PREFIX fb: <http://rdf.freebase.com/ns/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT DISTINCT ?cause ?cause_label WHERE {
  fb:m.0cgbf fb:people.deceased_person.cause_of_death ?cause .
  OPTIONAL {
    ?cause rdfs:label ?cause_label .
    FILTER ( lang( ?cause_label ) = 'en' )
  }
}

Got 2 rows and 2 columns:
| cause                           | cause_label            |
| ------------------------------- | ---------------------- |
| Pancreatic cancer (fb:m.01_qc_) | Pancreatic cancer (en) |
| heart attack (fb:m.0gk4g)       | heart attack (en)      |

Joan Crawford died of pancreatic cancer and heart attack.

[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:
freebase at https://qlever.cs.uni-freiburg.de/api/freebase

You can use the following SPARQL prefixes implicitly in all functions:
fb: <http://rdf.freebase.com/ns/
fbkey: <http://rdf.freebase.com/key/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
owl: <http://www.w3.org/2002/07/owl#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
skos: <http://www.w3.org/2004/02/skos/core#
dct: <http://purl.org/dc/terms/
dc: <http://purl.org/dc/elements/1.1/
prov: <http://www.w3.org/ns/prov#
schema: <http://schema.org/
geo: <http://www.opengis.net/ont/geosparql#
geosparql: <http://www.opengis.net/ont/geosparql#
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
wikibase: <http://wikiba.se/ontology#
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 did joan crawford died of?

[Assistant] Let's start by looking at some similar examples.

[Tool]
Example 1:
Question:
what was wrong with joan crawford?

SPARQL:
SELECT DISTINCT ?x WHERE {
  FILTER ( ?x != fb:m.0cgbf ) FILTER ( ! isLiteral( ?x ) || lang( ?x ) = '' || langMatches( lang( ?x ) , 'en' ) ) fb:m.0cgbf fb:medicine.notable_person_with_medical_condition.condition ?x .
}

Using entities:
Joan Crawford, also known as Lucille Fay LeSueur, Lucille Le Sueur, Cranberry, Billie Cassin, Billie (fb:m.0cgbf): Joan Crawford was an American film and television actress who st...ancy on the board of directors but was forcibly retired in 1973., has type Film actor

Using properties:
Condition (fb:medicine.notable_person_with_medical_condition.condition): part of Public figure with medical condition schema, links to type Disease or medical condition

Example 2:
Question:
what did lucille ball die of?

SPARQL:
SELECT DISTINCT ?x WHERE {
  FILTER ( ?x != fb:m.04nw9 ) FILTER ( ! isLiteral( ?x ) || lang( ?x ) = '' || langMatches( lang( ?x ) , 'en' ) ) fb:m.04nw9 fb:people.deceased_person.cause_of_death ?x .
}

Using entities:
Lucille Ball, also known as The Queen of Comedy, Diane Belmont, The First Lady of Television, Technicolor Tessie, Queen of the B movies (fb:m.04nw9): Lucille Désirée Ball was an American actress, comedienne, model,...cond child, Desiderio Alberto Arnaz IV, known as Desi Arnaz, Jr., has type Film actor

Using properties:
Cause of death (fb:people.deceased_person.cause_of_death): part of Deceased Person schema, links to type Cause Of Death

Example 3:
Question:
what did audrey hepburn died of?

SPARQL:
SELECT DISTINCT ?x WHERE {
  FILTER ( ?x != fb:m.0dqcm ) FILTER ( ! isLiteral( ?x ) || lang( ?x ) = '' || langMatches( lang( ?x ) , 'en' ) ) fb:m.0dqcm fb:people.deceased_person.cause_of_death ?x .
}

Using entities:
Audrey Hepburn, also known as Audrey Kathleen Hepburn-Ruston, Audrey Kathleen Ruston, Edda van Heemstra, Edda van Heemstra Hepburn-Ruston (fb:m.0dqcm): Audrey Hepburn was a British actress and humanitarian. Recognise... including English, French, Dutch, Italian, Spanish, and German., has type Celebrity

Using properties:
Cause of death (fb:people.deceased_person.cause_of_death): part of Deceased Person schema, links to type Cause Of Death

[Assistant]
From the similar examples, it appears that:

- Joan Crawford's Freebase entity is fb:m.0cgbf.
- The property for "cause of death" is fb:people.deceased_person.cause_of_death.

The relevant SPARQL pattern is:
fb:m.0cgbf fb:people.deceased_person.cause_of_death ?x .

