PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?test ?date ?operator ?yield ?yieldKilotons WHERE {
  ?test wdt:P31 wd:Q210112 .
  ?test wdt:P2108 ?yield .
  BIND( ?yield / 4.184E12 AS ?yieldKilotons ) OPTIONAL {
    ?test wdt:P585 ?date .
  }
  OPTIONAL {
    ?test wdt:P178 ?operator .
  }
  FILTER NOT EXISTS {
    ?test wdt:P361 ?series .
  }
}
LIMIT 100

The query was designed to retrieve details of nuclear weapons tests, including the date, operator, explosive energy equivalent, and their energy equivalent in kilotons, while excluding tests that are part of a nuclear test series. However, it appears that there are very few or no nuclear weapons tests in the dataset that have the yield property (P2108). This lack of data means that the query does 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 details of nuclear weapons tests, excluding those that are part of a nuclear test series? For each test, include the date (if available), operator (if available), explosive energy equivalent (if available), and their energy equivalent in kilotons (if available).

[Assistant]
To construct a SPARQL query that answers the user's question, I need to identify the relevant entities and properties. Let's start by searching for the entity representing "nuclear weapons tests" and the properties that might be associated with it, such as date, operator, and explosive energy equivalent.

First, I will search for the entity "nuclear weapons tests" and then look for the relevant properties.

[Tool]
Falling back to an unconstrained search on the full precomputed search indices:
SPARQL query contains no IRIs to constrain with

Top 10 entity alternatives:
1. Cancer following nuclear weapons tests (wd:Q45128117): scientific article published in April 1983
2. Cancer following nuclear weapons tests (wd:Q72562599): scientific article published on 01 October 1983
3. Cancer after nuclear weapons tests (wd:Q42733500): scientific article published on March 1988
4. Fallout from nuclear weapons tests (wd:Q79220414): scientific article published on 01 January 1958
5. Radioactive Fallout from Nuclear Weapons Tests (wd:Q81123730): scientific article published on 01 February 1965
6. Thyroid radioactivity after nuclear weapons tests (wd:Q74540816): scientific article
7. Cancer after nuclear weapons tests: Authors' reply (wd:Q46285168): scientific article published in March 1988
8. Cs137 Biospheric Contamination from Nuclear Weapons Tests (wd:Q78814922): scientific article published on 01 July 1959
9. Fallout from Nuclear Weapons Tests and Cancer Risks (wd:Q57482609)
10. Fallout from Nuclear Weapons Tests and Cancer Risks (wd:Q56002292)

No other items found

[Assistant]
It seems that the search for "nuclear weapons tests" returned scientific articles rather than the concept of nuclear weapons tests themselves. Let me try a more specific search for the concept of "nuclear weapons tests" and also search for the properties that might be associated with it, such as "date," "operator," and "explosive energy equivalent."

I will search for the entity "nuclear weapons test" and then look for the relevant properties.

[Tool]
Falling back to an unconstrained search on the full precomputed search indices:
SPARQL query contains no IRIs to constrain with

Top 10 entity alternatives:
1. nuclear weapons test, also known as nuclear test, nuclear tests, nuclear weapons testing, nuclear weapon tests (wd:Q210112): experiment carried out to determine the effectiveness, yield, and explosive capability of nuclear weapons
2. underground nuclear weapons test, also known as underground nuclear testing (wd:Q3058675): test detonation of nuclear weapons that is performed underground
3. Nuclear weapons testing (wd:Q58090221)
4. Nuclear weapons test ban 1988 (wd:Q69922466): scientific article published on 01 August 1988
5. nuclear weapons testing victims, also known as victims of nuclear weapons testing, atomic weapons testing victims (wd:Q113574952): people
6. Cancer following nuclear weapons tests (wd:Q45128117): scientific article published in April 1983
7. Cancer following nuclear weapons tests (wd:Q72562599): scientific article published on 01 October 1983
8. Cancer after nuclear weapons tests (wd:Q42733500): scientific article published on March 1988
9. Fallout from nuclear weapons tests (wd:Q79220414): scientific article published on 01 January 1958
10. Nuclear fusion without weapons testing (wd:Q60098831): scientific article published in Nature

No other items found

[Assistant]
The search has returned the entity "nuclear weapons test" (wd:Q210112), which is the concept we are looking for. Now, let's search for the properties that might be associated with this entity, such as "date," "operator," and "explosive energy equivalent."

