PREFIX fb: <http://rdf.freebase.com/ns/>
SELECT DISTINCT ?x WHERE {
  FILTER ( ?x != fb:m.02h3tp ) FILTER ( ! isLiteral( ?x ) || lang( ?x ) = '' || langMatches( lang( ?x ) , 'en' ) ) fb:m.02h3tp fb:people.deceased_person.cause_of_death ?x .
  ?x fb:people.cause_of_death.parent_cause_of_death fb:m.0qcr0 .
}

Patrick Swayze had pancreatic cancer.

[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 cancer did patrick swayze?

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

[Tool]
Example 1:
Question:
what type of cancer did patrick swayze die from?

SPARQL:
SELECT DISTINCT ?x WHERE {
  FILTER ( ?x != fb:m.02h3tp ) FILTER ( ! isLiteral( ?x ) || lang( ?x ) = '' || langMatches( lang( ?x ) , 'en' ) ) fb:m.02h3tp fb:people.deceased_person.cause_of_death ?x .
  ?x fb:people.cause_of_death.parent_cause_of_death fb:m.0qcr0 .
}

Using entities:
Patrick Swayze, also known as Buddy, Patrick Wayne Swayze (fb:m.02h3tp): Patrick Wayne Swayze was an American actor, dancer, and singer-s...was named by People magazine as its "Sexiest Man Alive" in 1991., Film actor
Cancer, also known as Malignant neoplasm (fb:m.0qcr0): Cancer /ˈkænsər/, also known as a malignant tumor or malignant n...y many such genetic changes are required before cancer develops., Malignant Neoplasm is a tumor composed of atypical neoplastic, o...n and non-Hodgkin lymphomas, leukemias, melanomas, and sarcomas., Disease or medical condition

Using properties:
Parent cause of death (fb:people.cause_of_death.parent_cause_of_death): Cause Of Death
Cause of death (fb:people.deceased_person.cause_of_death): Deceased Person, Cause Of Death

Example 2:
Question:
what films did patrick swayze star in?

SPARQL:
SELECT DISTINCT ?x WHERE {
  FILTER ( ?x != fb:m.02h3tp ) FILTER ( ! isLiteral( ?x ) || lang( ?x ) = '' || langMatches( lang( ?x ) , 'en' ) ) fb:m.02h3tp fb:film.actor.film ?y .
  ?y fb:film.performance.film ?x .
}

Using entities:
Patrick Swayze, also known as Buddy, Patrick Wayne Swayze (fb:m.02h3tp): Patrick Wayne Swayze was an American actor, dancer, and singer-s...was named by People magazine as its "Sexiest Man Alive" in 1991., Film actor

Using properties:
Film performances (fb:film.actor.film): Film performance, Film actor
Film (fb:film.performance.film): Film performance, Film

Example 3:
Question:
what did patrick swayze sing?

SPARQL:
SELECT DISTINCT ?x WHERE {
  FILTER ( ?x != fb:m.02h3tp ) FILTER ( ! isLiteral( ?x ) || lang( ?x ) = '' || langMatches( lang( ?x ) , 'en' ) ) fb:m.02h3tp fb:music.artist.track ?x .
}

Using entities:
Patrick Swayze, also known as Buddy, Patrick Wayne Swayze (fb:m.02h3tp): Patrick Wayne Swayze was an American actor, dancer, and singer-s...was named by People magazine as its "Sexiest Man Alive" in 1991., Film actor

Using properties:
Recordings (fb:music.artist.track): Musical Recording, Musical Artist

[Assistant] From the examples, we can see that the first example is the most relevant to our question. It provides a SPARQL query that retrieves the specific type of cancer that Patrick Swayze died from. Let's run this query to get the answer.

[Tool]
Got 1 row and 1 column:
| x                               |
| ------------------------------- |
| Pancreatic cancer (fb:m.01_qc_) |

[Assistant]
The SPARQL query has returned the answer that Patrick Swayze had pancreatic cancer.

I will now provide the final answer.

[Tool] Stopped generation process


PREFIX fb: <http://rdf.freebase.com/ns/>
SELECT ?book ?date WHERE {
  fb:m.01v9724 fb:book.author.works_written ?book .
  ?book fb:book.written_work.date_of_first_publication ?date .
}
ORDER BY ASC ( ?date )
LIMIT 1

The first book Charles Dickens wrote is 'Sketches by Boz.'

[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 was the first book charles dickens wrote?

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

[Tool]
Example 1:
Question:
what did charles dickens writer?

SPARQL:
SELECT DISTINCT ?x WHERE {
  FILTER ( ?x != fb:m.01v9724 ) FILTER ( ! isLiteral( ?x ) || lang( ?x ) = '' || langMatches( lang( ?x ) , 'en' ) ) fb:m.01v9724 fb:book.author.works_written ?x .
}

Using entities:
Charles Dickens, also known as Boz, Dickens Charles, Dickens, Charles John Huffham Dickens, Charles John Huffam Dickens (fb:m.01v9724): Charles John Huffam Dickens was an English writer and social cri...s humour, satire, and keen observation of character and society., Author

Using properties:
Works written (fb:book.author.works_written): Written Work, Author

Example 2:
Question:
what did charles dickens writer?

SPARQL:
SELECT DISTINCT ?x WHERE {
  FILTER ( ?x != fb:m.01v9724 ) FILTER ( ! isLiteral( ?x ) || lang( ?x ) = '' || langMatches( lang( ?x ) , 'en' ) ) fb:m.01v9724 fb:book.author.book_editions_published ?x .
}

Using entities:
Charles Dickens, also known as Boz, Dickens Charles, Dickens, Charles John Huffham Dickens, Charles John Huffam Dickens (fb:m.01v9724): Charles John Huffam Dickens was an English writer and social cri...s humour, satire, and keen observation of character and society., Author

Using properties:
Book editions published (fb:book.author.book_editions_published): Book Edition, Author

Example 3:
Question:
what writers influenced charles dickens?

SPARQL:
SELECT DISTINCT ?x WHERE {
  FILTER ( ?x != fb:m.01v9724 ) FILTER ( ! isLiteral( ?x ) || lang( ?x ) = '' || langMatches( lang( ?x ) , 'en' ) ) fb:m.01v9724 fb:influence.influence_node.influenced_by ?x .
}

Using entities:
Charles Dickens, also known as Boz, Dickens Charles, Dickens, Charles John Huffham Dickens, Charles John Huffam Dickens (fb:m.01v9724): Charles John Huffam Dickens was an English writer and social cri...s humour, satire, and keen observation of character and society., Author

Using properties:
Influenced By (fb:influence.influence_node.influenced_by): Influence Node

[Assistant] From the examples, we can see that the entity for Charles Dickens is `fb:m.01v9724`. We also have a property `fb:book.author.works_written` which links an author to their works. However, this property does not specify the order of the works. To find the first book, we need to look for a property that indicates the publication date or order of the books. Let's search for such a property.

[Tool]
Top 10 property alternatives:
1. Book editions published (fb:book.author.book_editions_published): Book Edition, Author
2. Works written (fb:book.author.works_written): Written Work, Author
3. Date of death (fb:people.deceased_person.date_of_death): Deceased Person, Date/Time
4. Date of birth (fb:people.person.date_of_birth): Date/Time, Person
5. Works edited (fb:book.author.works_edited): Written Work, Author
6. Is reviewed (fb:freebase.valuenotation.is_reviewed): Value Notation, Property
7. Works Written About This Topic (fb:book.book_subject.works): Literature Subject, Written Work
8. Article (fb:common.topic.article): Document, Topic
9. Series Written (or Contributed To) (fb:book.author.series_written_or_contributed_to): Literary Series, Author
10. Key (fb:type.object.key): Object, Key

No other items found

[Assistant]
Unfortunately, the search did not yield a property that directly indicates the publication date of Charles Dickens' works. However, we can try to use the `fb:book.author.works_written` property and then filter the results to find the earliest publication date. Let's start by listing the works written by Charles Dickens and see if we can find a property that indicates the publication date for each work.

First, let's list the works written by Charles Dickens.