To provide a more informative answer, I'll also try to get the label of the cause of death.

Let's construct the SPARQL query accordingly.

[Tool]
Got 80 rows and 2 columns, showing the first 5 and last 5 rows below:
| cause                           | cause_label                         |
| ------------------------------- | ----------------------------------- |
| Pancreatic cancer (fb:m.01_qc_) | Alvleesklierkanker (nl)             |
| Pancreatic cancer (fb:m.01_qc_) | Bukspottkörtelcancer (sv)           |
| Pancreatic cancer (fb:m.01_qc_) | Bukspyttkjertelkreft (no)           |
| Pancreatic cancer (fb:m.01_qc_) | Cáncer de páncreas (es)             |
| Pancreatic cancer (fb:m.01_qc_) | Cáncer de páncreas (es-419)         |
| ...                             | ...                                 |
| heart attack (fb:m.0gk4g)       | กล้ามเนื้อหัวใจตายเหตุขาดเลือด (th) |
| heart attack (fb:m.0gk4g)       | 심근 경색 (ko)                          |
| heart attack (fb:m.0gk4g)       | 心筋梗塞 (ja)                           |
| heart attack (fb:m.0gk4g)       | 心肌梗死 (zh)                           |
| heart attack (fb:m.0gk4g)       | 心肌梗死 (zh-Hant)                      |

[Tool]
Got 2 rows and 2 columns:
| cause                           | cause_label            |
| ------------------------------- | ---------------------- |
| Pancreatic cancer (fb:m.01_qc_) | Pancreatic cancer (en) |
| heart attack (fb:m.0gk4g)       | heart attack (en)      |

[Tool] Stopped generation process


PREFIX fb: <http://rdf.freebase.com/ns/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT DISTINCT ?school ?schoolLabel WHERE {
  fb:m.04jg1kh fb:people.person.education ?edu .
  ?edu fb:education.education.institution ?school .
  OPTIONAL {
    ?school rdfs:label ?schoolLabel
  }
}

Got 3 rows and 2 columns:
| school                                   | schoolLabel                     |
| ---------------------------------------- | ------------------------------- |
| Juneau-Douglas High School (fb:m.02fqd7) | Juneau-Douglas High School (en) |
| Wasilla High School (fb:m.04jdv0r)       | Wasilla High School (en)        |
| West Anchorage High School (fb:m.08r1_d) | West Anchorage High School (en) |

Bristol Palin went to Juneau-Douglas High School, Wasilla High School, and West Anchorage High School.

[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:
freebase at https://qlever.cs.uni-freiburg.de/api/freebase

You can use the following SPARQL prefixes implicitly in all functions:
fb: <http://rdf.freebase.com/ns/
fbkey: <http://rdf.freebase.com/key/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
owl: <http://www.w3.org/2002/07/owl#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
skos: <http://www.w3.org/2004/02/skos/core#
dct: <http://purl.org/dc/terms/
dc: <http://purl.org/dc/elements/1.1/
prov: <http://www.w3.org/ns/prov#
schema: <http://schema.org/
geo: <http://www.opengis.net/ont/geosparql#
geosparql: <http://www.opengis.net/ont/geosparql#
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
wikibase: <http://wikiba.se/ontology#
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 bristol palin go to school?

[Assistant] Let's start by looking at some similar examples.

[Tool]
Example 1:
Question:
where did barack obama went to school?

SPARQL:
SELECT DISTINCT ?x WHERE {
  FILTER ( ?x != fb:m.02mjmr ) FILTER ( ! isLiteral( ?x ) || lang( ?x ) = '' || langMatches( lang( ?x ) , 'en' ) ) fb:m.02mjmr fb:people.person.education ?y .
  ?y fb:education.education.institution ?x .
}

Using entities:
Barack Obama, also known as President Obama, President Barack Obama, President Barack Hussein Obama II, President Barack H. Obama, Obama (fb:m.02mjmr): Barack Hussein Obama II is the 44th and current President of the...mocratic Party primaries to receive the presidential nomination., Barack Hussein Obama II (/bəˈrɑːk huːˈseɪn oʊˈbɑːmə/; born Augus...ting the 13th District in the Illinois Senate from 1997 to 2004., has type US President

Using properties:
Institution (fb:education.education.institution): links to type Educational Institution, part of Education schema
Education (fb:people.person.education): links to type Education, part of Person schema

Example 2:
Question:
where did barack obama attend school?

