
| ----------------------------------- | ---------------- | -------------------------- |
| The Catcher in the Rye (wd:Q183883) | author (wdt:P50) | J. D. Salinger (wd:Q79904) |

[Assistant]
The author of "The Catcher in the Rye" is J. D. Salinger, represented by the entity `wd:Q79904`. Next, we need to find the place of birth of J. D. Salinger.

Let's search for the property "place of birth" to ensure we have the correct property to use in our query.

[Tool]
Top 10 property alternatives:
1. place of birth, also known as POB, location of birth, location born, born in, birthplace (wd:P19 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): 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 wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): 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 wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): 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 wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): 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 wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): 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 wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): 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 wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): 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 wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): 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 wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): 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 wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): what the place, monument, memorial, or holiday, commemorates, main subject

[Assistant]
The correct property for "place of birth" is `wdt:P19`. Now, let's find the place of birth of J. D. Salinger using this property.

We will execute a SPARQL query to get the place of birth of J. D. Salinger.

[Tool]
Got 1 row and 1 column:
| ?birthPlace            |
| ---------------------- |
| New York City (wd:Q60) |

[Assistant]
The place of birth of J. D. Salinger, the author of "The Catcher in the Rye," is New York City, represented by the entity `wd:Q60`.

To provide a complete answer, we can include the label of the place of birth in the final SPARQL query.

Let's execute the final SPARQL query to get both the IRI and the label of the place of birth.

[Tool]
Got 1 row and 2 columns:
| ?birthPlace            | ?birthPlaceLabel |
| ---------------------- | ---------------- |
| New York City (wd:Q60) | New York City    |

[Assistant]
The place of birth of J. D. Salinger, the author of "The Catcher in the Rye," is New York City.

Here is the final SPARQL query and answer:

```sparql
SELECT ?birthPlace ?birthPlaceLabel
WHERE {
  wd:Q79904 wdt:P19 ?birthPlace .
  OPTIONAL { ?birthPlace rdfs:label ?birthPlaceLabel . FILTER(LANG(?birthPlaceLabel) = 'en') }
}
```

Answer: New York City

Now, I will provide the final answer using the `answer` function.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
ASK {
  wd:Q213849 wdt:P576 ?dissolved
}

False

[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] Does the ATI Company still exist?

[Assistant]
To determine if the ATI Company still exists, we need to find the entity for ATI Company in the knowledge graph and check if it has a property indicating its current status, such as "dissolved" or "active."

First, let's search for the entity "ATI Company" in the knowledge graph.

[Tool]
Top 10 entity alternatives:
1. company, also known as co., firm (wd:Q783794): legal entity representing an association of people, whether natural, legal or a mixture of both, with a specific objective
2. company, also known as company (military unit), military company (wd:Q102538): military unit size designation
3. enterprise, also known as business enterprise, firm, company (wd:Q6881511): organizational unit producing goods or services, which benefits ...n-making, especially for the allocation of its current resources
4. Ati (wd:Q755791): city
5. Aashaadha, also known as Ashadha, Āṭi (wd:Q1105198): month in Hindu calender
6. Artigas Airport, also known as ATI, SUAG (wd:Q1430852): airport
7. Company (wd:Q225093): 2002 film directed by Ram Gopal Varma
8. Company (wd:Q2915810): 1970 musical comedy by Stephen Sondheim
9. Company (wd:Q23723998): 2016 single by Justin Bieber
10. Ati, also known as Ati language, Ati (Philippines) (wd:Q3217458): Malayo-Polynesian language spoken and native to the Ati people of Panay

[Assistant]
None of the top 10 results seem to match the ATI Company specifically. Let's try a more targeted search by including "Advanced Micro Devices" or "AMD" in the query, as ATI was acquired by AMD.

Let's search for "ATI Technologies" or "ATI" in the knowledge graph.

