PREFIX ps: <http://www.wikidata.org/prop/statement/>
PREFIX pq: <http://www.wikidata.org/prop/qualifier/>
PREFIX xsd: <http://www.w3.org/2001/XMLSchema#>
PREFIX p: <http://www.wikidata.org/prop/>
PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?primeMinister ?primeMinisterLabel ?start ?end WHERE {
  wd:Q29 p:P6 ?statement .
  ?statement ps:P6 ?primeMinister .
  ?statement pq:P580 ?start .
  ?statement pq:P582 ?end .
  FILTER ( ?start <= '2011-12-31' ^^ xsd:date && ?end >= '2011-01-01' ^^ xsd:date ) OPTIONAL {
    ?primeMinister rdfs:label ?primeMinisterLabel .
    FILTER ( LANG( ?primeMinisterLabel ) = 'en' )
  }
}

José Luis Rodríguez Zapatero was the Prime Minister of Spain in 2011.

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

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

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

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

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

[User] who is the prime minister of spain 2011?

[Assistant]
To find out who was the Prime Minister of Spain in 2011, we need to identify the relevant entities and properties in the knowledge graph. We will start by searching for the entity representing Spain and the property for "Prime Minister."

Let's begin by searching for the entity "Spain."

[Tool]
Top 10 entity alternatives:
1. Spain, also known as Kingdom of Spain (wd:Q29): country in southwestern Europe with territories in Africa
2. Spain men's national football team, also known as La Furia, The Spanish Fury, The Red One, The Red Fury, The Fury (wd:Q42267): men's national association football team representing Spain
3. Second Spanish Republic, also known as Spain (wd:Q178038): political regime established in Spain between April 14, 1931 and April 1, 1939
4. New Spain, also known as Colonial Central America, Central America under Spain, Viceroyalty of New Spain, Spanish Mexico, Spanish Central America (wd:Q170603): viceroyalty of the Spanish Empire (1535-1821)
5. Spain under the Restoration, also known as Bourbon Restoration, Spain, Second Bourbon Restoration, Restoration, Restoration (Spain) (wd:Q1044536): name given to a period between 1874 (end of First Spanish Republ...econd Spanish Republic), and the state of Spain during that time
6. Kingdom of Spain (1820-1823), also known as Kingdom of Spain, Spain, Trienio Liberal (wd:Q238809): 1820–1823 Spanish political period
7. Spain under Joseph Bonaparte, also known as Kingdom of Spain, Napoleonic Spain, Spain (wd:Q1709185): Napoleonic client state (1808–1813)
8. Sexenio Democrático, also known as Kingdom of Spain, Spain (wd:Q12411956): 1868–1874 period of fu under a provisional government
9. Ominous Decade, also known as Kingdom of Spain, second restoration of absolutism, Spain (wd:Q2378204): period in the history of Spain, corresponding to the second rest...reign of Fernando VII from August 31, 1823 to September 29, 1833
10. Hispanic Monarchy, also known as Spains, Hispanic Crown, Spain, Kingdom of Spains, Crown of Spain (wd:Q766543): (1479-1716) set of territories distributed throughout the world,...monarch and corresponding to the period of the House of Habsburg

[Assistant] The top result for "Spain" is the entity `wd:Q29`, which represents the modern country of Spain. Next, we need to find the property that represents "Prime Minister." Let's search for the property "Prime Minister."

[Tool]
Top 10 property alternatives:
1. head of government, also known as head of national government, mayor, premier, president, prime minister (wd:P6 as pqn/ps/pq/prn/psv/wdt/pr/pqv/p/prv/psn/wdtn): head of the executive power of this town, city, municipality, state, country, or other governmental body, director / manager, chairperson
2. office held by head of government, also known as title of head of government, position of head of government, office of head of government, head of government's office, position held by head of government (wd:P1313 as pqn/ps/pq/prn/psv/wdt/pr/pqv/p/prv/psn/wdtn): political office that is fulfilled by the head of the government of this item
3. office held by head of state, also known as head of state, position held by head of state, state headed by (wd:P1906 as pqn/ps/pq/prn/psv/wdt/pr/pqv/p/prv/psn/wdtn): political office that is fulfilled by the head of state of this item
4. head of state, also known as leader, state headed by, monarch, president, queen (wd:P35 as pqn/ps/pq/prn/psv/wdt/pr/pqv/p/prv/psn/wdtn): official with the highest formal authority in a country/state, director / manager, chairperson
5. position held by head of the organization, also known as position held by head of the organisation, secretary's position, president's position, position held by head of the organization, office held by head of the organisation (wd:P2388 as pqn/ps/pq/prn/psv/wdt/pr/pqv/p/prv/psn/wdtn): position of the head of this item
6. member of cabinet, also known as cabinet, minister of cabinet (wd:P5054 as pqn/ps/pq/prn/psv/wdt/pr/pqv/p/prv/psn/wdtn): qualifier for "position held" (P39) to indicate the cabinet to which a minister belongs
7. rector, also known as chancellor, university president, Rector (academia), president (wd:P1075 as pqn/ps/pq/prn/psv/wdt/pr/pqv/p/prv/psn/wdtn): senior official in an educational institution., director / manager, chairperson
8. chairperson, also known as dean, headed by, leader, president, chairwoman (wd:P488 as pqn/ps/pq/prn/psv/wdt/pr/pqv/p/prv/psn/wdtn): presiding member of an organization, group or body, director / manager, significant person
9. legislative body, also known as aboriginal council, Zila, Tehsil, rural council, representative body (wd:P194 as pqn/ps/pq/prn/psv/wdt/pr/pqv/p/prv/psn/wdtn): legislative body governing this entity; political institution wi...ted representatives, such as a parliament/legislature or council
10. party chief representative, also known as communist party chief, Communist Party Secretary, party chief, party secretary (wd:P210 as pqn/ps/pq/prn/psv/wdt/pr/pqv/p/prv/psn/wdtn): chief representative of a party in an institution or an administrative unit (use qualifier to identify the party)

[Assistant]
The top result for "Prime Minister" is the property `wd:P6`, which represents the head of government. Now, we need to find the specific person who was the Prime Minister of Spain in 2011. We will use the `wd:P6` property and the `wd:Q29` entity to construct a query that filters by the year 2011.

Let's execute a SPARQL query to find the Prime Minister of Spain in 2011.

[Tool]
Got 2 rows and 2 columns:
| ?primeMinister            | ?primeMinisterLabel          |
| ------------------------- | ---------------------------- |
| Mariano Rajoy (wd:Q10819) | Mariano Rajoy                |
| wd:Q41395                 | José Luis Rodríguez Zapatero |

[Assistant]
The query returned two results for the Prime Minister of Spain in 2011: Mariano Rajoy and José Luis Rodríguez Zapatero. To determine which one was the Prime Minister in 2011, we need to check the exact dates of their terms.

Let's refine the query to include the start and end dates of their terms to confirm who was the Prime Minister in 2011.

[Tool]
Got 2 rows and 4 columns:
| ?primeMinister            | ?primeMinisterLabel          | ?start               | ?end                 |
| ------------------------- | ---------------------------- | -------------------- | -------------------- |
| Mariano Rajoy (wd:Q10819) | Mariano Rajoy                | 2011-12-21T00:00:00Z | 2018-06-01T00:00:00Z |
| wd:Q41395                 | José Luis Rodríguez Zapatero | 2004-04-16T00:00:00Z | 2011-12-21T00:00:00Z |

[Assistant]
The refined query shows that José Luis Rodríguez Zapatero was the Prime Minister of Spain from April 16, 2004, to December 21, 2011, and Mariano Rajoy took over on December 21, 2011.

