PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX fb: <http://rdf.freebase.com/ns/>
SELECT DISTINCT ?state ?stateLabel WHERE {
  fb:m.018qjq fb:geography.river.cities ?city .
  ?city fb:location.location.containedby ?state .
  ?state fb:type.object.type fb:location.administrative_division .
  FILTER NOT EXISTS {
    ?state fb:type.object.type fb:location.country
  }
  ?state rdfs:label ?stateLabel .
  FILTER ( lang( ?stateLabel ) = 'en' ) FILTER ( ! CONTAINS( ?stateLabel , "County" ) ) FILTER ( ! CONTAINS( ?stateLabel , "Municipality" ) )
}

Got 5 rows and 2 columns:
| state                         | stateLabel           |
| ----------------------------- | -------------------- |
| Baja California (fb:m.01ccgq) | Baja California (en) |
| California (fb:m.01n7q)       | California (en)      |
| Nevada (fb:m.059_c)           | Nevada (en)          |
| Sonora (fb:m.0ldff)           | Sonora (en)          |
| Arizona (fb:m.0vmt)           | Arizona (en)         |

The Colorado River runs through the states Baja California and Sonora in Mexico, and California, Nevada, and Arizona in the United States.

[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] which states does the colorado river run through?

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

[Tool]
Example 1:
Question:
what countries in the world speak arabic?

SPARQL:
SELECT DISTINCT ?x WHERE {
  FILTER ( ?x != fb:m.0jzc ) FILTER ( ! isLiteral( ?x ) || lang( ?x ) = '' || langMatches( lang( ?x ) , 'en' ) ) fb:m.0jzc fb:language.human_language.countries_spoken_in ?x .
}

Using entities:
Arabic Language, also known as اللغة العربية, عربي, /m/0jzc, Arabic (fb:m.0jzc): Arabic /ˈærəbɪk/ is the Classical Arabic language of the 6th cen...her as a single language for political and/or religious reasons., has type Human Language

Using properties:
Spoken in countries (fb:language.human_language.countries_spoken_in): part of Human Language schema, links to type Country

Example 2:
Question:
what did fred goodwin do?

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

Using entities:
Fred Goodwin (fb:m.05cfvw): Frederick Anderson "Fred" Goodwin, FRSE FCIBS is a Scottish char...2004 for "services to banking", was annulled on 1 February 2012., has type Person

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

Example 3:
Question:
who started southwest airlines?

SPARQL:
SELECT DISTINCT ?x WHERE {
  FILTER ( ?x != fb:m.0gztl ) FILTER ( ! isLiteral( ?x ) || lang( ?x ) = '' || langMatches( lang( ?x ) , 'en' ) ) fb:m.0gztl fb:organization.organization.founders ?x .
}

Using entities:
Southwest Airlines, also known as Southwest (fb:m.0gztl): Southwest Airlines Co. is a major U.S. airline and the world's l...de with over 650 in service, each averaging six flights per day., has type Airline

Using properties:
Founders (fb:organization.organization.founders): links to type Organization founder, part of Organization schema

[Assistant]
From the examples, I see that the approach is to first find the entity for the subject (in this case "Colorado River") and then find the property that links it to the states it runs through.

Step 1: Search for the entity "Colorado River" in the freebase knowledge graph.

[Tool]
Top 10 entity alternatives:
1. Colorado River (fb:m.018qjq): The Colorado River is one of the principal rivers of the Southwe... almost 40 million people both inside and outside the watershed., has type River
2. Colorado River (fb:m.018qj9): The Colorado River is a river in the south of Argentina. The Col...on the river traverses, and to regulate the river's water level., has type River
3. Colorado River (fb:m.018qk6): The Colorado River is a river that runs through the U.S. state o...y City before emptying into the Gulf of Mexico at Matagorda Bay., has type River
4. Colorado River (fb:m.0cd2h2): The Colorado River, or the Rio Colorado, in Costa Rica is a trib...rist destination, particularly for fishing for tarpon and snook., has type River
5. Colorado River (fb:m.06wb1rj): The Colorado River is a river of Chile., has type River
6. Colorado River (fb:m.0ql50g4): The Río Colorado is a river of Bolivia in the Potosí Department, Nor Lípez Province., has type River
7. Colorado River (fb:m.06w912z): The Colorado River is a river of Chile., has type River
8. Colorado River (fb:m.06w1mzv): The Colorado River is a river of Chile., has type River
9. Colorado River (fb:m.06w6t9l): Colorado River is a river of Costa Rica. It is a tributary of the Tempisque River., has type River
10. Colorado River (fb:m.0rglnx1): has type Musical Recording

[Assistant]
There are multiple entities named "Colorado River." The first one (fb:m.018qjq) is described as one of the principal rivers of the Southwestern United States, which matches the well-known Colorado River. I will use this entity for further exploration.

Step 2: Search for properties of the Colorado River (fb:m.018qjq) that might relate to the states it runs through. I will search for properties related to "state" or "location."

[Tool]
Top 10 property alternatives:
1. Key (fb:type.object.key): part of Object schema, links to type Key
2. Cities (fb:geography.river.cities): links to type City/Town/Village, part of River schema
3. Type (fb:type.object.type): part of Object schema, links to type Type
4. Category (fb:geography.geographical_feature.category): links to type Geographical feature category, part of Geographical Feature schema
5. Image (fb:common.topic.image): part of Topic schema, links to type Image
6. Name (fb:type.object.name): part of Object schema, links to type Text
7. Description (fb:common.topic.description): part of Topic schema, links to type Text
8. Length (fb:geography.river.length): links to type Floating Point Number, part of River schema
9. Mouth (fb:geography.river.mouth): links to type Location, part of River schema
10. Origin (fb:geography.river.origin): links to type Location, part of River schema

No other items found

[Assistant]
The properties related to the Colorado River include cities it runs through, its length, mouth, and origin, but there is no direct property mentioning states it runs through.

Step 3: Since there is no direct property for states, I will try to find the states that contain the river or are connected to it by location. I will check the locations related to the river's origin and mouth to see if they are states or can lead to states. Let's first find the origin and mouth of the Colorado River (fb:m.018qjq).

[Tool]
Got 1 row and 4 columns:
| origin                             | originLabel              | mouth                            | mouthLabel              |
| ---------------------------------- | ------------------------ | -------------------------------- | ----------------------- |
| La Poudre Pass Lake (fb:m.03nscyt) | La Poudre Pass Lake (en) | Gulf of California (fb:m.012dwh) | Gulf of California (en) |

[Assistant]
The origin of the Colorado River is La Poudre Pass Lake, and its mouth is the Gulf of California.

Step 4: I will now check the locations of La Poudre Pass Lake and Gulf of California to see if they are within any states or regions. Let's start with La Poudre Pass Lake.

[Tool]
Got 51 rows and 3 columns, showing the first 10 rows below:
| subject                            | property                                                            | object                                                                   |
| ---------------------------------- | ------------------------------------------------------------------- | ------------------------------------------------------------------------ |
| La Poudre Pass Lake (fb:m.03nscyt) | Type (fb:type.object.type)                                          | Topic (fb:common.topic)                                                  |
| La Poudre Pass Lake (fb:m.03nscyt) | Key (fb:type.object.key)                                            | /en/la_poudre_pass_lake                                                  |
| La Poudre Pass Lake (fb:m.03nscyt) | Name (fb:type.object.name)                                          | La Poudre hágó-tó (hu)                                                   |
| La Poudre Pass Lake (fb:m.03nscyt) | Topic equivalent webpage (fb:common.topic.topic_equivalent_webpage) | <http://en.wikipedia.org/wiki/index.html?curid=15754034>                 |
| La Poudre Pass Lake (fb:m.03nscyt) | Notable for (fb:common.topic.notable_for)                           | fb:g.1257p9t10                                                           |
| La Poudre Pass Lake (fb:m.03nscyt) | Notable types (fb:common.topic.notable_types)                       | Lake (fb:m.01xs05r)                                                      |
| La Poudre Pass Lake (fb:m.03nscyt) | Description (fb:common.topic.description)                           | A La Poudre hágó-tó 3101 méter m...nyonnal összekötő mászóösvényen. (hu) |
| La Poudre Pass Lake (fb:m.03nscyt) | Article (fb:common.topic.article)                                   | fb:m.03nscyy                                                             |
| La Poudre Pass Lake (fb:m.03nscyt) | Contained by (fb:location.location.containedby)                     | Rocky Mountain National Park (fb:m.01p_zv)                               |
| La Poudre Pass Lake (fb:m.03nscyt) | Geolocation (fb:location.location.geolocation)                      | fb:m.0w6clln                                                             |
| ...                                | ...                                                                 | ...                                                                      |

[Assistant]
La Poudre Pass Lake is contained by Rocky Mountain National Park (fb:m.01p_zv).

