PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX fb: <http://rdf.freebase.com/ns/>
SELECT DISTINCT ?profession ?professionLabel WHERE {
  fb:m.087k1_ fb:people.person.profession ?profession .
  OPTIONAL {
    ?profession rdfs:label ?professionLabel .
    FILTER ( lang( ?professionLabel ) = 'en' )
  }
}

Got 1 row and 2 columns:
| profession           | professionLabel |
| -------------------- | --------------- |
| Actor (fb:m.02hrh1q) | Actor (en)      |

Helen Flanagan is known as an actress and model. According to the Freebase knowledge graph, her profession is listed as Actor, and the description also mentions that she is a model.

[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., has type Physician

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

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, Anna-Lou Leibovitz, Annie Leibowitz (fb:m.015m2c): Anna-Lou "Annie" Leibovitz is an American portrait photographer., has type Visual Artist

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

[Assistant]
From the similar examples, it seems that the property "fb:people.person.profession" is used to describe what a person does (their profession).

Next, I will search for the entity "Helen Flanagan" in the Freebase knowledge graph to find the corresponding entity identifier.

[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., has type TV Actor
2. Helen Flanagan (fb:m.0_z3nl7): Helen Flanagan is a cinematographer., has type Film cinematographer
3. Helen Flanagan (fb:m.0ygdbgn): Helen Flanagan is a fictional character from the 2011 film Butter., has type Film character
4. Helen Flanagan Pictures (fb:m.0c1_pkz)
5. 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., has type TV Episode
6. 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., has type TV Episode
7. Helen, also known as H-Bomb, Queen of the Nautch Girls, Miss Helen, 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., has type 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", has type Football player
9. Helen, also known as White County / Helen city, Helen, Georgia (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., has type 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., has type City/Town/Village

[Assistant]
I found multiple entities named "Helen Flanagan." The most relevant one appears to be fb:m.087k1_ which is described as Helen Joyce Gabriel Flanagan, an English actress, model, and TV actor. This seems to be the person the question is about.

Next, I will check the properties of this entity to find the property that describes what she does (likely profession or occupation).

[Tool]
Top 10 property alternatives:
1. Profession (fb:people.person.profession): links to type Profession, part of Person schema
2. Country of nationality (fb:people.person.nationality): part of Person schema, links to type Country
3. Place of birth (fb:people.person.place_of_birth): links to type Location, part of Person schema
4. Date of birth (fb:people.person.date_of_birth): links to type Date/Time, part of Person schema
5. Type (fb:type.object.type): part of Object schema, links to type Type
6. Name (fb:type.object.name): part of Object schema, links to type Text
7. Gender (fb:people.person.gender): part of Person schema, links to type Gender
8. Key (fb:type.object.key): part of Object schema, links to type Key
9. Notable types (fb:common.topic.notable_types): part of Topic schema, links to type Type
10. Also known as (fb:common.topic.alias): part of Topic schema, links to type Text

No other items found

[Assistant]
The property "fb:people.person.profession" is the appropriate property to use to find out what Helen Flanagan does.

I will now write a SPARQL query to get the professions of Helen Flanagan (fb:m.087k1_).

[Tool]
Got 1 row and 2 columns:
| profession           | professionLabel |
| -------------------- | --------------- |
| Actor (fb:m.02hrh1q) | Actor (en)      |

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The answer 'Actor' is correct but incomplete. Helen Flanagan is known to have multiple professions including actress and model. The SPARQL query should be refined to retrieve all professions associated with Helen Flanagan, not just one. This can be done by ensuring the query returns all distinct professions without limiting the result to a single one. Additionally, the answer should mention all relevant professions found, such as actress and model, to provide a more comprehensive response.

[Assistant] Thank you for the feedback. I will refine the SPARQL query to ensure it retrieves all distinct professions associated with Helen Flanagan and provide a comprehensive answer mentioning all relevant professions.

[Tool]
Got 1 row and 2 columns:
| profession           | professionLabel |
| -------------------- | --------------- |
| Actor (fb:m.02hrh1q) | Actor (en)      |

[Tool]
Got 1 row and 3 columns:
| subject                      | property                                 | object               |
| ---------------------------- | ---------------------------------------- | -------------------- |
| Helen Flanagan (fb:m.087k1_) | Profession (fb:people.person.profession) | Actor (fb:m.02hrh1q) |

[Tool]
Top 10 property alternatives:
1. Profession (fb:people.person.profession): links to type Profession, part of Person schema
2. Country of nationality (fb:people.person.nationality): part of Person schema, links to type Country
3. Place of birth (fb:people.person.place_of_birth): links to type Location, part of Person schema
4. Date of birth (fb:people.person.date_of_birth): links to type Date/Time, part of Person schema
5. Gender (fb:people.person.gender): part of Person schema, links to type Gender
6. Ethnicity (fb:people.person.ethnicity): links to type Ethnicity, part of Person schema
7. Type (fb:type.object.type): part of Object schema, links to type Type
8. Name (fb:type.object.name): part of Object schema, links to type Text
9. Key (fb:type.object.key): part of Object schema, links to type Key
10. Daylife Topic (fb:common.identity.daylife_topic): links to type Enumeration, part of Identity schema

No other items found

[Tool]
Top 10 property alternatives:
1. Model (fb:base.motorcycle.motorcycle_video.model): part of Motorcycle video schema, links to type Motorcycle model
2. Model (fb:base.motorcycle.motorcycle_generation.model): part of Motorcycle generation schema, links to type Motorcycle model
3. Model (fb:base.sharing.sharing_system.model): part of Sharing system schema, links to type Sharing model
4. Model (fb:user.kebert.default_domain.cell_phones.model): part of Cell Phones schema, links to type Topic
5. Model (fb:base.motorcycle.privately_owned_motorcycle.original_model): part of Privately owned motorcycle schema, links to type Motorcycle model
6. Model (fb:base.cgcollection.computer_game_platform_release.model): part of Computer Game Platform Release schema, links to type Computer Game Platform Model
7. Model (fb:base.engineering1.rfid_tag_device.model): part of RFID Tag Device schema, links to type Text
8. Model (fb:user.daepark.default_domain.golf_club.model): part of Golf Club schema, links to type Text
9. Model (fb:base.cimis.procedure.model): part of Procedure schema, links to type Text
10. Model (fb:automotive.model_year.model): part of Automobile Model Year schema, links to type Automobile Model