[Tool]
Got 345 rows and 3 columns, showing the first 10 rows below:
| subject                        | property                                     | object                             |
| ------------------------------ | -------------------------------------------- | ---------------------------------- |
| Charles Dickens (fb:m.01v9724) | Works written (fb:book.author.works_written) | A Christmas Carol (fb:m.0js1m)     |
| Charles Dickens (fb:m.01v9724) | Works written (fb:book.author.works_written) | Oliver Twist (fb:m.015cf8)         |
| Charles Dickens (fb:m.01v9724) | Works written (fb:book.author.works_written) | A Tale of Two Cities (fb:m.09c55p) |
| Charles Dickens (fb:m.01v9724) | Works written (fb:book.author.works_written) | David Copperfield (fb:m.0g_b_)     |
| Charles Dickens (fb:m.01v9724) | Works written (fb:book.author.works_written) | Great Expectations (fb:m.01316b)   |
| Charles Dickens (fb:m.01v9724) | Works written (fb:book.author.works_written) | The Pickwick Papers (fb:m.026v43)  |
| Charles Dickens (fb:m.01v9724) | Works written (fb:book.author.works_written) | Nicholas Nickleby (fb:m.03q_qg)    |
| Charles Dickens (fb:m.01v9724) | Works written (fb:book.author.works_written) | Bleak House (fb:m.028y3p)          |
| Charles Dickens (fb:m.01v9724) | Works written (fb:book.author.works_written) | Little Dorrit (fb:m.012yyq)        |
| Charles Dickens (fb:m.01v9724) | Works written (fb:book.author.works_written) | Hard Times (fb:m.03g9m8)           |
| ...                            | ...                                          | ...                                |

[Assistant]
We have a list of works written by Charles Dickens. Now, we need to find the publication dates for these works. Let's search for a property that indicates the publication date of a book.

Let's search for a property related to "publication date" for one of the books, for example, `A Christmas Carol` (fb:m.0js1m).

[Tool]
Top 10 property alternatives:
1. Date of first publication (fb:book.written_work.date_of_first_publication): Written Work, Date/Time
2. Copyright date (fb:book.written_work.copyright_date): Written Work, Date/Time
3. Editions (fb:book.book.editions): Book Edition, Book
4. Author (fb:book.written_work.author): Written Work, Author
5. Editor (fb:book.written_work.editor): Written Work, Author
6. Article (fb:common.topic.article): Document, Topic
7. Subjects (fb:book.written_work.subjects): Literature Subject, Written Work
8. Key (fb:type.object.key): Object, Key
9. Genre (fb:book.book.genre): Literary Genre, Book
10. Original language (fb:book.written_work.original_language): Human Language, Written Work

No other items found

[Assistant]
We found a property `fb:book.written_work.date_of_first_publication` that indicates the date of first publication for a written work. We can use this property to find the publication dates of Charles Dickens' works and then determine the earliest one.

Let's construct a SPARQL query to find the first book Charles Dickens wrote by sorting the works by their publication date and selecting the earliest one.

Here is the SPARQL query:

```sparql
SELECT ?book ?date WHERE {
  fb:m.01v9724 fb:book.author.works_written ?book .
  ?book fb:book.written_work.date_of_first_publication ?date .
} ORDER BY ASC(?date) LIMIT 1
```

Let's execute this query.

[Tool]
Got 1 row and 2 columns:
| book                          | date             |
| ----------------------------- | ---------------- |
| Sketches by Boz (fb:m.01_wr2) | 1836 (xsd:gYear) |

[Assistant]
The first book Charles Dickens wrote is "Sketches by Boz," which was published in 1836.

Here is the final SPARQL query and answer:

```sparql
SELECT ?book ?date WHERE {
  fb:m.01v9724 fb:book.author.works_written ?book .
  ?book fb:book.written_work.date_of_first_publication ?date .
} ORDER BY ASC(?date) LIMIT 1
```

Answer: The first book Charles Dickens wrote is "Sketches by Boz."

[Tool] Stopped generation process


PREFIX fb: <http://rdf.freebase.com/ns/>
SELECT DISTINCT ?language WHERE {
  {
    fb:m.01mjq fb:location.country.official_language ?language
  } UNION {
    fb:m.01mjq fb:location.country.languages_spoken ?language
  }
}

Got 13 rows and 1 column, showing the first 5 and last 5 rows below:
| language                          |
| --------------------------------- |
| Romani language (fb:m.012psb)     |
| Rusyn Language (fb:m.013hyy)      |
| Bulgarian Language (fb:m.01bkv)   |
| Czech Language (fb:m.01wgr)       |
| Hungarian language (fb:m.02ztjwg) |
| ...                               |
| Russian Language (fb:m.06b_j)     |
| Slovak Language (fb:m.06zvx)      |
| Ukrainian Language (fb:m.0cjk9)   |
| Serbian language (fb:m.0k0sb)     |
| Croatian language (fb:m.0k0sv)    |

The official language of the Czech Republic is the Czech Language. Other languages spoken in the Czech Republic include Romani, Rusyn, Bulgarian, Hungarian, Russian, Slovak, Ukrainian, Serbian, and Croatian.

[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 is spoken in czech republic?

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

[Tool]
Example 1:
Question:
what do people in the czech republic speak?

SPARQL:
SELECT DISTINCT ?x WHERE {
  FILTER ( ?x != fb:m.01mjq ) FILTER ( ! isLiteral( ?x ) || lang( ?x ) = '' || langMatches( lang( ?x ) , 'en' ) ) fb:m.01mjq fb:location.country.official_language ?x .
}

Using entities:
Czech Republic, also known as Bohemia (fb:m.01mjq): The Czech Republic, is a landlocked country in Central Europe bo...ized mainly by the emperor and princes of the Holy Roman Empire., Country

Using properties:
Official Language (fb:location.country.official_language): Human Language, Country

Example 2:
Question:
what do people in the czech republic speak?

SPARQL:
SELECT DISTINCT ?x WHERE {
  FILTER ( ?x != fb:m.01mjq ) FILTER ( ! isLiteral( ?x ) || lang( ?x ) = '' || langMatches( lang( ?x ) , 'en' ) ) fb:m.01mjq fb:location.country.languages_spoken ?x .
}

Using entities:
Czech Republic, also known as Bohemia (fb:m.01mjq): The Czech Republic, is a landlocked country in Central Europe bo...ized mainly by the emperor and princes of the Holy Roman Empire., Country

Using properties:
Languages spoken (fb:location.country.languages_spoken): Human Language, Country

Example 3:
Question:
what language do people in czech republic speak?

SPARQL:
SELECT DISTINCT ?x WHERE {
  FILTER ( ?x != fb:m.01mjq ) FILTER ( ! isLiteral( ?x ) || lang( ?x ) = '' || langMatches( lang( ?x ) , 'en' ) ) fb:m.01mjq fb:location.country.official_language ?x .
}

Using entities:
Czech Republic, also known as Bohemia (fb:m.01mjq): The Czech Republic, is a landlocked country in Central Europe bo...ized mainly by the emperor and princes of the Holy Roman Empire., Country

Using properties:
Official Language (fb:location.country.official_language): Human Language, Country

[Assistant] Based on the examples, it seems like we need to find the official language or languages spoken in the Czech Republic. Let's first identify the entity for the Czech Republic.

[Tool]
Top 10 entity alternatives:
1. Czech Republic, also known as Bohemia (fb:m.01mjq): The Czech Republic, is a landlocked country in Central Europe bo...ized mainly by the emperor and princes of the Holy Roman Empire., Country
2. Mrdrchain, also known as Czech Republic, MRDRCHAIN (fb:m.0fpp763): Mrdrchain is a 2010 short animation film written and directed by Ondrej Svadlena., Film
3. Czech Republic (fb:m.0sndgq9): Musical Recording
4. Czech Republic (fb:m.03c3ks2): In European elections, Czech Republic is a constituency of the E...nty-four MEPs. It covers the member state of the Czech Republic., Political District
5. Czech Republic (fb:m.05dlwwg): The Czech Republic, land of ornate castles and mystical legends,... landmarks alike, so kick back, drink up and let it all sink in., TV Episode
6. Czech Republic (fb:m.0f75lvn): Musical Recording
7. Czech Republic (fb:m.0799b2k): TV Episode
8. Czech Republic (fb:m.0d_mqs2): Musical Recording
9. Czech Republic (fb:m.07lbfj3): TV Episode
10. Episode 45, also known as Czech Republic (fb:m.0kxxg5q): TV Episode

[Assistant]
The correct entity for the Czech Republic is `fb:m.01mjq`. Now, let's look for the properties that might give us the official language or languages spoken in the Czech Republic.