Step 5: I will now check if Rocky Mountain National Park is contained by any state.

[Tool]
Got 2 rows and 3 columns:
| subject                                    | property                                        | object                       |
| ------------------------------------------ | ----------------------------------------------- | ---------------------------- |
| Rocky Mountain National Park (fb:m.01p_zv) | Contained by (fb:location.location.containedby) | Colorado (fb:m.01n4w)        |
| Rocky Mountain National Park (fb:m.01p_zv) | Contained by (fb:location.location.containedby) | Rocky Mountains (fb:m.06c6l) |

[Assistant]
Rocky Mountain National Park is contained by the state of Colorado (fb:m.01n4w).

Step 6: Now I will check the location of the mouth of the river, the Gulf of California (fb:m.012dwh), to see if it is contained by any state or region.

[Tool]
Got 1 row and 3 columns:
| subject                          | property                                        | object                     |
| -------------------------------- | ----------------------------------------------- | -------------------------- |
| Gulf of California (fb:m.012dwh) | Contained by (fb:location.location.containedby) | North America (fb:m.059g4) |

[Assistant]
The Gulf of California is contained by North America, which is a continent, not a state.

Step 7: Since the river runs through multiple states, I will try to find states that the river runs through by checking locations related to the river. I will check the property "fb:geography.river.cities" to find cities the river runs through and then find the states of those cities.

[Tool]
Got 8 rows and 2 columns:
| city                                | cityLabel                  |
| ----------------------------------- | -------------------------- |
| Mexicali (fb:m.01n8m_)              | Mexicali (en)              |
| Los Angeles (fb:m.030qb3t)          | Los Angeles (en)           |
| San Luis Río Colorado (fb:m.062dv9) | San Luis Río Colorado (en) |
| San Diego (fb:m.071vr)              | San Diego (en)             |
| Las Vegas (fb:m.0cv3w)              | Las Vegas (en)             |
| Phoenix (fb:m.0d35y)                | Phoenix (en)               |
| Tucson (fb:m.0fr0t)                 | Tucson (en)                |
| San Bernardino (fb:m.0r4qq)         | San Bernardino (en)        |

[Assistant]
The Colorado River runs through or near the cities Mexicali, Los Angeles, San Luis Río Colorado, San Diego, Las Vegas, Phoenix, Tucson, and San Bernardino.

Step 8: I will now find the states that contain these cities. Let's start with Mexicali.

[Tool]
Got 3 rows and 3 columns:
| subject                | property                                        | object                              |
| ---------------------- | ----------------------------------------------- | ----------------------------------- |
| Mexicali (fb:m.01n8m_) | Contained by (fb:location.location.containedby) | Mexico (fb:m.0b90_r)                |
| Mexicali (fb:m.01n8m_) | Contained by (fb:location.location.containedby) | Baja California (fb:m.01ccgq)       |
| Mexicali (fb:m.01n8m_) | Contained by (fb:location.location.containedby) | Mexicali Municipality (fb:m.081z_h) |

[Assistant]
Mexicali is contained by the state Baja California (fb:m.01ccgq) in Mexico.

Step 9: I will now check the state for Los Angeles.

[Tool]
Got 4 rows and 3 columns:
| subject                    | property                                        | object                                 |
| -------------------------- | ----------------------------------------------- | -------------------------------------- |
| Los Angeles (fb:m.030qb3t) | Contained by (fb:location.location.containedby) | United States of America (fb:m.09c7w0) |
| Los Angeles (fb:m.030qb3t) | Contained by (fb:location.location.containedby) | California (fb:m.01n7q)                |
| Los Angeles (fb:m.030qb3t) | Contained by (fb:location.location.containedby) | Los Angeles County (fb:m.0kpys)        |
| Los Angeles (fb:m.030qb3t) | Contained by (fb:location.location.containedby) | Southern California (fb:m.0gx1l)       |

[Assistant]
Los Angeles is contained by the state California (fb:m.01n7q) in the United States.

Step 10: I will now check the state for San Luis Río Colorado.

[Tool]
Got 3 rows and 3 columns:
| subject                             | property                                        | object                                            |
| ----------------------------------- | ----------------------------------------------- | ------------------------------------------------- |
| San Luis Río Colorado (fb:m.062dv9) | Contained by (fb:location.location.containedby) | Mexico (fb:m.0b90_r)                              |
| San Luis Río Colorado (fb:m.062dv9) | Contained by (fb:location.location.containedby) | Sonora (fb:m.0ldff)                               |
| San Luis Río Colorado (fb:m.062dv9) | Contained by (fb:location.location.containedby) | San Luis Río Colorado Municipality (fb:m.09v18_7) |

[Assistant]
San Luis Río Colorado is contained by the state Sonora (fb:m.0ldff) in Mexico.

Step 11: I will now check the state for San Diego.

[Tool]
Got 6 rows and 3 columns:
| subject                | property                                        | object                                 |
| ---------------------- | ----------------------------------------------- | -------------------------------------- |
| San Diego (fb:m.071vr) | Contained by (fb:location.location.containedby) | United States of America (fb:m.09c7w0) |
| San Diego (fb:m.071vr) | Contained by (fb:location.location.containedby) | California (fb:m.01n7q)                |
| San Diego (fb:m.071vr) | Contained by (fb:location.location.containedby) | San Diego County (fb:m.0l2rj)          |
| San Diego (fb:m.071vr) | Contained by (fb:location.location.containedby) | San Diego–Tijuana (fb:m.02758s0)       |
| San Diego (fb:m.071vr) | Contained by (fb:location.location.containedby) | Area code 858 (fb:m.06r6lp)            |
| San Diego (fb:m.071vr) | Contained by (fb:location.location.containedby) | 92101 (fb:m.01zmr01)                   |

[Assistant]
San Diego is contained by the state California (fb:m.01n7q) in the United States.

Step 12: I will now check the state for Las Vegas.

[Tool]
Got 4 rows and 3 columns:
| subject                | property                                        | object                                 |
| ---------------------- | ----------------------------------------------- | -------------------------------------- |
| Las Vegas (fb:m.0cv3w) | Contained by (fb:location.location.containedby) | United States of America (fb:m.09c7w0) |
| Las Vegas (fb:m.0cv3w) | Contained by (fb:location.location.containedby) | Nevada (fb:m.059_c)                    |
| Las Vegas (fb:m.0cv3w) | Contained by (fb:location.location.containedby) | Clark County (fb:m.0d1y7)              |
| Las Vegas (fb:m.0cv3w) | Contained by (fb:location.location.containedby) | Area codes 702 and 725 (fb:m.04zdfg)   |

[Assistant]
Las Vegas is contained by the state Nevada (fb:m.059_c) in the United States.

Step 13: I will now check the state for Phoenix.

[Tool]
Got 3 rows and 3 columns:
| subject              | property                                        | object                                 |
| -------------------- | ----------------------------------------------- | -------------------------------------- |
| Phoenix (fb:m.0d35y) | Contained by (fb:location.location.containedby) | United States of America (fb:m.09c7w0) |
| Phoenix (fb:m.0d35y) | Contained by (fb:location.location.containedby) | Arizona (fb:m.0vmt)                    |
| Phoenix (fb:m.0d35y) | Contained by (fb:location.location.containedby) | Maricopa County (fb:m.0m27n)           |

[Assistant]
Phoenix is contained by the state Arizona (fb:m.0vmt) in the United States.

Step 14: I will now check the state for Tucson.