[Tool]
Top 10 property alternatives:
1. Occupation (fb:fictional_universe.fictional_character.occupation): part of Fictional Character schema, links to type Character Occupation
2. Profession (fb:user.osprey.default_domain.occupation.profession): part of Occupation schema, links to type Profession
3. Profession (fb:user.thadguidry.default_domain.hand_tool.profession): part of Hand Tool schema, links to type Profession
4. profession (fb:base.sportbase.club_owner.profession): part of Sport Club Owner schema, links to type Text
5. Profession (fb:people.person.profession): links to type Profession, part of Person schema
6. Professions (fb:user.narphorium.default_domain.job_title.professions): links to type Profession, part of Job Title schema
7. Professions (fb:base.warofdragons.player.professions): links to type Profession Ranking, part of Player schema
8. Area of profession (fb:base.morstministryofresearchscienceandtechnology.morst_author.area_of_profession): part of MoRST Author schema, links to type Text
9. Job (fb:user.tpshek.default_domain.employee.job): part of Employee schema, links to type Job
10. Employed by (fb:base.represent.agent.employed_by): links to type Agent-agency relationship, part of Agent schema

[Assistant]
The property "fb:people.person.profession" is the only relevant property for profession/occupation for Helen Flanagan in Freebase. The current data only shows "Actor" as her profession. There is no additional profession such as "model" listed in the knowledge graph for this entity.

I will finalize the answer stating that according to the Freebase knowledge graph, Helen Flanagan's profession is Actor. If there are other professions like model, they are not listed in this knowledge graph.

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The SPARQL query correctly retrieves Helen Flanagan's profession from Freebase, returning 'Actor' as her profession. However, the answer is incomplete because Helen Flanagan is also known as a model, which is not reflected in the query results. To improve, the query should be refined or expanded to capture all professions associated with Helen Flanagan, potentially by checking for additional profession entries or related properties. This will provide a more comprehensive answer to the user's question about what Helen Flanagan does.

[Assistant] I understand the feedback that Helen Flanagan is known to have multiple professions including actress and model, but the Freebase knowledge graph currently only lists "Actor" as her profession. To address this, I will try to find if there are any other properties or related entities that might indicate her other professions such as "model." I will search for all properties of Helen Flanagan to see if there is any other relevant information that can help capture her multiple professions.

[Tool]
Got 134 rows and 3 columns, showing the first 10 rows below:
| subject                      | property                                                            | object                                                                   |
| ---------------------------- | ------------------------------------------------------------------- | ------------------------------------------------------------------------ |
| Helen Flanagan (fb:m.087k1_) | Type (fb:type.object.type)                                          | Topic (fb:common.topic)                                                  |
| Helen Flanagan (fb:m.087k1_) | Key (fb:type.object.key)                                            | /authority/daylife/topic/0gSP1AG1Cjeuq                                   |
| Helen Flanagan (fb:m.087k1_) | Name (fb:type.object.name)                                          | Helen Flanagan (en)                                                      |
| Helen Flanagan (fb:m.087k1_) | Topic equivalent webpage (fb:common.topic.topic_equivalent_webpage) | <http://ar.wikipedia.org/wiki/%47%4A%44%4A%46_%41%44%27%46%27%3A%27%46>  |
| Helen Flanagan (fb:m.087k1_) | Notable for (fb:common.topic.notable_for)                           | fb:g.125bd4dls                                                           |
| Helen Flanagan (fb:m.087k1_) | Notable types (fb:common.topic.notable_types)                       | TV Actor (fb:m.01xrzlq)                                                  |
| Helen Flanagan (fb:m.087k1_) | Description (fb:common.topic.description)                           | Helen Joyce Flanagan es una actr...ie Webster en Coronation Street. (es) |
| Helen Flanagan (fb:m.087k1_) | Article (fb:common.topic.article)                                   | fb:m.087k24                                                              |
| Helen Flanagan (fb:m.087k1_) | Also known as (fb:common.topic.alias)                               | Helen Daniella Flanagan (en)                                             |
| Helen Flanagan (fb:m.087k1_) | Gender (fb:people.person.gender)                                    | Female (fb:m.02zsn)                                                      |
| ...                          | ...                                                                 | ...                                                                      |

[Assistant] I found many properties for Helen Flanagan (fb:m.087k1_). Among them, "fb:common.topic.notable_types" has the value "TV Actor" which is related to her profession. I will check if there are other notable types or related properties that might indicate her other professions such as model.

[Tool]
Got 1 row and 3 columns:
| subject                      | property                                      | object                  |
| ---------------------------- | --------------------------------------------- | ----------------------- |
| Helen Flanagan (fb:m.087k1_) | Notable types (fb:common.topic.notable_types) | TV Actor (fb:m.01xrzlq) |

[Assistant] The property "fb:common.topic.notable_types" for Helen Flanagan only lists "TV Actor" as a notable type. I will now check the description property "fb:common.topic.description" to see if it contains any text mentioning other professions such as model.