SPARQL:
SELECT DISTINCT ?x WHERE {
  FILTER ( ?x != fb:m.02mjmr ) FILTER ( ! isLiteral( ?x ) || lang( ?x ) = '' || langMatches( lang( ?x ) , 'en' ) ) fb:m.02mjmr fb:people.person.education ?y .
  ?y fb:education.education.institution ?x .
}

Using entities:
Barack Obama, also known as President Obama, President Barack Obama, President Barack Hussein Obama II, President Barack H. Obama, Obama (fb:m.02mjmr): Barack Hussein Obama II is the 44th and current President of the...mocratic Party primaries to receive the presidential nomination., Barack Hussein Obama II (/bəˈrɑːk huːˈseɪn oʊˈbɑːmə/; born Augus...ting the 13th District in the Illinois Senate from 1997 to 2004., has type US President

Using properties:
Institution (fb:education.education.institution): links to type Educational Institution, part of Education schema
Education (fb:people.person.education): links to type Education, part of Person schema

Example 3:
Question:
where did pres. obama go to school?

SPARQL:
SELECT DISTINCT ?x WHERE {
  FILTER ( ?x != fb:m.02mjmr ) FILTER ( ! isLiteral( ?x ) || lang( ?x ) = '' || langMatches( lang( ?x ) , 'en' ) ) fb:m.02mjmr fb:people.person.education ?y .
  ?y fb:education.education.institution ?x .
}

Using entities:
Barack Obama, also known as President Obama, President Barack Obama, President Barack Hussein Obama II, President Barack H. Obama, Obama (fb:m.02mjmr): Barack Hussein Obama II is the 44th and current President of the...mocratic Party primaries to receive the presidential nomination., Barack Hussein Obama II (/bəˈrɑːk huːˈseɪn oʊˈbɑːmə/; born Augus...ting the 13th District in the Illinois Senate from 1997 to 2004., has type US President

Using properties:
Institution (fb:education.education.institution): links to type Educational Institution, part of Education schema
Education (fb:people.person.education): links to type Education, part of Person schema

[Assistant]
The similar examples show that to answer "where did [person] go to school?", we need:
- The entity for the person (here: Bristol Palin).
- The property fb:people.person.education linking to an education node.
- The property fb:education.education.institution linking the education node to the school.

First, I need to find the Freebase entity for Bristol Palin.

[Tool]
Top 10 entity alternatives:
1. Bristol Palin, also known as Bristol Sheeran Marie Palin (fb:m.04jg1kh): Bristol Sheeran Marie Palin is an American public speaker and re...son, where she was eliminated in the fourth week of competition., has type TV Personality
2. Bristol Palin (fb:m.0j47m1j): Bristol Palin is a fictional character from Who's Nailin' Palin? 2., has type Film character
3. Bristol Palin Dancing (fb:m.0nn5g58): has type Musical Recording
4. Bristol Palin headshot (fb:m.0dhbj7w)
5. Bristol Palin Dancing (fb:m.0q8zlqj)
6. Bristol Palin: Life's a Tripp (fb:m.0jzx723): With never-before-granted access to Bristol’s real-life experien...single-handedly writes the next chapter in her and Tripp’s life., Bristol Palin: Life's a Tripp is an American Reality-documentary...evision series on Lifetime. The series debuted on June 19, 2012., has type TV Program
7. Don Rickles, Bristol Palin, Colbie Caillat (fb:m.0kc3w_p): has type TV Episode
8. Bristol Palin at Single Source Speakers (fb:m.0crksk0)
9. Bristol, also known as Bristol, UK, City Of Bristol (fb:m.095l0): Bristol is a city, unitary authority and county in South West En...prosperity has been linked with the sea since its earliest days., has type English unitary authority
10. Bristol, also known as Bristol city, Bristol city / Bristol city, Bristol, Virginia (fb:m.0mp4w): Bristol is an independent city in the U.S. state of Virginia. As...ed Statistical Area – commonly known as the "Tri-Cities" region., has type US County

[Assistant]
The correct entity for Bristol Palin (the American public speaker and TV personality) is fb:m.04jg1kh.

Now, I will construct a SPARQL query using the pattern from the examples:
- Get the education nodes for Bristol Palin via fb:people.person.education.
- Get the institutions via fb:education.education.institution.
- Optionally, get the labels for the institutions.

Let's write and execute this query.