I will search for these properties using the entity "nuclear weapons test" as a reference.

### Search for Properties
1. **Date**: This could be represented by `P585` (point in time).
2. **Operator**: This could be represented by `P178` (operator).
3. **Explosive Energy Equivalent**: This could be represented by `P2108` (yield).

Let's confirm these properties.

[Tool]
Top 10 property alternatives:
1. GND ID, also known as Deutschen Nationalbibliothek ID, Universal Authority File, Integrated Authority File, IndividualisedGnd, GND-IDN (wd:P227 as wdtn/wdt/p): identifier from an international authority file of names, subjects, and organizations
2. different from, also known as not to be confused with, to be distinguished from, similar to, see also, rejected match (wd:P1889 as wdt/p): item that is different from another item, with which it may be confused
3. Microsoft Academic ID, also known as MS Academic ID, Microsoft ID, Microsoft Academic Work ID, Microsoft Academic topic ID, Microsoft Academic Source ID (wd:P6366 as wdtn/wdt/p): identifier for an object or topic in the Microsoft Academic Graph (until 31 December 2021)
4. image, also known as still capture, still, screenshot, screen capture, portrait (wd:P18 as wdt/p): image of relevant illustration of the subject; if available, als...tor map, flag image, signature image, logo image, collage image)
5. Freebase ID, also known as Freebase, MID, Freebase identifier, FID (wd:P646 as wdt/p): identifier for a page in the Freebase database. Format: "/m/0" f...r IDs starting with "/g/", use Google Knowledge Graph ID (P2671)
6. facet of, also known as subitem of, topic of, subtopic of, subject in, section in (wd:P1269 as wdt/p): topic of which this item is an aspect; item that offers a broader perspective on the same topic
7. topic's main category, also known as article's main category, category, category for this topic, catmain, has category (wd:P910 as wdt/p): main Wikimedia category
8. has list, also known as list, topic's list, topic list, related list, list for this topic (wd:P2354 as wdt/p): Wikimedia list related to this subject
9. FAST ID, also known as Faceted Application of Subject Terminology ID, FAST subject heading, fst, worldcat.org/fast (wd:P2163 as wdtn/wdt/p): authority control identifier in WorldCat's “FAST Linked Data” authority file
10. subclass of, also known as rdfs:subClassOf, sort of, subcategory of, subgenre of, subtype of (wd:P279 as wdt/p): this item is a subclass (subset) of that item; ALL instances of ...stance of volcanic landform); Everest is an instance of mountain

No other items found

[Assistant]
The search for properties related to "nuclear weapons test" did not return the expected properties like "date," "operator," and "explosive energy equivalent." Let me manually search for these properties:

1. **Date**: `P585` (point in time)
2. **Operator**: `P178` (operator)
3. **Explosive Energy Equivalent**: `P2108` (yield)

Now, I will construct a SPARQL query to retrieve the details of nuclear weapons tests, excluding those that are part of a nuclear test series. I will include the date, operator, and explosive energy equivalent, and convert the energy equivalent to kilotons if available.

### Constructing the SPARQL Query

1. **Identify the entity for "nuclear weapons test"**: `wd:Q210112`
2. **Properties**:
   - Date: `wdt:P585`
   - Operator: `wdt:P178`
   - Explosive Energy Equivalent: `wdt:P2108`

3. **Exclude tests that are part of a nuclear test series**: We need to check if the test is part of a series, which could be represented by a property like `P361` (part of).

Let's start with a basic query and then refine it.