[Tool]
Got 7 rows and 3 columns:
| subject                      | property                                  | object                                                                   |
| ---------------------------- | ----------------------------------------- | ------------------------------------------------------------------------ |
| Helen Flanagan (fb:m.087k1_) | Description (fb:common.topic.description) | Helen Joyce Flanagan es una actr...ie Webster en Coronation Street. (es) |
| Helen Flanagan (fb:m.087k1_) | Description (fb:common.topic.description) | Helen Joyce Gabriel Flanagan ada...ronation Street selama 12 tahun. (id) |
| Helen Flanagan (fb:m.087k1_) | Description (fb:common.topic.description) | Helen Joyce Gabriel Flanagan è u...lle100 donne più sexy del mondo. (it) |
| Helen Flanagan (fb:m.087k1_) | Description (fb:common.topic.description) | Helen Joyce Gabriel Flanagan is ...Sexiest Women in the World poll. (en) |
| Helen Flanagan (fb:m.087k1_) | Description (fb:common.topic.description) | هيلين جويس غابرييل فلاناغان Hele...م في مجلة إف إتش إم في سنة 2013. (ar) |
| Helen Flanagan (fb:m.087k1_) | Description (fb:common.topic.description) | هيلين فلاناغان هي ممثلة وعارضة أزياء إنجليزية (ar)                       |
| Helen Flanagan (fb:m.087k1_) | Description (fb:common.topic.description) | 헬렌 플래너건은 잉글랜드의 배우, 모델, 사회자이다. (ko)                                       |

[Assistant]
The English description (fb:common.topic.description) for Helen Flanagan says: "Helen Joyce Gabriel Flanagan is an English actress, model, and TV actor..." This confirms that she is also known as a model.

I will now finalize the answer to mention both actress and model as her professions based on the description text.

[Tool] Stopped generation process


PREFIX fb: <http://rdf.freebase.com/ns/>
SELECT DISTINCT ?placeOfBirth ?placeLived WHERE {
  fb:m.0261x8t fb:people.person.place_of_birth ?placeOfBirth .
  OPTIONAL {
    fb:m.0261x8t fb:people.person.places_lived ?placeLivedNode .
    ?placeLivedNode fb:people.place_lived.location ?placeLived .
  }
}

Got 2 rows and 2 columns:
| placeOfBirth               | placeLived                 |
| -------------------------- | -------------------------- |
| Los Angeles (fb:m.030qb3t) | Los Angeles (fb:m.030qb3t) |
| Los Angeles (fb:m.030qb3t) | Calabasas (fb:m.0kkph)     |

Kim Kardashian was born in Los Angeles. She has also lived in Los Angeles and Calabasas.

[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 Kim, Kim West, Kimmie, Kim Kardashian-West, Kimberly Noel "Kim" Kardashian (fb:m.0261x8t): Kimberly "Kim" Kardashian West is an American television and soc...y television personality, with estimated earnings of $6 million., has type Celebrity
Marriage, also known as Matrimony, Wedlock (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., has type Religious Practice

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

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, Robyn Fenty, RiRi, New Queen of Pop (fb:m.06mt91): Robyn Rihanna Fenty, known professionally as Rihanna, is a Barba...ammy Awards, winning Best Rap/Sung Collaboration for "Umbrella"., has type Musical Artist

Using properties:
Places lived (fb:people.person.places_lived): links to type Place lived, part of Person schema
Location (fb:people.place_lived.location): part of Place lived schema, links to type 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, Robyn Fenty, RiRi, New Queen of Pop (fb:m.06mt91): Robyn Rihanna Fenty, known professionally as Rihanna, is a Barba...ammy Awards, winning Best Rap/Sung Collaboration for "Umbrella"., has type Musical Artist

Using properties:
Place of birth (fb:people.person.place_of_birth): links to type Location, part of Person schema

[Assistant]
From the similar examples, we see two main ways to interpret "where did Kim Kardashian come from?":
1. Place of birth (fb:people.person.place_of_birth)
2. Places lived (fb:people.person.places_lived)

We should first identify the entity for Kim Kardashian in Freebase and then query for her place of birth and places lived. Let's start by searching for the entity "Kim Kardashian" in Freebase.

[Tool]
Top 10 entity alternatives:
1. Kim Kardashian, also known as Kim, Kim West, Kimmie, Kim Kardashian-West, Kimberly Noel "Kim" Kardashian (fb:m.0261x8t): Kimberly "Kim" Kardashian West is an American television and soc...y television personality, with estimated earnings of $6 million., has type 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., has type TV Episode
3. Kim Kardashian (fb:m.06xy8z0): John Caparulo, Jen Kirkman, Ross Mathews, has type TV Episode
4. Kim Kardashian (fb:m.0gg_zfd): has type TV Episode
5. Kim Kardashian (fb:m.0kc3ypk): has type TV Episode
6. Kim Kardashian (fb:m.0g05d33): has type TV Episode
7. Kim Kardashian (fb:m.06y25xd): has type TV Episode
8. Kim Kardashian (fb:m.0xtwmq5): has type Musical Recording
9. Kim Kardashian (fb:m.0tm0357): has type Musical Recording
10. Kim Kardashian (fb:m.0_hgg8w): has type TV Episode

[Assistant] The entity for Kim Kardashian as a celebrity is fb:m.0261x8t. Now, I will query for her place of birth and places lived. Let's start with the place of birth.

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

[Assistant] Kim Kardashian's place of birth is Los Angeles (fb:m.030qb3t). Now, let's also check the places she has lived.

[Tool]
Got 2 rows and 1 column:
| placeLived                 |
| -------------------------- |
| Los Angeles (fb:m.030qb3t) |
| Calabasas (fb:m.0kkph)     |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves Kim Kardashian's place of birth and places she has lived, which directly answers the question 'where did Kim Kardashian come from?'. The query uses appropriate properties and entities, and the results include Los Angeles as her birthplace and both Los Angeles and Calabasas as places she has lived. The answer is complete and accurate based on the data retrieved from the freebase knowledge graph. No further refinement is necessary.