[Tool]
Top 10 entity alternatives:
1. ATI Technologies, also known as Array Technologies Incorporated (wd:Q213849): Canadian technology corporation
2. Atipa Technologies (wd:Q67904906): American hardware manufacturer
3. technology, also known as technologies, technological sciences, technicology, tech, technological science (wd:Q11016): making, modification, usage, and knowledge of tools, machines, t... and methods of organization, or tools and techniques so created
4. Ati (wd:Q755791): city
5. Aashaadha, also known as Ashadha, Āṭi (wd:Q1105198): month in Hindu calender
6. Artigas Airport, also known as ATI, SUAG (wd:Q1430852): airport
7. Ati, also known as Ati language, Ati (Philippines) (wd:Q3217458): Malayo-Polynesian language spoken and native to the Ati people of Panay
8. The Alan Turing Institute, also known as Turing Institute, turing.ac.uk, ATI (wd:Q16826821): research institute in Britain
9. Boneh-ye Ati, also known as Boneh-ye ‘Āţī, ‘Āţī (wd:Q4941616): village in Iran
10. Allegheny Technologies, also known as Allegheny Technologies Incorporated, ATI, ATI Metals (wd:Q1361648): company

[Assistant]
The top result, "ATI Technologies" (wd:Q213849), seems to be the correct entity for ATI Company. Now, let's check if this entity has any properties that indicate its current status, such as "dissolved" or "active."

We can look for properties like "dissolved" (P576) or "inception" (P571) to determine if the company is still active.

Let's list the triples for this entity to see if we can find relevant information.

[Tool]
Got 302 rows and 3 columns, showing the first 10 rows below:
| subject                       | property                         | object                                                                                |
| ----------------------------- | -------------------------------- | ------------------------------------------------------------------------------------- |
| ATI Technologies (wd:Q213849) | instance of (wdt:P31)            | business (wd:Q4830453)                                                                |
| ATI Technologies (wd:Q213849) | country (wdt:P17)                | Canada (wd:Q16)                                                                       |
| ATI Technologies (wd:Q213849) | Commons category (wdt:P373)      | ATI Technologies                                                                      |
| ATI Technologies (wd:Q213849) | image (wdt:P18)                  | <http://commons.wikimedia.org/wiki/Special:FilePath/Atitechnologiessiliconvalley.jpg> |
| ATI Technologies (wd:Q213849) | inception (wdt:P571)             | 1985-08-01T00:00:00Z                                                                  |
| ATI Technologies (wd:Q213849) | official name (wdt:P1448)        | ATI Technologies Inc.                                                                 |
| ATI Technologies (wd:Q213849) | official website (wdt:P856)      | <http://www.ati.com/>                                                                 |
| ATI Technologies (wd:Q213849) | different from (wdt:P1889)       | ATI Systems (wd:Q76809554)                                                            |
| ATI Technologies (wd:Q213849) | owned by (wdt:P127)              | AMD (wd:Q128896)                                                                      |
| ATI Technologies (wd:Q213849) | headquarters location (wdt:P159) | Markham (wd:Q44016)                                                                   |
| ...                           | ...                              | ...                                                                                |

[Assistant]
From the listed triples, we can see that ATI Technologies (wd:Q213849) has the following relevant properties:
- **Inception (P571)**: 1985-08-01T00:00:00Z
- **Owned by (P127)**: AMD (wd:Q128896)

There is no property indicating that the company has been dissolved. Instead, it is owned by AMD, which suggests that it still exists as a part of AMD.

To confirm this, we can construct an ASK query to check if ATI Technologies has a "dissolved" property (P576). If the query returns false, it means the company has not been dissolved and is still active.

Let's execute the ASK query.

[Tool] True

[Assistant]
The ASK query returned `True`, which indicates that ATI Technologies does have a "dissolved" property. This means that the company has been dissolved.

Therefore, the answer to the question "Does the ATI Company still exist?" is **False**.

Let's provide the final answer.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?instrument ?instrumentLabel WHERE {
  wd:Q1779 wdt:P1303 ?instrument .
  OPTIONAL {
    ?instrument rdfs:label ?instrumentLabel .
    FILTER ( LANG( ?instrumentLabel ) = 'en' )
  }
}

Got 3 rows and 2 columns:
| ?instrument          | ?instrumentLabel |
| -------------------- | ---------------- |
| voice (wd:Q17172850) | voice            |
| cornet (wd:Q202027)  | cornet           |
| trumpet (wd:Q8338)   | trumpet          |

Louis Armstrong played the following instruments: voice, cornet, and trumpet.

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

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

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

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

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

[User] What instruments did Louis Armstrong play?

[Assistant] To answer the question about the instruments played by Louis Armstrong, we need to identify the entity for Louis Armstrong and the property that indicates the instruments he played. Let's start by searching for the entity representing Louis Armstrong in the knowledge graph.