We can use the properties `fb:location.country.official_language` and `fb:location.country.languages_spoken` as suggested by the examples.

Let's start with the `fb:location.country.official_language` property.

[Tool]
Got 1 row and 1 column:
| language                    |
| --------------------------- |
| Czech Language (fb:m.01wgr) |

[Assistant]
The official language of the Czech Republic is the Czech Language (`fb:m.01wgr`).

To ensure completeness, let's also check if there are any other languages spoken in the Czech Republic using the `fb:location.country.languages_spoken` property.

[Tool]
Got 13 rows and 1 column, showing the first 5 and last 5 rows below:
| language                          |
| --------------------------------- |
| Romani language (fb:m.012psb)     |
| Rusyn Language (fb:m.013hyy)      |
| Bulgarian Language (fb:m.01bkv)   |
| Czech Language (fb:m.01wgr)       |
| Hungarian language (fb:m.02ztjwg) |
| ...                               |
| Russian Language (fb:m.06b_j)     |
| Slovak Language (fb:m.06zvx)      |
| Ukrainian Language (fb:m.0cjk9)   |
| Serbian language (fb:m.0k0sb)     |
| Croatian language (fb:m.0k0sv)    |

[Assistant]
The languages spoken in the Czech Republic include:

- Romani language (`fb:m.012psb`)
- Rusyn Language (`fb:m.013hyy`)
- Bulgarian Language (`fb:m.01bkv`)
- Czech Language (`fb:m.01wgr`)
- Hungarian language (`fb:m.02ztjwg`)
- Russian Language (`fb:m.06b_j`)
- Slovak Language (`fb:m.06zvx`)
- Ukrainian Language (`fb:m.0cjk9`)
- Serbian language (`fb:m.0k0sb`)
- Croatian language (`fb:m.0k0sv`)

However, the official language is the Czech Language (`fb:m.01wgr`).

Now, let's combine both queries into a single SPARQL query to provide a comprehensive answer.

[Tool] Stopped generation process


PREFIX fb: <http://rdf.freebase.com/ns/>
SELECT ?placeOfBirth WHERE {
  fb:m.04s9n fb:people.person.place_of_birth ?placeOfBirth .
}

Got 1 row and 1 column:
| placeOfBirth       |
| ------------------ |
| Mecca (fb:m.058wp) |

Mecca (fb:m.058wp)

[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 was the prophet mohammed from?

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

[Tool]
Example 1:
Question:
what country was jesus born?

SPARQL:
SELECT DISTINCT ?x WHERE {
  fb:m.045m1_ fb:people.person.place_of_birth ?y .
  ?y fb:location.location.containedby ?x .
  ?x fb:common.topic.notable_types fb:m.01mp .
}

Using entities:
Country, also known as Empire (fb:m.01mp): The type country in Freebase can and should be used with a varie...s with little population or autonomy will be typed as a country.
Jesus Christ, also known as Yeshua, Jesus, son of Mary, Jesus, Jesus of Nazareth, Jesus Christ, Son of God, Son of Mary (fb:m.045m1_): Jesus, also referred to as Jesus of Nazareth, is the central fig...ted as "AD" or sometimes as "CE" is based on the birth of Jesus., Deity

Using properties:
Notable types (fb:common.topic.notable_types): Topic, Type
Contained by (fb:location.location.containedby): Location
Place of birth (fb:people.person.place_of_birth): Location, Person

Example 2:
Question:
what country was bin laden from?

SPARQL:
SELECT DISTINCT ?x WHERE {
  FILTER ( ?x != fb:m.05mg9 ) FILTER ( ! isLiteral( ?x ) || lang( ?x ) = '' || langMatches( lang( ?x ) , 'en' ) ) fb:m.05mg9 fb:people.person.nationality ?x .
}

Using entities:
Osama bin Laden, also known as Sheik al-Mujahid, The Director, The Emir, The Jihadist Sheik, The Prince (fb:m.05mg9): Osama bin Mohammed bin Awad bin Laden was the founder of al-Qaed...ted States, initiating a series of bombings and related attacks., Organization leader

Using properties:
Country of nationality (fb:people.person.nationality): Country, Person

Example 3:
Question:
who was the first wife of prophet muhammad?

SPARQL:
SELECT DISTINCT ?x WHERE {
  FILTER ( ?x != fb:m.04s9n ) FILTER ( ! isLiteral( ?x ) || lang( ?x ) = '' || langMatches( lang( ?x ) , 'en' ) ) fb:m.04s9n fb:people.person.spouse_s ?y .
  ?y fb:people.marriage.spouse ?x .
  ?y fb:people.marriage.type_of_union fb:m.04ztj .
  ?y fb:people.marriage.from ?sk0 .
}
ORDER BY xsd:datetime ( ?sk0 )
LIMIT 1

Using entities:
Muhammad in Islam, also known as Mohammed, Mahomet, Muhammad, Muḥammad, Muhammad, Muḥammad ibn `Abd Allāh, Muhammad in Islam (fb:m.04s9n): Muḥammad ibn ʿAbd Allāh ibn ʿAbd al-Muṭṭalib ibn Hāshim, in shor...ed a model of the life-style that Muslims are obliged to follow., Muhammad, full name Abū al-Qāsim Muḥammad ibn ʿAbd Allāh ibn ʿAb...s visited by Gabriel and received his first revelation from God., Military Commander
Marriage, also known as Wedlock, Matrimony (fb:m.04ztj): Marriage, also called matrimony or wedlock, is a socially or rit...of concerns for women's rights and because of international law., Religious Practice

Using properties:
From (fb:people.marriage.from): Date/Time, Marriage
Spouse (fb:people.marriage.spouse): Marriage, Person
Type of union (fb:people.marriage.type_of_union): Marriage/union type, Marriage
Spouse (or domestic partner) (fb:people.person.spouse_s): Marriage, Person

[Assistant] Based on the examples, we need to find the place of birth of Prophet Muhammad. Let's search for the entity "Prophet Muhammad" in Freebase.

[Tool]
Top 10 entity alternatives:
1. Prophet Muhammad (fb:m.06jcj98): Book
2. The Prophet Muhammad (fb:m.08hbqrs): Book Edition
3. Muhammad the prophet (fb:m.0697sj_): Book
4. The Prophet Muhammad (fb:m.06fczcz): Book
5. Muhammad the prophet (fb:m.0d9mnhz): Book Edition
6. Muhammad the prophet (fb:m.0d9n1qm): Book Edition
7. Muhammad the Prophet (fb:m.0w10_3g): Muhammad the Prophet is a book written by Tawfiq al-Hakim ., Written Work
8. Muhammad: The Last Prophet (fb:m.027nkyc): Muhammad: The Last Prophet is a 2002 animated film and quranic e... his perspective, and his words are paraphrased by the narrator., Film
9. Muhammad, Prophet of God (fb:m.088_b_v): Book Edition
10. Any prophet after Muhammad? (fb:m.0bhzz0c): Book Edition

[Assistant] None of these entities seem to represent the person "Prophet Muhammad". Let me try searching again with just "Muhammad".