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX fb: <http://rdf.freebase.com/ns/>
SELECT DISTINCT ?case ?caseLabel WHERE {
  fb:m.07sz1 fb:law.court.legal_cases ?case .
  OPTIONAL {
    ?case rdfs:label ?caseLabel .
    FILTER ( lang( ?caseLabel ) = 'en' )
  }
}
LIMIT 50

Got 50 rows and 2 columns, showing the first 5 and last 5 rows below:
| case                                                                                | caseLabel                                                                |
| ----------------------------------------------------------------------------------- | ------------------------------------------------------------------------ |
| 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)                                                 |
| ...                                                                                | ...                                                                      |
| NAACP v. Alabama (fb:m.016mxn)                                                      | NAACP v. Alabama (en)                                                    |
| Santa Clara County v. Southern Pacific Railroad Co. (fb:m.016mz5)                   | Santa Clara County v. Southern Pacific Railroad Co. (en)                 |
| Connecticut General Life Insurance Co. v. Johnson (fb:m.016n01)                     | Connecticut General Life Insurance Co. v. Johnson (en)                   |
| Wheeling Steel Corp. v. Glander (fb:m.016n0d)                                       | Wheeling Steel Corp. v. Glander (en)                                     |
| Regents of the University of California v. Bakke (fb:m.016pz5)                      | Regents of the University of California v. Bakke (en)                    |

The Supreme Court cases are legal cases linked to the Supreme Court of the United States (fb:m.07sz1) via the property fb:law.court.legal_cases. Here are some examples of Supreme Court cases with their labels: 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, NAACP v. Alabama, Santa Clara County v. Southern Pacific Railroad Co., Connecticut General Life Insurance Co. v. Johnson, Wheeling Steel Corp. v. Glander, and Regents of the University of California v. Bakke.

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

Using properties:
Judges (fb:law.court.judges): links to type Judicial tenure, part of Court schema
From date (fb:law.judicial_tenure.from_date): part of Judicial tenure schema, links to type Date/Time
Judge (fb:law.judicial_tenure.judge): part of Judicial tenure schema, links to type Judge
To date (fb:law.judicial_tenure.to_date): part of Judicial tenure schema, links to type 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 United States Supreme Court, U.S. Supreme Court, us supreme court, SCOTUS (fb:m.07sz1): The Supreme Court of the United States is the highest federal co...efs that track with those philosophical or political categories., has type Court

Using properties:
Jurisdiction (fb:law.court.jurisdiction): links to type Court jurisdiction area, part of Court schema

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

Using properties:
Offices/Positions Within the Body (fb:government.governmental_body.offices_positions): links to type Government Office or Title, part of Governmental Body schema

[Assistant]
The examples show that the Supreme Court of the United States is represented by the entity fb:m.07sz1 in Freebase. To find Supreme Court cases, we should look for properties related to cases or decisions linked to this court entity.

Next, I will search for properties of the Supreme Court entity (fb:m.07sz1) that might relate to cases or decisions. This will help identify the relevant property to retrieve Supreme Court cases.

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

No other items found

[Assistant]
The property "Legal cases" (fb:law.court.legal_cases) seems to be the most relevant property to retrieve Supreme Court cases linked to the Supreme Court entity (fb:m.07sz1).

I will now construct a SPARQL query to get the legal cases of the Supreme Court of the United States using this property. I will also try to get the labels of the cases for better readability.

[Tool]
Got 50 rows and 2 columns, showing the first 5 and last 5 rows below:
| case                                                                                | caseLabel                                                                |
| ----------------------------------------------------------------------------------- | ------------------------------------------------------------------------ |
| 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)                                                 |
| ...                                                                                | ...                                                                      |
| NAACP v. Alabama (fb:m.016mxn)                                                      | NAACP v. Alabama (en)                                                    |
| Santa Clara County v. Southern Pacific Railroad Co. (fb:m.016mz5)                   | Santa Clara County v. Southern Pacific Railroad Co. (en)                 |
| Connecticut General Life Insurance Co. v. Johnson (fb:m.016n01)                     | Connecticut General Life Insurance Co. v. Johnson (en)                   |
| Wheeling Steel Corp. v. Glander (fb:m.016n0d)                                       | Wheeling Steel Corp. v. Glander (en)                                     |
| Regents of the University of California v. Bakke (fb:m.016pz5)                      | Regents of the University of California v. Bakke (en)                    |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves legal cases linked to the Supreme Court of the United States using the property fb:law.court.legal_cases. It also optionally retrieves English labels for these cases, which is helpful for readability. The answer provides a clear explanation and examples of Supreme Court cases, matching the query results. The query respects the requirement to return identifiers and optionally labels, and the answer is complete and accurate. No further refinement is necessary.


PREFIX fb: <http://rdf.freebase.com/ns/>
SELECT DISTINCT ?spouseName WHERE {
  fb:m.018fzs fb:people.person.spouse_s ?marriage .
  ?marriage fb:people.marriage.spouse ?spouse .
  ?spouse fb:type.object.name ?spouseName .
  ?spouse fb:people.person.gender fb:m.02zsn .
  FILTER ( ?spouse != fb:m.018fzs )
}

Got 11 rows and 1 column, showing the first 5 and last 5 rows below:
| spouseName             |
| ---------------------- |
| Callista Gingrich (en) |
| Callista Gingrich (fr) |
| Callista Gingrich (it) |
| Callista Gingrich (pl) |
| Callista Gingrich (pt) |
| ...                    |
| Jackie Battley (it)    |
| Jackie Battley (pl)    |
| Marianne Ginther (en)  |
| Marianne Ginther (it)  |
| Marianne Ginther (pl)  |

Newt Gingrich's wives are Callista Gingrich, Marianne Ginther, and Jackie Battley.

[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 Newt, Rep. Newt Gingrich, Rep. Gingrich, Newton "Newt" Leroy Gingrich, Newton Leroy "Newt" 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., has type 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): part of Topic schema, links to type Type
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:
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 Matrimony, Wedlock (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., has type Religious Practice
Martin Luther King, Jr., also known as Michael King, MLK, M.L.K., Michael Luther King Jr., Michael King, Jr. (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., has type Author

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

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 Women, Woman, 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., has type Literature Subject
Abraham Lincoln, also known as The Sage of Springfield, The Great Emancipator, The Illinois Baboon, The Jester, The Martyr President (fb:m.0gzh): Abraham Lincoln /ˈeɪbrəhæm ˈlɪŋkən/ was the 16th President of th...ew Republican Party, which had a statewide majority in Illinois., has type US President

Using properties:
Spouse (fb:people.marriage.spouse): part of Marriage schema, links to type Person
Gender (fb:people.person.gender): part of Person schema, links to type Gender
Spouse (or domestic partner) (fb:people.person.spouse_s): links to type Marriage, part of Person schema

[Assistant]
From the similar examples, it appears that the property for spouse or wife in Freebase is fb:people.person.spouse_s which links to a marriage entity, and then from the marriage entity, the spouse can be found using fb:people.marriage.spouse. Also, the spouse's gender can be filtered to female using fb:people.person.gender.