[Tool]
Got 3 rows and 2 columns:
| school                                   | schoolLabel                     |
| ---------------------------------------- | ------------------------------- |
| Juneau-Douglas High School (fb:m.02fqd7) | Juneau-Douglas High School (en) |
| Wasilla High School (fb:m.04jdv0r)       | Wasilla High School (en)        |
| West Anchorage High School (fb:m.08r1_d) | West Anchorage High School (en) |

[Tool] Stopped generation process


PREFIX fb: <http://rdf.freebase.com/ns/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT DISTINCT ?location ?locationLabel WHERE {
  fb:m.036mk fb:location.location.containedby ?location .
  OPTIONAL {
    ?location rdfs:label ?locationLabel .
    FILTER ( lang( ?locationLabel ) = "en" )
  }
}

Got 2 rows and 2 columns:
| location                   | locationLabel     |
| -------------------------- | ----------------- |
| Egypt (fb:m.02k54)         | Egypt (en)        |
| Giza Plateau (fb:m.06bkmh) | Giza Plateau (en) |

The Giza pyramids (Great Pyramid of Giza) are located in the place identified by the object of fb:location.location.containedby. The query also retrieves the human-readable label for the location if available.

[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:
freebase at https://qlever.cs.uni-freiburg.de/api/freebase

You can use the following SPARQL prefixes implicitly in all functions:
fb: <http://rdf.freebase.com/ns/
fbkey: <http://rdf.freebase.com/key/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
owl: <http://www.w3.org/2002/07/owl#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
skos: <http://www.w3.org/2004/02/skos/core#
dct: <http://purl.org/dc/terms/
dc: <http://purl.org/dc/elements/1.1/
prov: <http://www.w3.org/ns/prov#
schema: <http://schema.org/
geo: <http://www.opengis.net/ont/geosparql#
geosparql: <http://www.opengis.net/ont/geosparql#
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
wikibase: <http://wikiba.se/ontology#
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 is giza pyramids located?

[Assistant] Let's start by looking at some similar examples.

[Tool]
Example 1:
Question:
where is pyramids of giza located?

SPARQL:
SELECT DISTINCT ?x WHERE {
  FILTER ( ?x != fb:m.036mk ) FILTER ( ! isLiteral( ?x ) || lang( ?x ) = '' || langMatches( lang( ?x ) , 'en' ) ) fb:m.036mk fb:location.location.containedby ?x .
}

Using entities:
Great Pyramid of Giza, also known as Khufu's Horizon, Pyramid of Khufu, Pyramid of Cheops (fb:m.036mk): The Great Pyramid of Giza is the oldest and largest of the three... place. There are three known chambers inside the Great Pyramid., has type Tourist attraction

Using properties:
Contained by (fb:location.location.containedby): part of Location schema, links to type Location

Example 2:
Question:
where is pyramids of giza located?

SPARQL:
SELECT DISTINCT ?x WHERE {
  FILTER ( ?x != fb:m.036mk ) FILTER ( ! isLiteral( ?x ) || lang( ?x ) = '' || langMatches( lang( ?x ) , 'en' ) ) fb:m.036mk fb:base.ancientegypt.pyramid.site ?x .
}

Using entities:
Great Pyramid of Giza, also known as Khufu's Horizon, Pyramid of Khufu, Pyramid of Cheops (fb:m.036mk): The Great Pyramid of Giza is the oldest and largest of the three... place. There are three known chambers inside the Great Pyramid., has type Tourist attraction

Using properties:
Site (fb:base.ancientegypt.pyramid.site): links to type Pyramid site, part of Pyramid schema

Example 3:
Question:
where is pyramids of giza located?

SPARQL:
SELECT DISTINCT ?x WHERE {
  FILTER ( ?x != fb:m.036mk ) FILTER ( ! isLiteral( ?x ) || lang( ?x ) = '' || langMatches( lang( ?x ) , 'en' ) ) fb:m.036mk fb:architecture.building.building_complex ?x .
}

Using entities:
Great Pyramid of Giza, also known as Khufu's Horizon, Pyramid of Khufu, Pyramid of Cheops (fb:m.036mk): The Great Pyramid of Giza is the oldest and largest of the three... place. There are three known chambers inside the Great Pyramid., has type Tourist attraction

Using properties:
Building Complex (fb:architecture.building.building_complex): links to type Building complex, part of Building schema

[Assistant]
Based on the similar examples, the entity for the Great Pyramid of Giza is fb:m.036mk, and the property fb:location.location.containedby is used to find its location. To provide a more informative answer, I will also try to retrieve the label of the location.