[Tool]
Got 4 rows and 3 columns:
| subject             | property                                        | object                                 |
| ------------------- | ----------------------------------------------- | -------------------------------------- |
| Tucson (fb:m.0fr0t) | Contained by (fb:location.location.containedby) | United States of America (fb:m.09c7w0) |
| Tucson (fb:m.0fr0t) | Contained by (fb:location.location.containedby) | Arizona (fb:m.0vmt)                    |
| Tucson (fb:m.0fr0t) | Contained by (fb:location.location.containedby) | Pima County (fb:m.0m2by)               |
| Tucson (fb:m.0fr0t) | Contained by (fb:location.location.containedby) | Area code 520 (fb:m.0bf1zb)            |

[Assistant]
Tucson is contained by the state Arizona (fb:m.0vmt) in the United States.

Step 15: I will now check the state for San Bernardino.

[Tool]
Got 4 rows and 3 columns:
| subject                     | property                                        | object                                 |
| --------------------------- | ----------------------------------------------- | -------------------------------------- |
| San Bernardino (fb:m.0r4qq) | Contained by (fb:location.location.containedby) | United States of America (fb:m.09c7w0) |
| San Bernardino (fb:m.0r4qq) | Contained by (fb:location.location.containedby) | California (fb:m.01n7q)                |
| San Bernardino (fb:m.0r4qq) | Contained by (fb:location.location.containedby) | San Bernardino County (fb:m.0kvt9)     |
| San Bernardino (fb:m.0r4qq) | Contained by (fb:location.location.containedby) | Area code 909 (fb:m.05wkfl)            |

[Assistant]
San Bernardino is contained by the state California (fb:m.01n7q) in the United States.

Step 16: Now I have identified the states that the Colorado River runs through based on the cities it runs through. The states are: Baja California, California, Sonora, Nevada, and Arizona.

I will now prepare the final SPARQL query to retrieve these states for the Colorado River (fb:m.018qjq) and provide the answer.

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The SPARQL query returns locations that are not states, such as cities, counties, and area codes, which is not correct for the question asking specifically for states. The query should be refined to filter results to only include entities that are states. Additionally, Baja California and Sonora are states in Mexico, not U.S. states, so the answer should clarify the distinction or specify the country if relevant. The query should also ensure it only returns states through which the Colorado River actually runs, not just states containing cities along the river. Filtering by type dbo:State or equivalent in Freebase and verifying the river's path would improve accuracy.

[Assistant]
Thank you for the feedback. To refine the query, I will add a filter to ensure that only entities that are states are returned. In Freebase, states are typically typed as administrative divisions or similar. I will check the type of the locations and filter for those that are states or equivalent administrative divisions.

Step 1: I will first check the type of one of the identified states, e.g., California, to find the appropriate type to filter for states.

[Tool]
Got 54 rows and 3 columns, showing the first 10 rows below:
| subject                 | property                   | object                                                        |
| ----------------------- | -------------------------- | ------------------------------------------------------------- |
| California (fb:m.01n7q) | Type (fb:type.object.type) | Topic (fb:common.topic)                                       |
| California (fb:m.01n7q) | Type (fb:type.object.type) | Abstract (fb:base.type_ontology.abstract)                     |
| California (fb:m.01n7q) | Type (fb:type.object.type) | Inanimate (fb:base.type_ontology.inanimate)                   |
| California (fb:m.01n7q) | Type (fb:type.object.type) | Agent (fb:base.type_ontology.agent)                           |
| California (fb:m.01n7q) | Type (fb:type.object.type) | Location (fb:location.location)                               |
| California (fb:m.01n7q) | Type (fb:type.object.type) | Organization (fb:organization.organization)                   |
| California (fb:m.01n7q) | Type (fb:type.object.type) | Statistical region (fb:location.statistical_region)           |
| California (fb:m.01n7q) | Type (fb:type.object.type) | Dated location (fb:location.dated_location)                   |
| California (fb:m.01n7q) | Type (fb:type.object.type) | Administrative Division (fb:location.administrative_division) |
| California (fb:m.01n7q) | Type (fb:type.object.type) | Literature Subject (fb:book.book_subject)                     |
| ...                     | ...                        | ...                                                           |

[Assistant]
California is typed as an Administrative Division (fb:location.administrative_division).

Step 2: I will refine the SPARQL query to only include locations that are of type Administrative Division to better filter for states.

Refined SPARQL query:
SELECT DISTINCT ?state ?stateLabel WHERE {
  fb:m.018qjq fb:geography.river.cities ?city .
  ?city fb:location.location.containedby ?state .
  ?state fb:type.object.type fb:location.administrative_division .
  ?state rdfs:label ?stateLabel .
  FILTER (lang(?stateLabel) = 'en')
}

I will execute this refined query to check the results.

[Tool]
Got 15 rows and 2 columns, showing the first 5 and last 5 rows below:
| state                                  | stateLabel                    |
| -------------------------------------- | ----------------------------- |
| Baja California (fb:m.01ccgq)          | Baja California (en)          |
| California (fb:m.01n7q)                | California (en)               |
| Nevada (fb:m.059_c)                    | Nevada (en)                   |
| Mexicali Municipality (fb:m.081z_h)    | Mexicali Municipality (en)    |
| United States of America (fb:m.09c7w0) | United States of America (en) |
| ...                                    | ...                           |
| San Diego County (fb:m.0l2rj)          | San Diego County (en)         |
| Sonora (fb:m.0ldff)                    | Sonora (en)                   |
| Maricopa County (fb:m.0m27n)           | Maricopa County (en)          |
| Pima County (fb:m.0m2by)               | Pima County (en)              |
| Arizona (fb:m.0vmt)                    | Arizona (en)                  |

[Assistant]
The refined query still returns some entities that are not states, such as municipalities, counties, and the United States of America.

Step 3: I will further refine the query by excluding known non-state administrative divisions such as municipalities, counties, and countries. I will exclude entities with labels containing "County," "Municipality," and "United States of America."

Refined SPARQL query:
SELECT DISTINCT ?state ?stateLabel WHERE {
  fb:m.018qjq fb:geography.river.cities ?city .
  ?city fb:location.location.containedby ?state .
  ?state fb:type.object.type fb:location.administrative_division .
  ?state rdfs:label ?stateLabel .
  FILTER (lang(?stateLabel) = 'en')
  FILTER (!CONTAINS(?stateLabel, \"County\"))
  FILTER (!CONTAINS(?stateLabel, \"Municipality\"))
  FILTER (?stateLabel != \"United States of America\")
}

I will execute this refined query to check the results.

[Tool]
Got 7 rows and 2 columns:
| state                                  | stateLabel                    |
| -------------------------------------- | ----------------------------- |
| Baja California (fb:m.01ccgq)          | Baja California (en)          |
| California (fb:m.01n7q)                | California (en)               |
| Nevada (fb:m.059_c)                    | Nevada (en)                   |
| United States of America (fb:m.09c7w0) | United States of America (en) |
| Mexico (fb:m.0b90_r)                   | Mexico (en)                   |
| Sonora (fb:m.0ldff)                    | Sonora (en)                   |
| Arizona (fb:m.0vmt)                    | Arizona (en)                  |

[Assistant]
The refined query still returns "United States of America" and "Mexico," which are countries, not states. I will exclude these as well.

Final refined SPARQL query:
SELECT DISTINCT ?state ?stateLabel WHERE {
  fb:m.018qjq fb:geography.river.cities ?city .
  ?city fb:location.location.containedby ?state .
  ?state fb:type.object.type fb:location.administrative_division .
  ?state rdfs:label ?stateLabel .
  FILTER (lang(?stateLabel) = 'en')
  FILTER (!CONTAINS(?stateLabel, "County"))
  FILTER (!CONTAINS(?stateLabel, "Municipality"))
  FILTER (?stateLabel != "United States of America")
  FILTER (?stateLabel != "Mexico")
}

I will now provide the final answer based on this refined query.

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The SPARQL query correctly identifies states and administrative divisions through which the Colorado River runs, including Baja California, Sonora, California, Nevada, and Arizona. However, the query also returns 'United States of America' and 'Mexico' which are countries, not states. Although the query attempts to filter these out, the filters are applied on labels and may not be sufficient. It would be better to refine the query to exclude entities that are countries explicitly by their type or to restrict to states/provinces only. Additionally, the query uses the property 'fb:geography.river.cities' to find cities along the river and then finds states containing those cities, which might miss states the river runs through but without cities linked in the data. A more direct property or relation indicating the river's path through states or administrative divisions would be preferable if available. Overall, the answer is mostly correct but the query can be improved to avoid including countries and ensure completeness.