[Tool]
Top 10 entity alternatives:
1. Muhammad in Islam, also known as Mohammed, Mahomet, Muhammad, Muḥammad, Muhammad, Muḥammad ibn `Abd Allāh, Muhammad in Islam (fb:m.04s9n): Muḥammad ibn ʿAbd Allāh ibn ʿAbd al-Muṭṭalib ibn Hāshim, in shor...ed a model of the life-style that Muslims are obliged to follow., Muhammad, full name Abū al-Qāsim Muḥammad ibn ʿAbd Allāh ibn ʿAb...s visited by Gabriel and received his first revelation from God., Military Commander
2. Alp Arslan, also known as Abu Shuja, Adud ad-Dawlah, Alp Arslan ibn Chaghri-Beg ibn Mikail ibn Seljuq ibn Duqaq, Diya ad-Din, Muhammad (fb:m.0kdl): Alp Arslan was the second Sultan of the Seljuk Empire and great-...ained the name Alp Arslan, which means "Heroic Lion" in Turkish., Noble person
3. Prophets in Islam, also known as Muhammad (fb:m.024b22): Belief
4. Muhammad, also known as Surat Muhammad (fb:m.04vlym): Surat Muhammad is the 47th sura of the Qur'an with 38 ayat. The ...dr took place during Ramadan, in year 2 of the Islamic calendar.
5. Muhammad (fb:m.012fjwq7): Muhammad: The Messenger of God is an upcoming 2015 Iranian film ... by Vittorio Storaro and film score is composed by A. R. Rahman., Film
6. Muhammad, also known as Muhammad: His Life Based on the Earliest Sources (fb:m.04wdb8g): Muhammad: His Life Based on the Earliest Sources is an award-win... 1983 biography of the Islamic prophet Muhammad by Martin Lings., Book
7. Muhammad (fb:m.08p_zw6): Book Edition
8. Muhammad, also known as Mohammad of Tabaristan (fb:m.0_fpvzp): Muhammad of Tabaristan was the ruler of the Bavand dynasty from ...1271. He was the son and successor of Ardashir II of Tabaristan., Monarch
9. Muhammad (fb:m.0264__l)
10. Muhammad: The Messenger of God, also known as Muhammad (fb:m.08wxhk): Muhammad, The Messenger of God is a book about Islam written by Betty Kelen., Book

[Assistant] The first entity "Muhammad in Islam" seems to be the correct representation of the person "Prophet Muhammad". Now let's look for the property "place of birth" for this entity.

[Tool]
Top 10 property alternatives:
1. Place of birth (fb:people.person.place_of_birth): Location, Person
2. Country of nationality (fb:people.person.nationality): Country, Person
3. Date of death (fb:people.deceased_person.date_of_death): Deceased Person, Date/Time
4. Place of death (fb:people.deceased_person.place_of_death): Deceased Person, Location
5. Profession (fb:people.person.profession): Profession, Person
6. Name (fb:type.object.name): Object, Text
7. Place of burial (fb:people.deceased_person.place_of_burial): Place of interment, Deceased Person
8. Key (fb:type.object.key): Object, Key
9. entry (fb:user.tsegaran.random.taxonomy_subject.entry): Taxonomy Subject, Taxonomy Entry
10. Ethnicity (fb:people.person.ethnicity): Ethnicity, Person

No other items found

[Assistant]
The property "Place of birth" (fb:people.person.place_of_birth) is relevant to our query. Now, let's construct a SPARQL query to find the place of birth of Prophet Muhammad.

```sparql
SELECT ?placeOfBirth WHERE {
  fb:m.04s9n fb:people.person.place_of_birth ?placeOfBirth .
}
```

Let's execute this query.

[Tool]
Got 1 row and 1 column:
| placeOfBirth       |
| ------------------ |
| Mecca (fb:m.058wp) |

[Assistant]
The place of birth of Prophet Muhammad is Mecca.

Here is the final SPARQL query and answer:

```sparql
SELECT ?placeOfBirth WHERE {
  fb:m.04s9n fb:people.person.place_of_birth ?placeOfBirth .
}
```

Answer: Mecca (fb:m.058wp)

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

[Tool] Stopped generation process


PREFIX fb: <http://rdf.freebase.com/ns/>
SELECT DISTINCT ?parent WHERE {
  fb:m.02vntj fb:people.person.parents ?parent .
}

Got 2 rows and 1 column:
| parent                                |
| ------------------------------------- |
| Gerald Hathaway (fb:m.07ylp26)        |
| Kate McCauley Hathaway (fb:m.07ylp2d) |

Anne Hathaway's parents are Gerald Hathaway and Kate McCauley Hathaway.

[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] who is anne hathaway parents?

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

[Tool]
Example 1:
Question:
where was anne hathaway born?

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

Using entities:
Anne Hathaway, also known as Enn Kheteuey, Annie, Anne Jacqueline Hathaway, Anne Whitney Hathaway, An Hasawei (fb:m.02vntj): Anne Jacqueline Hathaway is an American actress, singer, and pro...he Dark Knight Rises and Fantine in Tom Hooper's Les Misérables., Celebrity

Using properties:
Place of birth (fb:people.person.place_of_birth): Location, Person

Example 2:
Question:
who is john cabot's parents?

SPARQL:
SELECT DISTINCT ?x WHERE {
  FILTER ( ?x != fb:m.040t9 ) FILTER ( ! isLiteral( ?x ) || lang( ?x ) = '' || langMatches( lang( ?x ) , 'en' ) ) fb:m.040t9 fb:people.person.parents ?x .
}

Using entities:
John Cabot (fb:m.040t9): John Cabot was an Italian navigator and explorer whose 1497 disc...conclusion that the landing was at Cape Bonavista, Newfoundland., Deceased Person

Using properties:
Parents (fb:people.person.parents): Person

Example 3:
Question:
who is kristen stewart parents?

SPARQL:
SELECT DISTINCT ?x WHERE {
  FILTER ( ?x != fb:m.07swvb ) FILTER ( ! isLiteral( ?x ) || lang( ?x ) = '' || langMatches( lang( ?x ) , 'en' ) ) fb:m.07swvb fb:people.person.parents ?x .
}

Using entities:
Kristen Stewart, also known as Ki Ki, Stew, KStew, Kristen Jaymes Stewart, Kris (fb:m.07swvb): Kristen Jaymes Stewart (born April 9, 1990) is an American actre... 9
 RFID Accessory
 http://www.jinmuyu.com.cn/english/index.html, Kristen Jaymes Stewart is an American actress, known for playing... for her role opposite Juliette Binoche in Clouds of Sils Maria., Celebrity

Using properties:
Parents (fb:people.person.parents): Person

[Assistant] Based on the examples, it seems like we need to find the entity for Anne Hathaway and then use the `parents` property to find her parents. Let's first search for the entity for Anne Hathaway.

[Tool]
Top 10 entity alternatives:
1. Anne Hathaway, also known as Enn Kheteuey, Annie, Anne Jacqueline Hathaway, Anne Whitney Hathaway, An Hasawei (fb:m.02vntj): Anne Jacqueline Hathaway is an American actress, singer, and pro...he Dark Knight Rises and Fantine in Tom Hooper's Les Misérables., Celebrity
2. Anne Hathaway, also known as Ann Hathaway (fb:m.03mzbg): Anne Hathaway was the wife of William Shakespeare, the English p... subject of much speculation by historians and creative writers., Deceased Person
3. Anne Hathaway (fb:m.05ngh3d): Three people die in an attempt to get a jump on their holiday sh...on's mouthpiece, and Anne Hathaway vows to become a train wreck., TV Episode
4. Anne Hathaway (fb:m.0j946gh): One of the sweetest stars in Hollywood, ANNE HATHAWAY, is here t...he very first time to perform her hit song, "Dancing on My Own.", One of the sweetest stars in Hollywood, ANNE HATHAWAY, is here t...p star. She's here to perform her hit song, "Dancing on My Own.", TV Episode
5. Anne Hathaway (fb:m.0kb0jh6): Warren Buffett enters the "class warfare" fray, Fitch downgrades...rsey's credit rating, and Anne Hathaway talks Scrabble strategy., TV Episode
6. Anne Hathaway (fb:m.0jgxn99): Actress Anne Hathaway on her movie The Dark Knight Rises; Round ...ion with comics Greg Proops, Heather McDonald, and Ross Mathews., TV Episode
7. Anne Hathaway (fb:m.07kcjnv): TV Episode
8. Anne Hathaway (fb:m.07mls9g): TV Episode
9. Anne Hathaway (fb:m.0wfdz3f): America temporarily avoids the Fiscal Cliff, House Republicans v...kage, and Anne Hathaway divulges the ending to "Les Miserables"., TV Episode
10. Anne Hathaway (fb:m.0wcgs37): TV Episode

[Assistant]
The top result for Anne Hathaway is the correct one, which is `fb:m.02vntj`. Now let's use the `parents` property to find her parents.

I will now construct a SPARQL query to find Anne Hathaway's parents.