Here is the SPARQL query I will use:

```sparql
SELECT DISTINCT ?location ?locationLabel WHERE {
  fb:m.036mk fb:location.location.containedby ?location .
  OPTIONAL { ?location rdfs:label ?locationLabel . FILTER (lang(?locationLabel) = "en") }
}
```

Now, I will provide this as the answer.

[Tool] Stopped generation process


PREFIX fb: <http://rdf.freebase.com/ns/>
SELECT DISTINCT ?language WHERE {
  fb:m.07ssc fb:location.country.languages_spoken ?language .
}

Got 8 rows and 1 column:
| language                           |
| ---------------------------------- |
| Cornish Language (fb:m.01v0g)      |
| English Language (fb:m.02h40lc)    |
| Esperanto Language (fb:m.02jcw)    |
| Irish (fb:m.03x42)                 |
| Scottish Gaelic (fb:m.070zw)       |
| Welsh Language (fb:m.083tk)        |
| British Sign Language (fb:m.0ct8m) |
| Scots Language (fb:m.0h407)        |

The major languages spoken in the United Kingdom are: English, Welsh, Scottish Gaelic, Irish, Scots, Cornish, British Sign Language, and Esperanto.

[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:
freebase at https://qlever.cs.uni-freiburg.de/api/freebase

You can use the following SPARQL prefixes implicitly in all functions:
fb: <http://rdf.freebase.com/ns/
fbkey: <http://rdf.freebase.com/key/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
owl: <http://www.w3.org/2002/07/owl#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
skos: <http://www.w3.org/2004/02/skos/core#
dct: <http://purl.org/dc/terms/
dc: <http://purl.org/dc/elements/1.1/
prov: <http://www.w3.org/ns/prov#
schema: <http://schema.org/
geo: <http://www.opengis.net/ont/geosparql#
geosparql: <http://www.opengis.net/ont/geosparql#
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
wikibase: <http://wikiba.se/ontology#
qb: <http://purl.org/linked-data/cube#
void: <http://rdfs.org/ns/void#

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

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

[User] what are the major languages spoken in the united kingdom?

[Assistant] Let's start by looking at some similar examples.

[Tool]
Example 1:
Question:
what dialects are spoken in the uk?

SPARQL:
SELECT DISTINCT ?x WHERE {
  FILTER ( ?x != fb:m.07ssc ) FILTER ( ! isLiteral( ?x ) || lang( ?x ) = '' || langMatches( lang( ?x ) , 'en' ) ) fb:m.07ssc fb:location.country.languages_spoken ?x .
}

Using entities:
United Kingdom, also known as United Kingdom of Great Britain and Northern Ireland, United Kingdom of Great Britain and Ireland, United Kingdom of Great Britain, UK, U.K. (fb:m.07ssc): The United Kingdom of Great Britain and Northern Ireland, common...urth-largest in Europe and second-largest in the European Union., has type Country

Using properties:
Languages spoken (fb:location.country.languages_spoken): links to type Human Language, part of Country schema

Example 2:
Question:
what language is mainly spoken in england?

SPARQL:
SELECT DISTINCT ?x WHERE {
  FILTER ( ?x != fb:m.02jx1 ) FILTER ( ! isLiteral( ?x ) || lang( ?x ) = '' || langMatches( lang( ?x ) , 'en' ) ) fb:m.02jx1 fb:location.country.languages_spoken ?x .
  ?x fb:language.human_language.main_country fb:m.02jx1 .
}

Using entities:
England, also known as Albion, England, Loegria, Pow Sows (fb:m.02jx1): England /ˈɪŋɡlənd/ is a country that is part of the United Kingd... had a significant cultural and legal impact on the wider world., has type Country

Using properties:
Main Country (fb:language.human_language.main_country): part of Human Language schema, links to type Country
Languages spoken (fb:location.country.languages_spoken): links to type Human Language, part of Country schema

Example 3:
Question:
what are the major religions in uk?

SPARQL:
SELECT DISTINCT ?x WHERE {
  FILTER ( ?x != fb:m.07ssc ) FILTER ( ! isLiteral( ?x ) || lang( ?x ) = '' || langMatches( lang( ?x ) , 'en' ) ) fb:m.07ssc fb:location.statistical_region.religions ?y .
  ?y fb:location.religion_percentage.religion ?x .
}

Using entities:
United Kingdom, also known as United Kingdom of Great Britain and Northern Ireland, United Kingdom of Great Britain and Ireland, United Kingdom of Great Britain, UK, U.K. (fb:m.07ssc): The United Kingdom of Great Britain and Northern Ireland, common...urth-largest in Europe and second-largest in the European Union., has type Country

Using properties:
Religion (fb:location.religion_percentage.religion): part of Religion percentage schema, links to type Religion
Religions (fb:location.statistical_region.religions): links to type Religion percentage, part of Statistical region schema

[Assistant]
From the similar examples, I see that:

- The United Kingdom entity in Freebase is fb:m.07ssc.
- The property for languages spoken in a country is fb:location.country.languages_spoken.
- To get the major languages, we can use this property, and optionally filter or rank by prominence if possible, but Freebase may not distinguish "major" vs "minor" languages directly.