[Tool]
Top 10 entity alternatives:
1. Louis Armstrong, also known as Satchelmouth, Satch, Satchmo, Louis Daniel Armstrong, Dipper (wd:Q1779): American jazz musician, trumpeter and singer (1901–1971), film score composer, radio personality, recording artist, jazz musician, street artist, film actor, songwriter, bandleader, trumpeter, conductor, writer, singer, actor
2. Louis Armstrong (wd:Q98823980): photograph by Lisette Model (MET, 2019.33)
3. Louis Armstrong (wd:Q132754304): online exhibition from Louis Armstrong House and Archives, Queens College, City University of New York
4. Louis Armstrong (wd:Q100721665): college basketball player (1991–1992) Northern Iowa, basketball player
5. Louis Armstrong Stadium (wd:Q1029132): tennis venue in New York City from 1978 to 2016
6. Louis Armstrong Park (wd:Q931042): park in New Orleans, Louisiana, U.S.
7. Louis Armstrong House, also known as Louis Armstrong House Museum (wd:Q6686652): NY location listed on National Register of Historic Places
8. Louise Armstrong (wd:Q6688616): American writer and feminist, human rights activist, children's writer, writer
9. Louis Armstrong Stadium (wd:Q47487977): tennis stadium opened in 2018, replacing a 1978 venue of the same name
10. Louis Armstrong Jazzfesztivál (wd:Q65218436)

[Assistant] The top result for Louis Armstrong is the correct one (wd:Q1779). Now, let's find the property that indicates the instruments he played. We can search for properties related to "instrument" or "played" to find the appropriate property.

[Tool]
Top 10 property alternatives:
1. instrument, also known as uses this instrument, teaches instrument, instruments, plays this instrument, plays instrument (wd:P1303 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): musical instrument that a person plays or teaches or used in a music occupation, uses
2. uses, also known as uses trope, used, using, wielded, wields (wd:P2283 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): item or concept used by the subject or in the operation (see also instrument [P1303] and armament [P520])
3. instrumentation, also known as scoring, scored for, orchestration, instruments employed, orchestrated for (wd:P870 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): combination of musical instruments employed in a composition or accompanying a (folk) dance
4. performer, also known as actor, sung by, singer, recording by, recorded by (wd:P175 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): actor, musician, band or other performer associated with this role or musical work, contributor to the creative work or subject
5. setlist, also known as set list, works performed, songs performed, performances, performance list (wd:P9793 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): performances of songs or other music at an event; concert program, presented works
6. produced sound, also known as call, makes call, makes sound, sound, sound emitted (wd:P4733 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): item for the sound generated by the subject, for instance the cry of an animal
7. orchestration, also known as scoring, score notation, orchestration notation, orchestration in notated form, notated scoring (wd:P11862 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): an enumeration of the instruments used in a musical composition or arrangement described using any system of score notation
8. has melody, also known as uses tune, to the tune of, uses melody, TTTO, has tune (wd:P1625 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): this work has the melody of the following work, references work, tradition or theory
9. beats per minute, also known as BPM, tempo, musical tempo, metronome mark, bpm (wd:P1725 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): tempo of a musical work, indicated numerically (use P1558 for qualitative tempo markings), frequency
10. tempo marking, also known as tempo, musical tempo (wd:P1558 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): qualitative indication about the speed or pace of a given musical piece (use P1725 for numerical tempo markings)

[Assistant]
The property "instrument" (wd:P1303) seems to be the most relevant for indicating the instruments played by a musician. Let's use this property to find the instruments played by Louis Armstrong (wd:Q1779).

I will now construct a SPARQL query to retrieve the instruments played by Louis Armstrong.

[Tool]
Got 3 rows and 1 column:
| ?instrument          |
| -------------------- |
| voice (wd:Q17172850) |
| cornet (wd:Q202027)  |
| trumpet (wd:Q8338)   |

[Assistant]
The SPARQL query returned the instruments played by Louis Armstrong, which include his voice, cornet, and trumpet. To provide a more complete answer, I will also include the labels of these instruments in the final query.

Let's modify the query to include the labels of the instruments.

[Tool]
Got 3 rows and 2 columns:
| ?instrument          | ?instrumentLabel |
| -------------------- | ---------------- |
| voice (wd:Q17172850) | voice            |
| cornet (wd:Q202027)  | cornet           |
| trumpet (wd:Q8338)   | trumpet          |

[Assistant]
The SPARQL query has successfully retrieved the instruments played by Louis Armstrong along with their labels. The instruments are:

- Voice (wd:Q17172850)
- Cornet (wd:Q202027)
- Trumpet (wd:Q8338)

Now, I will provide the final SPARQL query and the answer to the user's question.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ( COUNT( ?scale ) AS ?count ) WHERE {
  ?scale wdt:P31 wd:Q179651 .
}

Got 1 row and 1 column:
| ?count |
| ------ |
| 22     |

There are 22 musical scales.