Since the question asks specifically about the Prime Minister of Spain in 2011, the correct answer is José Luis Rodríguez Zapatero, as he was in office for the majority of the year 2011.

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 ?placeOfDeath WHERE {
  wd:Q1317 wdt:P20 ?placeOfDeath .
}

Osama bin Laden's compound in Abbottabad (wd:Q3065522)

[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 bin laden found and killed?

[Assistant]
To answer the question about where Bin Laden was found and killed, we need to identify the relevant entity for Bin Laden and then find the location associated with his death.

### Step 1: Identify the entity for Osama Bin Laden
I will start by searching for the entity "Osama Bin Laden" in the knowledge graph.

[Tool]
Top 10 entity alternatives:
1. Osama bin Laden, also known as Usama bin Laden, Usāmah bin Muḥammad bin ‘Awaḍ bin Lādin, Osama bin Mohammed bin Awad bin Laden, Crankshaft (wd:Q1317): Saudi terrorist and co-founder of al-Qaeda (1957–2011), businessperson, civil engineer, terrorist, jihadist
2. Osama bin Laden (wd:Q10612826): rogue bull elephant in India
3. death of Osama bin Laden, also known as Geronimo EKIA, killing of Bin Laden, killing of Osama bin Laden, Operation Neptune Spear, Osama bin Laden death (wd:Q19085): U.S. military operation in Abbottabad, Pakistan
4. Osama bin Laden bodyguards (wd:Q7105668): bodyguards of Osama Bin Laden
5. Osama Bin Laden Tape (wd:Q110056559): sketch from Saturday Night Live
6. Meeting Osama Bin Laden (wd:Q129687082): 2004 Television film
7. Operation Osama Bin Laden (wd:Q122824240): 2021 video game
8. Targeted: Osama Bin Laden (wd:Q129687094): 2004 Television film
9. Fatwas of Osama bin Laden (wd:Q5437340)
10. 2007 Osama bin Laden video (wd:Q4609081): 2007 film

[Assistant]
The top result for "Osama Bin Laden" is `wd:Q1317`, which is the correct entity for Osama Bin Laden, the founder of al-Qaeda.

### Step 2: Identify the property for the place of death
Next, I will search for the property that represents the place of death.

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

[Assistant]
The property for the place of death is `wd:P20`.

### Step 3: Query the place of death for Osama Bin Laden
Now, I will construct a SPARQL query to find the place of death for Osama Bin Laden (`wd:Q1317`).

[Tool]
Got 1 row and 1 column:
| ?placeOfDeath                                          |
| ------------------------------------------------------ |
| Osama bin Laden's compound in Abbottabad (wd:Q3065522) |

[Assistant]
The place where Osama Bin Laden was found and killed is his compound in Abbottabad, Pakistan.

### Final Answer
Here is the final SPARQL query and the answer to the question:

```sparql
SELECT ?placeOfDeath WHERE {
  wd:Q1317 wdt:P20 ?placeOfDeath .
}
```

The answer is: **Osama bin Laden's compound in Abbottabad (wd:Q3065522)**.

[Tool] Stopped generation process


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?movie ?movieLabel WHERE {
  ?movie wdt:P161 wd:Q36767 .
  OPTIONAL {
    ?movie rdfs:label ?movieLabel .
    FILTER ( LANG( ?movieLabel ) = "en" )
  }
}

Got 39 rows and 2 columns, showing the first 5 and last 5 rows below:
| ?movie                                                 | ?movieLabel                               |
| ------------------------------------------------------ | ----------------------------------------- |
| Harry Potter and the Goblet of Fire (wd:Q102225)       | Harry Potter and the Goblet of Fire       |
| Harry Potter and the Order of the Phoenix (wd:Q102235) | Harry Potter and the Order of the Phoenix |
| Vanity Fair (wd:Q1046841)                              | Vanity Fair                               |
| The Batman: Part II (wd:Q111187129)                    | The Batman — Part II                      |
| Mickey 17 (wd:Q112977213)                              | Mickey 17                                 |
| ...                                                    | ...                                       |
| Remember Me (wd:Q632680)                               | Remember Me                               |
| Tenet (wd:Q63985561)                                   | Tenet                                     |
| The Twilight Saga (wd:Q652599)                         | The Twilight Saga                         |
| Dark Kingdom: The Dragon King (wd:Q701947)             | Dark Kingdom: The Dragon King             |
| Cosmopolis (wd:Q737055)                                | Cosmopolis                                |

The query confirms that Robert Pattinson is indeed an actor, among other occupations. Now, let's try a different approach to find the movies he has acted in. We can use the property `wdt:P161` (cast member) in a more flexible way by searching for movies where Robert Pattinson is listed as a cast member through statements.

I will execute the following SPARQL query:

```sparql
SELECT ?movie ?movieLabel
WHERE {
  ?movie wdt:P161 wd:Q36767 .
  OPTIONAL { ?movie rdfs:label ?movieLabel . FILTER(LANG(?movieLabel) = "en") }
}
```

This query will return the movies where Robert Pattinson is listed as a cast member and their English labels.

Let's execute this query.

<tool_call>
{"name": "execute", "arguments": "{'kg': 'wikidata', 'sparql': 'SELECT ?movie ?movieLabel WHERE { ?movie wdt:P161 wd:Q36767 . OPTIONAL { ?movie rdfs:label ?movieLabel . FILTER(LANG(?movieLabel) = \\"en\\") } }'}"}
</tool_call>

[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 movies have robert pattinson in them?

[Assistant]
To answer the question about the movies Robert Pattinson has been in, we need to identify the entity for Robert Pattinson and then find the movies he has acted in. Let's start by searching for Robert Pattinson in the knowledge graph.

I will use the `search_entity` function to find the entity for Robert Pattinson.

[Tool]
Top 10 entity alternatives:
1. Robert Pattinson, also known as Robert Douglas Thomas Pattinson (wd:Q36767): British actor and model, television actor, film producer, stage actor, film actor, composer, singer, actor, model
2. Robert Pattinson, also known as Sir Robert Pattinson (wd:Q7528828): British politician (1872-1954), politician
3. Robert Kyle Pattinson (wd:Q76133988): Peerage person ID=554665
4. Robert Clive Pattinson (wd:Q79322762): gynecologist
5. Sir Robert Pattinson Academy (wd:Q15277935): school in Lincolnshire, UK
6. Sir Robert Pattinson Academy (wd:Q122684378): single academy trust
7. Robert Pattinson and Dracula are distant relatives (wd:Q17707978): Wikinews article
8. Robert, also known as Robert of Clermont (wd:Q266309): Count of Clermont-en-Beauvaisis
9. Robert (wd:Q4927937): male given name
10. Prince Robert, Duke of Chartres, also known as Robert (wd:Q502885): Union Army soldier (1840–1910), military personnel

[Assistant]
The top result for "Robert Pattinson" is the British actor and model, which is the correct entity we are looking for. The IRI for Robert Pattinson is `wd:Q36767`.

Next, we need to find the property that indicates the movies he has acted in. A common property for this would be "cast member of" or something similar. Let's search for properties related to acting in movies.

I will use the `search_property` function to find the relevant property.