Next, I will search for the entity Newt Gingrich in Freebase to get his identifier.

[Tool]
Top 10 entity alternatives:
1. Newt Gingrich, also known as Newt, Rep. Newt Gingrich, Rep. Gingrich, Newton "Newt" Leroy Gingrich, Newton Leroy "Newt" 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., has type 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"., has type TV Episode
3. Newt Gingrich (fb:m.05nfcb3): has type TV Episode
4. Newt Gingrich (fb:m.0dl0lms): Richard Shelby releases nominees, and Newt Gingrich discusses the radical Obama administration., has type TV Episode
5. Newt Gingrich (fb:m.06y3kvd): has type TV Episode
6. Newt Gingrich (fb:m.05nfprm): has type TV Episode
7. Newt Gingrich (fb:m.05nfcqx): has type TV Episode, Colin Quinn
8. Newt Gingrich, also known as Newt Gingrich, Jessalyn Gilsig (fb:m.0bmn7ll): has type TV Episode
9. Newt Gingrich (fb:m.0pwb1p): has type Musical Recording
10. 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., has type TV Episode

[Assistant]
The entity for Newt Gingrich as an American politician is fb:m.018fzs.

Next, I will search for the spouse property of Newt Gingrich to confirm the exact property to use.

[Tool]
Top 10 property alternatives:
1. Spouse (or domestic partner) (fb:people.person.spouse_s): links to type Marriage, part of Person schema
2. Profession (fb:people.person.profession): links to type Profession, part of Person schema
3. Country of nationality (fb:people.person.nationality): part of Person schema, links to type Country
4. Gender (fb:people.person.gender): part of Person schema, links to type Gender
5. Name (fb:type.object.name): part of Object schema, links to type Text
6. Date of birth (fb:people.person.date_of_birth): links to type Date/Time, part of Person schema
7. Key (fb:type.object.key): part of Object schema, links to type Key
8. Supported by (fb:base.propositions.proposition_issue.supported_by): part of Proposition Issue schema, links to type Proposition
9. Place of birth (fb:people.person.place_of_birth): links to type Location, part of Person schema
10. Parents (fb:people.person.parents): part of Person schema, links to type Person

No other items found

[Assistant]
The property for spouse or domestic partner of Newt Gingrich is fb:people.person.spouse_s.

Now I will write a SPARQL query to get the spouse of Newt Gingrich using this property and then get the spouse's name.

[Tool]
Got 10 rows and 2 columns:
| spouse                      | spouseName         |
| --------------------------- | ------------------ |
| Newt Gingrich (fb:m.018fzs) | Newt Gingrich (ca) |
| Newt Gingrich (fb:m.018fzs) | Newt Gingrich (cs) |
| Newt Gingrich (fb:m.018fzs) | Newt Gingrich (da) |
| Newt Gingrich (fb:m.018fzs) | Newt Gingrich (de) |
| Newt Gingrich (fb:m.018fzs) | Newt Gingrich (en) |
| Newt Gingrich (fb:m.018fzs) | Newt Gingrich (es) |
| Newt Gingrich (fb:m.018fzs) | Newt Gingrich (et) |
| Newt Gingrich (fb:m.018fzs) | Newt Gingrich (fi) |
| Newt Gingrich (fb:m.018fzs) | Newt Gingrich (fr) |
| Newt Gingrich (fb:m.018fzs) | Newt Gingrich (it) |

[Assistant]
The query returned Newt Gingrich himself as the spouse, which is not correct. I need to add a filter to exclude Newt Gingrich from the spouse results and also filter for female gender to get his wife's name.

I will update the query accordingly.

[Tool]
Got 10 rows and 2 columns:
| spouse                           | spouseName             |
| -------------------------------- | ---------------------- |
| Callista Gingrich (fb:m.05znhhq) | Callista Gingrich (en) |
| Callista Gingrich (fb:m.05znhhq) | Callista Gingrich (fr) |
| Callista Gingrich (fb:m.05znhhq) | Callista Gingrich (it) |
| Callista Gingrich (fb:m.05znhhq) | Callista Gingrich (pl) |
| Callista Gingrich (fb:m.05znhhq) | Callista Gingrich (pt) |
| Marianne Ginther (fb:m.0661_f)   | Marianne Ginther (en)  |
| Marianne Ginther (fb:m.0661_f)   | Marianne Ginther (it)  |
| Marianne Ginther (fb:m.0661_f)   | Marianne Ginther (pl)  |
| Jackie Battley (fb:m.0j1782w)    | Jackie Battley (en)    |
| Jackie Battley (fb:m.0j1782w)    | Jackie Battley (it)    |

[Assistant]
Newt Gingrich has multiple spouses listed: Callista Gingrich, Marianne Ginther, and Jackie Battley.

I will provide the names of his wives as the answer.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the names of Newt Gingrich's wives by querying the spouse relationships and filtering for female spouses. The answer lists the three wives found in the query results, which matches the execution result. The query respects the requirement to return identifiers and labels, and the answer is complete and accurate. No further refinement is necessary.


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX fb: <http://rdf.freebase.com/ns/>
SELECT DISTINCT ?actor ?actorLabel WHERE {
  fb:m.02rrfzf fb:film.film.starring ?performance .
  ?performance fb:film.performance.actor ?actor .
  ?performance fb:film.performance.character fb:m.02ql50 .
  OPTIONAL {
    ?actor rdfs:label ?actorLabel FILTER ( lang( ?actorLabel ) = 'en' )
  }
}

Got 2 rows and 2 columns:
| actor                       | actorLabel        |
| --------------------------- | ----------------- |
| Alexa Vega (fb:m.02z7h0)    | Alexa Vega (en)   |
| Addisyn Fair (fb:m.0zfn9cs) | Addisyn Fair (en) |

The actors who played Carmen Cortez in the film Spy Kids are Alexa Vega and Addisyn Fair. Alexa Vega played the main role of Carmen Cortez, and Addisyn Fair played the younger version of Carmen Cortez.

