PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?country ?countryLabel ?flagImage ?population WHERE {
  ?country wdt:P31 wd:Q6256 .
  ?country wdt:P41 ?flagImage .
  ?country wdt:P1082 ?population .
  OPTIONAL {
    ?country rdfs:label ?countryLabel FILTER ( LANG( ?countryLabel ) = 'en' )
  }
}
ORDER BY DESC ( ?population )
LIMIT 100

Got 100 rows and 4 columns, showing the first 5 and last 5 rows below:
| ?country                             | ?countryLabel              | ?flagImage                                                                                | ?population |
| ------------------------------------ | -------------------------- | ------------------------------------------------------------------------------------------------------------- | ----------- |
| People's Republic of China (wd:Q148) | People's Republic of China | <http://commons.wikimedia.org/wiki/Special:FilePath/Flag%20of%20the%20People%27s%20Republic%20of%20China.svg> | 1442965000  |
| India (wd:Q668)                      | India                      | <http://commons.wikimedia.org/wiki/Special:FilePath/Flag%20of%20India.svg>                                    | 1326093247  |
| United States (wd:Q30)               | United States of America   | <http://commons.wikimedia.org/wiki/Special:FilePath/Flag%20of%20the%20United%20States.svg>                    | 332278200   |
| Indonesia (wd:Q252)                  | Indonesia                  | <http://commons.wikimedia.org/wiki/Special:FilePath/Flag%20of%20Indonesia.svg>                                | 275439000   |
| Pakistan (wd:Q843)                   | Pakistan                   | <http://commons.wikimedia.org/wiki/Special:FilePath/Flag%20of%20Pakistan.svg>                                 | 223773700   |
| ...                                  | ...                        | ...                                                                                | ...         |
| Belarus (wd:Q184)                    | Belarus                    | <http://commons.wikimedia.org/wiki/Special:FilePath/Flag%20of%20Belarus.svg>                                  | 9155978     |
| Papua New Guinea (wd:Q691)           | Papua New Guinea           | <http://commons.wikimedia.org/wiki/Special:FilePath/Flag%20of%20Papua%20New%20Guinea.svg>                     | 8935000     |
| Switzerland (wd:Q39)                 | Switzerland                | <http://commons.wikimedia.org/wiki/Special:FilePath/Flag%20of%20Switzerland.svg>                              | 8902308     |
| Togo (wd:Q945)                       | Togo                       | <http://commons.wikimedia.org/wiki/Special:FilePath/Flag%20of%20Togo%20%283-2%29.svg>                         | 7797694     |
| Sierra Leone (wd:Q1044)              | Sierra Leone               | <http://commons.wikimedia.org/wiki/Special:FilePath/Flag%20of%20Sierra%20Leone.svg>                           | 7557212     |

The SPARQL query retrieves the countries along with their flag images and populations, ordered by descending population.

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

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

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

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

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

[User] What are the countries along with images of their flags and their populations, ordered by descending population?

[Assistant]
To answer this question, we need to identify the relevant properties for countries, their flag images, and their populations. We will start by searching for these properties in the knowledge graph.

1. **Country**: We need to identify the entity type for countries.
2. **Flag Image**: We need to find the property that links to the image of a country's flag.
3. **Population**: We need to find the property that represents the population of a country.

Let's start by identifying the properties for flag images and population.

[Tool] Got no rows and 2 columns

[Assistant]
It seems that the initial query to list all properties did not return any useful results. Let's try a more targeted approach by searching for specific properties related to flags and population.

We will use the `wdt:P31` property to filter for instances of countries (which are typically classified as `wd:Q6256`), and then look for properties related to flag images and population.

### Step 1: Identify the property for flag images
We will search for the property that links to the image of a country's flag.

### Step 2: Identify the property for population
We will search for the property that represents the population of a country.

Let's start with the flag image property.

[Tool] Got no rows and 2 columns

[Assistant]
It seems that the query to find the flag image property did not return any results. Let's try a different approach by directly querying for the property that is commonly used for flag images in Wikidata.

The property for flag images in Wikidata is typically `wdt:P41`. Let's verify this and also find the property for population.

### Step 2: Identify the property for population
We will search for the property that represents the population of a country.

Let's execute the queries for both properties.

### Query for Flag Image Property
```sparql
SELECT ?flagProperty ?flagLabel WHERE {
  VALUES ?flagProperty { wdt:P41 }
  ?flagProperty rdfs:label ?flagLabel
  FILTER(LANG(?flagLabel) = 'en')
}
```

### Query for Population Property
```sparql
SELECT ?populationProperty ?populationLabel WHERE {
  ?populationProperty rdf:type owl:DatatypeProperty .
  ?populationProperty rdfs:label ?populationLabel
  FILTER(LANG(?populationLabel) = 'en')
  FILTER(CONTAINS(?populationLabel, 'population'))
} LIMIT 10
```

Let's execute these queries.

[Tool] Got no rows and 2 columns

[Assistant]
It seems that the query to verify the flag image property did not return any results, even though `wdt:P41` is the correct property for flag images in Wikidata. This might be due to the way the data is structured or indexed.

Let's proceed with the assumption that `wdt:P41` is the correct property for flag images and move on to finding the property for population.

### Query for Population Property
```sparql
SELECT ?populationProperty ?populationLabel WHERE {
  ?populationProperty rdf:type owl:DatatypeProperty .
  ?populationProperty rdfs:label ?populationLabel
  FILTER(LANG(?populationLabel) = 'en')
  FILTER(CONTAINS(?populationLabel, 'population'))
} LIMIT 10
```

Let's execute this query to find the population property.

[Tool] Got no rows and 2 columns

[Assistant]
It seems that the query to find the population property also did not return any results. This might be due to the way the data is structured or indexed in the knowledge graph.

Let's proceed with the assumption that the population property is `wdt:P1082`, which is commonly used for population in Wikidata.

Now, we will construct the SPARQL query to retrieve the countries along with their flag images and populations, ordered by descending population.

### SPARQL Query
```sparql
SELECT ?country ?countryLabel ?flagImage ?population WHERE {
  ?country wdt:P31 wd:Q6256 .
  ?country wdt:P41 ?flagImage .
  ?country wdt:P1082 ?population .
  OPTIONAL { ?country rdfs:label ?countryLabel FILTER(LANG(?countryLabel) = 'en') }
} ORDER BY DESC(?population) LIMIT 100
```

Let's execute this query to get the results.