[Tool]
Got 100 rows and 5 columns, showing the first 5 and last 5 rows below:
| ?test                       | ?date                | ?operator                                                      | ?yield | ?yieldKilotons |
| --------------------------- | -------------------- | -------------------------------------------------------------- | ------ | -------------- |
| Vela incident (wd:Q1192659) | 1979-09-22T00:00:00Z |                                                                |        |                |
| Joe 20 (wd:Q120648419)      | 1956-02-02T00:00:00Z | National Research Centre Kurchatov Institute (wd:Q1794356)     |        |                |
| Joe 20 (wd:Q120648419)      | 1956-02-02T00:00:00Z | S.P. Korolev Rocket and Space Corporation Energia (wd:Q763402) |        |                |
| wd:Q16723006                | 1956-08-24T00:00:00Z |                                                                |        |                |
| Test No. 6 (wd:Q2329367)    | 1967-06-17T00:00:00Z |                                                                |        |                |
| ...                         | ...                  | ...                                                            | ...    | ...            |
| Bonarda (wd:Q98505351)      | 1980-09-25T00:00:00Z |                                                                |        |                |
| Bonefish (wd:Q98505353)     | 1964-02-18T00:00:00Z |                                                                |        |                |
| Borate (wd:Q98505357)       | 1987-10-23T00:00:00Z |                                                                |        |                |
| Bordeaux (wd:Q98505359)     | 1967-08-18T00:00:00Z |                                                                |        |                |
| Borrego (wd:Q98505360)      | 1982-09-29T00:00:00Z |                                                                |        |                |

[Assistant]
The initial query has returned some results, but it seems that the explosive energy equivalent (`?yield`) and its conversion to kilotons (`?yieldKilotons`) are not being populated for many tests. This could be due to the fact that the `P2108` property (yield) is not consistently used or is not available for many tests.

Let's refine the query to ensure that we only include tests where the yield is available and convert it to kilotons correctly. We will also add labels for better readability.

### Refining the SPARQL Query

1. **Filter tests where the yield is available**.
2. **Add labels for better readability**.

Here is the refined query:

```sparql
SELECT ?test ?testLabel ?date ?operator ?operatorLabel ?yield ?yieldKilotons
WHERE {
  ?test wdt:P31 wd:Q210112 .
  ?test wdt:P2108 ?yield .
  BIND(?yield / 4.184E12 AS ?yieldKilotons)
  OPTIONAL { ?test wdt:P585 ?date . }
  OPTIONAL { ?test wdt:P178 ?operator . }
  FILTER NOT EXISTS { ?test wdt:P361 ?series . }
  SERVICE wikibase:label { bd:serviceParam wikibase:language "en". }
}
LIMIT 100
```

However, since the `SERVICE wikibase:label` is not supported, I will use `rdfs:label` to get the labels.

Let's execute the refined query.

[Tool] Got no rows and 7 columns

[Assistant]
It seems that the refined query did not return any results, which suggests that there might be fewer tests with the yield property available or that the filtering conditions are too strict. Let's try a more relaxed query to see if we can get more results and then filter out the ones without the yield property.

### Relaxing the Query

1. **Remove the yield filter initially**.
2. **Include all tests and then filter out those without the yield property in the results**.

Here is the relaxed query:

```sparql
SELECT ?test ?testLabel ?date ?operator ?operatorLabel ?yield ?yieldKilotons
WHERE {
  ?test wdt:P31 wd:Q210112 .
  OPTIONAL { ?test wdt:P585 ?date . }
  OPTIONAL { ?test wdt:P178 ?operator . }
  OPTIONAL { ?test wdt:P2108 ?yield . BIND(?yield / 4.184E12 AS ?yieldKilotons) }
  FILTER NOT EXISTS { ?test wdt:P361 ?series . }
  OPTIONAL { ?test rdfs:label ?testLabel . FILTER(LANG(?testLabel) = 'en') }
  OPTIONAL { ?operator rdfs:label ?operatorLabel . FILTER(LANG(?operatorLabel) = 'en') }
}
LIMIT 100
```

Let's execute this relaxed query to see if we get more results.

[Tool]
SPARQL execution failed:
Tried to allocate 3.3 GB, but only 2.1 GB were available. Clear the cache or allow more memory for QLever during startup

[Assistant]
It seems that the query is too complex and is causing a memory issue. To address this, I will simplify the query by removing the label retrieval and focusing on the core information. We can then add the label retrieval in a separate step if needed.

### Simplified Query

1. **Focus on the core information: test, date, operator, yield, and yield in kilotons**.
2. **Remove the label retrieval to reduce complexity**.

Here is the simplified query:

```sparql
SELECT ?test ?date ?operator ?yield ?yieldKilotons
WHERE {
  ?test wdt:P31 wd:Q210112 .
  OPTIONAL { ?test wdt:P585 ?date . }
  OPTIONAL { ?test wdt:P178 ?operator . }
  OPTIONAL { ?test wdt:P2108 ?yield . BIND(?yield / 4.184E12 AS ?yieldKilotons) }
  FILTER NOT EXISTS { ?test wdt:P361 ?series . }
}
LIMIT 100
```

Let's execute this simplified query to see if it returns results without causing memory issues.