[Assistant]
Thank you for the detailed feedback. To improve the query, I will explicitly exclude entities that are typed as countries and restrict the results to entities typed as administrative divisions but not countries. This will avoid relying solely on label filters.

Additionally, I will check if there is a more direct property linking the Colorado River to states or administrative divisions it runs through, instead of inferring from cities.

Step 1: I will search for properties of the Colorado River (fb:m.018qjq) that might directly relate to states or administrative divisions. I will search for properties related to "state" or "administrative division."

[Tool]
Top 10 property alternatives:
1. Key (fb:type.object.key): part of Object schema, links to type Key
2. Cities (fb:geography.river.cities): links to type City/Town/Village, part of River schema
3. Type (fb:type.object.type): part of Object schema, links to type Type
4. Category (fb:geography.geographical_feature.category): links to type Geographical feature category, part of Geographical Feature schema
5. Image (fb:common.topic.image): part of Topic schema, links to type Image
6. Name (fb:type.object.name): part of Object schema, links to type Text
7. Description (fb:common.topic.description): part of Topic schema, links to type Text
8. Length (fb:geography.river.length): links to type Floating Point Number, part of River schema
9. Mouth (fb:geography.river.mouth): links to type Location, part of River schema
10. Origin (fb:geography.river.origin): links to type Location, part of River schema

No other items found

[Assistant]
There is no direct property linking the Colorado River to states or administrative divisions it runs through. The closest property is "fb:geography.river.cities" which links to cities along the river.

Step 2: I will refine the query to:
- Use the cities along the river to find states or administrative divisions.
- Filter for entities typed as administrative divisions.
- Exclude entities typed as countries.
- Exclude entities with labels containing "County" or "Municipality" to avoid smaller divisions.

Refined SPARQL query:
SELECT DISTINCT ?state ?stateLabel WHERE {
  fb:m.018qjq fb:geography.river.cities ?city .
  ?city fb:location.location.containedby ?state .
  ?state fb:type.object.type fb:location.administrative_division .
  FILTER NOT EXISTS { ?state fb:type.object.type fb:location.country }
  ?state rdfs:label ?stateLabel .
  FILTER (lang(?stateLabel) = 'en')
  FILTER (!CONTAINS(?stateLabel, "County"))
  FILTER (!CONTAINS(?stateLabel, "Municipality"))
}

I will execute this refined query to check the results.

[Tool]
Got 5 rows and 2 columns:
| state                         | stateLabel           |
| ----------------------------- | -------------------- |
| Baja California (fb:m.01ccgq) | Baja California (en) |
| California (fb:m.01n7q)       | California (en)      |
| Nevada (fb:m.059_c)           | Nevada (en)          |
| Sonora (fb:m.0ldff)           | Sonora (en)          |
| Arizona (fb:m.0vmt)           | Arizona (en)         |

[Tool] Stopped generation process


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX fb: <http://rdf.freebase.com/ns/>
SELECT DISTINCT ?location ?locationLabel WHERE {
  fb:m.0hrf6ww fb:time.event.locations ?location .
  OPTIONAL {
    ?location rdfs:label ?locationLabel .
    FILTER ( lang( ?locationLabel ) = 'en' )
  }
}

The 2012 Masters Tournament was held at Augusta National Golf Course.

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

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

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

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

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

[User] where is augusta masters 2012?

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

[Tool]
Example 1:
Question:
where jay z was raised?

SPARQL:
SELECT DISTINCT ?x WHERE {
  FILTER ( ?x != fb:m.01vw20h ) FILTER ( ! isLiteral( ?x ) || lang( ?x ) = '' || langMatches( lang( ?x ) , 'en' ) ) fb:m.01vw20h fb:people.person.place_of_birth ?x .
}

Using entities:
Jay-Z, also known as Lucky Lefty, S-dot, Shawn Carter, Shawn C. Carter, Shawn Corey Carter (fb:m.01vw20h): Shawn Corey Carter, known by his stage name Jay Z, is an America...y Roc Nation Sports and is a certified NBA and MLB sports agent., has type Musical Artist

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

Example 2:
Question:
who runs the cornelia marie now?

SPARQL:
SELECT DISTINCT ?x WHERE {
  FILTER ( ?x != fb:m.02qn24x ) FILTER ( ! isLiteral( ?x ) || lang( ?x ) = '' || langMatches( lang( ?x ) , 'en' ) ) fb:m.02qn24x fb:boats.ship.owners ?y .
  ?y fb:boats.ship_ownership.owner ?x .
}

Using entities:
FV Cornelia Marie (fb:m.02qn24x): The FV Cornelia Marie is one of the commercial crab fishing boat... repowered the boat with new diesels and repaired her structure., has type Ship

Using properties:
Owners (fb:boats.ship.owners): links to type Ship ownership, part of Ship schema
Owner (fb:boats.ship_ownership.owner): part of Ship ownership schema, links to type Ship owner

Example 3:
Question:
what do you speak in singapore?

SPARQL:
SELECT DISTINCT ?x WHERE {
  FILTER ( ?x != fb:m.06t2t ) FILTER ( ! isLiteral( ?x ) || lang( ?x ) = '' || langMatches( lang( ?x ) , 'en' ) ) fb:m.06t2t fb:location.country.languages_spoken ?x .
}

Using entities:
Singapore, also known as Singapura, Republic of Singapore (fb:m.06t2t): Singapore, officially the Republic of Singapore, is a modern cit...Singapore became one of the British Straits Settlements in 1826., has type Country

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

[Assistant]
The question is "where is Augusta Masters 2012?" which refers to the location of the Augusta Masters golf tournament in the year 2012.

Step 1: Identify the entity "Augusta Masters 2012". This likely refers to the 2012 edition of the Masters Tournament held in Augusta.

Step 2: Search for the entity "Augusta Masters 2012" or "Masters Tournament 2012" in the knowledge graph.

I will start by searching for the entity "Masters Tournament 2012" to see if it exists in the knowledge graph.

[Tool]
Top 10 entity alternatives:
1. 2012 Masters Tournament (fb:m.0hrf6ww): The 2012 Masters Tournament was the 76th Masters Tournament, hel...the Masters; Ángel Cabrera won on the second extra hole in 2009., has type Competition
2. Masters Tournament, also known as Masters, US Masters, The US Masters, The Masters, Masters Golf Tournament (fb:m.014njb): The Masters Tournament, also known as The Masters or The US Mast...e times uses the same green jacket awarded upon his initial win., has type Sports League Championship
3. 2012 Masters (fb:m.0hgmjk_): The 2012 BGC Masters was a professional non-ranking snooker tour...10–6 in the final. This was Robertson's 10th professional title.
4. Masters Tournament (fb:m.0jt2zhs)
5. Masters Tournament (fb:m.0blcnl7)
6. 2012 Sony Ericsson Open, also known as 2012 Miami Masters (fb:m.0j45mwb): The 2012 Sony Ericsson Open, a men's and women's tennis tourname...orld Tour Masters 1000 and Premier Mandatory event respectively., has type Multi-event tournament
7. 2009 Masters Tournament (fb:m.04gt3yd): The 2009 Masters Tournament was the 73rd Masters Tournament, hel...ame the first Masters champion from Argentina and South America., has type Sports League Championship Event
8. 2006 Masters Tournament (fb:m.02wyqgy): The 2006 Masters Tournament was the 70th Masters Tournament, pla...e purse was $7 million and the winner's share was $1.26 million., has type Sports League Championship Event
9. 2007 Masters Tournament (fb:m.02qfcbs): The 2007 Masters Tournament was 71st Masters Tournament, held Ap...he field; Johnson's 289 tied for the highest winning score ever., has type Sports League Championship Event
10. 2008 Masters Tournament (fb:m.02wbs_n): The 2008 Masters Tournament was the 72nd Masters Tournament, hel...the Wednesday before the first round, was won by Rory Sabbatini., has type Sports League Championship Event

[Assistant]
I found an entity for "2012 Masters Tournament" with the identifier fb:m.0hrf6ww. This entity represents the 76th Masters Tournament held in 2012.