[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 played carmen cortez in spy kids?

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

[Tool]
Example 1:
Question:
who played juni in spy kids 4?

SPARQL:
SELECT DISTINCT ?x WHERE {
  FILTER ( ?x != fb:m.0ds67cb ) FILTER ( ! isLiteral( ?x ) || lang( ?x ) = '' || langMatches( lang( ?x ) , 'en' ) ) fb:m.0ds67cb fb:film.film.starring ?y .
  ?y fb:film.performance.actor ?x .
  ?y fb:film.performance.character fb:m.02ql73 .
}

Using entities:
Juni Cortez (fb:m.02ql73): Junito Rocket Racer Rebel "Juni" Cortez is a fictional character... back in the organization so they could recover the Transmooker., has type Film character
Spy Kids: All the Time in the World, also known as Spy Kids 4: Armageddon, Spy Kids 4D, Spy Kids: All the Time in the World in 4D (fb:m.0ds67cb): Spy Kids: All the Time in the World is a 2011 Latino-American 4D...without the distribution of Walt Disney Studios Motion Pictures., has type Film

Using properties:
Performances (fb:film.film.starring): links to type Film performance, part of Film schema
Actor (fb:film.performance.actor): part of Film performance schema, links to type Film actor
Character (fb:film.performance.character): part of Film performance schema, links to type Film character

Example 2:
Question:
who plays sarah wittle in jumanji?

SPARQL:
SELECT DISTINCT ?x WHERE {
  FILTER ( ?x != fb:m.09w353 ) FILTER ( ! isLiteral( ?x ) || lang( ?x ) = '' || langMatches( lang( ?x ) , 'en' ) ) fb:m.09w353 fb:film.film.starring ?y .
  ?y fb:film.performance.actor ?x .
  ?y fb:film.performance.character fb:m.0b3x5zt .
}

Using entities:
Jumanji (fb:m.09w353): Jumanji is a 1995 American fantasy adventure film, directed by J...r, British Columbia. The film was released on December 15, 1995., has type Film
Sarah Whittle (fb:m.0b3x5zt): Sarah Whittle is a fictional character from the 1995 film Jumanji., has type Film character

Using properties:
Performances (fb:film.film.starring): links to type Film performance, part of Film schema
Actor (fb:film.performance.actor): part of Film performance schema, links to type Film actor
Character (fb:film.performance.character): part of Film performance schema, links to type Film character

Example 3:
Question:
where did carmen electra grow up?

SPARQL:
SELECT DISTINCT ?x WHERE {
  FILTER ( ?x != fb:m.01lbp ) FILTER ( ! isLiteral( ?x ) || lang( ?x ) = '' || langMatches( lang( ?x ) , 'en' ) ) fb:m.01lbp fb:people.person.place_of_birth ?x .
}

Using entities:
Carmen Electra, also known as Carmen Elektra, Tara Leigh Patrick (fb:m.01lbp): Tara Leigh Patrick, better known by her stage name Carmen Electr..., and Disaster Movie. She hosted MTV Spring Break for some time., has type Celebrity

Using properties:
Place of birth (fb:people.person.place_of_birth): links to type Location, part of Person schema

[Assistant]
From the examples, it is clear that the query pattern to find the actor who played a character in a film involves:
- Identifying the film entity
- Identifying the character entity
- Using the property fb:film.film.starring to get performances in the film
- Using the properties fb:film.performance.actor and fb:film.performance.character to link the actor and character in the performance

Next, I will search for the entity "Carmen Cortez" to find the character entity.

[Tool]
Top 10 entity alternatives:
1. Baby Carmen, also known as Carmen Cortez (fb:m.02ql50): Carmen Elizabeth Juanita Costa Brava Cortez is a fictional chara...had kept that knowledge to himself on her mother's instructions., has type Film character
2. Carmen (fb:m.09g6g): Carmen is an opera in four acts by the French composer Georges B... were critical, and the French public was generally indifferent., has type Opera
3. Cortez, also known as Montezuma County / Cortez city, Cortez, Colorado (fb:m.0rc25): The City of Cortez is a Home Rule Municipality that is the count... The city population was 8,482 at the 2010 United States Census., has type City/Town/Village
4. Carmen Ejogo, also known as Carmen, Carmen Elizabeth Ejogo (fb:m.07fnrq): Carmen Elizabeth Ejogo is a British actress and singer. She bega...e met with King and was given King's blessing for her portrayal., has type Film actor
5. Carmen, also known as Bizet's Carmen (fb:m.08tbx6): Carmen is a film directed by Francesco Rosi. It is a film versio...ngs, and shot scenes in some of the exact places that Doré drew., has type Award-Winning Work
6. Carmen, also known as Carlos Saura Dance Trilogy, Part 1: Carmen (fb:m.02pwmj7): Carmen is a 1983 Spanish film adaptation of the novel Carmen by ...sonal lives Bizet's tragic love affair, up to its lethal climax., has type Award-Winning Work
7. Carmen, also known as Alfalfa County / Carmen town, Carmen, Oklahoma (fb:m.0z3_c): Carmen is a town in Alfalfa County, Oklahoma, United States. The population was 355 at the 2010 census., has type City/Town/Village
8. Risë Stevens, also known as Rise Stevens, Risë Steenberg, Risë Gus Steenberg, Carmen (fb:m.0953c4): Risë Stevens was an American operatic mezzo-soprano., has type Musical Artist
9. Carmen, also known as Carmen (London Symphony Orchestra feat. conductor: Claudio Abbado) (fb:m.03_dwxc): has type Consumer product
10. Carmen, also known as Carmen - Cyc - (fb:m.067_f8b): Carmen is a novella by Prosper Mérimée, written and first publis... of dramatic works, including the famous opera by Georges Bizet., has type Book

[Assistant] The entity "Carmen Cortez" as a film character is identified as fb:m.02ql50. Now I will search for the film "Spy Kids" to find the film entity.