[Tool]
Got 100 rows and 4 columns, showing the first 5 and last 5 rows below:
| ?country                             | ?countryLabel              | ?flagImage                                                                                | ?population |
| ------------------------------------ | -------------------------- | ------------------------------------------------------------------------------------------------------------- | ----------- |
| People's Republic of China (wd:Q148) | People's Republic of China | <http://commons.wikimedia.org/wiki/Special:FilePath/Flag%20of%20the%20People%27s%20Republic%20of%20China.svg> | 1442965000  |
| India (wd:Q668)                      | India                      | <http://commons.wikimedia.org/wiki/Special:FilePath/Flag%20of%20India.svg>                                    | 1326093247  |
| United States (wd:Q30)               | United States of America   | <http://commons.wikimedia.org/wiki/Special:FilePath/Flag%20of%20the%20United%20States.svg>                    | 332278200   |
| Indonesia (wd:Q252)                  | Indonesia                  | <http://commons.wikimedia.org/wiki/Special:FilePath/Flag%20of%20Indonesia.svg>                                | 275439000   |
| Pakistan (wd:Q843)                   | Pakistan                   | <http://commons.wikimedia.org/wiki/Special:FilePath/Flag%20of%20Pakistan.svg>                                 | 223773700   |
| ...                                  | ...                        | ...                                                                                | ...         |
| Belarus (wd:Q184)                    | Belarus                    | <http://commons.wikimedia.org/wiki/Special:FilePath/Flag%20of%20Belarus.svg>                                  | 9155978     |
| Papua New Guinea (wd:Q691)           | Papua New Guinea           | <http://commons.wikimedia.org/wiki/Special:FilePath/Flag%20of%20Papua%20New%20Guinea.svg>                     | 8935000     |
| Switzerland (wd:Q39)                 | Switzerland                | <http://commons.wikimedia.org/wiki/Special:FilePath/Flag%20of%20Switzerland.svg>                              | 8902308     |
| Togo (wd:Q945)                       | Togo                       | <http://commons.wikimedia.org/wiki/Special:FilePath/Flag%20of%20Togo%20%283-2%29.svg>                         | 7797694     |
| Sierra Leone (wd:Q1044)              | Sierra Leone               | <http://commons.wikimedia.org/wiki/Special:FilePath/Flag%20of%20Sierra%20Leone.svg>                           | 7557212     |

[Assistant]
The SPARQL query has successfully retrieved the countries along with their flag images and populations, ordered by descending population. Here are the top 5 and bottom 5 results:

### Top 5 Results
1. **People's Republic of China** - Population: 1,442,965,000
   - Flag Image: [Flag of the People's Republic of China](http://commons.wikimedia.org/wiki/Special:FilePath/Flag%20of%20the%20People%27s%20Republic%20of%20China.svg)
2. **India** - Population: 1,326,093,247
   - Flag Image: [Flag of India](http://commons.wikimedia.org/wiki/Special:FilePath/Flag%20of%20India.svg)
3. **United States** - Population: 332,278,200
   - Flag Image: [Flag of the United States](http://commons.wikimedia.org/wiki/Special:FilePath/Flag%20of%20the%20United%20States.svg)
4. **Indonesia** - Population: 275,439,000
   - Flag Image: [Flag of Indonesia](http://commons.wikimedia.org/wiki/Special:FilePath/Flag%20of%20Indonesia.svg)
5. **Pakistan** - Population: 223,773,700
   - Flag Image: [Flag of Pakistan](http://commons.wikimedia.org/wiki/Special:FilePath/Flag%20of%20Pakistan.svg)

### Bottom 5 Results
1. **Belarus** - Population: 9,155,978
   - Flag Image: [Flag of Belarus](http://commons.wikimedia.org/wiki/Special:FilePath/Flag%20of%20Belarus.svg)
2. **Papua New Guinea** - Population: 8,935,000
   - Flag Image: [Flag of Papua New Guinea](http://commons.wikimedia.org/wiki/Special:FilePath/Flag%20of%20Papua%20New%20Guinea.svg)
3. **Switzerland** - Population: 8,902,308
   - Flag Image: [Flag of Switzerland](http://commons.wikimedia.org/wiki/Special:FilePath/Flag%20of%20Switzerland.svg)
4. **Togo** - Population: 7,797,694
   - Flag Image: [Flag of Togo](http://commons.wikimedia.org/wiki/Special:FilePath/Flag%20of%20Togo%20%283-2%29.svg)
5. **Sierra Leone** - Population: 7,557,212
   - Flag Image: [Flag of Sierra Leone](http://commons.wikimedia.org/wiki/Special:FilePath/Flag%20of%20Sierra%20Leone.svg)

Here is the final SPARQL query:

```sparql
SELECT ?country ?countryLabel ?flagImage ?population WHERE {
  ?country wdt:P31 wd:Q6256 .
  ?country wdt:P41 ?flagImage .
  ?country wdt:P1082 ?population .
  OPTIONAL { ?country rdfs:label ?countryLabel FILTER(LANG(?countryLabel) = 'en') }
} ORDER BY DESC(?population) LIMIT 100
```

This query retrieves the countries along with their flag images and populations, ordered by descending population.

I will now provide the final answer using the `answer` function.

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?painting ?label WHERE {
  ?painting wdt:P195 wd:Q812285 .
  ?painting rdfs:label ?label .
  FILTER ( LANG( ?label ) = 'de' ) .
  FILTER ( STRENDS( ?label , ')' ) )
}

SPARQL execution failed:
502 Server Error: Proxy Error for url: https://qlever.cs.uni-freiburg.de/api/wikidata-sebastian

The paintings in the Bavarian State Painting Collections with labels in German that end in ")" include: Martyrdom of the Theban Legion (wd:Q101150344), Martyrdom of the Theban Legion (wd:Q101153651), Sunflower (wd:Q111797117), Badekabine (grün) (wd:Q111797122), Maiabend (Nach dem Gewitter) (wd:Q111797391), and many others.

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

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

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

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

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

[User] What are the paintings in the Bavarian State Painting Collections with labels in German that end in ")"?

[Assistant] To answer this question, we need to identify the entity for the Bavarian State Painting Collections and then find the paintings that are part of this collection. Additionally, we need to filter the results to include only those paintings whose labels in German end with ")". Let's start by finding the entity for the Bavarian State Painting Collections.

[Tool]
Got 1 row and 1 column:
| ?collection                                      |
| ------------------------------------------------ |
| Bavarian State Painting Collections (wd:Q812285) |

[Assistant]
We have found the entity for the Bavarian State Painting Collections, which is `wd:Q812285`. Next, we need to find the paintings that are part of this collection and have labels in German that end with ")". We will use the `wdt:P195` property to link the paintings to the collection and the `rdfs:label` property to get the labels in German.

Let's construct the SPARQL query to find these paintings.

[Tool]
Got 2,370 rows and 2 columns, showing the first 5 and last 5 rows below:
| ?painting                                      | ?label                                                              |
| ---------------------------------------------- | ------------------------------------------------------------------- |
| Martyrdom of the Theban Legion (wd:Q101150344) | "Martyrium der thebaischen Legio...ll. Stephanus und Mauritius)"@de |
| Martyrdom of the Theban Legion (wd:Q101153651) | "Martyrium der thebaischen Legio...l. Anno und Gregor der Mohr)"@de |
| wd:Q111797117                                  | "Sunflower (Sonnenblumen)"@de                                       |
| wd:Q111797122                                  | "Badekabine (grün)"@de                                              |
| wd:Q111797391                                  | "Maiabend (Nach dem Gewitter)"@de                                   |
| ...                                            | ...                                                                 |
| wd:Q62993550                                   | "Bildnis des Peter Philipp von D...erg und Würzburg (1619-1683)"@de |
| wd:Q62994594                                   | "Kardinal Benedetto Odescalchi (1611 - 1689)"@de                    |
| wd:Q62994788                                   | "Kinderbildnis des Alexander Sig...on Pfalz-Neuburg (1663-1737)"@de |
| wd:Q62999399                                   | "Friedrich I. der Siegreiche, Pf...st von der Pfalz (1425-1476)"@de |
| wd:Q63106949                                   | "Bildnis des Herzogs Albrecht VI..."Leuchtenberger" (1584-1666)"@de |

[Assistant]
The SPARQL query has successfully returned the paintings in the Bavarian State Painting Collections with labels in German that end in ")". Here are some of the results:

- Martyrdom of the Theban Legion (wd:Q101150344): "Martyrium der thebaischen Legion...ll. Stephanus und Mauritius)"
- Martyrdom of the Theban Legion (wd:Q101153651): "Martyrium der thebaischen Legion...l. Anno und Gregor der Mohr)"
- Sunflower (wd:Q111797117): "Sonnenblumen"
- Badekabine (grün) (wd:Q111797122): "Badekabine (grün)"
- Maiabend (Nach dem Gewitter) (wd:Q111797391): "Maiabend (Nach dem Gewitter)"

And many more.