[Tool]
Got 2 rows and 1 column:
| parent                                |
| ------------------------------------- |
| Gerald Hathaway (fb:m.07ylp26)        |
| Kate McCauley Hathaway (fb:m.07ylp2d) |

[Assistant]
The SPARQL query has successfully returned the parents of Anne Hathaway. Her parents are Gerald Hathaway and Kate McCauley Hathaway.

Here is the final SPARQL query and the answer:

```sparql
SELECT DISTINCT ?parent WHERE {
  fb:m.02vntj fb:people.person.parents ?parent .
}
```

Answer: Anne Hathaway's parents are Gerald Hathaway and Kate McCauley Hathaway.

[Tool] Stopped generation process


PREFIX fb: <http://rdf.freebase.com/ns/>
SELECT DISTINCT ?profession WHERE {
  fb:m.087k1_ fb:people.person.profession ?profession .
}

Got 1 row and 1 column:
| profession           |
| -------------------- |
| Actor (fb:m.02hrh1q) |

Helen Flanagan is an actor.

[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 does helen flanagan do?

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

[Tool]
Example 1:
Question:
what did florence sabin do?

SPARQL:
SELECT DISTINCT ?x WHERE {
  FILTER ( ?x != fb:m.033_w4 ) FILTER ( ! isLiteral( ?x ) || lang( ?x ) = '' || langMatches( lang( ?x ) , 'en' ) ) fb:m.033_w4 fb:people.person.profession ?x .
}

Using entities:
Florence R. Sabin, also known as Dr. Florence R. Sabin, Florence Sabin (fb:m.033_w4): Florence Rena Sabin was an American medical scientist. She was a... in Colorado, and in 1951 received a Lasker Award for this work., Physician

Using properties:
Profession (fb:people.person.profession): Profession, Person

Example 2:
Question:
what does annie leibovitz do?

SPARQL:
SELECT DISTINCT ?x WHERE {
  FILTER ( ?x != fb:m.015m2c ) FILTER ( ! isLiteral( ?x ) || lang( ?x ) = '' || langMatches( lang( ?x ) , 'en' ) ) fb:m.015m2c fb:people.person.profession ?x .
}

Using entities:
Annie Leibovitz, also known as Anna-Lou "Annie" Leibovitz, Annie Leibowitz, Anna-Lou Leibovitz (fb:m.015m2c): Anna-Lou "Annie" Leibovitz is an American portrait photographer., Visual Artist

Using properties:
Profession (fb:people.person.profession): Profession, Person

[Assistant] Based on the examples, it seems like we need to find Helen Flanagan's profession. Let's first search for Helen Flanagan in the Freebase knowledge graph.

[Tool]
Top 10 entity alternatives:
1. Helen Flanagan, also known as Helen Daniella Flanagan (fb:m.087k1_): Helen Joyce Gabriel Flanagan is an English actress, model, and t...h candidate in the 2013 FHM 100 Sexiest Women in the World poll., TV Actor
2. Helen Flanagan (fb:m.0_z3nl7): Helen Flanagan is a cinematographer., Film cinematographer
3. Helen Flanagan (fb:m.0ygdbgn): Helen Flanagan is a fictional character from the 2011 film Butter., Film character
4. Helen Flanagan Pictures (fb:m.0c1_pkz)
5. Helen Flanagan, Henning Wehn, and Miles Jupp, also known as Helen Flanagan, Henning Wehn, Miles Jupp, Alex Brooker (fb:m.0yldrqp): Extended version of the show guest staring Helen Flanagan, Henning Wehn, Miles Jupp and Alex Brooker., TV Episode
6. Helen Flanagan, Henning Wehn, Miles Jupp, TBA, also known as Helen Flanagan, Henning Wehn, Miles Jupp, Alex Brooker (fb:m.0y5r68h): Jimmy Carr hosts the topical comedy panel show, with team captai...uests Helen Flanagan, Henning Wehn. Alex Brooker and Miles Jupp., TV Episode
7. Helen, also known as Queen of the Nautch Girls, Miss Helen, Helen Jairag, Helen Richardson Khan, Helen Richardson (fb:m.070c93): Helen Jairag Richardson is a Burma-born Indian film actress and ...s the second wife of Salim Khan, and step-mother of Salman Khan., Award Winner
8. Jon Flanagan, also known as Flanagan, Jonathon Patrick Flanagan (fb:m.0gkzb7h): Jonathon Patrick "Jon" Flanagan is an English professional footb...ion". This has led to fans dubbing Flanagan as "the Scouse Cafu", Football player
9. Helen, also known as Helen, Georgia, White County / Helen city (fb:m.0r_0f): Helen is a city in White County, Georgia, United States, along the Chattahoochee River. The population was 430 at the 2000 census., City/Town/Village
10. Flanagan, also known as Flanagan, Illinois, Livingston County / Flanagan village (fb:m.0sbmb): Flanagan is a village in Livingston County, Illinois, United Sta...ool and grade school are both located within the village limits., City/Town/Village

[Assistant] It looks like the first result is the correct Helen Flanagan, who is an English actress, model, and TV actor. Now let's check her profession using the `fb:people.person.profession` property.

[Tool]
Got 1 row and 1 column:
| profession           |
| -------------------- |
| Actor (fb:m.02hrh1q) |

[Assistant]
The SPARQL query has returned that Helen Flanagan's profession is "Actor".

Let's wrap this up and provide the final answer.

[Tool] Stopped generation process


PREFIX fb: <http://rdf.freebase.com/ns/>
SELECT ?placeOfBirth WHERE {
  fb:m.0261x8t fb:people.person.place_of_birth ?placeOfBirth .
}

Got 1 row and 1 column:
| placeOfBirth               |
| -------------------------- |
| Los Angeles (fb:m.030qb3t) |

Los Angeles

[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 kim kardashian come from?

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

[Tool]
Example 1:
Question:
who was kim kardashian's first husband?

SPARQL:
SELECT DISTINCT ?x WHERE {
  FILTER ( ?x != fb:m.0261x8t ) FILTER ( ! isLiteral( ?x ) || lang( ?x ) = '' || langMatches( lang( ?x ) , 'en' ) ) fb:m.0261x8t fb:people.person.spouse_s ?y .
  ?y fb:people.marriage.spouse ?x .
  ?y fb:people.marriage.type_of_union fb:m.04ztj .
  ?y fb:people.marriage.to ?sk0 .
}
ORDER BY xsd:datetime ( ?sk0 )
LIMIT 1

Using entities:
Kim Kardashian, also known as Kimmie, Kim, Kimberly Noel Kardashian, Kimberly Noel "Kim" Kardashian, Kim West (fb:m.0261x8t): Kimberly "Kim" Kardashian West is an American television and soc...y television personality, with estimated earnings of $6 million., Celebrity
Marriage, also known as Wedlock, Matrimony (fb:m.04ztj): Marriage, also called matrimony or wedlock, is a socially or rit...of concerns for women's rights and because of international law., Religious Practice

Using properties:
Spouse (fb:people.marriage.spouse): Marriage, Person
To (fb:people.marriage.to): Date/Time, Marriage
Type of union (fb:people.marriage.type_of_union): Marriage/union type, Marriage
Spouse (or domestic partner) (fb:people.person.spouse_s): Marriage, Person

Example 2:
Question:
where did rihanna come from?

SPARQL:
SELECT DISTINCT ?x WHERE {
  FILTER ( ?x != fb:m.06mt91 ) FILTER ( ! isLiteral( ?x ) || lang( ?x ) = '' || langMatches( lang( ?x ) , 'en' ) ) fb:m.06mt91 fb:people.person.places_lived ?y .
  ?y fb:people.place_lived.location ?x .
}

Using entities:
Rihanna, also known as The Barbados Babe, Robyn Rihanna Fenty, Caribbean Queen, Robyn Fenty, RiRi (fb:m.06mt91): Robyn Rihanna Fenty, known professionally as Rihanna, is a Barba...ammy Awards, winning Best Rap/Sung Collaboration for "Umbrella"., Musical Artist

Using properties:
Places lived (fb:people.person.places_lived): Place lived, Person
Location (fb:people.place_lived.location): Place lived, Location

Example 3:
Question:
where did rihanna come from?