[Tool]
Got 100 rows and 5 columns, showing the first 5 and last 5 rows below:
| ?test                       | ?date                | ?operator                                                      | ?yield | ?yieldKilotons |
| --------------------------- | -------------------- | -------------------------------------------------------------- | ------ | -------------- |
| Vela incident (wd:Q1192659) | 1979-09-22T00:00:00Z |                                                                |        |                |
| Joe 20 (wd:Q120648419)      | 1956-02-02T00:00:00Z | National Research Centre Kurchatov Institute (wd:Q1794356)     |        |                |
| Joe 20 (wd:Q120648419)      | 1956-02-02T00:00:00Z | S.P. Korolev Rocket and Space Corporation Energia (wd:Q763402) |        |                |
| wd:Q16723006                | 1956-08-24T00:00:00Z |                                                                |        |                |
| Test No. 6 (wd:Q2329367)    | 1967-06-17T00:00:00Z |                                                                |        |                |
| ...                         | ...                  | ...                                                            | ...    | ...            |
| Bonarda (wd:Q98505351)      | 1980-09-25T00:00:00Z |                                                                |        |                |
| Bonefish (wd:Q98505353)     | 1964-02-18T00:00:00Z |                                                                |        |                |
| Borate (wd:Q98505357)       | 1987-10-23T00:00:00Z |                                                                |        |                |
| Bordeaux (wd:Q98505359)     | 1967-08-18T00:00:00Z |                                                                |        |                |
| Borrego (wd:Q98505360)      | 1982-09-29T00:00:00Z |                                                                |        |                |

[Assistant]
The simplified query has returned results, but it appears that many tests do not have the yield property populated. To ensure that we only include tests with the yield property, we can add a filter to exclude tests where the yield is not available.

### Final Query

1. **Filter tests where the yield is available**.
2. **Include the date, operator, yield, and yield in kilotons**.

Here is the final query:

```sparql
SELECT ?test ?date ?operator ?yield ?yieldKilotons
WHERE {
  ?test wdt:P31 wd:Q210112 .
  ?test wdt:P2108 ?yield .
  BIND(?yield / 4.184E12 AS ?yieldKilotons)
  OPTIONAL { ?test wdt:P585 ?date . }
  OPTIONAL { ?test wdt:P178 ?operator . }
  FILTER NOT EXISTS { ?test wdt:P361 ?series . }
}
LIMIT 100
```

Let's execute this final query to ensure it returns the desired results.

[Tool] Got no rows and 5 columns

[Assistant]
It seems that even with the filter for the yield property, no results are being returned. This suggests that there might be very few or no nuclear weapons tests in the dataset that meet all the criteria (i.e., have a yield, are not part of a series, and have the required properties).

To further investigate, let's try a more relaxed query to see if we can get any tests that have the yield property, regardless of whether they are part of a series or not. This will help us understand if the issue is with the yield property or the series filter.

### Relaxed Query to Check Yield Property

1. **Remove the series filter**.
2. **Include the date, operator, yield, and yield in kilotons**.

Here is the relaxed query:

```sparql
SELECT ?test ?date ?operator ?yield ?yieldKilotons
WHERE {
  ?test wdt:P31 wd:Q210112 .
  ?test wdt:P2108 ?yield .
  BIND(?yield / 4.184E12 AS ?yieldKilotons)
  OPTIONAL { ?test wdt:P585 ?date . }
  OPTIONAL { ?test wdt:P178 ?operator . }
}
LIMIT 100
```

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

[Tool] Got no rows and 5 columns

[Assistant]
It appears that even when relaxing the query to include tests that are part of a series, no results are being returned. This suggests that there might be very few or no nuclear weapons tests in the dataset that have the yield property (`P2108`).

Given this, it seems that the data in Wikidata might not be comprehensive enough to answer the user's question as specified. However, I will provide the best attempt at a SPARQL query that includes the yield property, even though it may not return any results.

### Best Attempt at the SPARQL Query

1. **Include the date, operator, yield, and yield in kilotons**.
2. **Filter out tests that are part of a series**.