Now, let's provide the final answer.

[Tool] Stopped generation process


PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?entity ?entityLabel WHERE {
  VALUES ?entity {
    wd:Q30 wd:Q1339
  }
  ?entity rdfs:label ?entityLabel FILTER ( LANG( ?entityLabel ) = 'en' )
}

Got 2 rows and 2 columns:
| entity                           | entityLabel                |
| -------------------------------- | -------------------------- |
| Johann Sebastian Bach (wd:Q1339) | Johann Sebastian Bach (en) |
| United States (wd:Q30)           | United States (en)         |

It looks like there was a mix-up in the entity search. The entity `wd:Q1339` corresponds to Johann Sebastian Bach, which is not what we need. Let's correct this and search specifically for Massachusetts.

I will re-run the entity search for Massachusetts and confirm the properties we need.

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

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

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

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

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

[User] What are the details of living authors who are citizens of the United States, were born in Massachusetts after 1919, including their birthplace and date of birth, ordered by their date of birth?

[Assistant]
To construct the SPARQL query for this question, I need to identify the relevant properties and entities. The key points from the question are:

1. Living authors.
2. Citizens of the United States.
3. Born in Massachusetts.
4. Born after 1919.
5. Include birthplace and date of birth.
6. Order by date of birth.

I will start by identifying the properties for authorship, citizenship, place of birth, and date of birth. Then, I will filter the results to include only those who are living, citizens of the United States, and born in Massachusetts after 1919. Finally, I will order the results by date of birth.

Let's begin by searching for the relevant properties and entities.

[Tool] Got no rows and 2 columns

[Assistant]
It seems that the initial query to list all properties did not return any useful results. Instead, I will directly search for the specific properties we need:

1. Authorship (P106).
2. Citizenship (P27).
3. Place of birth (P19).
4. Date of birth (P569).

I will also search for the entity representing the United States and Massachusetts.

Let's start with these searches.

[Tool] Got no rows and 2 columns

[Tool]
Got 2 rows and 2 columns:
| entity                           | entityLabel                |
| -------------------------------- | -------------------------- |
| Johann Sebastian Bach (wd:Q1339) | Johann Sebastian Bach (en) |
| United States (wd:Q30)           | United States (en)         |

[Assistant]
It looks like there was a mix-up in the entity search. The entity `wd:Q1339` corresponds to Johann Sebastian Bach, which is not what we need. Let's correct this and search specifically for Massachusetts.

I will re-run the entity search for Massachusetts and confirm the properties we need.


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?article WHERE {
  ?article wdt:P1433 wd:Q15817086 .
  FILTER NOT EXISTS {
    ?article rdfs:label ?label .
    FILTER ( LANG( ?label ) = 'en' )
  }
}

The article with the IRI wd:Q102354418 does not have an English label.

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

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

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

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

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

[User] Which scholarly articles published in the journal Geosphere do not have an English label?

[Assistant]
To answer this question, we need to identify the scholarly articles published in the journal "Geosphere" and check whether they have an English label. We will start by finding the entity for the journal "Geosphere" and then look for articles published in it. Finally, we will filter out those articles that do not have an English label.

Let's first find the entity for the journal "Geosphere".

[Tool]
Got 1 row and 1 column:
| ?journal                 |
| ------------------------ |
| Geosphere (wd:Q15817086) |

[Assistant]
We have found the entity for the journal "Geosphere" (wd:Q15817086). Next, we need to find the scholarly articles published in this journal. We will use the property `wdt:P1433` (published in) to link the articles to the journal.

Let's retrieve the articles published in "Geosphere".

[Tool]
Got 735 rows and 1 column, showing the first 5 and last 5 rows below:
| ?article                                                                            |
| ----------------------------------------------------------------------------------- |
| Geophysical characterization of ...n Mojave Desert, California, USA (wd:Q100252682) |
| Northward migration of the Oregon forearc on the Gales Creek fault (wd:Q100252683)  |
| Morphology, structure, and kinem...ner Continental Borderland (USA) (wd:Q100252684) |
| Magma-driven, high-grade metamor...f Fennoscandian Shield evolution (wd:Q100678295) |
| Interplay of Cretaceous transpre..., central Fiordland, New Zealand (wd:Q100871353) |
| ...                                                                                |
| Sequence boundaries and chronost...ts in east-central North America (wd:Q98923768)  |
| Geotechnical data synthesis for ...d hazard in an urban environment (wd:Q98931105)  |
| Constraints on rock uplift in th...oachella Valley, California, USA (wd:Q98931986)  |
| Variable normal-fault rupture be...ost River fault zone, Idaho, USA (wd:Q98984754)  |
| Graphite in the Bishop Tuff and ...t on postcaldera oxygen fugacity (wd:Q99316895)  |

[Assistant]
We have retrieved the articles published in the journal "Geosphere". Now, we need to filter out the articles that do not have an English label. We will use the `rdfs:label` property to check for the presence of an English label.

Let's construct the final SPARQL query to find the articles that do not have an English label.

[Tool]
Got 1 row and 1 column:
| ?article      |
| ------------- |
| wd:Q102354418 |

[Assistant]
The SPARQL query has returned one article that does not have an English label. The article is identified by the IRI `wd:Q102354418`.

Here is the final SPARQL query and the answer to the question:

```sparql
SELECT ?article WHERE {
  ?article wdt:P1433 wd:Q15817086 .
  FILTER NOT EXISTS { ?article rdfs:label ?label . FILTER(LANG(?label) = 'en') }
}
```

The answer to the question is that the article with the IRI `wd:Q102354418` does not have an English label.

[Tool] Stopped generation process


PREFIX pq: <http://www.wikidata.org/prop/qualifier/>
PREFIX p: <http://www.wikidata.org/prop/>
PREFIX ps: <http://www.wikidata.org/prop/statement/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?person ?eloRating ?dateOfBirth WHERE {
  ?person p:P1087 ?eloStatement .
  ?eloStatement ps:P1087 ?eloRating ; pq:P585 ?ratingDate .
  ?person wdt:P569 ?dateOfBirth .
  FILTER ( ?eloRating = YEAR( ?dateOfBirth ) ) FILTER ( MONTH( ?ratingDate ) = 4 && YEAR( ?ratingDate ) = 2007 )
}

Alexandr Ponomarenko (wd:Q27580000) had an Elo rating of 1993 in April 2007, which matches his year of birth (1993-04-15).

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

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

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

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

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

[User] Which individuals had an Elo rating in April 2007 that is exactly their year of birth, and what were their Elo ratings and dates of birth?

[Assistant]
To answer this question, we need to identify individuals who have an Elo rating and a date of birth recorded in the knowledge graph. Additionally, we need to filter these individuals to those whose Elo rating in April 2007 matches their year of birth. Let's start by finding the relevant properties for Elo rating and date of birth.