SPARQL:
SELECT DISTINCT ?x WHERE {
  FILTER ( ?x != fb:m.06mt91 ) FILTER ( ! isLiteral( ?x ) || lang( ?x ) = '' || langMatches( lang( ?x ) , 'en' ) ) fb:m.06mt91 fb:people.person.place_of_birth ?x .
}

Using entities:
Rihanna, also known as The Barbados Babe, Robyn Rihanna Fenty, Caribbean Queen, Robyn Fenty, RiRi (fb:m.06mt91): Robyn Rihanna Fenty, known professionally as Rihanna, is a Barba...ammy Awards, winning Best Rap/Sung Collaboration for "Umbrella"., Musical Artist

Using properties:
Place of birth (fb:people.person.place_of_birth): Location, Person

[Assistant] Based on the examples, we can see that the place of birth or places lived are relevant properties to look at for finding where someone comes from. Let's first identify the entity for Kim Kardashian.

[Tool]
Top 10 entity alternatives:
1. Kim Kardashian, also known as Kimmie, Kim, Kimberly Noel Kardashian, Kimberly Noel "Kim" Kardashian, Kim West (fb:m.0261x8t): Kimberly "Kim" Kardashian West is an American television and soc...y television personality, with estimated earnings of $6 million., Celebrity
2. Kim Kardashian, also known as Petite Ninja Warriors (fb:m.0745l_5): The models navigate their way through Los Angeles as they attend...e ladies to hang on wires. Model Jessica White is a guest judge., TV Episode
3. Kim Kardashian (fb:m.06xy8z0): John Caparulo, Jen Kirkman, Ross Mathews, TV Episode
4. Kim Kardashian (fb:m.0gg_zfd): TV Episode
5. Kim Kardashian (fb:m.0xtwmq5): Musical Recording
6. Kim Kardashian (fb:m.0kc3ypk): TV Episode
7. Kim Kardashian (fb:m.0g05d33): TV Episode
8. Kim Kardashian (fb:m.06y25xd): TV Episode
9. Kim Kardashian (fb:m.0tm0357): Musical Recording
10. Kim Kardashian (fb:m.0_hgg8w): TV Episode

[Assistant] The top result for Kim Kardashian is the correct one, `fb:m.0261x8t`. Now let's check if she has a place of birth or places lived associated with her.

[Tool]
Got 1 row and 3 columns:
| subject                       | property                                         | object                     |
| ----------------------------- | ------------------------------------------------ | -------------------------- |
| Kim Kardashian (fb:m.0261x8t) | Place of birth (fb:people.person.place_of_birth) | Los Angeles (fb:m.030qb3t) |

[Assistant] Kim Kardashian's place of birth is Los Angeles. We can now construct a simple SPARQL query to confirm this information.

[Tool]
Got 1 row and 1 column:
| placeOfBirth               |
| -------------------------- |
| Los Angeles (fb:m.030qb3t) |

[Assistant] The SPARQL query confirms that Kim Kardashian's place of birth is Los Angeles. Therefore, the answer to the question "Where did Kim Kardashian come from?" is Los Angeles.

[Tool] Stopped generation process


PREFIX fb: <http://rdf.freebase.com/ns/>
SELECT ?case ?caseName WHERE {
  fb:m.07sz1 fb:law.court.legal_cases ?case .
  OPTIONAL {
    ?case fb:type.object.name ?caseName .
    FILTER ( LANG( ?caseName ) = 'en' )
  }
}

Got 954 rows and 2 columns, showing the first 5 and last 5 rows below:
| case                                                                                | caseName                                                                 |
| ----------------------------------------------------------------------------------- | ------------------------------------------------------------------------ |
| Burwell v. Hobby Lobby (fb:m.0102pqly)                                              | Burwell v. Hobby Lobby (en)                                              |
| Motor Vehicles Manufacturers Ass... Mutual Automobile Insurance Co. (fb:m.010f95gt) | Motor Vehicles Manufacturers Ass... Mutual Automobile Insurance Co. (en) |
| Schuette v. Coalition to Defend Affirmative Action (fb:m.010f9y51)                  | Schuette v. Coalition to Defend Affirmative Action (en)                  |
| Myers v. United States (fb:m.01_0hd)                                                | Myers v. United States (en)                                              |
| Riley v. California (fb:m.010hmy_z)                                                 | Riley v. California (en)                                                 |
| ...                                                                                | ...                                                                      |
| National Federation of Independent Business v. Sebelius (fb:m.0j7l53h)              | National Federation of Independent Business v. Sebelius (en)             |
| National Gay Task Force v. Board of Education (fb:m.0k3p257)                        | National Gay Task Force v. Board of Education (en)                       |
| Dred Scott v. Sandford (fb:m.0qjlj)                                                 | Dred Scott v. Sandford (en)                                              |
| Bush v. Gore (fb:m.0qjn1)                                                           | Bush v. Gore (en)                                                        |
| Law v. Siegel (fb:m.0_xc06k)                                                        | Law v. Siegel (en)                                                       |

The Supreme Court cases include Burwell v. Hobby Lobby, Motor Vehicles Manufacturers Ass... Mutual Automobile Insurance Co., Schuette v. Coalition to Defend Affirmative Action, Myers v. United States, Riley v. California, and many others.

[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 supreme court cases?

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

[Tool]
Example 1:
Question:
who are the judges of the supreme court?

SPARQL:
SELECT DISTINCT ?x WHERE {
  FILTER ( ?x != fb:m.07sz1 ) FILTER ( ! isLiteral( ?x ) || lang( ?x ) = '' || langMatches( lang( ?x ) , 'en' ) ) fb:m.07sz1 fb:law.court.judges ?y .
  ?y fb:law.judicial_tenure.judge ?x .
  FILTER ( NOT EXISTS {
    ?y fb:law.judicial_tenure.from_date ?sk0
  }
  || EXISTS {
    ?y fb:law.judicial_tenure.from_date ?sk1 .
    FILTER ( xsd:datetime ( ?sk1 ) <= "2015-08-10" ^^ xsd:dateTime )
  }
  ) FILTER ( NOT EXISTS {
    ?y fb:law.judicial_tenure.to_date ?sk2
  }
  || EXISTS {
    ?y fb:law.judicial_tenure.to_date ?sk3 .
    FILTER ( xsd:datetime ( ?sk3 ) >= "2015-08-10" ^^ xsd:dateTime )
  }
  )
}

Using entities:
Supreme Court of the United States, also known as SCOTUS, U.S. Supreme Court, United States Supreme Court, us supreme court (fb:m.07sz1): The Supreme Court of the United States is the highest federal co...efs that track with those philosophical or political categories., Court

Using properties:
Judges (fb:law.court.judges): Judicial tenure, Court
From date (fb:law.judicial_tenure.from_date): Judicial tenure, Date/Time
Judge (fb:law.judicial_tenure.judge): Judicial tenure, Judge
To date (fb:law.judicial_tenure.to_date): Judicial tenure, Date/Time

Example 2:
Question:
what is the jurisdiction of the us supreme court?

SPARQL:
SELECT DISTINCT ?x WHERE {
  FILTER ( ?x != fb:m.07sz1 ) FILTER ( ! isLiteral( ?x ) || lang( ?x ) = '' || langMatches( lang( ?x ) , 'en' ) ) fb:m.07sz1 fb:law.court.jurisdiction ?x .
}

Using entities:
Supreme Court of the United States, also known as SCOTUS, U.S. Supreme Court, United States Supreme Court, us supreme court (fb:m.07sz1): The Supreme Court of the United States is the highest federal co...efs that track with those philosophical or political categories., Court

Using properties:
Jurisdiction (fb:law.court.jurisdiction): Court jurisdiction area, Court

Example 3:
Question:
what is a judge in the supreme court called?

SPARQL:
SELECT DISTINCT ?x WHERE {
  FILTER ( ?x != fb:m.07sz1 ) FILTER ( ! isLiteral( ?x ) || lang( ?x ) = '' || langMatches( lang( ?x ) , 'en' ) ) fb:m.07sz1 fb:government.governmental_body.offices_positions ?x .
}

Using entities:
Supreme Court of the United States, also known as SCOTUS, U.S. Supreme Court, United States Supreme Court, us supreme court (fb:m.07sz1): The Supreme Court of the United States is the highest federal co...efs that track with those philosophical or political categories., Court

Using properties:
Offices/Positions Within the Body (fb:government.governmental_body.offices_positions): Government Office or Title, Governmental Body

[Assistant] Based on the examples, it seems like we need to look for cases related to the Supreme Court of the United States. Let's first identify the entity for the Supreme Court of the United States.