[Tool]
Top 10 property alternatives:
1. depicted by, also known as acted by, shown in, seen in, portrayed by, played by (wd:P1299 as pqn/ps/pq/prn/psv/wdt/pr/pqv/p/prv/psn/wdtn): object depicting this subject (object being creative works such as books, films, paintings)
2. character role, also known as role, plays, performer of, as, acting role (wd:P453 as pqn/ps/pq/prn/psv/wdt/pr/pqv/p/prv/psn/wdtn): specific role played or filled by subject -- use only as qualifier of "cast member" (P161), "voice actor" (P725)
3. class of object(s) of occurrence, also known as may happen to, may occur to items of the class, object class of action, object class of occurrence, of (wd:P12913 as pqn/ps/pq/prn/psv/wdt/pr/pqv/p/prv/psn/wdtn): class that includes the object(s) to which this occurrence (or class of occurrence) occurs or occurred
4. used by, also known as armiger, user, played by, of (wd:P1535 as pqn/ps/pq/prn/psv/wdt/pr/pqv/p/prv/psn/wdtn): item or concept that makes use of the subject (use sub-properties when appropriate)
5. performer, also known as actor, sung by, singer, recording by, recorded by (wd:P175 as pqn/ps/pq/prn/psv/wdt/pr/pqv/p/prv/psn/wdtn): actor, musician, band or other performer associated with this role or musical work, contributor to the creative work or subject
6. cast member, also known as feat., starring (film/play), film starring, starring, actor (wd:P161 as pqn/ps/pq/prn/psv/wdt/pr/pqv/p/prv/psn/wdtn): actor in the subject production [use "character role" (P453) and...use "recorded participant" (P11108) for non-fiction productions], significant person, performer
7. present in work, also known as is shown in, in work, in narrative, character in, from work (wd:P1441 as pqn/ps/pq/prn/psv/wdt/pr/pqv/p/prv/psn/wdtn): this (fictional or fictionalized) entity, place, or person appea...r works, P1343 for entities described in non-fictional accounts)
8. agent of action, also known as being done by, initiator, initiated by, done by, doer (wd:P12995 as pqn/ps/pq/prn/psv/wdt/pr/pqv/p/prv/psn/wdtn): particular item that initiates this action or class of actions
9. agents of action have role, also known as actors have role, agent has role, agent of action has role, agents have role, done by agent(s) with role (wd:P12993 as pqn/ps/pq/prn/psv/wdt/pr/pqv/p/prv/psn/wdtn): role that agents of this action take on in the context of this action
10. describes actor of (wd:P12027 as pqn/ps/pq/prn/psv/wdt/pr/pqv/p/prv/psn/wdtn): predicate sense whose actor (an agent or a cause—basically the instigator of an action) is denoted by this sense

[Assistant]
The property "cast member" (P161) seems to be the most appropriate for finding the movies Robert Pattinson has acted in. This property indicates the actors who are part of a film or production.

Now, let's construct a SPARQL query to find the movies where Robert Pattinson (wd:Q36767) is listed as a cast member.

I will execute the following SPARQL query:

```sparql
SELECT ?movie ?movieLabel
WHERE {
  wd:Q36767 wdt:P161 ?movie .
  OPTIONAL { ?movie rdfs:label ?movieLabel . FILTER(LANG(?movieLabel) = "en") }
}
```

This query will return the movies where Robert Pattinson is a cast member and their English labels.

Let's execute this query.

[Tool] Got no rows and 2 columns

[Assistant]
It appears that the initial query did not return any results. This might be because the property `wdt:P161` (cast member) is not directly linked to Robert Pattinson in the way we expected. Let's try another approach by using the property `wdt:P106` (occupation) to confirm that Robert Pattinson is indeed an actor and then look for the movies he has acted in using a different property or a more complex query.

First, let's verify that Robert Pattinson is an actor by checking his occupation.

I will execute the following SPARQL query:

```sparql
SELECT ?occupation ?occupationLabel
WHERE {
  wd:Q36767 wdt:P106 ?occupation .
  OPTIONAL { ?occupation rdfs:label ?occupationLabel . FILTER(LANG(?occupationLabel) = "en") }
}
```

This query will return Robert Pattinson's occupations and their English labels.

Let's execute this query.

[Tool]
Got 8 rows and 2 columns:
| ?occupation                     | ?occupationLabel |
| ------------------------------- | ---------------- |
| television actor (wd:Q10798782) | television actor |
| film actor (wd:Q10800557)       | film actor       |
| singer (wd:Q177220)             | singer           |
| stage actor (wd:Q2259451)       | stage actor      |
| film producer (wd:Q3282637)     | film producer    |
| actor (wd:Q33999)               | actor            |
| composer (wd:Q36834)            | composer         |
| model (wd:Q4610556)             | model            |

[Assistant]
The query confirms that Robert Pattinson is indeed an actor, among other occupations. Now, let's try a different approach to find the movies he has acted in. We can use the property `wdt:P161` (cast member) in a more flexible way by searching for movies where Robert Pattinson is listed as a cast member through statements.

I will execute the following SPARQL query:

```sparql
SELECT ?movie ?movieLabel
WHERE {
  ?movie wdt:P161 wd:Q36767 .
  OPTIONAL { ?movie rdfs:label ?movieLabel . FILTER(LANG(?movieLabel) = "en") }
}
```

This query will return the movies where Robert Pattinson is listed as a cast member and their English labels.

Let's execute this query.

<tool_call>
{"name": "execute", "arguments": "{'kg': 'wikidata', 'sparql': 'SELECT ?movie ?movieLabel WHERE { ?movie wdt:P161 wd:Q36767 . OPTIONAL { ?movie rdfs:label ?movieLabel . FILTER(LANG(?movieLabel) = \\"en\\") } }'}"}
</tool_call>


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?language ?numSpeakers WHERE {
  VALUES ?language {
    wd:Q178440 wd:Q58680
  }
  ?language wdt:P1098 ?numSpeakers .
}
ORDER BY DESC ( ?numSpeakers )
LIMIT 1

The most spoken language in Afghanistan is Pashto.

[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 language do most people speak in afghanistan?

[Assistant]
To answer the question about the most spoken language in Afghanistan, we need to identify the relevant entities and properties in the knowledge graph. We will start by searching for the entity representing Afghanistan and then look for properties related to languages spoken in the country.

First, let's search for the entity representing Afghanistan.

[Tool]
Top 10 entity alternatives:
1. Afghanistan, also known as Afghaunistaun, Afghaunistan, Afghanisthan, Affghaunistan, Afghania (wd:Q889): country in Central and South Asia
2. Afghanistan, also known as Affghanistan, Affghanisthan, Afghaunistaun, Affghaunistan, Afghania (wd:Q889): country in Central and South Asia
3. Kingdom of Afghanistan, also known as Afghanistan, Afghan Kingdom (wd:Q1138904): kingdom in Central Asia between 1926–1973
4. Afghanistan (wd:Q50172288): scientific article published in May 1983
5. Afghanistan (wd:Q47409831): scientific article published in July 1986
6. Afghanistan (wd:Q27715795): journal
7. Afghanistan (wd:Q124440154): journal article from 'Ethnohistory' published in 1973
8. Afghanistan (wd:Q119628112): painting by James Hart Dyke (b.1966), The Black Watch Castle & Museum
9. Afghanistan (wd:Q119441439): painting by Wilhelmina Barns-Graham (1912–2004), Wilhelmina Barns-Graham Trust
10. Afghanistan (wd:Q103889244): encyclopedia article

[Assistant] The top result for "Afghanistan" is `wd:Q889`, which represents the country in Central and South Asia. Next, we need to find the property that indicates the languages spoken in a country. Let's search for properties related to "language" or "spoken language" for the entity `wd:Q889`.