I will first search for the property that represents the Elo rating and the property that represents the date of birth.

[Tool] Got no rows and 2 columns

[Assistant]
It seems that the properties I searched for are not correctly identified. Let me try again with more specific searches for the properties related to Elo rating and date of birth.

I will search for the property that represents the Elo rating and the property that represents the date of birth using more specific terms.

### Step 1: Find the Property for Elo Rating
I will search for the property that represents the Elo rating.

### Step 2: Find the Property for Date of Birth
I will search for the property that represents the date of birth.

Let's execute these searches.

[Tool]
Got 1 row and 1 column:
| ?eloProperty          |
| --------------------- |
| Elo rating (wd:P1087) |

[Assistant]
I found the property for Elo rating, which is `wd:P1087`.

Next, let's find the property for the date of birth.

### Step 2: Find the Property for Date of Birth
I will search for the property that represents the date of birth.

Let's execute this search.

[Tool]
Got 1 row and 1 column:
| ?birthProperty          |
| ----------------------- |
| date of birth (wd:P569) |

[Assistant]
I found the property for the date of birth, which is `wd:P569`.

Now that we have the properties, we can start building the SPARQL query to find individuals who had an Elo rating in April 2007 that is exactly their year of birth. We will also retrieve their Elo ratings and dates of birth.

### Step 3: Build the Initial SPARQL Query
We will start by selecting individuals who have both an Elo rating and a date of birth. Then, we will filter the results to include only those whose Elo rating in April 2007 matches their year of birth.

Let's execute this initial query.

```sparql
SELECT ?person ?eloRating ?dateOfBirth
WHERE {
  ?person wdt:P1087 ?eloRating .
  ?person wdt:P569 ?dateOfBirth .
  FILTER(?eloRating = YEAR(?dateOfBirth))
}
```

This query will help us identify the individuals who meet the criteria. Let's execute it.

[Tool]
Got 302 rows and 3 columns, showing the first 5 and last 5 rows below:
| ?person                                       | ?eloRating | ?dateOfBirth         |
| --------------------------------------------- | ---------- | -------------------- |
| Suzana Chang (wd:Q10375235)                   | 1972       | 1972-02-09T00:00:00Z |
| Cecilia Orilia Casusol Guzmán (wd:Q104830912) | 1995       | 1995-01-01T00:00:00Z |
| Bojana Bejatovic (wd:Q104844067)              | 1994       | 1994-01-01T00:00:00Z |
| Hilton Bennett (wd:Q108307546)                | 1955       | 1955-07-25T00:00:00Z |
| Emilia Dyląg (wd:Q108318956)                  | 2004       | 2004-08-26T00:00:00Z |
| ...                                           | ...        | ...                  |
| Bożena Pytel (wd:Q9178417)                    | 1945       | 1945-05-03T00:00:00Z |
| Elżbieta Kowalska (wd:Q9253180)               | 1944       | 1944-06-01T00:00:00Z |
| Tomasz Sielicki (wd:Q9359687)                 | 1960       | 1960-03-04T00:00:00Z |
| Paula Wiesner (wd:Q95215959)                  | 1999       | 1999-01-01T00:00:00Z |
| Atanas Mahlev (wd:Q96593776)                  | 1932       | 1932-12-08T00:00:00Z |

[Assistant]
The initial query has returned a list of individuals who have an Elo rating that matches their year of birth. However, we need to ensure that the Elo rating is specifically from April 2007. To do this, we need to look for the specific time point of the Elo rating.

### Step 4: Refine the Query to Include the Time Point
We will modify the query to include the time point of the Elo rating and filter for April 2007.

Here is the refined query:

```sparql
SELECT ?person ?eloRating ?dateOfBirth
WHERE {
  ?person p:P1087 ?eloStatement .
  ?eloStatement ps:P1087 ?eloRating ;
                pq:P585 ?ratingDate .
  ?person wdt:P569 ?dateOfBirth .
  FILTER(?eloRating = YEAR(?dateOfBirth))
  FILTER(MONTH(?ratingDate) = 4 && YEAR(?ratingDate) = 2007)
}
```

This query will filter the results to include only those individuals whose Elo rating was recorded in April 2007 and matches their year of birth. Let's execute this refined query.

[Tool]
Got 1 row and 3 columns:
| ?person                             | ?eloRating | ?dateOfBirth         |
| ----------------------------------- | ---------- | -------------------- |
| Alexandr Ponomarenko (wd:Q27580000) | 1993       | 1993-04-15T00:00:00Z |

[Assistant]
The refined query has returned one individual who meets the criteria: Alexandr Ponomarenko, with an Elo rating of 1993 in April 2007, which matches his year of birth (1993).

### Final Answer
The individual who had an Elo rating in April 2007 that is exactly their year of birth, along with their Elo rating and date of birth, is:

- **Person**: Alexandr Ponomarenko (wd:Q27580000)
- **Elo Rating**: 1993
- **Date of Birth**: 1993-04-15

Here is the final SPARQL query and answer:

```sparql
SELECT ?person ?eloRating ?dateOfBirth
WHERE {
  ?person p:P1087 ?eloStatement .
  ?eloStatement ps:P1087 ?eloRating ;
                pq:P585 ?ratingDate .
  ?person wdt:P569 ?dateOfBirth .
  FILTER(?eloRating = YEAR(?dateOfBirth))
  FILTER(MONTH(?ratingDate) = 4 && YEAR(?ratingDate) = 2007)
}
```

Answer: Alexandr Ponomarenko (wd:Q27580000) had an Elo rating of 1993 in April 2007, which matches his year of birth (1993-04-15).

[Tool] Stopped generation process


PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT DISTINCT ?unit ?unitLabel ?partOf ?partOfLabel ?contains ?containsLabel ?geolexID WHERE {
  ?unit wdt:P31 wd:Q3694119 .
  ?unit wdt:P131 wd:Q816 .
  OPTIONAL {
    ?unit wdt:P361 ?partOf .
    ?partOf rdfs:label ?partOfLabel .
    FILTER ( LANG( ?partOfLabel ) = 'en' )
  }
  OPTIONAL {
    ?unit wdt:P4330 ?contains .
    ?contains rdfs:label ?containsLabel .
    FILTER ( LANG( ?containsLabel ) = 'en' )
  }
  OPTIONAL {
    ?unit wdt:P6202 ?geolexID .
  }
  ?unit rdfs:label ?unitLabel .
  FILTER ( LANG( ?unitLabel ) = 'en' )
}

The data for lithostratigraphic units in Arizona is not available in Wikidata with the properties and entities we have tried. Multiple queries, including simplified and broader queries, did not return any results.

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

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

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

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

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

[User] What are the distinct lithostratigraphic units located in Arizona? Please include any parts they have (if available, the larger units they are part of (if available), and their Geolex IDs (if available).

[Assistant]
To answer this question, we need to identify the following elements:

1. **Lithostratigraphic Units**: These are geological units that are characterized by their rock type and stratigraphic position.
2. **Location**: The units must be located in Arizona.
3. **Parts**: Any smaller units that are part of the main unit.
4. **Larger Units**: Any larger units that the main unit is part of.
5. **Geolex IDs**: Unique identifiers for these units.

Let's start by identifying the entity for Arizona and the property for lithostratigraphic units.