I will construct a SPARQL query to retrieve all languages spoken in the United Kingdom using the property fb:location.country.languages_spoken, and include their labels for readability.

[Tool]
Got 8 rows and 2 columns:
| language                           | languageLabel              |
| ---------------------------------- | -------------------------- |
| Cornish Language (fb:m.01v0g)      | Cornish Language (en)      |
| English Language (fb:m.02h40lc)    | English Language (en)      |
| Esperanto Language (fb:m.02jcw)    | Esperanto Language (en)    |
| Irish (fb:m.03x42)                 | Irish (en)                 |
| Scottish Gaelic (fb:m.070zw)       | Scottish Gaelic (en)       |
| Welsh Language (fb:m.083tk)        | Welsh Language (en)        |
| British Sign Language (fb:m.0ct8m) | British Sign Language (en) |
| Scots Language (fb:m.0h407)        | Scots Language (en)        |

[Tool] Stopped generation process


PREFIX fb: <http://rdf.freebase.com/ns/>
SELECT ?influencer WHERE {
  fb:m.04107 fb:influence.influence_node.influenced_by ?influencer .
}

Got 4 rows and 1 column:
| influencer                      |
| ------------------------------- |
| Sherwood Anderson (fb:m.023jy9) |
| Thomas Malory (fb:m.07jrh)      |
| William Faulkner (fb:m.084w8)   |
| Robert Burns (fb:m.09482)       |

John Steinbeck was inspired by Sherwood Anderson, Thomas Malory, William Faulkner, and Robert Burns.

[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:
freebase at https://qlever.cs.uni-freiburg.de/api/freebase

You can use the following SPARQL prefixes implicitly in all functions:
fb: <http://rdf.freebase.com/ns/
fbkey: <http://rdf.freebase.com/key/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
owl: <http://www.w3.org/2002/07/owl#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
skos: <http://www.w3.org/2004/02/skos/core#
dct: <http://purl.org/dc/terms/
dc: <http://purl.org/dc/elements/1.1/
prov: <http://www.w3.org/ns/prov#
schema: <http://schema.org/
geo: <http://www.opengis.net/ont/geosparql#
geosparql: <http://www.opengis.net/ont/geosparql#
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
wikibase: <http://wikiba.se/ontology#
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 inspired steinbeck?

[Assistant] Let's start by looking at some similar examples.

[Tool]
Example 1:
Question:
what inspired steinbeck to write?

SPARQL:
SELECT DISTINCT ?x WHERE {
  FILTER ( ?x != fb:m.04107 ) FILTER ( ! isLiteral( ?x ) || lang( ?x ) = '' || langMatches( lang( ?x ) , 'en' ) ) fb:m.04107 fb:influence.influence_node.influenced_by ?x .
}

Using entities:
John Steinbeck, also known as John Ernst Steinbeck, Steinbeck, John, John Ernst Steinbeck, Jr. (fb:m.04107): John Ernst Steinbeck, Jr. was an American author of twenty-seven..., especially as applied to downtrodden or everyman protagonists., has type Author

Using properties:
Influenced By (fb:influence.influence_node.influenced_by): part of Influence Node schema, links to type Influence Node

Example 2:
Question:
what is john steinbeck best known for?

SPARQL:
SELECT DISTINCT ?x WHERE {
  FILTER ( ?x != fb:m.04107 ) FILTER ( ! isLiteral( ?x ) || lang( ?x ) = '' || langMatches( lang( ?x ) , 'en' ) ) fb:m.04107 fb:people.person.profession ?x .
}

Using entities:
John Steinbeck, also known as John Ernst Steinbeck, Steinbeck, John, John Ernst Steinbeck, Jr. (fb:m.04107): John Ernst Steinbeck, Jr. was an American author of twenty-seven..., especially as applied to downtrodden or everyman protagonists., has type Author

Using properties:
Profession (fb:people.person.profession): links to type Profession, part of Person schema

Example 3:
Question:
what inspired scott fitzgerald?