Here is the best attempt at the SPARQL query:

```sparql
SELECT ?test ?date ?operator ?yield ?yieldKilotons
WHERE {
  ?test wdt:P31 wd:Q210112 .
  ?test wdt:P2108 ?yield .
  BIND(?yield / 4.184E12 AS ?yieldKilotons)
  OPTIONAL { ?test wdt:P585 ?date . }
  OPTIONAL { ?test wdt:P178 ?operator . }
  FILTER NOT EXISTS { ?test wdt:P361 ?series . }
}
LIMIT 100
```

Since this query does not return any results, I will provide an explanation and the best attempt at the SPARQL query.

### Explanation

The query was designed to retrieve details of nuclear weapons tests, including the date, operator, explosive energy equivalent, and their energy equivalent in kilotons, while excluding tests that are part of a nuclear test series. However, it appears that there are very few or no nuclear weapons tests in the dataset that have the yield property (`P2108`). This lack of data means that the query does not return any results.

### Best Attempt at the SPARQL Query

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?part ?partLabel ?coordinates ?route ?routeLabel WHERE {
  wd:Q41150 wdt:P527 ?part .
  ?part wdt:P625 ?coordinates .
  ?part wdt:P31 ?route .
  ?route wdt:P31 wd:Q337912 .
  OPTIONAL {
    ?part rdfs:label ?partLabel .
    FILTER ( LANG( ?partLabel ) = 'en' )
  }
  OPTIONAL {
    ?route rdfs:label ?routeLabel .
    FILTER ( LANG( ?routeLabel ) = 'en' )
  }
}

The part of the Camino de Santiago found is 'Way of Saint James in Czechia' with coordinates (15.124914, 49.808510). This part is part of the route 'Way of St. James', which is an instance of a pilgrims' way.

[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 items are part of the Camino de Santiago (also known as the Way of Saint James), including their coordinates, and the routes they are part of (where those routes are instances of a pilgrims' way)?

[Assistant]
To answer this question, we need to identify the items that are part of the Camino de Santiago, also known as the Way of Saint James. We will look for items that are part of this route and also try to find their coordinates and the specific routes they belong to, where these routes are instances of a pilgrims' way.

### Step 1: Identify the Camino de Santiago (Way of Saint James)
First, let's find the entity for the Camino de Santiago (Way of Saint James).

### Step 2: Identify the properties for being part of a route and for coordinates
We need to find the properties that indicate an item is part of a route and the property for coordinates.

### Step 3: Identify the property for being a pilgrims' way
We need to find the property that indicates a route is a pilgrims' way.

### Step 4: Construct the SPARQL query
We will construct a SPARQL query to find the items that are part of the Camino de Santiago, their coordinates, and the routes they are part of, where those routes are instances of a pilgrims' way.

Let's start by finding the entity for the Camino de Santiago (Way of Saint James).

[Tool]
Falling back to an unconstrained search on the full precomputed search indices:
SPARQL query contains no IRIs to constrain with

Top 10 entity alternatives:
1. Church of Saint James the Greater, Santiago del Collado (wd:Q117662503): Santiago del Collado parish church
2. Wayside Cross of Chapel of Santa Lucía, Santiago de Compostela, also known as Wayside Cross of Chapel of Saint Lucy, Santiago de Compostela (wd:Q106872241): wayside cross in Santiago de Compostela
3. Way of Saint James, also known as Camino de santago, Way of St. James, Way of St James, way of Santiago, The Way (wd:Q41150): Catholic pilgrimage to Santiago de Compostela, Spain
4. Wayside Cross of Saint Mary Church, Cesar, Santiago de Compostela, also known as Church stone cross (wd:Q106916341): wayside cross in Santiago de Compostela
5. Catalan Way of saint James (wd:Q5742366): pilgrinage route by the Ebro in catalonia
6. Pomeranian Way of Saint James (wd:Q11823712)
7. Pilgrims of Way of Saint James (wd:Q25397976)
8. Way of Saint James of Manzanal, also known as Via Nova Way, Way of St. James for Manzanal (wd:Q75708014): pilgrims' way, part of Santiago Way
9. Greaterpolish Way of Saint James (wd:Q9373070)
10. Lowersilesian  Way of Saint James (wd:Q9209199)

No other items found

[Assistant]
From the search results, the entity for the Camino de Santiago (Way of Saint James) is `wd:Q41150`.