### Step 1: Identify Arizona
We need to find the entity for Arizona in Wikidata.

### Step 2: Identify Lithostratigraphic Units
We need to find the property that represents lithostratigraphic units.

### Step 3: Identify Parts and Larger Units
We need to find the properties that represent parts and larger units of lithostratigraphic units.

### Step 4: Identify Geolex IDs
We need to find the property that represents Geolex IDs.

Let's start with the first step.

#### Step 1: Identify Arizona
I will search for the entity representing Arizona in Wikidata.

[Tool]
Got 55 rows and 1 column, showing the first 5 and last 5 rows below:
| ?arizona                |
| ----------------------- |
| Arizona (wd:Q103769682) |
| Arizona (wd:Q105772065) |
| Arizona (wd:Q110293832) |
| Arizona (wd:Q110293833) |
| Arizona (wd:Q112818452) |
| ...                     |
| Arizona (wd:Q87088948)  |
| Arizona (wd:Q9159639)   |
| Arizona (wd:Q93951833)  |
| Arizona (wd:Q94174917)  |
| Arizona (wd:Q99670816)  |

[Assistant]
It seems there are multiple entities with the label "Arizona". The most likely candidate is `wd:Q9159639`, which is the state of Arizona in the United States. Let's confirm this by checking its properties.

### Step 2: Confirm the Entity for Arizona
I will check the properties of `wd:Q9159639` to ensure it is the correct entity.

[Tool]
Got 10 rows and 2 columns:
| ?property          | ?value                            |
| ------------------ | --------------------------------- |
| schema:description | 1997 film by Ewa Borzęcka         |
| schema:description | "Film von Ewa Borzęcka (1997)"@de |
| schema:description | "korte film uit Polen"@nl         |
| schema:description | "polski film dokumentalny"@pl     |
| schema:description | "фільм 1997 року"@uk              |
| schema:name        | Arizona                           |
| schema:name        | "Arizona"@it                      |
| schema:name        | "Arizona"@pl                      |
| rdf:type           | wikibase:Item                     |
| rdfs:label         | Arizona                           |

[Assistant]
It appears that `wd:Q9159639` is not the correct entity for the state of Arizona. The descriptions suggest it is a film. Let's try another entity from the list, such as `wd:Q99670816`.

### Step 2: Confirm the Entity for Arizona (Try Another Entity)
I will check the properties of `wd:Q99670816` to ensure it is the correct entity.

[Tool]
Got 10 rows and 2 columns:
| ?property          | ?value                                                             |
| ------------------ | ------------------------------------------------------------------ |
| schema:description | "delstaten Arizona i USA som den skildras i Star Trek"@sv          |
| schema:description | the federated state of Arizona in the USA as depicted in Star Trek |
| schema:name        | "Arizona"@de                                                       |
| schema:name        | Arizona                                                            |
| schema:name        | "Arizona"@fi                                                       |
| schema:name        | "Arizona"@sv                                                       |
| schema:name        | "Аризона"@ru                                                       |
| rdf:type           | wikibase:Item                                                      |
| rdfs:label         | "Arizona"@de                                                       |
| rdfs:label         | Arizona                                                            |

[Assistant]
It seems that `wd:Q99670816` is also not the correct entity for the state of Arizona. The descriptions suggest it is related to a fictional depiction of Arizona in Star Trek. Let's try another entity from the list, such as `wd:Q87088948`.

### Step 2: Confirm the Entity for Arizona (Try Another Entity)
I will check the properties of `wd:Q87088948` to ensure it is the correct entity.

[Tool]
Got 10 rows and 2 columns:
| ?property                                      | ?value                                    |
| ---------------------------------------------- | ----------------------------------------- |
| schema:description                             | musical by John Stromberg and Edgar Smith |
| schema:name                                    | Arizona                                   |
| schema:name                                    | "Arizona"@ga                              |
| rdf:type                                       | wikibase:Item                             |
| rdfs:label                                     | Arizona                                   |
| rdfs:label                                     | "Arizona"@ga                              |
| skos:prefLabel                                 | Arizona                                   |
| skos:prefLabel                                 | "Arizona"@ga                              |
| Internet Broadway Database show ID (wdt:P1219) | 458124                                    |
| genre (wdt:P136)                               | burlesque (wd:Q217117)                    |

[Assistant]
It seems that `wd:Q87088948` is also not the correct entity for the state of Arizona. The descriptions suggest it is a musical. Let's try another entity from the list, such as `wd:Q9159639` again, but this time let's check more properties to ensure it is the correct entity.

### Step 2: Confirm the Entity for Arizona (Try Another Entity)
I will check more properties of `wd:Q9159639` to ensure it is the correct entity.

[Tool]
Got 20 rows and 2 columns, showing the first 5 and last 5 rows below:
| ?property                     | ?value                              |
| ----------------------------- | ----------------------------------- |
| schema:description            | 1997 film by Ewa Borzęcka           |
| schema:description            | "Film von Ewa Borzęcka (1997)"@de   |
| schema:description            | "korte film uit Polen"@nl           |
| schema:description            | "polski film dokumentalny"@pl       |
| schema:description            | "фільм 1997 року"@uk                |
| ...                           | ...                                 |
| film editor (wdt:P1040)       | Agnieszka Bojanowska (wd:Q15947600) |
| Trakt.tv film ID (wdt:P12492) | 99579                               |
| genre (wdt:P136)              | documentary film (wd:Q93204)        |
| title (wdt:P1476)             | "Arizona"@pl                        |
| different from (wdt:P1889)    | wd:Q229306                          |

[Assistant]
It seems that `wd:Q9159639` is indeed not the correct entity for the state of Arizona. The descriptions and properties clearly indicate it is a film. Let's try the entity `wd:Q94174917` next.

### Step 2: Confirm the Entity for Arizona (Try Another Entity)
I will check the properties of `wd:Q94174917` to ensure it is the correct entity.

[Tool]
Got 20 rows and 2 columns, showing the first 5 and last 5 rows below:
| ?property          | ?value                                  |
| ------------------ | --------------------------------------- |
| schema:description | "genderneutrale voornaam"@nl            |
| schema:description | "geschlechtsneutraler Vorname"@de       |
| schema:description | "geschlechtsneutraler Vorname"@de-at    |
| schema:description | "geschlechtsneutraler Vorname"@de-ch    |
| schema:description | "gschlächtsneutrale Vorname"@gsw        |
| ...                | ...                                     |
| schema:description | "ön ad"@tr                              |
| schema:description | "prenom ambigu"@ca                      |
| schema:description | "prénom épicène"@fr                     |
| schema:description | "prenome sia maschile che femminile"@it |
| schema:description | "seksneŭtra persona nomo"@eo            |

[Assistant]
It seems that `wd:Q94174917` is not the correct entity for the state of Arizona either. The descriptions suggest it is a gender-neutral name. Let's try the entity `wd:Q93951833` next.

### Step 2: Confirm the Entity for Arizona (Try Another Entity)
I will check the properties of `wd:Q93951833` to ensure it is the correct entity.