[Tool]
Top 10 property alternatives:
1. official language, also known as language spoken, spoken in, speaking, language official (wd:P37 as wdt/p): language designated as official by this item, language used
2. language used, also known as languages used, medium of instruction, used language, uses language, working language (wd:P2936 as wdt/p): language widely used (spoken or written) in this place or at this event or organisation
3. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as wdt/p): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
4. native label, also known as official title, original label, original language label, original language name, original language title (wd:P1705 as wdt/p): label for the items in their official language  or their original language, name
5. culture, also known as archaeological culture, civilisation, civilization (wd:P2596 as wdt/p): human culture or people (or several cultures) associated with this item, part of
6. ethnic group, also known as ethnic or cultural origin, tribal affiliation, race, people, ethnicity (wd:P172 as wdt/p): subject's ethnicity (consensus is that a VERY high standard of p...agreed on by scholars, or 3) is fictional and portrayed as such)
7. country, also known as sovereign state, state, land, host country (wd:P17 as wdt/p): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
8. described by source, also known as mentioned in, source of item, reviewed in, mentioned in news article, talked about in (wd:P1343 as wdt/p): work where this item is described, attested in
9. Libraries Australia ID, also known as CNLKIN, NLA Kinetica Service identifier, NLA (Australia) identifier, NLA (Australia) ID, Libraries Australia identifier (wd:P409 as wdt/p): identifier issued by the National Library of Australia (see also...F component. Format: 1-12 digits, removing leading zero-padding.
10. Unicode character, also known as emoji, emote, pictograph, Unicode symbol (wd:P487 as wdt/p): Unicode character representing the item (only if this is not a c...acter or a compatiblity character: in that case, use only P4213)

No other items found

[Assistant]
The top relevant property for languages spoken in a country is `wdt:P37` (official language) and `wdt:P2936` (language used). We will use these properties to find the languages spoken in Afghanistan.

Let's execute a SPARQL query to find the languages spoken in Afghanistan using both properties.

```sparql
SELECT ?language WHERE {
  wd:Q889 wdt:P37|wdt:P2936 ?language .
}
```

This query will return the languages that are either official or widely used in Afghanistan.

[Tool]
Got 46 rows and 1 column, showing the first 5 and last 5 rows below:
| ?language                          |
| ---------------------------------- |
| Arabic (wd:Q13955)                 |
| Nuristani (wd:Q161804)             |
| Pamir (wd:Q1772864)                |
| Dari (wd:Q178440)                  |
| Balochi (wd:Q33049)                |
| ...                                |
| Inku (wd:Q4159744)                 |
| Afghan Sign Language (wd:Q4689093) |
| Tajiki Arabic (wd:Q56833)          |
| Pahlavni (wd:Q7124567)             |
| Turkmen (wd:Q9267)                 |

[Assistant]
The query returned a list of languages spoken in Afghanistan. However, it includes both official and widely used languages, and we need to determine which one is the most spoken. To do this, we can use the `wdt:P1098` property, which represents the number of speakers of a language.

Let's modify the query to include the number of speakers for each language and sort the results to find the most spoken language.

```sparql
SELECT ?language ?numSpeakers WHERE {
  wd:Q889 wdt:P37|wdt:P2936 ?language .
  ?language wdt:P1098 ?numSpeakers .
}
ORDER BY DESC(?numSpeakers)
LIMIT 1
```

This query will return the language with the highest number of speakers in Afghanistan.

[Tool]
Got 1 row and 2 columns:
| ?language          | ?numSpeakers |
| ------------------ | ------------ |
| Arabic (wd:Q13955) | 315421300    |

[Assistant]
The query returned that Arabic (wd:Q13955) is the language with the highest number of speakers in Afghanistan, with 315,421,300 speakers.

However, this number seems unusually high for a country like Afghanistan, which has a population of around 38 million. This suggests that the data might be incorrect or incomplete. Let's verify the official languages of Afghanistan and cross-check the number of speakers for the most common languages.

We know that the official languages of Afghanistan are Dari and Pashto. Let's specifically check the number of speakers for these languages.

```sparql
SELECT ?language ?numSpeakers WHERE {
  VALUES ?language { wd:Q178440 wd:Q1860 }
  ?language wdt:P1098 ?numSpeakers .
}
ORDER BY DESC(?numSpeakers)
LIMIT 1
```

This query will return the number of speakers for Dari (wd:Q178440) and Pashto (wd:Q1860), and we can determine which one is the most spoken.

[Tool]
Got 1 row and 2 columns:
| ?language          | ?numSpeakers |
| ------------------ | ------------ |
| English (wd:Q1860) | 753359540    |

[Assistant]
It appears there was a mistake in the previous query. The language `wd:Q1860` actually refers to English, not Pashto. Let's correct this and specifically check the number of speakers for Dari (wd:Q178440) and Pashto (wd:Q1860).

Here is the corrected query:

```sparql
SELECT ?language ?numSpeakers WHERE {
  VALUES ?language { wd:Q178440 wd:Q1860 }
  ?language wdt:P1098 ?numSpeakers .
}
ORDER BY DESC(?numSpeakers)
LIMIT 1
```

Let's execute this query again to get the correct number of speakers for Dari and Pashto.

[Tool]
Got 1 row and 2 columns:
| ?language          | ?numSpeakers |
| ------------------ | ------------ |
| English (wd:Q1860) | 753359540    |

[Assistant]
It seems there is a persistent issue with the language identifiers. Let's manually verify the correct identifiers for Dari and Pashto.

1. **Dari**: Search for "Dari language"
2. **Pashto**: Search for "Pashto language"

Let's search for these entities to ensure we have the correct identifiers.

### Search for Dari Language

[Tool]
Top 10 entity alternatives:
1. Dari, also known as fa-AF, fa_AF, fa-af, Eastern Farsi, Dari language (wd:Q178440): dialect of the Persian language spoken in Afghanistan
2. Zoroastrian Dari, also known as Zoroastrian Dari language, Gavrŭni, Gabrōni, Gabri language, Dari language (Zoroastrian) (wd:Q32389): Northwestern Iranian ethnolect
3. Dari (language/dialect) (wd:L1196362-S1)
4. Dari (language/dialect) (wd:L1196363-S1)
5. language, also known as ways to talk, linguistic system, systems of communication, system of communication, linguistic systems (wd:Q315): structured system of communication
6. language, also known as human language, particular language, languages, idioms, lang (wd:Q34770): particular system of communication, often named for the region or peoples that use it
7. Darlag County, also known as Dari, Dari County, Tarlag (wd:Q1166385): county in Qinghai, China
8. New Persian, also known as Dari, Modern Persian (wd:Q56356571): modern stage of the Persian language
9. Dari (wd:Q1924589): town in Jharkhand, India
10. dopamine reuptake inhibitor, also known as Inhibitors, Dopamine Uptake, Uptake Inhibitors, Dopamine, Reuptake Inhibitors, Dopamine, Inhibitors, Dopamine Reuptake, DRI (wd:Q899647): class of drug

[Assistant]
The correct identifier for the Dari language is `wd:Q178440`.

### Search for Pashto Language

Now, let's search for the Pashto language.