[Tool]
Top 10 entity alternatives:
1. Supreme Court of the United States, also known as SCOTUS, U.S. Supreme Court, United States Supreme Court, us supreme court (fb:m.07sz1): The Supreme Court of the United States is the highest federal co...efs that track with those philosophical or political categories., Court
2. The Supreme Court of the United States (fb:m.068xzg8): Book
3. The Supreme Court of the United States (fb:m.06hd54w): Book
4. The Supreme Court of the United States (fb:m.06v1f6r): Book
5. The Supreme Court of the United States (fb:m.06vvjt0): Book
6. Supreme Court of the United States (fb:m.03s6x67)
7. Supreme Court of the United States (fb:m.07pwv4y)
8. Supreme Court of the United States (fb:m.0bk60s7)
9. Demographics of the Supreme Court of the United States (fb:m.0118p_hr): The demographics of the Supreme Court of the United States encom...he 21st century saw the first appointment of a Hispanic justice.
10. Clerk of the Supreme Court of the United States (fb:m.02qr0s7): The Clerk of the Supreme Court of the United States is the offic...d maintaining its records. The current Clerk is Scott S. Harris., Government Office or Title

[Assistant] The correct entity for the Supreme Court of the United States is `fb:m.07sz1`. Now, let's find out what properties are associated with this entity that might relate to cases.

[Tool]
Top 10 property alternatives:
1. Legal cases (fb:law.court.legal_cases): Legal case, Court
2. Type (fb:type.object.type): Object, Type
3. Decision (fb:user.rca.default_domain.court.decision): US Court Decision, Court
4. Image (fb:common.topic.image): Topic, Image
5. Description (fb:common.topic.description): Topic, Text
6. Name (fb:type.object.name): Object, Text
7. Key (fb:type.object.key): Object, Key
8. Subject of (fb:common.topic.subject_of): Topic
9. Jurisdiction (fb:law.court.jurisdiction): Court jurisdiction area, Court
10. Jurisdiction (fb:government.governmental_body.jurisdiction): Governmental Jurisdiction, Governmental Body

No other items found

[Assistant]
The property `fb:law.court.legal_cases` seems to be the most relevant for finding the legal cases associated with the Supreme Court of the United States. Let's construct a SPARQL query to retrieve these cases.

### Step 1: Simple Query to Retrieve Cases
We'll start with a simple query to retrieve the legal cases associated with the Supreme Court of the United States.

```sparql
SELECT ?case WHERE {
  fb:m.07sz1 fb:law.court.legal_cases ?case .
}
```

Let's execute this query to see the results.

[Tool]
Got 954 rows and 1 column, showing the first 5 and last 5 rows below:
| case                                                                                |
| ----------------------------------------------------------------------------------- |
| Burwell v. Hobby Lobby (fb:m.0102pqly)                                              |
| Motor Vehicles Manufacturers Ass... Mutual Automobile Insurance Co. (fb:m.010f95gt) |
| Schuette v. Coalition to Defend Affirmative Action (fb:m.010f9y51)                  |
| Myers v. United States (fb:m.01_0hd)                                                |
| Riley v. California (fb:m.010hmy_z)                                                 |
| ...                                                                                |
| National Federation of Independent Business v. Sebelius (fb:m.0j7l53h)              |
| National Gay Task Force v. Board of Education (fb:m.0k3p257)                        |
| Dred Scott v. Sandford (fb:m.0qjlj)                                                 |
| Bush v. Gore (fb:m.0qjn1)                                                           |
| Law v. Siegel (fb:m.0_xc06k)                                                        |

[Assistant]
The query has returned a list of legal cases associated with the Supreme Court of the United States. To provide more context, we can also include the names of these cases. Let's modify the query to include the names of the cases.

### Step 2: Include Case Names
We'll add an optional clause to retrieve the names of the cases.

```sparql
SELECT ?case ?caseName WHERE {
  fb:m.07sz1 fb:law.court.legal_cases ?case .
  OPTIONAL { ?case fb:type.object.name ?caseName . }
}
```

Let's execute this updated query.

[Tool]
Got 1,387 rows and 2 columns, showing the first 5 and last 5 rows below:
| case                                                                                | caseName                                                                 |
| ----------------------------------------------------------------------------------- | ------------------------------------------------------------------------ |
| Burwell v. Hobby Lobby (fb:m.0102pqly)                                              | Burwell v. Hobby Lobby (en)                                              |
| Motor Vehicles Manufacturers Ass... Mutual Automobile Insurance Co. (fb:m.010f95gt) | Motor Vehicles Manufacturers Ass... Mutual Automobile Insurance Co. (en) |
| Schuette v. Coalition to Defend Affirmative Action (fb:m.010f9y51)                  | Schuette v. Coalition to Defend Affirmative Action (en)                  |
| Myers v. United States (fb:m.01_0hd)                                                | Myers v. United States (en)                                              |
| Riley v. California (fb:m.010hmy_z)                                                 | Riley v. California (en)                                                 |
| ...                                                                                | ...                                                                      |
| Bush v. Gore (fb:m.0qjn1)                                                           | Bush v. Gore (fr)                                                        |
| Bush v. Gore (fb:m.0qjn1)                                                           | Contestazioni sulle elezioni presidenziali statunitensi del 2000 (it)    |
| Bush v. Gore (fb:m.0qjn1)                                                           | Буш против Гора (sr)                                                     |
| Bush v. Gore (fb:m.0qjn1)                                                           | ブッシュ対ゴア事件 (ja)                                                           |
| Law v. Siegel (fb:m.0_xc06k)                                                        | Law v. Siegel (en)                                                       |

[Assistant]
The query has successfully returned the legal cases associated with the Supreme Court of the United States along with their names. However, some cases have multiple names in different languages. To ensure clarity, we can filter the results to only include the English names.

### Step 3: Filter for English Names
We'll add a filter to ensure that we only get the English names of the cases.

```sparql
SELECT ?case ?caseName WHERE {
  fb:m.07sz1 fb:law.court.legal_cases ?case .
  OPTIONAL { ?case fb:type.object.name ?caseName . FILTER(LANG(?caseName) = 'en') }
}
```

Let's execute this final query.

[Tool]
Got 954 rows and 2 columns, showing the first 5 and last 5 rows below:
| case                                                                                | caseName                                                                 |
| ----------------------------------------------------------------------------------- | ------------------------------------------------------------------------ |
| Burwell v. Hobby Lobby (fb:m.0102pqly)                                              | Burwell v. Hobby Lobby (en)                                              |
| Motor Vehicles Manufacturers Ass... Mutual Automobile Insurance Co. (fb:m.010f95gt) | Motor Vehicles Manufacturers Ass... Mutual Automobile Insurance Co. (en) |
| Schuette v. Coalition to Defend Affirmative Action (fb:m.010f9y51)                  | Schuette v. Coalition to Defend Affirmative Action (en)                  |
| Myers v. United States (fb:m.01_0hd)                                                | Myers v. United States (en)                                              |
| Riley v. California (fb:m.010hmy_z)                                                 | Riley v. California (en)                                                 |
| ...                                                                                | ...                                                                      |
| National Federation of Independent Business v. Sebelius (fb:m.0j7l53h)              | National Federation of Independent Business v. Sebelius (en)             |
| National Gay Task Force v. Board of Education (fb:m.0k3p257)                        | National Gay Task Force v. Board of Education (en)                       |
| Dred Scott v. Sandford (fb:m.0qjlj)                                                 | Dred Scott v. Sandford (en)                                              |
| Bush v. Gore (fb:m.0qjn1)                                                           | Bush v. Gore (en)                                                        |
| Law v. Siegel (fb:m.0_xc06k)                                                        | Law v. Siegel (en)                                                       |

[Assistant]
The final query has successfully returned the legal cases associated with the Supreme Court of the United States, along with their English names. This provides a clear and concise list of the cases.