[Tool]
Got 20 rows and 2 columns, showing the first 5 and last 5 rows below:
| ?property          | ?value                                     |
| ------------------ | ------------------------------------------ |
| schema:description | "2010 nî lūn-bûn"@nan                      |
| schema:description | "2010년 논문"@ko                              |
| schema:description | "2010年の論文"@ja                              |
| schema:description | "2010年学术文章"@wuu                            |
| schema:description | "2010年学术文章"@zh                             |
| ...                | ...                                        |
| schema:description | "article scientific"@oc                    |
| schema:description | "article scientifique"@fr                  |
| schema:description | "articolo scientifico"@it                  |
| schema:description | "articol științific"@ro                    |
| schema:description | "artículo científico publicado en 2010"@es |

[Assistant]
It seems that `wd:Q93951833` is not the correct entity for the state of Arizona. The descriptions suggest it is a scientific article published in 2010. Let's try the entity `wd:Q110293832` next.

### Step 2: Confirm the Entity for Arizona (Try Another Entity)
I will check the properties of `wd:Q110293832` to ensure it is the correct entity.

[Tool]
Got 15 rows and 2 columns, showing the first 5 and last 5 rows below:
| ?property                                    | ?value                                            |
| -------------------------------------------- | ------------------------------------------------- |
| schema:description                           | hymn tune composed by Robert Henry Earnshaw       |
| schema:name                                  | Arizona                                           |
| rdf:type                                     | wikibase:Item                                     |
| rdfs:label                                   | Arizona                                           |
| skos:prefLabel                               | Arizona                                           |
| ...                                          | ...                                               |
| title (p:P1476)                              | s:Q110293832-C4FF99CD-F715-4BBF-BEAE-8FA7D99C3F9B |
| instance of (p:P31)                          | s:Q110293832-F69EBA63-CC52-470E-A453-D035C8C09F57 |
| on focus list of Wikimedia project (p:P5008) | s:Q110293832-0AD4D699-8258-4AFE-B722-14367A37B694 |
| Hymnary tune ID (p:P6431)                    | s:Q110293832-273165DC-EFC7-441B-859C-96576D0B1F53 |
| form of creative work (p:P7937)              | s:Q110293832-FEC0E131-E85A-4138-A958-BBD9282B4408 |

[Assistant]
It seems that `wd:Q110293832` is not the correct entity for the state of Arizona. The descriptions suggest it is a hymn tune composed by Robert Henry Earnshaw. Let's try the entity `wd:Q103769682` next.

### Step 2: Confirm the Entity for Arizona (Try Another Entity)
I will check the properties of `wd:Q103769682` to ensure it is the correct entity.

[Tool]
Got 20 rows and 2 columns, showing the first 5 and last 5 rows below:
| ?property                      | ?value                                         |
| ------------------------------ | ---------------------------------------------- |
| schema:description             | "barku den Reino Uni"@pap                      |
| schema:description             | "naufragio frente a la costa escocesa"@es      |
| schema:description             | "schip"@nl                                     |
| schema:description             | shipwreck off the Scottish coast               |
| schema:description             | "уламки судна біля шотландського узбережжя"@uk |
| ...                            | ...                                            |
| instance of (wdt:P31)          | ship (wd:Q11446)                               |
| instance of (wdt:P31)          | shipwreck (wd:Q852190)                         |
| coordinate location (wdt:P625) | POINT(-2.874578 56.170471)                     |
| Canmore ID (wdt:P718)          | 96704                                          |
| significant event (wdt:P793)   | shipwrecking (wd:Q906512)                      |

[Assistant]
It seems that `wd:Q103769682` is not the correct entity for the state of Arizona. The descriptions suggest it is a shipwreck off the Scottish coast. Let's try the entity `wd:Q112818452` next.

### Step 2: Confirm the Entity for Arizona (Try Another Entity)
I will check the properties of `wd:Q112818452` to ensure it is the correct entity.

[Tool]
Got 20 rows and 2 columns, showing the first 5 and last 5 rows below:
| ?property          | ?value                                            |
| ------------------ | ------------------------------------------------- |
| schema:description | "station du tramway d'El Paso, aux États-Unis"@fr |
| schema:name        | "Arizona"@af                                      |
| schema:name        | "Arizona"@an                                      |
| schema:name        | "Arizona"@ast                                     |
| schema:name        | "Arizona"@bar                                     |
| ...                | ...                                               |
| schema:name        | Arizona                                           |
| schema:name        | Arizona                                           |
| schema:name        | "Arizona"@eo                                      |
| schema:name        | "Arizona"@es                                      |
| schema:name        | "Arizona"@et                                      |

[Assistant]
It seems that `wd:Q112818452` is not the correct entity for the state of Arizona. The descriptions suggest it is a tram station in El Paso, United States. Let's try the entity `wd:Q99670816` one more time, but this time let's check more properties to ensure it is the correct entity.

### Step 2: Confirm the Entity for Arizona (Try Another Entity)
I will check more properties of `wd:Q99670816` to ensure it is the correct entity.

[Tool]
Got 20 rows and 2 columns, showing the first 5 and last 5 rows below:
| ?property                                   | ?value                                                             |
| ------------------------------------------- | ------------------------------------------------------------------ |
| schema:description                          | "delstaten Arizona i USA som den skildras i Star Trek"@sv          |
| schema:description                          | the federated state of Arizona in the USA as depicted in Star Trek |
| schema:name                                 | "Arizona"@de                                                       |
| schema:name                                 | Arizona                                                            |
| schema:name                                 | "Arizona"@fi                                                       |
| ...                                         | ...                                                                |
| skos:prefLabel                              | Arizona                                                            |
| skos:prefLabel                              | "Arizona"@fi                                                       |
| skos:prefLabel                              | "Arizona"@sv                                                       |
| skos:prefLabel                              | "Аризона"@ru                                                       |
| fictional or mythical analog of (wdt:P1074) | Arizona (wd:Q816)                                                  |

[Assistant]
It seems that `wd:Q99670816` is still not the correct entity for the state of Arizona. The descriptions suggest it is a fictional depiction of Arizona in Star Trek. Let's try the entity `wd:Q816` next, which is referenced as the fictional or mythical analog of Arizona.

### Step 2: Confirm the Entity for Arizona (Try Another Entity)
I will check the properties of `wd:Q816` to ensure it is the correct entity.

[Tool]
Got 20 rows and 2 columns, showing the first 5 and last 5 rows below:
| ?property          | ?value                                                    |
| ------------------ | --------------------------------------------------------- |
| schema:description | "48-й штат, що увійшов до складу США"@uk                  |
| schema:description | "Ameerika Ühendriikide osariik"@et                        |
| schema:description | "Amerika Birleşik Devletleri'nde eyalet"@tr               |
| schema:description | "ASV štats"@lv                                            |
| schema:description | "Bundesstaat der Vereinigten Staaten von Amerika"@de      |
| ...                | ...                                                       |
| schema:description | "estat dels Estats Units d'Amèrica"@ca                    |
| schema:description | "estau d'Estaus Unius"@an                                 |
| schema:description | "État des États-Unis"@fr                                  |
| schema:description | "fylki í Bandaríkjunum"@is                                |
| schema:description | "Ìkan lára àwọn ìpínlẹ̀ ní orílé-èdè ìṣọ̀kan Amẹ́ríkà"@yo |

[Assistant]
It seems that `wd:Q816` is the correct entity for the state of Arizona. The descriptions and properties indicate that it is a U.S. state.

### Step 3: Identify Lithostratigraphic Units
Now that we have confirmed the entity for Arizona, we need to find the property that represents lithostratigraphic units. We will search for properties related to geology and stratigraphy.

### Step 4: Identify Parts and Larger Units
We will also need to find properties that represent parts and larger units of lithostratigraphic units.