[Tool]
Top 10 entity alternatives:
1. Pashto, also known as Pushtoo, Pushto language, Pushto, ps, Pashtun language (wd:Q58680): Indo-Aryan language of Afghanistan and Pakistan
2. Pashto language (wd:L1320867-S1)
3. Pashto language (wd:L1320869-S1)
4. Pashto language (wd:L933704-S1)
5. Pashto language (wd:L933705-S1)
6. Pashto (language) (wd:L613020-S1)
7. Pashto language (wd:L1320865-S1)
8. Southern Pashto, also known as Kandahārí Pashtó, Kandahari Pashto, South Western Pashto, Southwestern Pashto, Southern Pashto dialect (wd:Q16112855): Pashto dialect
9. Northern Pashto, also known as Northern Pashto dialect, Northern Pashto language, Peshawari Pashto, Yusufzai Pashto, Yusufzai (Peshawari) Pashto (wd:Q12642194): language
10. Central Pashto, also known as Central Pashto dialect, Central Pashto language, Manźanəi Pax̌to (wd:Q5061628): language

[Assistant]
The correct identifier for the Pashto language is `wd:Q58680`.

Now that we have the correct identifiers for Dari and Pashto, let's execute the query again to find the number of speakers for these languages and determine which one is the most spoken in Afghanistan.

```sparql
SELECT ?language ?numSpeakers WHERE {
  VALUES ?language { wd:Q178440 wd:Q58680 }
  ?language wdt:P1098 ?numSpeakers .
}
ORDER BY DESC(?numSpeakers)
LIMIT 1
```

[Tool]
Got 1 row and 2 columns:
| ?language          | ?numSpeakers |
| ------------------ | ------------ |
| Pashto (wd:Q58680) | 39000000     |

[Assistant]
The query returned that Pashto (wd:Q58680) is the language with the highest number of speakers in Afghanistan, with approximately 39 million speakers.

Therefore, the most spoken language in Afghanistan is Pashto.

Here is the final SPARQL query and answer:

```sparql
SELECT ?language ?numSpeakers WHERE {
  VALUES ?language { wd:Q178440 wd:Q58680 }
  ?language wdt:P1098 ?numSpeakers .
}
ORDER BY DESC(?numSpeakers)
LIMIT 1
```

The most spoken language in Afghanistan is Pashto.

[Tool] Stopped generation process


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?placeOfBirth ?placeOfBirthLabel WHERE {
  wd:Q11578 wdt:P19 ?placeOfBirth .
  OPTIONAL {
    ?placeOfBirth rdfs:label ?placeOfBirthLabel .
    FILTER ( LANG( ?placeOfBirthLabel ) = "en" )
  }
}

Got 1 row and 2 columns:
| ?placeOfBirth        | ?placeOfBirthLabel |
| -------------------- | ------------------ |
| Lynwood (wd:Q849619) | Lynwood            |

Venus Williams came from Lynwood, California.

[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 did venus williams come from?

[Assistant]
To answer the question "Where did Venus Williams come from?", we need to identify the place of birth or origin of Venus Williams. Let's start by finding the entity for Venus Williams in the knowledge graph.

I will search for the entity "Venus Williams" in Wikidata.

[Tool]
Top 10 entity alternatives:
1. Venus Williams, also known as Venus Ebony Starr Williams (wd:Q11578): American tennis player (born 1980), tennis player, entrepreneur, writer
2. B. Venus Williams (wd:Q102291516): Ph.D. Dartmouth College 2005
3. Williams sisters, also known as Venus and Serena Williams (wd:Q1180052): doubles partnership between Venus and Serena Williams
4. Venus Williams career statistics (wd:Q7920613)
5. 2014 Venus Williams tennis season (wd:Q16960857)
6. Venus Williams at 2009 US Open (wd:Q124025673)
7. Venus Williams at the 2013 US Open (wd:Q124025332)
8. Venus, also known as Planet Venus, Sol II, Sol 2, ♀ (wd:Q313): planet second-closest to the Sun in the Solar System
9. Venus, also known as ♀, Planet Venus, Sol 2, Sol II (wd:Q313): planet second-closest to the Sun in the Solar System
10. Venus (wd:Q47652): Roman goddess of love, sexuality, procreation and pleasure

[Assistant]
The top result for "Venus Williams" is the correct entity (wd:Q11578). Now, let's find the property that represents the place of birth or origin. We can search for properties related to "birth" or "origin" for this entity.

I will search for properties related to "birth" for the entity Venus Williams.

[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/p): most specific known birth location of a person, animal or fictional character, location
2. birth name, also known as née, name at birth, name before marriage, ne, né (wd:P1477 as wdt/p): full name of a person at birth, if different from their current, generally used name, name
3. date of birth, also known as year of birth, birthdate, DOB, born on, born (wd:P569 as wdt/p): date on which the subject was born, inception
4. work period (start), also known as start working, flourished (start), start time for work, start date of activity, fl. (start) (wd:P2031 as wdt/p): start of period during which a person or group flourished (fl. = "floruit") in their professional activity, start time, floruit
5. sex or gender, also known as gender or sex, sex, gender identity, gender expression, gender (wd:P21 as wdt/p): sex or gender identity of human or animal. For human: male, fema...m, female organism. Groups of same gender use subclass of (P279)
6. country of citizenship, also known as subject of (country), nation of citizenship, national of, nationality, nation (wd:P27 as wdt/p): the object is a country that recognizes the subject as its citizen, country
7. described by source, also known as mentioned in, source of item, reviewed in, mentioned in news article, talked about in (wd:P1343 as wdt/p): work where this item is described, attested in
8. mother, also known as mom, is child of, mommy, mum, mummy (wd:P25 as wdt/p): female parent of the subject. For stepmother, use "stepparent" (P3448), parent
9. father, also known as son of, child of, parent, is son of, is daughter of (wd:P22 as wdt/p): male parent of the subject. For stepfather, use "stepparent" (P3448), parent
10. given name, also known as name, proper name, personal name, middle name, forename (wd:P735 as wdt/p): first name or another given name of this person; values used with the property should not link disambiguations nor family names, name

No other items found

[Assistant]
The property "place of birth" (wdt:P19) is the most relevant for our query. Now, let's construct a SPARQL query to find the place of birth of Venus Williams (wd:Q11578).

I will execute the following SPARQL query:

```sparql
SELECT ?placeOfBirth ?placeOfBirthLabel
WHERE {
  wd:Q11578 wdt:P19 ?placeOfBirth.
  OPTIONAL { ?placeOfBirth rdfs:label ?placeOfBirthLabel . FILTER(LANG(?placeOfBirthLabel) = "en") }
}
```

This query will return the place of birth of Venus Williams and its label in English.

Let's execute the query.

[Tool]
Got 1 row and 2 columns:
| ?placeOfBirth        | ?placeOfBirthLabel |
| -------------------- | ------------------ |
| Lynwood (wd:Q849619) | Lynwood            |

[Assistant]
The place of birth of Venus Williams is Lynwood, California.

Here is the final SPARQL query and answer:

```sparql
SELECT ?placeOfBirth ?placeOfBirthLabel
WHERE {
  wd:Q11578 wdt:P19 ?placeOfBirth.
  OPTIONAL { ?placeOfBirth rdfs:label ?placeOfBirthLabel . FILTER(LANG(?placeOfBirthLabel) = "en") }
}
```

Answer: Venus Williams came from Lynwood, California.

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

[Tool] Stopped generation process


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?governmentForm ?governmentFormLabel WHERE {
  wd:Q16 wdt:P122 ?governmentForm .
  OPTIONAL {
    ?governmentForm rdfs:label ?governmentFormLabel .
    FILTER ( LANG( ?governmentFormLabel ) = "en" )
  }
}

Got 3 rows and 2 columns:
| ?governmentForm                     | ?governmentFormLabel    |
| ----------------------------------- | ----------------------- |
| parliamentary system (wd:Q166747)   | parliamentary system    |
| constitutional monarchy (wd:Q41614) | constitutional monarchy |
| federation (wd:Q43702)              | federation              |

Canada has a parliamentary system, a constitutional monarchy, and a federation as its forms of government.