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

```sparql
SELECT ?case ?caseName WHERE {
  fb:m.07sz1 fb:law.court.legal_cases ?case .
  OPTIONAL { ?case fb:type.object.name ?caseName . FILTER(LANG(?caseName) = 'en') }
}
```

The answer to the question "What are the Supreme Court cases?" is the list of cases and their English names as returned by the query.

[Tool] Stopped generation process


PREFIX fb: <http://rdf.freebase.com/ns/>
SELECT ?spouse ?date WHERE {
  fb:m.018fzs fb:people.person.spouse_s ?marriage .
  ?marriage fb:people.marriage.spouse ?spouse .
  ?marriage fb:people.marriage.from ?date
}
ORDER BY DESC ( ?date )
LIMIT 1

Callista Gingrich

[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 is newt gingrich's wife's name?

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

[Tool]
Example 1:
Question:
where did newt gingrich attend college?

SPARQL:
SELECT DISTINCT ?x WHERE {
  FILTER ( ?x != fb:m.018fzs ) FILTER ( ! isLiteral( ?x ) || lang( ?x ) = '' || langMatches( lang( ?x ) , 'en' ) ) fb:m.018fzs fb:people.person.education ?y .
  ?y fb:education.education.institution ?x .
  ?x fb:common.topic.notable_types fb:m.01y2hnl .
}

Using entities:
Newt Gingrich, also known as Rep. Newt Gingrich, Rep. Gingrich, Newton Leroy McPherson, Newton Leroy "Newt" Gingrich, Newton Leroy Gingrich (fb:m.018fzs): Newton Leroy "Newt" Gingrich is an American politician, historia...n 1997, and in 1998 passed the first balanced budget since 1969., U.S. Congressperson
College/University, also known as College, University (fb:m.01y2hnl): The College/University type is used for institutions that offer ...mation, please see the Freebase wiki page on College/University.

Using properties:
Notable types (fb:common.topic.notable_types): Topic, Type
Institution (fb:education.education.institution): Educational Institution, Education
Education (fb:people.person.education): Education, Person

Example 2:
Question:
who is martin luther king jr wife?

SPARQL:
SELECT DISTINCT ?x WHERE {
  FILTER ( ?x != fb:m.051cc ) FILTER ( ! isLiteral( ?x ) || lang( ?x ) = '' || langMatches( lang( ?x ) , 'en' ) ) fb:m.051cc fb:people.person.spouse_s ?y .
  ?y fb:people.marriage.spouse ?x .
  ?y fb:people.marriage.type_of_union fb:m.04ztj .
}

Using entities:
Marriage, also known as Wedlock, Matrimony (fb:m.04ztj): Marriage, also called matrimony or wedlock, is a socially or rit...of concerns for women's rights and because of international law., Religious Practice
Martin Luther King, Jr., also known as Martin Luther King, Jr, Michael King, Michael King, Jr., Michael Luther King Jr., MLK (fb:m.051cc): Martin Luther King, Jr., was an American Baptist minister, activ...Peace Prize for combating racial inequality through nonviolence., Martin Luther King is a fictional character in the film Theme of the Traitor and the Hero., Author

Using properties:
Spouse (fb:people.marriage.spouse): Marriage, Person
Type of union (fb:people.marriage.type_of_union): Marriage/union type, Marriage
Spouse (or domestic partner) (fb:people.person.spouse_s): Marriage, Person

Example 3:
Question:
what was lincoln's wife's name?

SPARQL:
SELECT DISTINCT ?x WHERE {
  FILTER ( ?x != fb:m.0gzh ) FILTER ( ! isLiteral( ?x ) || lang( ?x ) = '' || langMatches( lang( ?x ) , 'en' ) ) fb:m.0gzh fb:people.person.spouse_s ?y .
  ?y fb:people.marriage.spouse ?x .
  ?x fb:people.person.gender fb:m.02zsn .
}

Using entities:
Female, also known as Woman, Women, Girl, Gal, Dame (fb:m.02zsn): Female (♀) is the sex of an organism, or a part of an organism, ...esis). Some organisms can reproduce both sexually and asexually., Female is the sex of an organism, or a part of an organism, that...female mammals, including female humans, have two X chromosomes., Literature Subject
Abraham Lincoln, also known as The Great Emancipator, The Illinois Baboon, The Jester, The Martyr President, The Railsplitter (fb:m.0gzh): Abraham Lincoln /ˈeɪbrəhæm ˈlɪŋkən/ was the 16th President of th...ew Republican Party, which had a statewide majority in Illinois., US President

Using properties:
Spouse (fb:people.marriage.spouse): Marriage, Person
Gender (fb:people.person.gender): Person, Gender
Spouse (or domestic partner) (fb:people.person.spouse_s): Marriage, Person

[Assistant] Based on the examples, we need to find the entity for Newt Gingrich and then look for his spouse. Let's search for Newt Gingrich in the knowledge graph.

[Tool]
Top 10 entity alternatives:
1. Newt Gingrich, also known as Rep. Newt Gingrich, Rep. Gingrich, Newton Leroy McPherson, Newton Leroy "Newt" Gingrich, Newton Leroy Gingrich (fb:m.018fzs): Newton Leroy "Newt" Gingrich is an American politician, historia...n 1997, and in 1998 passed the first balanced budget since 1969., U.S. Congressperson
2. Newt Gingrich (fb:m.05nfprq): TONIGHT: Author of "Never Call Retreat," Newt Gingrich! Plus, Stephen Colbert with "This Week in God"., TV Episode
3. Newt Gingrich (fb:m.05nfcb3): TV Episode
4. Newt Gingrich (fb:m.05nfcqx): Colin Quinn, TV Episode
5. Newt Gingrich (fb:m.05nfprm): TV Episode
6. Newt Gingrich (fb:m.06y3kvd): TV Episode
7. Newt Gingrich (fb:m.0dl0lms): Richard Shelby releases nominees, and Newt Gingrich discusses the radical Obama administration., TV Episode
8. Newt Gingrich, also known as Newt Gingrich, Jessalyn Gilsig (fb:m.0bmn7ll): TV Episode
9. Newt Gingrich (fb:m.0w81t1v): The media weighs presidential nominees for 2016, Sonia Sotomayor...s, and Newt Gingrich admits he guessed wrong about the election., TV Episode
10. Newt Gingrich (fb:m.0z158s): Musical Recording

[Assistant] The top result for Newt Gingrich is `fb:m.018fzs`. Now let's find out who his spouse is using the property `fb:people.person.spouse_s`.

[Tool]
Got 4 rows and 1 column:
| spouse                           |
| -------------------------------- |
| Newt Gingrich (fb:m.018fzs)      |
| Callista Gingrich (fb:m.05znhhq) |
| Marianne Ginther (fb:m.0661_f)   |
| Jackie Battley (fb:m.0j1782w)    |

[Assistant]
It appears that Newt Gingrich has been married multiple times. The results show:

- Callista Gingrich (`fb:m.05znhhq`)
- Marianne Ginther (`fb:m.0661_f`)
- Jackie Battley (`fb:m.0j1782w`)

To determine which one is his current wife, we need to check the dates of their marriages. Let's find the marriage dates for these relationships.

[Tool]
Got 6 rows and 2 columns:
| spouse                           | date                  |
| -------------------------------- | --------------------- |
| Newt Gingrich (fb:m.018fzs)      | 2000-08-18 (xsd:date) |
| Callista Gingrich (fb:m.05znhhq) | 2000-08-18 (xsd:date) |
| Newt Gingrich (fb:m.018fzs)      | 1962-06-19 (xsd:date) |
| Jackie Battley (fb:m.0j1782w)    | 1962-06-19 (xsd:date) |
| Newt Gingrich (fb:m.018fzs)      | 1981-08-08 (xsd:date) |
| Marianne Ginther (fb:m.0661_f)   | 1981-08-08 (xsd:date) |

[Assistant]
The results show the following marriage dates:

- **Callista Gingrich**: August 18, 2000
- **Jackie Battley**: June 19, 1962
- **Marianne Ginther**: August 8, 1981

Since Callista Gingrich is the most recent marriage, she is Newt Gingrich's current wife.

Let's confirm this by returning the final SPARQL query and the answer.

[Tool] Stopped generation process