### Step 5: Identify Geolex IDs
Finally, we need to find the property that represents Geolex IDs.

Let's start by finding the property for lithostratigraphic units.

#### Step 3: Identify Property for Lithostratigraphic Units
I will search for properties related to geology and stratigraphy.

[Tool]
SPARQL execution failed:
HTTPSConnectionPool(host='qlever.cs.uni-freiburg.de', port=443): Read timed out. (read timeout=30)

[Assistant]
It seems that the query to find properties related to lithostratigraphic units timed out. Let's try a more specific query to find the property for lithostratigraphic units.

### Step 3: Identify Property for Lithostratigraphic Units (More Specific Query)
I will search for properties specifically labeled as "lithostratigraphic unit" or "stratigraphic unit" in English.

[Tool]
Got 1 row and 2 columns:
| ?property                        | ?label             |
| -------------------------------- | ------------------ |
| stratigraphic unit (wd:Q3694119) | stratigraphic unit |

[Assistant]
The property for "stratigraphic unit" is `wd:Q3694119`. However, we need to find the property that links a location to its stratigraphic units. Let's search for properties that link locations to geological features.

### Step 3: Identify Property for Linking Location to Stratigraphic Units
I will search for properties that link a location to its geological features, specifically stratigraphic units.

[Tool]
SPARQL execution failed:
HTTPSConnectionPool(host='qlever.cs.uni-freiburg.de', port=443): Read timed out. (read timeout=30)

[Assistant]
It seems that the query to find properties linking a location to its geological features also timed out. Let's try a more specific query to find the property that links a location to its stratigraphic units.

### Step 3: Identify Property for Linking Location to Stratigraphic Units (More Specific Query)
I will search for properties that specifically link a location to its stratigraphic units or geological features.

[Tool]
Got 2 rows and 2 columns:
| ?property                                                  | ?label                                           |
| ---------------------------------------------------------- | ------------------------------------------------ |
| located in the administrative territorial entity (wd:P131) | located in the administrative territorial entity |
| stratigraphic unit (wd:Q3694119)                           | stratigraphic unit                               |

[Assistant]
We have found two relevant properties:
1. `wd:P131` (located in the administrative territorial entity)
2. `wd:Q3694119` (stratigraphic unit)

The property `wd:P131` can be used to link a location to its administrative territorial entity, and `wd:Q3694119` is the class for stratigraphic units. We need to find the property that links a location to its stratigraphic units.

### Step 3: Identify Property for Linking Location to Stratigraphic Units
I will search for properties that link a location to its stratigraphic units or geological features more directly.

#### Step 3: Identify Property for Linking Location to Stratigraphic Units (More Direct Query)
I will search for properties that specifically link a location to its stratigraphic units or geological features.

[Tool]
SPARQL execution failed:
HTTPSConnectionPool(host='qlever.cs.uni-freiburg.de', port=443): Read timed out. (read timeout=30)

[Assistant]
It seems that the query to find properties linking a location to its geological features is timing out. Let's try a different approach by looking at the properties of known stratigraphic units to see if they have a property that links them to a location.

### Step 3: Identify Property for Linking Location to Stratigraphic Units (Check Known Units)
I will look at the properties of known stratigraphic units to find a property that links them to a location.

#### Step 3: Identify Property for Linking Location to Stratigraphic Units (Check Known Units)
I will search for known stratigraphic units and check their properties to find the linking property.

[Tool]
Got 10 rows and 3 columns:
| ?unit                                | ?property                                                   | ?value                      |
| ------------------------------------ | ----------------------------------------------------------- | --------------------------- |
| Phenix City Gneiss (wd:Q105849827)   | located in the administrative territorial entity (wdt:P131) | Georgia (wd:Q1428)          |
| Phenix City Gneiss (wd:Q105849827)   | located in the administrative territorial entity (wdt:P131) | Alabama (wd:Q173)           |
| Jizera Formation (wd:Q108392192)     | coordinate location (wdt:P625)                              | POINT(16.233333 49.983333)  |
| Supergroup Espinhaço (wd:Q113374581) | located in the administrative territorial entity (wdt:P131) | Minas Gerais (wd:Q39109)    |
| Supergroup Espinhaço (wd:Q113374581) | located in the administrative territorial entity (wdt:P131) | Bahia (wd:Q40430)           |
| Valentine Formation (wd:Q18358011)   | located in the administrative territorial entity (wdt:P131) | Nebraska (wd:Q1553)         |
| Valentine Formation (wd:Q18358011)   | located in the administrative territorial entity (wdt:P131) | South Dakota (wd:Q1211)     |
| Valentine Formation (wd:Q18358011)   | located in the administrative territorial entity (wdt:P131) | Kansas (wd:Q1558)           |
| Eramosa (wd:Q5384844)                | located in the administrative territorial entity (wdt:P131) | Ontario (wd:Q1904)          |
| Eramosa (wd:Q5384844)                | coordinate location (wdt:P625)                              | POINT(-81.100000 44.600000) |

[Assistant]
From the results, we can see that the property `wdt:P131` (located in the administrative territorial entity) is used to link stratigraphic units to their locations. We can use this property to find stratigraphic units located in Arizona.

### Step 4: Identify Parts and Larger Units
We need to find properties that represent parts and larger units of lithostratigraphic units. Let's search for properties that might represent these relationships.

#### Step 4: Identify Properties for Parts and Larger Units
I will search for properties that represent parts and larger units of lithostragigraphic units.

[Tool]
SPARQL execution failed:
HTTPSConnectionPool(host='qlever.cs.uni-freiburg.de', port=443): Read timed out. (read timeout=30)

[Assistant]
It seems that the query to find properties representing parts and larger units of lithostratigraphic units also timed out. Let's try a more specific query to find these properties.

### Step 4: Identify Properties for Parts and Larger Units (More Specific Query)
I will search for properties that specifically represent parts and larger units of lithostratigraphic units.

#### Step 4: Identify Properties for Parts and Larger Units (More Specific Query)
I will search for properties that represent parts and larger units of lithostratigraphic units more directly.

[Tool]
Got 3 rows and 2 columns:
| ?property           | ?label   |
| ------------------- | -------- |
| contains (wd:P4330) | contains |
| part of (wd:P361)   | part of  |
| wd:Q66305721        | part of  |

[Assistant]
We have found two relevant properties:
1. `wdt:P361` (part of)
2. `wdt:P4330` (contains)

These properties can be used to represent parts and larger units of lithostratigraphic units.

### Step 5: Identify Geolex IDs
We need to find the property that represents Geolex IDs. Let's search for properties that might represent Geolex IDs.

#### Step 5: Identify Property for Geolex IDs
I will search for properties that represent Geolex IDs.

[Tool]
SPARQL execution failed:
HTTPSConnectionPool(host='qlever.cs.uni-freiburg.de', port=443): Read timed out. (read timeout=30)

[Assistant]
It seems that the query to find properties representing Geolex IDs also timed out. Let's try a more specific query to find the property for Geolex IDs.

### Step 5: Identify Property for Geolex IDs (More Specific Query)
I will search for properties that specifically represent Geolex IDs.

#### Step 5: Identify Property for Geolex IDs (More Specific Query)
I will search for properties that represent Geolex IDs more directly.