Next, I will look for the location property of this entity to find out where the 2012 Masters Tournament took place. I will search for properties related to location for this entity.

[Tool]
Top 10 property alternatives:
1. Location(s) (fb:time.event.locations): links to type Location, part of Event schema
2. Name (fb:type.object.name): part of Object schema, links to type Text
3. Description (fb:common.topic.description): part of Topic schema, links to type Text
4. Key (fb:type.object.key): part of Object schema, links to type Key
5. Article (fb:common.topic.article): links to type Document, part of Topic schema
6. Winner (fb:award.competition.winner): part of Competition schema, links to type Competitor
7. Championship (fb:sports.sports_championship_event.championship): part of Sports League Championship Event schema, links to type Sports League Championship
8. Type (fb:type.object.type): part of Object schema, links to type Type
9. Start date (fb:time.event.start_date): links to type Date/Time, part of Event schema
10. End date (fb:time.event.end_date): links to type Date/Time, part of Event schema

No other items found

[Assistant]
The property "Location(s)" (fb:time.event.locations) is available for the 2012 Masters Tournament entity. This property should give us the location of the event.

I will now write a SPARQL query to get the location of the 2012 Masters Tournament using this property.

[Tool]
Got 1 row and 2 columns:
| location                                    | locationLabel                     |
| ------------------------------------------- | --------------------------------- |
| Augusta National Golf Course (fb:m.04tk4bp) | Augusta National Golf Course (en) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The system correctly identified the location of the 2012 Masters Tournament as Augusta National Golf Course. The SPARQL query is well-formed, uses the appropriate entity and property, and returns the expected location with its label. The answer is accurate and complete for the user's question.


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX fb: <http://rdf.freebase.com/ns/>
SELECT DISTINCT ?placeOfBirth ?placeOfBirthLabel ?placeLived WHERE {
  fb:m.0g7km1 fb:people.person.place_of_birth ?placeOfBirth .
  OPTIONAL {
    ?placeOfBirth rdfs:label ?placeOfBirthLabel
  }
  OPTIONAL {
    fb:m.0g7km1 fb:people.person.places_lived ?placeLived
  }
}

Got 93 rows and 3 columns, showing the first 5 and last 5 rows below:
| placeOfBirth         | placeOfBirthLabel | placeLived   |
| -------------------- | ----------------- | ------------ |
| Makati (fb:m.01dvzy) | Kota Makati (id)  | fb:m.03pg7h1 |
| Makati (fb:m.01dvzy) | Kota Makati (id)  | fb:m.03pnj_p |
| Makati (fb:m.01dvzy) | Kota Makati (id)  | fb:m.0wh35mh |
| Makati (fb:m.01dvzy) | Makati (en)       | fb:m.03pg7h1 |
| Makati (fb:m.01dvzy) | Makati (en)       | fb:m.03pnj_p |
| ...                  | ...               | ...          |
| Makati (fb:m.01dvzy) | 馬卡蒂 (zh-Hant)     | fb:m.03pnj_p |
| Makati (fb:m.01dvzy) | 馬卡蒂 (zh-Hant)     | fb:m.0wh35mh |
| Makati (fb:m.01dvzy) | 马卡蒂 (zh)          | fb:m.03pg7h1 |
| Makati (fb:m.01dvzy) | 马卡蒂 (zh)          | fb:m.03pnj_p |
| Makati (fb:m.01dvzy) | 马卡蒂 (zh)          | fb:m.0wh35mh |

Tim Tebow was born in Makati. The dataset lists three places he has lived, but their names are not available in the dataset. There is no specific property indicating where he grew up, so the exact location of his upbringing cannot be determined from this data.

[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 tim tebow grow up?

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

[Tool]
Example 1:
Question:
who was judy garland married to?

SPARQL:
SELECT DISTINCT ?x WHERE {
  FILTER ( ?x != fb:m.0g10g ) FILTER ( ! isLiteral( ?x ) || lang( ?x ) = '' || langMatches( lang( ?x ) , 'en' ) ) fb:m.0g10g 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
Judy Garland, also known as The Garland Sisters, Miss Show Business, Marie Gumm, Judy, Joots (fb:m.0g10g): Judy Garland was an American singer, actress, and vaudevillian. ...urn to acting, beginning with critically acclaimed performances., has type Musical Artist

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 2:
Question:
what dialects are spoken in the uk?

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

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

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

Example 3:
Question:
what did edward jenner do for a living?

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

Using entities:
Edward Jenner (fb:m.02ljb): Edward Jenner, FRS was an English physician and scientist who wa...the first person to describe the brood parasitism of the cuckoo., has type Academic

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

[Assistant]
The examples show how to find information about a person using their Freebase entity and relevant properties. For the question "where did Tim Tebow grow up?", we need to:

1. Find the Freebase entity for Tim Tebow.
2. Identify properties related to "grow up" or "hometown" or "place raised" for a person.
3. Query the place where Tim Tebow grew up.

I will start by searching for the entity "Tim Tebow" in Freebase.

[Tool]
Top 10 entity alternatives:
1. Tim Tebow, also known as Timmy Tebow, Timothy Richard Tebow (fb:m.0g7km1): Timothy Richard Tebow is an American football quarterback for th...nship game. The Gators again went 13–1 in 2009, his senior year., has type Organization leader
2. Tim Tebow (fb:m.0kb0gyz): Eric Cantor wants to justify tornado relief, and Tim Tebow talks about his missionary parents., has type TV Episode
3. Tim Tebow 20071223 (fb:m.04y1g7p)
4. E! Entertainment Special: Tim Tebow’s Wild Rise, also known as Tim Tebow's Wild Rise (fb:m.0_gh0x7): E! Entertainment Special: Tim Tebow’s Wild Rise is a 2013 Telly Award winning film., has type Award-Winning Work
5. Tim Tebow: Everything in Between (fb:m.0_z1bfk): has type Award-Winning Work
6. Molly Shannon, Tim Tebow, Matt Nathanson (fb:m.0j75m7b): has type TV Episode
7. Tim Burton, also known as Tim, ティモシー・ウィリアム・バートン, Timothy William Burton, Timothy Walter "Tim" Burton, Timothy Walter Burton (fb:m.07rd7): Timothy Walter "Tim" Burton is an American film director, produc...become a close friend of Burton since their first film together., has type Film director
8. Tim Curry, also known as Timothy James Curry, Timothy James "Tim" Curry, Tim, The Cheshire Cat (fb:m.07rzf): Timothy James "Tim" Curry is an English actor, singer, and compo...Broadway and West End productions of Spamalot from 2005 to 2007., has type Film actor
9. Tim Armstrong, also known as Rancid, Tim Timebomb Sings Songs from RocknNRoll Theater, Tim Timebomb, Timothy Lockwood Armstrong, Tim Armstrong (fb:m.01tv3x2): Timothy Lockwood Armstrong, is an American musician, songwriter,...and Pink and he has also worked with Gwen Stefani and Joe Walsh., has type Musical Artist
10. Tim Robbins, also known as Timothy Francis "Tim" Robbins, Timothy Francis Robbins, Tim (fb:m.01nr36): Timothy Francis "Tim" Robbins is an American actor, screenwriter...porting Actor, and for directing films such as Dead Man Walking., has type Film actor

[Assistant] The most relevant entity for Tim Tebow is fb:m.0g7km1. Now, I will search for properties related to "grow up" or "hometown" or "place raised" for this entity to find the appropriate property that indicates where Tim Tebow grew up.

[Tool]
Top 10 property alternatives:
1. Parents (fb:people.person.parents): part of Person schema, links to type Person
2. Passing (fb:american_football.football_player.passing): links to type Player Passing Statistics, part of American football player schema
3. Gender (fb:people.person.gender): part of Person schema, links to type Gender
4. Date of birth (fb:people.person.date_of_birth): links to type Date/Time, part of Person schema
5. Daylife Topic (fb:common.identity.daylife_topic): links to type Enumeration, part of Identity schema
6. Name (fb:type.object.name): part of Object schema, links to type Text
7. Nickname (fb:base.schemastaging.context_name.nickname): part of Context name schema, links to type Text
8. Height (fb:people.person.height_meters): links to type Floating Point Number, part of Person schema
9. Type (fb:type.object.type): part of Object schema, links to type Type
10. Place of birth (fb:people.person.place_of_birth): links to type Location, part of Person schema

No other items found

[Assistant] There is no direct property for "grow up" or "hometown" for Tim Tebow in the properties of the entity. However, "Place of birth" (fb:people.person.place_of_birth) is available, which might give some indication of where he grew up or was born. I will query the place of birth for Tim Tebow first.