[Tool]
Top 10 entity alternatives:
1. Spy Kids (fb:m.02rrfzf): Spy Kids is a 2001 American science fantasy family adventure fil...me a commercial success by grossing over $147 million worldwide., has type Award-Winning Work
2. Spy Kids (fb:m.01bn5b): The Spy Kids series consists of four American/Spanish family act...ong Hispanic heritage theme, as Rodriguez is of Mexican descent., has type Film series
3. Spy Kids (fb:m.030b0nq): has type Musical Release
4. Spy Kids, also known as Spy Kids Soundtrack (fb:m.01fq2m3): has type Soundtrack
5. Spy Kids (fb:m.07kxdbt): has type TV Episode
6. Spy Kids (fb:m.0h0s_m7): has type Fictional Character
7. Spy Kids (fb:m.08vs6c3)
8. Spy Kids (fb:m.08w6pz1)
9. Spy Kids (fb:m.08wbq60)
10. SPY KIDS (fb:m.08w7t7r)

[Assistant] The film "Spy Kids" is identified as fb:m.02rrfzf. Now I will construct a SPARQL query to find the actor who played the character Carmen Cortez (fb:m.02ql50) in the film Spy Kids (fb:m.02rrfzf).

[Tool]
Got 2 rows and 2 columns:
| actor                       | actorLabel        |
| --------------------------- | ----------------- |
| Alexa Vega (fb:m.02z7h0)    | Alexa Vega (en)   |
| Addisyn Fair (fb:m.0zfn9cs) | Addisyn Fair (en) |

[Assistant]
The actors who played Carmen Cortez in the film Spy Kids are Alexa Vega and Addisyn Fair. Alexa Vega played the main role of Carmen Cortez, and Addisyn Fair played the younger version of Carmen Cortez.

I will now provide the final answer.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the actors who played the character Carmen Cortez in the film Spy Kids. It uses the appropriate entities and properties to link the film, the character, and the actors. The result includes both Alexa Vega and Addisyn Fair, which matches the human-readable answer provided. The query also optionally retrieves English labels for the actors, which is helpful. The answer is complete and accurate based on the knowledge graph data. No further refinement is necessary.


PREFIX fb: <http://rdf.freebase.com/ns/>
SELECT DISTINCT ?formOfGovernment WHERE {
  fb:m.09c7w0 fb:location.country.form_of_government ?formOfGovernment .
}

Got 3 rows and 1 column:
| formOfGovernment                      |
| ------------------------------------- |
| Presidential system (fb:m.01d9r3)     |
| Constitutional republic (fb:m.0c9rw5) |
| Federal republic (fb:m.0j729)         |

The United States has a form of government that is described as a Presidential system, a Constitutional republic, and a Federal republic.

[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 type of democracy is the united states?

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

[Tool]
Example 1:
Question:
what type of government is the us government?

SPARQL:
SELECT DISTINCT ?x WHERE {
  FILTER ( ?x != fb:m.09c7w0 ) FILTER ( ! isLiteral( ?x ) || lang( ?x ) = '' || langMatches( lang( ?x ) , 'en' ) ) fb:m.09c7w0 fb:location.country.form_of_government ?x .
}

Using entities:
United States of America, also known as U.S. of A., USA, U.S.A., US, U.S. (fb:m.09c7w0): The United States of America, commonly referred to as the United...s emerged from 13 British colonies located along the East Coast., has type Country

Using properties:
Form of Government (fb:location.country.form_of_government): links to type Form of Government, part of Country schema

Example 2:
Question:
what kind government does the us have?

SPARQL:
SELECT DISTINCT ?x WHERE {
  FILTER ( ?x != fb:m.09c7w0 ) FILTER ( ! isLiteral( ?x ) || lang( ?x ) = '' || langMatches( lang( ?x ) , 'en' ) ) fb:m.09c7w0 fb:location.country.form_of_government ?x .
}

Using entities:
United States of America, also known as U.S. of A., USA, U.S.A., US, U.S. (fb:m.09c7w0): The United States of America, commonly referred to as the United...s emerged from 13 British colonies located along the East Coast., has type Country

Using properties:
Form of Government (fb:location.country.form_of_government): links to type Form of Government, part of Country schema

Example 3:
Question:
what kind of system of government does the united states have?

SPARQL:
SELECT DISTINCT ?x WHERE {
  FILTER ( ?x != fb:m.09c7w0 ) FILTER ( ! isLiteral( ?x ) || lang( ?x ) = '' || langMatches( lang( ?x ) , 'en' ) ) fb:m.09c7w0 fb:location.country.form_of_government ?x .
}

Using entities:
United States of America, also known as U.S. of A., USA, U.S.A., US, U.S. (fb:m.09c7w0): The United States of America, commonly referred to as the United...s emerged from 13 British colonies located along the East Coast., has type Country

Using properties:
Form of Government (fb:location.country.form_of_government): links to type Form of Government, part of Country schema

[Assistant]
From the similar examples, it is clear that the property "fb:location.country.form_of_government" is used to find the type of government or democracy of a country. The entity for the United States is "fb:m.09c7w0".

I will now write a SPARQL query to get the form of government of the United States using this property.

[Tool]
Got 3 rows and 1 column:
| formOfGovernment                      |
| ------------------------------------- |
| Presidential system (fb:m.01d9r3)     |
| Constitutional republic (fb:m.0c9rw5) |
| Federal republic (fb:m.0j729)         |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the types of government associated with the United States from the knowledge graph. The answer accurately reflects the query results, listing the United States as having a Presidential system, a Constitutional republic, and a Federal republic. This is a complete and correct response to the user's question about the type of democracy in the United States.