SPARQL:
SELECT DISTINCT ?x WHERE {
  FILTER ( ?x != fb:m.02zjd ) FILTER ( ! isLiteral( ?x ) || lang( ?x ) = '' || langMatches( lang( ?x ) , 'en' ) ) fb:m.02zjd fb:influence.influence_node.influenced_by ?x .
}

Using entities:
F. Scott Fitzgerald, also known as Fitzgerald, F Scott Fitzgerald, Francis Scott Key Fitzgerald (fb:m.02zjd): Francis Scott Key Fitzgerald was an American author of novels an...at treat themes of youth and promise along with age and despair., has type Author

Using properties:
Influenced By (fb:influence.influence_node.influenced_by): part of Influence Node schema, links to type Influence Node

[Assistant]
From the similar examples, it is clear that the property fb:influence.influence_node.influenced_by is used to represent what inspired or influenced an author. The entity for John Steinbeck is fb:m.04107.

I will write a SPARQL query to find the entities that inspired (influenced) John Steinbeck, returning their IRIs and optionally their labels.

[Tool]
Got 129 rows and 2 columns, showing the first 5 and last 5 rows below:
| influencer                      | influencer_label       |
| ------------------------------- | ---------------------- |
| Sherwood Anderson (fb:m.023jy9) | Sherwood Anderson (ca) |
| Sherwood Anderson (fb:m.023jy9) | Sherwood Anderson (cs) |
| Sherwood Anderson (fb:m.023jy9) | Sherwood Anderson (de) |
| Sherwood Anderson (fb:m.023jy9) | Sherwood Anderson (en) |
| Sherwood Anderson (fb:m.023jy9) | Sherwood Anderson (es) |
| ...                             | ...                    |
| Robert Burns (fb:m.09482)       | रॉबर्ट बर्न्स (hi)     |
| Robert Burns (fb:m.09482)       | 로버트 번스 (ko)            |
| Robert Burns (fb:m.09482)       | ロバート・バーンズ (ja)         |
| Robert Burns (fb:m.09482)       | 罗伯特·伯恩斯 (zh)           |
| Robert Burns (fb:m.09482)       | 羅伯特·伯恩斯 (zh-Hant)      |

[Tool]
Got 4 rows and 1 column:
| influencer                      |
| ------------------------------- |
| Sherwood Anderson (fb:m.023jy9) |
| Thomas Malory (fb:m.07jrh)      |
| William Faulkner (fb:m.084w8)   |
| Robert Burns (fb:m.09482)       |

[Tool]
Got 4 rows and 2 columns:
| influencer                      | label                  |
| ------------------------------- | ---------------------- |
| Sherwood Anderson (fb:m.023jy9) | Sherwood Anderson (en) |
| Thomas Malory (fb:m.07jrh)      | Thomas Malory (en)     |
| William Faulkner (fb:m.084w8)   | William Faulkner (en)  |
| Robert Burns (fb:m.09482)       | Robert Burns (en)      |

[Tool] Stopped generation process


PREFIX fb: <http://rdf.freebase.com/ns/>
SELECT DISTINCT ?instrument WHERE {
  fb:m.04n32 fb:music.group_member.instruments_played ?instrument .
}

Got 2 rows and 1 column:
| instrument           |
| -------------------- |
| Cornet (fb:m.020w2)  |
| Trumpet (fb:m.07gql) |

Louis Armstrong played the cornet and the trumpet.

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

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

You can use the following SPARQL prefixes implicitly in all functions:
fb: <http://rdf.freebase.com/ns/
fbkey: <http://rdf.freebase.com/key/
rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: <http://www.w3.org/2000/01/rdf-schema#
owl: <http://www.w3.org/2002/07/owl#
xsd: <http://www.w3.org/2001/XMLSchema#
foaf: <http://xmlns.com/foaf/0.1/
skos: <http://www.w3.org/2004/02/skos/core#
dct: <http://purl.org/dc/terms/
dc: <http://purl.org/dc/elements/1.1/
prov: <http://www.w3.org/ns/prov#
schema: <http://schema.org/
geo: <http://www.opengis.net/ont/geosparql#
geosparql: <http://www.opengis.net/ont/geosparql#
gn: <http://www.geonames.org/ontology#
bd: <http://www.bigdata.com/rdf#
hint: <http://www.bigdata.com/queryHints#
wikibase: <http://wikiba.se/ontology#
qb: <http://purl.org/linked-data/cube#
void: <http://rdfs.org/ns/void#

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

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

[User] what instruments did louis armstrong play?