[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 musical scales are there?

[Assistant]
To answer the question "How many musical scales are there?", we need to identify the concept of a musical scale in the knowledge graph and then count the number of distinct scales.

### Step 1: Identify the Concept of Musical Scale
First, let's search for the entity representing "musical scale" in the knowledge graph.

[Tool]
Top 10 entity alternatives:
1. scale, also known as gamut, musical scale (wd:Q179651): set of musical notes ordered by pitch
2. musical scale (wd:L490906-S1)
3. Japanese musical scale (wd:Q1683319): Scales used in Japanese traditional music
4. minor scale; musical scale (wd:L739761-S2)
5. A Perfect Musical Scale (wd:Q60136008): scientific article published in Nature
6. Synthetic Musical Scales (wd:Q58123356)
7. type of musical scale (wd:L640378-S8)
8. MUSICAL INTELLIGENCE AND SCALE PREFERENCE. (wd:Q30335517): scientific article
9. sixth note in musical scale (wd:L739149-S1)
10. sixth note of musical scale (wd:L1405299-S1)

[Assistant]
From the search results, the most relevant entity for "musical scale" is `wd:Q179651`, which is described as "set of musical notes ordered by pitch."

### Step 2: Identify Properties Related to Musical Scales
Next, we need to find properties that might link to different types of musical scales. We can search for properties related to "scale" or "musical scale" to see if there are any specific properties that can help us.

Let's search for properties related to "musical scale."

[Tool]
Top 10 property alternatives:
1. ascending scale, also known as arohana (wd:P7598 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): sequence of notes starting from a tonic in one octave and ending with the tonic one octave above
2. scale, also known as scale ratio (wd:P1752 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): proportional ratio of a linear dimension of a ọnụ ọgụgụ, map, etc,  to the same feature of the original - 1:n. Use 1 for lifesize
3. musical bars shown, also known as measures, musical measures, musical bars, bars, bar number (wd:P7141 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): qualifier of the initial and final musical bars shown in a quotation or excerpt
4. tonality, also known as in key, key, key of musical composition, key used, musical key (wd:P826 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): key of a musical composition
5. descending scale, also known as raga theme, avarohana (wd:P7599 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): sequence of notes starting from a tonic in one octave and ending with the tonic one octave below
6. instrument, also known as uses this instrument, teaches instrument, instruments, plays this instrument, plays instrument (wd:P1303 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): musical instrument that a person plays or teaches or used in a music occupation, uses
7. beats per minute, also known as BPM, tempo, musical tempo, metronome mark, bpm (wd:P1725 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): tempo of a musical work, indicated numerically (use P1558 for qualitative tempo markings), frequency
8. tempo marking, also known as tempo, musical tempo (wd:P1558 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): qualitative indication about the speed or pace of a given musical piece (use P1725 for numerical tempo markings)
9. measurement scale, also known as measured by (wd:P1880 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): scale by which a phenomenon is measured
10. LilyPond notation, also known as musical notation (wd:P6883 as wdt/psv/p/pr/wdtn/pqn/pq/psn/prn/pqv/prv/ps): musical notation in LilyPond syntax

[Assistant]
From the search results, the properties related to musical scales are not directly useful for counting the number of musical scales. However, we can use the entity `wd:Q179651` to find instances of musical scales.

### Step 3: Count the Number of Musical Scales
We can use the `wdt:P31` property (instance of) to find all instances of `wd:Q179651` (musical scale). Let's write a SPARQL query to count these instances.

Here is the SPARQL query to count the number of musical scales:

```sparql
SELECT (COUNT(?scale) AS ?count)
WHERE {
  ?scale wdt:P31 wd:Q179651 .
}
```

Let's execute this query to get the count.

[Tool]
Got 1 row and 1 column:
| ?count |
| ------ |
| 22     |

[Assistant]
The SPARQL query returned a count of 22 musical scales.

### Final Answer
There are 22 musical scales according to the data in Wikidata.

Here is the final SPARQL query and answer:

```sparql
SELECT (COUNT(?scale) AS ?count)
WHERE {
  ?scale wdt:P31 wd:Q179651 .
}
```

Answer: There are 22 musical scales.

Now, I will provide the final answer using the `answer` function.

[Tool] Stopped generation process