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX fb: <http://rdf.freebase.com/ns/>
SELECT DISTINCT ?institution ?institutionLabel ?degree ?degreeLabel WHERE {
  fb:m.025s5v9 fb:people.person.education ?education .
  ?education fb:education.education.institution ?institution .
  OPTIONAL {
    ?education fb:education.education.degree ?degree .
    ?degree rdfs:label ?degreeLabel
    FILTER ( lang( ?degreeLabel ) = "en" )
  }
  OPTIONAL {
    ?institution rdfs:label ?institutionLabel FILTER ( lang( ?institutionLabel ) = "en" )
  }
}

Got 3 rows and 4 columns:
| institution                                        | institutionLabel                         | degree                         | degreeLabel           |
| -------------------------------------------------- | ---------------------------------------- | ------------------------------ | --------------------- |
| Harvard Law School (fb:m.014zws)                   | Harvard Law School (en)                  | Juris Doctor (fb:m.013zdg)     | Juris Doctor (en)     |
| Princeton University (fb:m.05zl0)                  | Princeton University (en)                | Bachelor of Arts (fb:m.014mlp) | Bachelor of Arts (en) |
| Whitney M. Young Magnet High School (fb:m.09rs7mx) | Whitney M. Young Magnet High School (en) |                                |                       |

Michelle Obama graduated from Princeton University with a Bachelor of Arts degree and from Harvard Law School with a Juris Doctor degree. She also attended Whitney M. Young Magnet High School, which is a 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 michelle obama graduated from?

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

[Tool]
Example 1:
Question:
which college did obama graduated?

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 .
  ?y fb:education.education.degree fb:m.014mlp .
}

Using entities:
Bachelor of Arts, also known as BA (Hons), Bachelor, BA, Artium Baccalaureus, AB (fb:m.014mlp): A Bachelor of Arts, from the Latin artium baccalaureus or baccal...l institutions set the preferred abbreviation for their degrees., has type Degree
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:
Degree (fb:education.education.degree): part of Education schema, links to type Degree
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 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 3:
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

[Assistant]
From the similar examples, we see that the property fb:people.person.education links a person to their education records, and the property fb:education.education.institution links an education record to the educational institution. We need to find the entity for Michelle Obama and then query for the institutions she graduated from.

Step 1: Search for the entity "Michelle Obama" in the freebase knowledge graph.

[Tool]
Top 10 entity alternatives:
1. Michelle Obama, also known as Renaissance, The Closer, Mooch, Michelle Robinson Obama, Michelle Robinson (fb:m.025s5v9): Michelle LaVaughn Robinson Obama is an American lawyer and write...y awareness, nutrition, physical activity, and healthful eating., has type Celebrity
2. Michelle Obama (fb:m.05ng7x9): has type TV Episode
3. Michelle Obama (fb:m.0jtjc1l): Troops and their families face unique economic challenges, Steph...pundit, and Michelle Obama voices support for military families., has type TV Episode
4. Michelle Obama (fb:m.0kb0lr_): Jon recalls a conversation with Roger Ailes, examines the good a..., and talks to Michelle Obama about the importance of gardening., has type TV Episode
5. Michelle Obama, also known as First Lady Michelle Obama (fb:m.0lcl317): Oprah and the staff welcome first lady Michelle Obama. Then, Harpo takes on a challenge to go vegan for one week., has type TV Episode
6. Michelle Obama (fb:m.0j9tzr1): has type TV Episode
7. Michelle Obama (fb:m.0gyxqp0): Michelle Obama is a fictional character in the computer animated comedy TV series The Simpsons., has type Film character
8. Michelle Obama (fb:m.05ld044)
9. Michelle Obama (fb:m.03s87_g)
10. Michelle Obama, Brandy (fb:m.0w8brbs): has type TV Episode

[Assistant] The entity for Michelle Obama as a person is fb:m.025s5v9. Now, I will query for the educational institutions she graduated from using the properties fb:people.person.education and fb:education.education.institution.

[Tool]
Got 3 rows and 2 columns:
| institution                                        | institutionLabel                         |
| -------------------------------------------------- | ---------------------------------------- |
| Harvard Law School (fb:m.014zws)                   | Harvard Law School (en)                  |
| Princeton University (fb:m.05zl0)                  | Princeton University (en)                |
| Whitney M. Young Magnet High School (fb:m.09rs7mx) | Whitney M. Young Magnet High School (en) |

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The SPARQL query correctly retrieves the educational institutions Michelle Obama graduated from, returning their identifiers and English labels. However, the answer includes Princeton University, which is incorrect as Michelle Obama attended Princeton University for her undergraduate studies, but she did not graduate from Harvard Law School and Princeton University simultaneously; she graduated from Princeton University and then Harvard Law School. The query does not distinguish the level or type of degree obtained or the order of attendance. To improve accuracy, the query could be refined to include the degree or graduation year if available, to better reflect the educational timeline. Also, Whitney M. Young Magnet High School is a high school, which is typically not considered a graduation institution in the same sense as universities. The answer should clarify this distinction or focus on higher education institutions if the user expects that. Overall, the query is good but the answer could be more precise and nuanced regarding the educational background of Michelle Obama.

[Assistant] Thank you for the feedback. To improve the accuracy and nuance of the answer, I will refine the query to include the degree or type of education Michelle Obama received at each institution, and also distinguish between high school and higher education institutions. This will help clarify the educational timeline and the nature of each institution. I will query for the degree or education type along with the institution.

[Tool]
Got 3 rows and 4 columns:
| institution                                        | institutionLabel                         | degree                         | degreeLabel           |
| -------------------------------------------------- | ---------------------------------------- | ------------------------------ | --------------------- |
| Harvard Law School (fb:m.014zws)                   | Harvard Law School (en)                  | Juris Doctor (fb:m.013zdg)     | Juris Doctor (en)     |
| Princeton University (fb:m.05zl0)                  | Princeton University (en)                | Bachelor of Arts (fb:m.014mlp) | Bachelor of Arts (en) |
| Whitney M. Young Magnet High School (fb:m.09rs7mx) | Whitney M. Young Magnet High School (en) |                                |                       |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves Michelle Obama's educational institutions and degrees, including Princeton University and Harvard Law School, which matches the provided answer. The query also optionally retrieves labels for institutions and degrees in English, which is appropriate. The inclusion of Whitney M. Young Magnet High School is also accurate as part of her education history. The answer is complete and correctly reflects the query results. No further refinement is necessary.