[Tool]
Got 1 row and 2 columns:
| placeOfBirth         | placeOfBirthLabel |
| -------------------- | ----------------- |
| Makati (fb:m.01dvzy) | Makati (en)       |

[Assistant] Tim Tebow's place of birth is Makati. To better answer the question "where did Tim Tebow grow up?", I will now check if there is any property related to "hometown" or "location lived" or "residence" for Tim Tebow. I will search for properties with the query "hometown" for the entity.

[Tool]
Top 10 property alternatives:
1. Place of birth (fb:people.person.place_of_birth): links to type Location, part of Person schema
2. Country of nationality (fb:people.person.nationality): part of Person schema, links to type Country
3. Places lived (fb:people.person.places_lived): links to type Place lived, part of Person schema
4. Profession (fb:people.person.profession): links to type Profession, part of Person schema
5. Date of birth (fb:people.person.date_of_birth): links to type Date/Time, part of Person schema
6. Official name (fb:base.schemastaging.context_name.official_name): part of Context name schema, links to type Text
7. Official website (fb:common.topic.official_website): part of Topic schema, links to type URI
8. Name (fb:type.object.name): part of Object schema, links to type Text
9. Teams (fb:sports.pro_athlete.teams): links to type Sports team roster, part of Athlete schema
10. Nickname (fb:base.schemastaging.context_name.nickname): part of Context name schema, links to type Text

No other items found

[Assistant] There is a property "Places lived" (fb:people.person.places_lived) which might indicate where Tim Tebow grew up or lived. I will query the places Tim Tebow has lived.

[Tool]
Got 3 rows and 2 columns:
| placeLived   | placeLivedLabel |
| ------------ | --------------- |
| fb:m.03pg7h1 |                 |
| fb:m.03pnj_p |                 |
| fb:m.0wh35mh |                 |

[Assistant] Tim Tebow has three places he has lived according to the data, but they do not have English labels. I will try to get the labels for these places separately to understand where he grew up. I will query the labels for these three places.

[Tool] Got no rows and 2 columns

[Assistant] The places Tim Tebow lived do not have English labels in the dataset. I will try to find other properties related to "hometown" or "grew up" by searching for properties with the query "hometown" in the whole Freebase knowledge graph to see if there is a more suitable property.

[Tool]
Top 10 property alternatives:
1. birthPlace (fb:base.svocab.person.birthplace): part of Person schema, links to type Text
2. City of origin (fb:user.margolin.art_object.folk_art_object.city_of_origin): links to type City/Town/Village, part of Folk art object schema
3. Where I Grew Up (fb:freebase.user_profile.hometown): part of User Profile schema, links to type Location
4. Local Name (fb:base.rosetta.languoid.local_name): links to type Local Name, part of Languoid schema
5. City/Town (fb:user.cip22.default_domain.recording_studio.city_town): links to type City/Town/Village, part of Recording Studio schema
6. City/Town (fb:location.mailing_address.citytown): links to type Location, part of Address schema
7. Place of Residence (fb:base.musiteca.music_teacher.place_of_residence): links to type Situation, part of Composer schema
8. Place of Residence (fb:base.musiteca.performer.place_of_residence): part of Performer schema, links to type Situation
9. Place of origin (fb:base.oysters.oyster.place_of_origin): links to type Natural Location, part of Oyster schema
10. Place of origin (fb:base.militaryinfiction.military_unit_in_fiction.place_of_origin): links to type Military unit place of origin in fiction, part of Military Unit in Fiction schema

[Assistant] There is a property "Where I Grew Up" (fb:freebase.user_profile.hometown) which seems to directly relate to the question. However, it is part of the User Profile schema, which might not be commonly used for people entities like Tim Tebow. I will check if Tim Tebow has this property.

[Tool] Got no rows and 2 columns

[Assistant]
Tim Tebow does not have the "Where I Grew Up" property in the User Profile schema. Given the available data, the best information we have about where Tim Tebow grew up is the places he has lived (fb:people.person.places_lived), although the specific places do not have English labels in the dataset. We also have his place of birth as Makati.

I will provide a query that returns Tim Tebow's place of birth and the places he has lived as the answer to where he grew up. This should cover the possible locations related to his upbringing.

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The answer correctly identifies Tim Tebow's place of birth as Makati and mentions places he has lived. However, the question specifically asks where he grew up, which is not necessarily the same as place of birth or places lived. The query retrieves places lived but does not clarify which of these corresponds to where he grew up. Additionally, the places lived do not have English labels, making the answer less informative. To improve, the query should attempt to find more specific information about where Tim Tebow grew up, possibly by exploring additional properties or related entities that indicate childhood or upbringing locations. Also, including labels for the places lived if available would enhance clarity.

[Assistant]
Thank you for the feedback. I understand that the question specifically asks where Tim Tebow grew up, which is distinct from place of birth or general places lived. I will try to refine the approach by exploring additional properties or related entities that might indicate childhood or upbringing locations.

Step 1: I will search for properties related to "childhood" or "upbringing" for Tim Tebow's entity to see if there are more specific properties than "places lived."

Step 2: I will also check if there are any related entities connected to Tim Tebow that might represent his childhood home or upbringing location.

I will start with searching properties of Tim Tebow's entity with the query "childhood."

[Tool]
Top 10 property alternatives:
1. Siblings (fb:people.person.sibling_s): links to type Sibling Relationship, part of Person schema
2. Parents (fb:people.person.parents): part of Person schema, links to type Person
3. Gender (fb:people.person.gender): part of Person schema, links to type Gender
4. Place of birth (fb:people.person.place_of_birth): links to type Location, part of Person schema
5. Date of birth (fb:people.person.date_of_birth): links to type Date/Time, part of Person schema
6. Height (fb:people.person.height_meters): links to type Floating Point Number, part of Person schema
7. Places lived (fb:people.person.places_lived): links to type Place lived, part of Person schema
8. Country of nationality (fb:people.person.nationality): part of Person schema, links to type Country
9. Image (fb:common.topic.image): part of Topic schema, links to type Image
10. Religion (fb:people.person.religion): links to type Religion, part of Person schema

No other items found

[Assistant] There are no specific properties related to "childhood" or "upbringing" for Tim Tebow beyond the general properties like place of birth and places lived. I will now try searching for properties related to "upbringing" for Tim Tebow's entity.

[Tool]
Top 10 property alternatives:
1. Parents (fb:people.person.parents): part of Person schema, links to type Person
2. Place of birth (fb:people.person.place_of_birth): links to type Location, part of Person schema
3. Siblings (fb:people.person.sibling_s): links to type Sibling Relationship, 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. Country of nationality (fb:people.person.nationality): part of Person schema, links to type Country
7. Places lived (fb:people.person.places_lived): links to type Place lived, part of Person schema
8. Profession (fb:people.person.profession): links to type Profession, part of Person schema
9. Religion (fb:people.person.religion): links to type Religion, part of Person schema
10. Height (fb:people.person.height_meters): links to type Floating Point Number, part of Person schema

No other items found

[Assistant]
There are still no specific properties related to "upbringing" for Tim Tebow beyond the general ones. I will now try to find if there is any information about Tim Tebow's childhood location by looking at related entities or descriptions.

I will search for triples where Tim Tebow is the subject and the object is a location or place to see if there are any other location-related properties that might indicate where he grew up.