[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 form of government does canada?

[Assistant] To answer the question about the form of government in Canada, we need to identify the entity for Canada and the property that describes its form of government. Let's start by searching for the entity representing Canada in the knowledge graph.

[Tool]
Top 10 entity alternatives:
1. Canada, also known as CA, CAN, Dominion of Canada, ISO 3166-1:CA (wd:Q16): country in North America
2. La Canyada, also known as Cañada (wd:Q1553440): municipality of Spain
3. Province of Canada, also known as British Canada, Canada, United Canadas, United Province of Canada (wd:Q1121436): 1841–1867 UK possession in North America
4. Canada, also known as French Canada (wd:Q2569593): French colony in New France between 1534 and 1763
5. Canada, also known as Canada, KS (wd:Q5029265): unincorporated community in Kansas, United States
6. Canada, also known as Canada, KY, Canada, Kentucky (wd:Q1031917): unincorporated community in Pike County, Kentucky, United States
7. Canadá (wd:Q20275156): human settlement in Mexico
8. Canada, also known as Kanada (wd:Q2684010): hamlet in Ooststellingwerf, Netherlands
9. Canada (wd:Q21287484): Wikimedia permanent duplicate item
10. Canada (wd:Q13265795): 2012 novel by Richard Ford

[Assistant] The top result for "Canada" is the country in North America, which is the entity we are looking for. The IRI for this entity is `wd:Q16`. Next, we need to find the property that describes the form of government. Let's search for properties related to "government" or "form of government".

[Tool]
Top 10 property alternatives:
1. basic form of government, also known as form of government, government, type of government (wd:P122 as pqn/ps/pq/prn/psv/wdt/pr/pqv/p/prv/psn/wdtn): subject's government
2. capital, also known as administrative seat, seat of government, seat, principal place, location of capital (wd:P36 as pqn/ps/pq/prn/psv/wdt/pr/pqv/p/prv/psn/wdtn): seat of government of a country, province, state or other type of administrative territorial entity
3. head of government, also known as head of national government, mayor, premier, president, prime minister (wd:P6 as pqn/ps/pq/prn/psv/wdt/pr/pqv/p/prv/psn/wdtn): head of the executive power of this town, city, municipality, state, country, or other governmental body, director / manager, chairperson
4. office held by head of government, also known as title of head of government, position of head of government, office of head of government, head of government's office, position held by head of government (wd:P1313 as pqn/ps/pq/prn/psv/wdt/pr/pqv/p/prv/psn/wdtn): political office that is fulfilled by the head of the government of this item
5. authority, also known as executive authority, governed by, governing authority, governing body, has authority (wd:P797 as pqn/ps/pq/prn/psv/wdt/pr/pqv/p/prv/psn/wdtn): entity having executive power on given entity
6. voting system, also known as electoral system, voting system, type of election (wd:P8196 as pqn/ps/pq/prn/psv/wdt/pr/pqv/p/prv/psn/wdtn): system used for this election or vote
7. Classification of the Functions of Government, also known as COFOG ID, COFOG number (wd:P9798 as pqn/ps/pq/prn/psv/wdt/pr/pqv/p/prv/psn/wdtn): UN classification to compare government agencies across countries
8. office held by head of state, also known as head of state, position held by head of state, state headed by (wd:P1906 as pqn/ps/pq/prn/psv/wdt/pr/pqv/p/prv/psn/wdtn): political office that is fulfilled by the head of state of this item
9. country, also known as sovereign state, state, land, host country (wd:P17 as pqn/ps/pq/prn/psv/wdt/pr/pqv/p/prv/psn/wdtn): sovereign state that this item is in (not to be used for human beings), located in the administrative territorial entity
10. foundational text, also known as main text, treaty, organic law, founding document, establishing document (wd:P457 as pqn/ps/pq/prn/psv/wdt/pr/pqv/p/prv/psn/wdtn): text through which an institution or object has been created or established

[Assistant]
The property `wd:P122` (basic form of government) seems to be the most relevant for our query. Now, let's construct a SPARQL query to find the form of government for Canada using this property.

Here is the initial SPARQL query:

```sparql
SELECT ?governmentForm WHERE {
  wd:Q16 wdt:P122 ?governmentForm .
}
```

Let's execute this query to see the results.

[Tool]
Got 3 rows and 1 column:
| ?governmentForm                     |
| ----------------------------------- |
| parliamentary system (wd:Q166747)   |
| constitutional monarchy (wd:Q41614) |
| federation (wd:Q43702)              |

[Assistant]
The results show that Canada has a parliamentary system, a constitutional monarchy, and a federation as its forms of government. To provide a more complete and human-readable answer, we can include the labels of these forms of government in the query.

Here is the updated SPARQL query:

```sparql
SELECT ?governmentForm ?governmentFormLabel WHERE {
  wd:Q16 wdt:P122 ?governmentForm .
  OPTIONAL { ?governmentForm rdfs:label ?governmentFormLabel . FILTER(LANG(?governmentFormLabel) = "en") }
}
```

Let's execute this query to get the labels.

[Tool]
Got 3 rows and 2 columns:
| ?governmentForm                     | ?governmentFormLabel    |
| ----------------------------------- | ----------------------- |
| parliamentary system (wd:Q166747)   | parliamentary system    |
| constitutional monarchy (wd:Q41614) | constitutional monarchy |
| federation (wd:Q43702)              | federation              |

[Assistant]
The results confirm that Canada has a parliamentary system, a constitutional monarchy, and a federation as its forms of government.

Here is the final SPARQL query and the answer to the user's question:

```sparql
SELECT ?governmentForm ?governmentFormLabel WHERE {
  wd:Q16 wdt:P122 ?governmentForm .
  OPTIONAL { ?governmentForm rdfs:label ?governmentFormLabel . FILTER(LANG(?governmentFormLabel) = "en") }
}
```

Answer: Canada has a parliamentary system, a constitutional monarchy, and a federation as its forms of government.

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

[Tool] Stopped generation process


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?team ?teamLabel ?sport ?award ?awardLabel ?hallOfFame WHERE {
  wd:Q193637 wdt:P54 ?team .
  wd:Q193637 wdt:P641 ?sport .
  wd:Q193637 wdt:P166 ?award .
  OPTIONAL {
    wd:Q193637 wdt:P3646 ?hallOfFame
  }
  .
  OPTIONAL {
    ?team rdfs:label ?teamLabel .
    FILTER ( LANG( ?teamLabel ) = 'en' )
  }
  .
  OPTIONAL {
    ?award rdfs:label ?awardLabel .
    FILTER ( LANG( ?awardLabel ) = 'en' )
  }
}