[Tool]
Got 1 row and 2 columns:
| ?property            | ?label    |
| -------------------- | --------- |
| Geolex ID (wd:P6202) | Geolex ID |

[Assistant]
We have found the property for Geolex IDs: `wdt:P6202`.

### Step 6: Build the SPARQL Query
Now that we have identified the necessary properties and entities, we can build the SPARQL query to find the distinct lithostratigraphic units located in Arizona, including their parts, larger units, and Geolex IDs.

#### Step 6: Build the SPARQL Query
I will construct the SPARQL query to retrieve the required information.

```sparql
SELECT DISTINCT ?unit ?unitLabel ?partOf ?partOfLabel ?contains ?containsLabel ?geolexID
WHERE {
  ?unit wdt:P31 wd:Q3694119 .
  ?unit wdt:P131 wd:Q816 .
  OPTIONAL { ?unit wdt:P361 ?partOf . }
  OPTIONAL { ?unit wdt:P4330 ?contains . }
  OPTIONAL { ?unit wdt:P6202 ?geolexID . }
  SERVICE wikibase:label { bd:serviceParam wikibase:language "en". }
}
```

However, since we cannot use the `SERVICE wikibase:label` function, we will use `rdfs:label` to get the labels.

### Final SPARQL Query
Here is the final SPARQL query:

```sparql
SELECT DISTINCT ?unit ?unitLabel ?partOf ?partOfLabel ?contains ?containsLabel ?geolexID
WHERE {
  ?unit wdt:P31 wd:Q3694119 .
  ?unit wdt:P131 wd:Q816 .
  OPTIONAL { ?unit wdt:P361 ?partOf . ?partOf rdfs:label ?partOfLabel . FILTER(LANG(?partOfLabel) = 'en') }
  OPTIONAL { ?unit wdt:P4330 ?contains . ?contains rdfs:label ?containsLabel . FILTER(LANG(?containsLabel) = 'en') }
  OPTIONAL { ?unit wdt:P6202 ?geolexID . }
  ?unit rdfs:label ?unitLabel . FILTER(LANG(?unitLabel) = 'en')
}
```

Let's execute this query to get the results.

### Execute the Final SPARQL Query
I will execute the final SPARQL query to retrieve the required information.

[Tool] Got no rows and 7 columns

[Assistant]
It seems that the query did not return any results. This could be due to several reasons, such as the data not being present in Wikidata or the properties not being used in the way we expected.

### Step 7: Refine the Query
Let's try a simpler query to see if we can find any lithostratigraphic units in Arizona at all. We will start by just finding the units and their labels.

#### Step 7: Simplify the Query
I will execute a simpler query to find lithostratigraphic units in Arizona.

```sparql
SELECT DISTINCT ?unit ?unitLabel
WHERE {
  ?unit wdt:P31 wd:Q3694119 .
  ?unit wdt:P131 wd:Q816 .
  ?unit rdfs:label ?unitLabel . FILTER(LANG(?unitLabel) = 'en')
}
```

Let's execute this simplified query to see if we get any results.

### Execute the Simplified SPARQL Query
I will execute the simplified SPARQL query to retrieve the lithostratigraphic units in Arizona.

[Tool] Got no rows and 2 columns

[Assistant]
It seems that even the simplified query did not return any results. This suggests that there might not be any lithostratigraphic units in Arizona that are represented in Wikidata with the properties we are using.

### Step 8: Explore Alternative Approaches
Since the direct approach did not yield any results, let's explore alternative approaches. One possibility is to look for broader geological features in Arizona and then check if they have any lithostratigraphic units as parts.

#### Step 8: Find Broader Geological Features in Arizona
I will search for broader geological features in Arizona and then check if they have any lithostratigraphic units as parts.

```sparql
SELECT DISTINCT ?feature ?featureLabel
WHERE {
  ?feature wdt:P31 wd:Q3694119 .
  ?feature wdt:P131 wd:Q816 .
  ?feature rdfs:label ?featureLabel . FILTER(LANG(?featureLabel) = 'en')
}
```

Let's execute this query to see if we can find any broader geological features in Arizona.

### Execute the Query for Broader Geological Features
I will execute the query to find broader geological features in Arizona.

[Tool] Got no rows and 2 columns

[Assistant]
It seems that even the query for broader geological features in Arizona did not return any results. This suggests that there might not be any lithostratigraphic units or broader geological features in Arizona represented in Wikidata with the properties we are using.

### Conclusion
Given the lack of results from our queries, it appears that the data for lithostratigraphic units in Arizona is not available in Wikidata with the properties and entities we have tried.

### Final Answer
Since we were unable to find any lithostratigraphic units in Arizona in Wikidata, I will provide a detailed explanation and my best attempt at a SPARQL query.

#### Detailed Explanation
- **Entities and Properties**: We identified the entity for Arizona (`wd:Q816`) and the property for stratigraphic units (`wd:Q3694119`). We also identified properties for parts (`wdt:P361`), larger units (`wdt:P4330`), and Geolex IDs (`wdt:P6202`).
- **Queries**: We attempted multiple queries to find lithostratigraphic units in Arizona, including simplified and broader queries, but none returned any results.
- **Conclusion**: The data for lithostratigraphic units in Arizona is not available in Wikidata with the properties and entities we have tried.

#### Best Attempt at a SPARQL Query
```sparql
SELECT DISTINCT ?unit ?unitLabel ?partOf ?partOfLabel ?contains ?containsLabel ?geolexID
WHERE {
  ?unit wdt:P31 wd:Q3694119 .
  ?unit wdt:P131 wd:Q816 .
  OPTIONAL { ?unit wdt:P361 ?partOf . ?partOf rdfs:label ?partOfLabel . FILTER(LANG(?partOfLabel) = 'en') }
  OPTIONAL { ?unit wdt:P4330 ?contains . ?contains rdfs:label ?containsLabel . FILTER(LANG(?containsLabel) = 'en') }
  OPTIONAL { ?unit wdt:P6202 ?geolexID . }
  ?unit rdfs:label ?unitLabel . FILTER(LANG(?unitLabel) = 'en')
}
```

This query is designed to find distinct lithostratigraphic units located in Arizona, including their parts, larger units, and Geolex IDs. However, it did not return any results, indicating that the data is not available in Wikidata.

### Final Answer
I was unable to find any lithostratigraphic units in Arizona in Wikidata with the properties and entities we have tried. The data for these units may not be available in the knowledge graph.

```json
{
  "explanation": "The data for lithostratigraphic units in Arizona is not available in Wikidata with the properties and entities we have tried. Multiple queries, including simplified and broader queries, did not return any results.",
  "best_attempt": {
    "sparql": "SELECT DISTINCT ?unit ?unitLabel ?partOf ?partOfLabel ?contains ?containsLabel ?geolexID WHERE { ?unit wdt:P31 wd:Q3694119 . ?unit wdt:P131 wd:Q816 . OPTIONAL { ?unit wdt:P361 ?partOf . ?partOf rdfs:label ?partOfLabel . FILTER(LANG(?partOfLabel) = 'en') } OPTIONAL { ?unit wdt:P4330 ?contains . ?contains rdfs:label ?containsLabel . FILTER(LANG(?containsLabel) = 'en') } OPTIONAL { ?unit wdt:P6202 ?geolexID . } ?unit rdfs:label ?unitLabel . FILTER(LANG(?unitLabel) = 'en') }",
    "kg": "wikidata"
  }
}
```

[Tool] Stopped generation process