[Tool]
Got 360 rows and 3 columns, showing the first 10 rows below:
| subject                 | property                                                            | object                                                                    |
| ----------------------- | ------------------------------------------------------------------- | ------------------------------------------------------------------------- |
| Tim Tebow (fb:m.0g7km1) | Type (fb:type.object.type)                                          | Topic (fb:common.topic)                                                   |
| Tim Tebow (fb:m.0g7km1) | Key (fb:type.object.key)                                            | /authority/daylife/topic/026a9ED8Eqb3M                                    |
| Tim Tebow (fb:m.0g7km1) | Name (fb:type.object.name)                                          | Tim Tebow (da)                                                            |
| Tim Tebow (fb:m.0g7km1) | Topic equivalent webpage (fb:common.topic.topic_equivalent_webpage) | <http://da.wikipedia.org/wiki/index.html?curid=468683>                    |
| Tim Tebow (fb:m.0g7km1) | Notable for (fb:common.topic.notable_for)                           | fb:g.1255t_dt0                                                            |
| Tim Tebow (fb:m.0g7km1) | Notable types (fb:common.topic.notable_types)                       | Organization leader (fb:m.02h51nz)                                        |
| Tim Tebow (fb:m.0g7km1) | Description (fb:common.topic.description)                           | Si Timothy Tebow ay ipinanganak ...ionary ang kanyang mga magulang. (fil) |
| Tim Tebow (fb:m.0g7km1) | Article (fb:common.topic.article)                                   | fb:m.0g7km6                                                               |
| Tim Tebow (fb:m.0g7km1) | Also known as (fb:common.topic.alias)                               | Timmy Tebow (en)                                                          |
| Tim Tebow (fb:m.0g7km1) | Gender (fb:people.person.gender)                                    | Male (fb:m.05zppz)                                                        |
| ...                     | ...                                                                 | ...                                                                       |

[Assistant] There are many properties for Tim Tebow, but none in the first 10 rows directly indicate a childhood or upbringing location. I will filter the properties to only those that link to a location or place to see if any are relevant to where he grew up.

[Tool]
Got 3 rows and 3 columns:
| subject                 | property                                     | object       |
| ----------------------- | -------------------------------------------- | ------------ |
| Tim Tebow (fb:m.0g7km1) | Places lived (fb:people.person.places_lived) | fb:m.03pg7h1 |
| Tim Tebow (fb:m.0g7km1) | Places lived (fb:people.person.places_lived) | fb:m.03pnj_p |
| Tim Tebow (fb:m.0g7km1) | Places lived (fb:people.person.places_lived) | fb:m.0wh35mh |

[Assistant]
The only location-related property that might indicate where Tim Tebow grew up is "places lived," but the places do not have English labels in the dataset. Since there is no direct property for "grew up" or "childhood location," I will try to find the labels for these places in other languages to see if we can get any useful information.

I will query the labels for these places without restricting to English language.

[Tool] Got no rows and 2 columns

[Assistant]
There are no labels available for the places Tim Tebow lived in any language in the dataset. Given the limitations of the dataset, the best available information to answer where Tim Tebow grew up is to mention his place of birth (Makati) and the places he has lived (though unnamed in the dataset).

I will provide a refined answer stating this clearly and noting the limitation of the dataset regarding the specific location where he grew up.

[Tool] Stopped generation process

[User]
Feedback (status=done):
The system correctly identified Tim Tebow's place of birth as Makati and retrieved places he has lived. It also correctly noted that the dataset does not provide a specific property for where he grew up, so the exact location of his upbringing cannot be determined from the available data. The SPARQL query is appropriate for retrieving the place of birth and places lived, and the answer accurately reflects the query results and dataset limitations. No further refinement is needed.


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX fb: <http://rdf.freebase.com/ns/>
SELECT DISTINCT ?mouth ?mouthLabel WHERE {
  fb:m.04ykz fb:geography.river.mouth ?mouth .
  OPTIONAL {
    ?mouth rdfs:label ?mouthLabel FILTER ( lang( ?mouthLabel ) = 'en' )
  }
}

The Missouri River ends at the Mississippi River.

[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 the missouri river ends?

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

[Tool]
Example 1:
Question:
which airport to fly in rome?

SPARQL:
SELECT DISTINCT ?x WHERE {
  FILTER ( ?x != fb:m.06c62 ) FILTER ( ! isLiteral( ?x ) || lang( ?x ) = '' || langMatches( lang( ?x ) , 'en' ) ) fb:m.06c62 fb:travel.travel_destination.how_to_get_here ?y .
  ?y fb:travel.transportation.transport_terminus ?x .
  ?x fb:common.topic.notable_types fb:m.01xpjyz .
}

Using entities:
Airport (fb:m.01xpjyz): An airport is a facility where aircraft such as airplanes and helicopters can take off and land.
Rome, also known as Comune of Rome, Рим, The eternal City, the City of seven hills, Rome, Italy (fb:m.06c62): Rome is a city and special comune in Italy. Rome is the capital ...pulation originated from a mix of Latins, Etruscans and Sabines., has type Italian comune

Using properties:
Notable types (fb:common.topic.notable_types): part of Topic schema, links to type Type
Transport terminus (fb:travel.transportation.transport_terminus): links to type Transport terminus, part of Transportation schema
How to get here (fb:travel.travel_destination.how_to_get_here): part of Travel destination schema, links to type Transportation

Example 2:
Question:
where was governor cuomo born?

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

Using entities:
Andrew Cuomo, also known as Andrew Mark Cuomo, Gov. Andrew Cuomo (fb:m.02pjpd): Andrew Mark Cuomo is an American politician who is the 56th and ...erm as Attorney General of New York in 2006; serving until 2011., has type Politician

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

Example 3:
Question:
who is married to garth brooks?

SPARQL:
SELECT DISTINCT ?x WHERE {
  FILTER ( ?x != fb:m.036px ) FILTER ( ! isLiteral( ?x ) || lang( ?x ) = '' || langMatches( lang( ?x ) , 'en' ) ) fb:m.036px fb:people.person.spouse_s ?y .
  ?y fb:people.marriage.spouse ?x .
  ?y fb:people.marriage.type_of_union fb:m.04ztj .
  FILTER ( NOT EXISTS {
    ?y fb:people.marriage.from ?sk0
  }
  || EXISTS {
    ?y fb:people.marriage.from ?sk1 .
    FILTER ( xsd:datetime ( ?sk1 ) <= "2015-08-10" ^^ xsd:dateTime )
  }
  ) FILTER ( NOT EXISTS {
    ?y fb:people.marriage.to ?sk2
  }
  || EXISTS {
    ?y fb:people.marriage.to ?sk3 .
    FILTER ( xsd:datetime ( ?sk3 ) >= "2015-08-10" ^^ xsd:dateTime )
  }
  )
}

Using entities:
Garth Brooks, also known as Chris Gaines, Troyal Garth Brooks, Brooks, Garth (fb:m.036px): Troyal Garth Brooks, best known as Garth Brooks, is an American ... artists of all time, having sold more than 150 million records., has type Musical Artist
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:
From (fb:people.marriage.from): links to type Date/Time, part of Marriage schema
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

[Assistant]
From the examples, I see that the approach is to identify the entity (in this case, "Missouri River") and then find the property that relates to where it ends. The property might be related to "mouth of the river" or "river end" or something similar.

Step 1: Search for the entity "Missouri River" in the knowledge graph.

[Tool]
Top 10 entity alternatives:
1. Missouri River (fb:m.04ykz): The Missouri River is the longest river in North America. Rising...coming part of the United States through the Louisiana Purchase., has type River
2. Missouri River (fb:m.0bp0gmw)
3. Missouri River (fb:m.011wf76): has type Musical Recording
4. Missouri River (fb:m.011wgx4): has type Musical Recording
5. Missouri River (fb:m.012vwcz0): has type TV Episode
6. Missouri River (fb:m.0lqqt68)
7. Missouri River (fb:m.0lsk00c)
8. Missouri River (fb:m.07r09y_)
9. Park Hills, also known as Park Hills, Missouri, St. Francois County / Park Hills city, Flat River, Missouri, Elvins, Missouri (fb:m.0w_gy): Park Hills is a city in St. Francois County, Missouri. The population was 8,759 at the 2010 census., has type City/Town/Village
10. Riverview, St. Louis County, Missouri, also known as St. Louis County / Riverview village, Riverview, Missouri, Riverview, St. Louis County, Missouri, Riverview (fb:m.04b2jy6): Riverview is a village in St. Louis County, Missouri, United States. The population was 2,856 at the 2010 census., has type City/Town/Village

[Assistant] The entity "Missouri River" is identified as fb:m.04ykz which is a river. Now, I will search for properties of this entity that might indicate where the river ends or its mouth. I will search for properties related to "mouth" or "end".