Got 24 rows and 6 columns, showing the first 5 and last 5 rows below:
| ?team                               | ?teamLabel             | ?sport                | ?award                               | ?awardLabel            | ?hallOfFame    |
| ----------------------------------- | ---------------------- | --------------------- | ------------------------------------ | ---------------------- | -------------- |
| Chicago Bulls (wd:Q128109)          | Chicago Bulls          | basketball (wd:Q5372) | NBA All-Defensive Team (wd:Q1465181) | NBA All-Defensive Team | scottie-pippen |
| Helsinki Seagulls (wd:Q1889253)     | Helsinki Seagulls      | basketball (wd:Q5372) | NBA All-Defensive Team (wd:Q1465181) | NBA All-Defensive Team | scottie-pippen |
| Portland Trail Blazers (wd:Q167253) | Portland Trail Blazers | basketball (wd:Q5372) | NBA All-Defensive Team (wd:Q1465181) | NBA All-Defensive Team | scottie-pippen |
| Houston Rockets (wd:Q161345)        | Houston Rockets        | basketball (wd:Q5372) | NBA All-Defensive Team (wd:Q1465181) | NBA All-Defensive Team | scottie-pippen |
| Sundsvall Dragons (wd:Q2405952)     | Sundsvall Dragons      | basketball (wd:Q5372) | NBA All-Defensive Team (wd:Q1465181) | NBA All-Defensive Team | scottie-pippen |
| ...                                 | ...                    | ...                   | ...                                  | ...                    | ...            |
| Helsinki Seagulls (wd:Q1889253)     | Helsinki Seagulls      | basketball (wd:Q5372) | All-NBA Team (wd:Q674359)            | All-NBA Team           | scottie-pippen |
| Portland Trail Blazers (wd:Q167253) | Portland Trail Blazers | basketball (wd:Q5372) | All-NBA Team (wd:Q674359)            | All-NBA Team           | scottie-pippen |
| Houston Rockets (wd:Q161345)        | Houston Rockets        | basketball (wd:Q5372) | All-NBA Team (wd:Q674359)            | All-NBA Team           | scottie-pippen |
| Torpan Pojat (wd:Q14622334)         | Torpan Pojat           | basketball (wd:Q5372) | All-NBA Team (wd:Q674359)            | All-NBA Team           | scottie-pippen |
| Chicago Bulls (wd:Q128109)          | Chicago Bulls          | basketball (wd:Q5372) | All-NBA Team (wd:Q674359)            | All-NBA Team           | scottie-pippen |

Scottie Pippen was known for his outstanding basketball career, primarily with the Chicago Bulls, and for receiving numerous awards and honors, including multiple selections to the NBA All-Defensive Team, the All-NBA Team, and his induction into the Naismith Memorial Basketball Hall of Fame.

[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 scottie pippen known for?

[Assistant]
To answer the question about what Scottie Pippen was known for, we need to identify the entity for Scottie Pippen and then look for properties that describe his notable achievements or roles.

### Step 1: Identify the entity for Scottie Pippen
Let's start by searching for the entity representing Scottie Pippen in the knowledge graph.

[Tool]
Top 10 entity alternatives:
1. Scottie Pippen, also known as No Tippin' Pippen, Scotty Maurice Pippen, Scott Pippen, Robin, Pip (wd:Q193637): American basketball player, basketball player, actor
2. Scotty Pippen Jr., also known as Scottie Pippen Jr. (wd:Q100901254): American basketball player, basketball player
3. Slam City with Scottie Pippen (wd:Q3486520): 1994 video game
4. Scottish Terrier, also known as Aberdeen Terrier, Scottie, Scotty Dog (wd:Q39035): dog breed
5. 2024 in anime, also known as Scottie (wd:Q116673398): overview of anime-related events during the year of 2024
6. Pippen, also known as Pippen (surname), Pippen (family name) (wd:Q7197481): family name
7. pronunciation respelling for English, also known as Scottie (wd:Q7249972): non-IPA notation used to convey the pronunciation of English words (lookig like "lew-TEE-shee-əm")
8. Scottie (wd:Q7437589): album by Shirley Scott
9. English-language vowel changes before historic /r/, also known as Scottie (wd:Q5378157): vowel shifts
10. IBM Open Class, also known as scottie (wd:Q5968916): C++ class library

[Assistant]
The top result for Scottie Pippen is `wd:Q193637`, which is the correct entity for the American basketball player.

### Step 2: Identify properties that describe what Scottie Pippen was known for
Next, we need to find properties that describe his notable achievements or roles. We can search for properties related to his career and achievements.

Let's list some of the properties associated with Scottie Pippen to see what he is known for.

[Tool]
Got 511 rows and 3 columns, showing the first 10 rows below:
| subject                     | property                         | object                                                                                |
| --------------------------- | -------------------------------- | -------------------------------------------------------------------------------------------------- |
| Scottie Pippen (wd:Q193637) | instance of (wdt:P31)            | human (wd:Q5)                                                                                |
| Scottie Pippen (wd:Q193637) | occupation (wdt:P106)            | actor (wd:Q33999)                                                                                |
| Scottie Pippen (wd:Q193637) | sex or gender (wdt:P21)          | male (wd:Q6581097)                                                                                |
| Scottie Pippen (wd:Q193637) | given name (wdt:P735)            | Maurice (wd:Q1472321)                                                                              |
| Scottie Pippen (wd:Q193637) | date of birth (wdt:P569)         | 1965-09-25T00:00:00Z                                                                               |
| Scottie Pippen (wd:Q193637) | Commons category (wdt:P373)      | Scottie Pippen                                                                                |
| Scottie Pippen (wd:Q193637) | image (wdt:P18)                  | <http://commons.wikimedia.org/wiki/Special:FilePath/Scottie%20Pippen%205-2-22%20%28cropped%29.jpg> |
| Scottie Pippen (wd:Q193637) | country of citizenship (wdt:P27) | United States (wd:Q30)                                                                             |
| Scottie Pippen (wd:Q193637) | family name (wdt:P734)           | Pippen (wd:Q7197481)                                                                               |
| Scottie Pippen (wd:Q193637) | place of birth (wdt:P19)         | Hamburg (wd:Q79657)                                                                                |
| ...                         | ...                              | ...                                                                                |

[Assistant]
From the list of properties, we can see several pieces of information about Scottie Pippen, but we need to focus on his notable achievements and roles. The property `occupation` shows that he was an actor, but we know he is primarily known for his basketball career. Let's search for properties related to his basketball career and achievements.

### Step 3: Search for properties related to basketball achievements
We can search for properties related to basketball achievements and roles to find out what Scottie Pippen was known for.

Let's search for properties related to basketball achievements for Scottie Pippen.

[Tool]
Top 10 property alternatives:
1. FIBA.com player ID (archived), also known as FIBA.com player ID, FIBA ID, FIBA identifier, FIBA player ID (wd:P3542 as wdt/p): identifier for a basketball player at archive.FIBA.com
2. RealGM basketball player ID (wd:P3957 as wdt/p): identifier for a basketball player on the RealGM website
3. Basketball Reference international player ID, also known as BRCIP, Basketball Reference player ID, Basketball-Reference.com Europe player ID, Basketball-Reference.com international player ID (wd:P4790 as wdt/p): identifier for a basketball player in a non-U.S. league on Basketball-Reference.com
4. member of sports team, also known as plays for, played for, sport team, team, team played for (wd:P54 as wdt/p): sports teams or clubs that the subject represents or represented, member of
5. sport, also known as play, plays, sport played, sports (wd:P641 as wdt/p): sport that the subject participates or participated in or is associated with
6. Eurobasket.com player ID, also known as Eurobasket.com ID, eurobasket.com identifier (wd:P3527 as wdt/p): ID for a basketball player at Eurobasket.com
7. NBA.com player ID (wd:P3647 as wdt/p): identifier for a basketball player on the National Basketball Association's website
8. Basketball Reference NBA player ID, also known as Basketball-Reference.com NBA player ID, BRCNBA (wd:P2685 as wdt/p): identifier for a NBA player on the Basketball Reference website
9. award received, also known as win, winner of, recognition title, received award, prize received (wd:P166 as wdt/p): award or recognition received by a person, organization or creative work
10. Naismith Memorial Basketball Hall of Fame ID (wd:P3646 as wdt/p): identifier on the Naismith Memorial Basketball Hall of Fame website

No other items found

[Assistant]
From the search results, we can see several properties related to Scottie Pippen's basketball career, such as `member of sports team`, `sport`, `award received`, and `NBA.com player ID`. These properties can help us understand what he was known for.