[Assistant] Let's start by looking at some similar examples.

[Tool]
Example 1:
Question:
what instrument did louis armstrong like to play?

SPARQL:
SELECT DISTINCT ?x WHERE {
  FILTER ( ?x != fb:m.04n32 ) FILTER ( ! isLiteral( ?x ) || lang( ?x ) = '' || langMatches( lang( ?x ) , 'en' ) ) fb:m.04n32 fb:music.group_member.instruments_played ?x .
}

Using entities:
Louis Armstrong, also known as Louis Armstrong: Satchmo, Louise Armstrong, Louis Daniel Armstrong, Louis Arnstrong, Louis Armstrong's Hot Seven (fb:m.04n32): Louis Armstrong, nicknamed Satchmo or Pops, was an American jazz... to his music in an America that was extremely racially divided., has type Musical Artist

Using properties:
Instruments Played (fb:music.group_member.instruments_played): links to type Musical instrument, part of Musician schema

Example 2:
Question:
what instrument was louis armstrong famous for?

SPARQL:
SELECT DISTINCT ?x WHERE {
  FILTER ( ?x != fb:m.04n32 ) FILTER ( ! isLiteral( ?x ) || lang( ?x ) = '' || langMatches( lang( ?x ) , 'en' ) ) fb:m.04n32 fb:music.group_member.instruments_played ?x .
}

Using entities:
Louis Armstrong, also known as Louis Armstrong: Satchmo, Louise Armstrong, Louis Daniel Armstrong, Louis Arnstrong, Louis Armstrong's Hot Seven (fb:m.04n32): Louis Armstrong, nicknamed Satchmo or Pops, was an American jazz... to his music in an America that was extremely racially divided., has type Musical Artist

Using properties:
Instruments Played (fb:music.group_member.instruments_played): links to type Musical instrument, part of Musician schema

Example 3:
Question:
what style of music did louis armstrong play?

SPARQL:
SELECT DISTINCT ?x WHERE {
  FILTER ( ?x != fb:m.04n32 ) FILTER ( ! isLiteral( ?x ) || lang( ?x ) = '' || langMatches( lang( ?x ) , 'en' ) ) fb:m.04n32 fb:music.artist.genre ?x .
}

Using entities:
Louis Armstrong, also known as Louis Armstrong: Satchmo, Louise Armstrong, Louis Daniel Armstrong, Louis Arnstrong, Louis Armstrong's Hot Seven (fb:m.04n32): Louis Armstrong, nicknamed Satchmo or Pops, was an American jazz... to his music in an America that was extremely racially divided., has type Musical Artist

Using properties:
Musical Genres (fb:music.artist.genre): part of Musical Artist schema, links to type Musical genre

[Assistant]
The similar examples show that the entity for Louis Armstrong is fb:m.04n32 and the property for instruments played is fb:music.group_member.instruments_played.

I will use this information to construct a SPARQL query that retrieves the instruments played by Louis Armstrong. To provide more human-readable results, I will also try to include the labels of the instruments using rdfs:label in an OPTIONAL clause.

Here is the SPARQL query I will use:

[Tool]
Got 73 rows and 2 columns, showing the first 5 and last 5 rows below:
| instrument           | instrumentLabel |
| -------------------- | --------------- |
| Cornet (fb:m.020w2)  | Cornet (en)     |
| Cornet (fb:m.020w2)  | Cornet (ro)     |
| Cornet (fb:m.020w2)  | Corneta (ca)    |
| Cornet (fb:m.020w2)  | Corneta (es)    |
| Cornet (fb:m.020w2)  | Corneta (pt)    |
| ...                  | ...             |
| Trumpet (fb:m.07gql) | ทรัมเป็ต (th)   |
| Trumpet (fb:m.07gql) | 트럼펫 (ko)        |
| Trumpet (fb:m.07gql) | トランペット (ja)     |
| Trumpet (fb:m.07gql) | 小号 (zh)         |
| Trumpet (fb:m.07gql) | 小號 (zh-Hant)    |

[Tool]
Got 2 rows and 1 column:
| instrument           |
| -------------------- |
| Cornet (fb:m.020w2)  |
| Trumpet (fb:m.07gql) |

[Tool]
Got 2 rows and 2 columns:
| instrument           | label        |
| -------------------- | ------------ |
| Cornet (fb:m.020w2)  | Cornet (en)  |
| Trumpet (fb:m.07gql) | Trumpet (en) |

[Tool] Stopped generation process