[Tool]
Top 10 property alternatives:
1. Mouth (fb:geography.river.mouth): links to type Location, part of River schema
2. Mouth (long./lat./elev.) (fb:geography.river.mouth_long_lat): links to type Geocode, part of River schema
3. Type (fb:type.object.type): part of Object schema, links to type Type
4. Image (fb:common.topic.image): part of Topic schema, links to type Image
5. entry (fb:user.tsegaran.random.taxonomy_subject.entry): part of Taxonomy Subject schema, links to type Taxonomy Entry
6. Pronunciation (fb:base.schemastaging.context_name.pronunciation): links to type Pronunciation, part of Context name schema
7. Contained by (fb:location.location.containedby): part of Location schema, links to type Location
8. Name (fb:type.object.name): part of Object schema, links to type Text
9. Partially contained by (fb:location.location.partially_containedby): part of Location schema, links to type Location
10. Partially contained by (fb:location.location.partially_contained_by): links to type Partial containment relationship, part of Location schema

No other items found

[Assistant] The property "Mouth" (fb:geography.river.mouth) seems to be the correct property to find where the Missouri River ends. Now, I will construct a SPARQL query to find the mouth (end location) of the Missouri River.

[Tool]
Got 1 row and 2 columns:
| mouth                          | mouthLabel             |
| ------------------------------ | ---------------------- |
| Mississippi River (fb:m.04yf_) | Mississippi River (en) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the mouth of the Missouri River using the property fb:geography.river.mouth. The query returns the identifier and English label of the river where the Missouri River ends, which is the Mississippi River. The answer is accurate and complete based on the knowledge graph data. No further refinement is necessary.


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX fb: <http://rdf.freebase.com/ns/>
SELECT DISTINCT ?place ?placeLabel WHERE {
  fb:m.01vsl3_ fb:people.deceased_person.place_of_death ?place .
  OPTIONAL {
    ?place rdfs:label ?placeLabel FILTER ( lang( ?placeLabel ) = 'en' )
  }
}

John Lennon died in New York City.

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

You have access to the following knowledge graphs:
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 do john lennon die?

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

[Tool]
Example 1:
Question:
what continent is australia in?

SPARQL:
SELECT DISTINCT ?x WHERE {
  FILTER ( ?x != fb:m.0chghy ) FILTER ( ! isLiteral( ?x ) || lang( ?x ) = '' || langMatches( lang( ?x ) , 'en' ) ) fb:m.0chghy fb:location.location.containedby ?x .
  ?x fb:common.topic.notable_types fb:m.01mh .
}

Using entities:
Continent (fb:m.01mh): A continent is a large land mass, defined mostly by conventional...but closely related to tectonic plates within the earth's crust.
Australia, also known as Commonwealth of Australia, The Commonwealth of Australia (fb:m.0chghy): Australia, officially the Commonwealth of Australia, is an Ocean...e six colonies federated, forming the Commonwealth of Australia., has type Country

Using properties:
Notable types (fb:common.topic.notable_types): part of Topic schema, links to type Type
Contained by (fb:location.location.containedby): part of Location schema, links to type Location

Example 2:
Question:
where does the zambezi river end?

SPARQL:
SELECT DISTINCT ?x WHERE {
  FILTER ( ?x != fb:m.0p_70 ) FILTER ( ! isLiteral( ?x ) || lang( ?x ) = '' || langMatches( lang( ?x ) , 'en' ) ) fb:m.0p_70 fb:geography.river.mouth ?x .
}

Using entities:
Zambezi, also known as Zambezi River (fb:m.0p_70): The Zambezi is the fourth-longest river in Africa, the longest e...Africa. There is also a smaller power station at Victoria Falls., has type River

Using properties:
Mouth (fb:geography.river.mouth): links to type Location, part of River schema

Example 3:
Question:
who is esther hicks?

SPARQL:
SELECT DISTINCT ?x WHERE {
  FILTER ( ?x != fb:m.06_0rt ) FILTER ( ! isLiteral( ?x ) || lang( ?x ) = '' || langMatches( lang( ?x ) , 'en' ) ) fb:m.06_0rt fb:people.person.profession ?x .
}

Using entities:
Esther Hicks, also known as Esther Weaver (fb:m.06_0rt): Esther Hicks is an American inspirational speaker and author. Sh...ribes what she is doing as tapping into "infinite intelligence"., has type Author

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

[Assistant]
From the examples, we see that to find the place where a person died, we need to identify the entity for the person (John Lennon) and then find a property related to "death place" or "place of death."

Step 1: Search for the entity "John Lennon" in the Freebase knowledge graph.

[Tool]
Top 10 entity alternatives:
1. John Lennon, also known as The Beatles, John, Plastic Ono Band, Lennon, John Winston Ono Lennon MBE (fb:m.01vsl3_): John Winston Ono Lennon MBE was an English singer and songwriter... wit in his music, writing, drawings, on film and in interviews., has type Musical Artist
2. John Lennon Silva Santos, also known as John Lennon (fb:m.0ngkm8x): John Lennon, fullname John Lennon Silva Santos is a Brazilian pr...ays in Brazilian Série B for Atlético Goianiense as a Left back., has type Football player
3. Jack Lennon, also known as John "Jack" Lennon, John Lennon (fb:m.0tlm12d): John Lennon was the father of Freddie Lennon., has type Deceased Person
4. John Lennon (fb:m.0bbmppm): John Lennon is a fictional character from the 2009 biographical film Nowhere Boy., The representation, in fictional works, of John Lennon., has type Film character
5. John Lennon (fb:m.05f3s0w): John Lennon, was a naval captain, born at Downpatrick, Northern ...he island without convoy, on account of the American privateers., has type Deceased Person
6. John Lennon (fb:m.0y2kdv): has type Musical Recording
7. John Lennon (fb:m.0_jkyrk): has type Composition
8. John Lennon (fb:m.0fwmmt3): has type Canonical Version
9. John Lennon (fb:m.0dt_9zt): has type Musical Recording
10. John Lennon (fb:m.023kqy2): has type Musical Recording

[Assistant] The most relevant entity for John Lennon, the English singer and songwriter, is fb:m.01vsl3_. Next, I will search for properties related to death or place of death for this entity.

[Tool]
Top 10 property alternatives:
1. Place of death (fb:people.deceased_person.place_of_death): part of Deceased Person schema, links to type Location
2. Place Murdered (fb:user.alexander.misc.murdered_person.place_murdered): part of Murdered Person schema, links to type Location
3. Place of cremation (fb:people.deceased_person.place_of_cremation): part of Deceased Person schema, links to type Location
4. Cause of death (fb:people.deceased_person.cause_of_death): part of Deceased Person schema, links to type Cause Of Death
5. Date of death (fb:people.deceased_person.date_of_death): part of Deceased Person schema, links to type Date/Time
6. Places lived (fb:people.person.places_lived): links to type Place lived, part of Person schema
7. Place Musical Career Began (fb:music.artist.origin): part of Musical Artist schema, links to type Location
8. Murdered By (fb:user.alexander.misc.murdered_person.murdered_by): part of Murdered Person schema, links to type Murderer
9. Place of birth (fb:people.person.place_of_birth): links to type Location, part of Person schema
10. Date Murdered (fb:user.alexander.misc.murdered_person.date_murdered): part of Murdered Person schema, links to type Date/Time

No other items found

[Assistant] The property "Place of death" (fb:people.deceased_person.place_of_death) seems to be the correct property to use for finding where John Lennon died. Now, I will write a SPARQL query to get the place where John Lennon (fb:m.01vsl3_) died.

[Tool]
Got 1 row and 2 columns:
| place                       | placeLabel         |
| --------------------------- | ------------------ |
| New York City (fb:m.02_286) | New York City (en) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the place of death for John Lennon using the property fb:people.deceased_person.place_of_death. It returns the identifier and the English label for the place, which is New York City. The answer given is accurate and complete based on the query result. No further refinement is necessary.