### Step 4: Build the SPARQL query
We will construct a SPARQL query to retrieve the teams he played for, the sport he played, the awards he received, and his Hall of Fame status.

Let's start with a simple query to get these details.

[Tool]
Got 24 rows and 4 columns, showing the first 5 and last 5 rows below:
| ?team                           | ?sport                | ?award                                                               | ?hallOfFame    |
| ------------------------------- | --------------------- | -------------------------------------------------------------------- | -------------- |
| Chicago Bulls (wd:Q128109)      | basketball (wd:Q5372) | NBA All-Defensive Team (wd:Q1465181)                                 | scottie-pippen |
| Chicago Bulls (wd:Q128109)      | basketball (wd:Q5372) | Elijah Pitts Award (wd:Q16834973)                                    | scottie-pippen |
| Chicago Bulls (wd:Q128109)      | basketball (wd:Q5372) | NBA All-Star Game Kobe Bryant Most Valuable Player Award (wd:Q31391) | scottie-pippen |
| Chicago Bulls (wd:Q128109)      | basketball (wd:Q5372) | All-NBA Team (wd:Q674359)                                            | scottie-pippen |
| Torpan Pojat (wd:Q14622334)     | basketball (wd:Q5372) | NBA All-Defensive Team (wd:Q1465181)                                 | scottie-pippen |
| ...                             | ...                   | ...                                                                  | ...            |
| Helsinki Seagulls (wd:Q1889253) | basketball (wd:Q5372) | All-NBA Team (wd:Q674359)                                            | scottie-pippen |
| Sundsvall Dragons (wd:Q2405952) | basketball (wd:Q5372) | NBA All-Defensive Team (wd:Q1465181)                                 | scottie-pippen |
| Sundsvall Dragons (wd:Q2405952) | basketball (wd:Q5372) | Elijah Pitts Award (wd:Q16834973)                                    | scottie-pippen |
| Sundsvall Dragons (wd:Q2405952) | basketball (wd:Q5372) | NBA All-Star Game Kobe Bryant Most Valuable Player Award (wd:Q31391) | scottie-pippen |
| Sundsvall Dragons (wd:Q2405952) | basketball (wd:Q5372) | All-NBA Team (wd:Q674359)                                            | scottie-pippen |

[Assistant]
The query results show that Scottie Pippen was known for playing basketball, particularly for the Chicago Bulls. He received several awards, including the NBA All-Defensive Team, the Elijah Pitts Award, the NBA All-Star Game Kobe Bryant Most Valuable Player Award, and the All-NBA Team. Additionally, he has a Hall of Fame ID, indicating his induction into the Naismith Memorial Basketball Hall of Fame.

### Step 5: Refine the SPARQL query
To make the results more readable and to include the labels of the teams and awards, we can add optional clauses to fetch the labels.

Let's refine the SPARQL query to include labels for the teams and awards.

[Tool]
Got 24 rows and 6 columns, showing the first 5 and last 5 rows below:
| ?team                               | ?teamLabel             | ?sport                | ?award                               | ?awardLabel            | ?hallOfFame    |
| ----------------------------------- | ---------------------- | --------------------- | ------------------------------------ | ---------------------- | -------------- |
| Chicago Bulls (wd:Q128109)          | Chicago Bulls          | basketball (wd:Q5372) | NBA All-Defensive Team (wd:Q1465181) | NBA All-Defensive Team | scottie-pippen |
| Torpan Pojat (wd:Q14622334)         | Torpan Pojat           | basketball (wd:Q5372) | NBA All-Defensive Team (wd:Q1465181) | NBA All-Defensive Team | scottie-pippen |
| Sundsvall Dragons (wd:Q2405952)     | Sundsvall Dragons      | basketball (wd:Q5372) | NBA All-Defensive Team (wd:Q1465181) | NBA All-Defensive Team | scottie-pippen |
| Houston Rockets (wd:Q161345)        | Houston Rockets        | basketball (wd:Q5372) | NBA All-Defensive Team (wd:Q1465181) | NBA All-Defensive Team | scottie-pippen |
| Portland Trail Blazers (wd:Q167253) | Portland Trail Blazers | basketball (wd:Q5372) | NBA All-Defensive Team (wd:Q1465181) | NBA All-Defensive Team | scottie-pippen |
| ...                                 | ...                    | ...                   | ...                                  | ...                    | ...            |
| Houston Rockets (wd:Q161345)        | Houston Rockets        | basketball (wd:Q5372) | All-NBA Team (wd:Q674359)            | All-NBA Team           | scottie-pippen |
| Helsinki Seagulls (wd:Q1889253)     | Helsinki Seagulls      | basketball (wd:Q5372) | All-NBA Team (wd:Q674359)            | All-NBA Team           | scottie-pippen |
| Torpan Pojat (wd:Q14622334)         | Torpan Pojat           | basketball (wd:Q5372) | All-NBA Team (wd:Q674359)            | All-NBA Team           | scottie-pippen |
| Chicago Bulls (wd:Q128109)          | Chicago Bulls          | basketball (wd:Q5372) | All-NBA Team (wd:Q674359)            | All-NBA Team           | scottie-pippen |
| Sundsvall Dragons (wd:Q2405952)     | Sundsvall Dragons      | basketball (wd:Q5372) | All-NBA Team (wd:Q674359)            | All-NBA Team           | scottie-pippen |

[Assistant]
The refined query provides a more readable output, including the labels for the teams and awards. Scottie Pippen was known for playing basketball, particularly for the Chicago Bulls, and he received several prestigious awards, including the NBA All-Defensive Team, the Elijah Pitts Award, the NBA All-Star Game Kobe Bryant Most Valuable Player Award, and the All-NBA Team. Additionally, he was inducted into the Naismith Memorial Basketball Hall of Fame.

### Final Answer
Based on the SPARQL query results, Scottie Pippen was known for his outstanding basketball career, primarily with the Chicago Bulls, and for receiving numerous awards and honors, including multiple selections to the NBA All-Defensive Team, the All-NBA Team, and his induction into the Naismith Memorial Basketball Hall of Fame.

Here is the final SPARQL query:

```sparql
SELECT ?team ?teamLabel ?sport ?award ?awardLabel ?hallOfFame WHERE {
  wd:Q193637 wdt:P54 ?team .
  wd:Q193637 wdt:P641 ?sport .
  wd:Q193637 wdt:P166 ?award .
  OPTIONAL { wd:Q193637 wdt:P3646 ?hallOfFame } .
  OPTIONAL { ?team rdfs:label ?teamLabel . FILTER(LANG(?teamLabel) = 'en') } .
  OPTIONAL { ?award rdfs:label ?awardLabel . FILTER(LANG(?awardLabel) = 'en') } .
}
```

And the answer to the question:

Scottie Pippen was known for his outstanding basketball career, primarily with the Chicago Bulls, and for receiving numerous awards and honors, including multiple selections to the NBA All-Defensive Team, the All-NBA Team, and his induction into the Naismith Memorial Basketball Hall of Fame.

[Tool] Stopped generation process