Next, we need to identify the properties for being part of a route and for coordinates. We will also identify the property for being a pilgrims' way.

### Step 2: Identify Properties
Let's search for the properties that indicate an item is part of a route and the property for coordinates.

### Step 3: Identify the Property for Being a Pilgrims' Way
We will also search for the property that indicates a route is a pilgrims' way.

Let's start by searching for the property that indicates an item is part of a route.

[Tool]
Falling back to an unconstrained search on the full precomputed search indices:
SPARQL query contains no IRIs to constrain with

Top 10 property alternatives:
1. route map, also known as schema, street map, railway map, subway map, transit map (wd:P15 as pqv/wdtn/psv/p/prv/prn/pr/ps/wdt/pq/psn/pqn): image of route map at Wikimedia Commons, locator map image
2. in operation on service, also known as transport route of vehicle, transport route operated, transport route served, transport route serviced, used on route (wd:P10788 as pqv/wdtn/psv/p/prv/prn/pr/ps/wdt/pq/psn/pqn): service that a vehicle is operating on
3. route number, also known as line number, public transport line number (wd:P1671 as pqv/wdtn/psv/p/prv/prn/pr/ps/wdt/pq/psn/pqn): number of a rail or other public transport line, location code
4. road number, also known as shield number, route number, highway number (wd:P1824 as pqv/wdtn/psv/p/prv/prn/pr/ps/wdt/pq/psn/pqn): number assigned to a stretch of public roadway; omit any prefix or suffix indicated by a road number formatter (P8498), location code
5. traffic sign, also known as road sign, trail blazer, shield, route shield, route marker (wd:P14 as pqv/wdtn/psv/p/prv/prn/pr/ps/wdt/pq/psn/pqn): graphic symbol describing the item, used at the side of or above roads to give instructions or provide information to road users, logo image
6. located on street, also known as on street, street address, street, square, road (wd:P669 as pqv/wdtn/psv/p/prv/prn/pr/ps/wdt/pq/psn/pqn): street, road, or square, where the item is located. To add the n...perty P6375 "street address", if there is no item for the street, location, part of
7. transport network, also known as transport network, transit network, tram network, trail system, system of routes (wd:P16 as pqv/wdtn/psv/p/prv/prn/pr/ps/wdt/pq/psn/pqn): network the infrastructure is a part of, part of
8. climbing route, also known as summit trail, normal route (wd:P7309 as pqv/wdtn/psv/p/prv/prn/pr/ps/wdt/pq/psn/pqn): route used to get closer to a high point
9. via, also known as waystation, journey via, route via, routing point, stopover (wd:P2825 as pqv/wdtn/psv/p/prv/prn/pr/ps/wdt/pq/psn/pqn): intermediate point on a journey - stopover location, waystation or routing point, location
10. America's Byways road ID, also known as Byways road ID, National Scenic Byway road ID, Byways ID, America's Byways ID (wd:P4172 as pqv/wdtn/psv/p/prv/prn/pr/ps/wdt/pq/psn/pqn): identifier for a United States road on the America's Byways website

No other items found

[Assistant]
From the search results, the property that indicates an item is part of a route is `wdt:P16` (transport network).

Next, let's search for the property that indicates the coordinates of an item.

### Step 2: Identify the Property for Coordinates
We will search for the property that indicates the coordinates of an item.

### Step 3: Identify the Property for Being a Pilgrims' Way
We will also search for the property that indicates a route is a pilgrims' way.

Let's start by searching for the property that indicates the coordinates of an item.

[Tool]
Falling back to an unconstrained search on the full precomputed search indices:
SPARQL query contains no IRIs to constrain with

Top 10 property alternatives:
1. coordinate location, also known as point on a map, gps coordinates, gps location, latitude, location (wd:P625 as pqv/wdtn/psv/p/prv/prn/pr/ps/wdt/pq/psn/pqn): geocoordinates of the subject. For Earth, please note that only WGS84 coordinating system is supported at the moment
2. this zoological name is coordinate with, also known as coordinate name (wd:P2743 as pqv/wdtn/psv/p/prv/prn/pr/ps/wdt/pq/psn/pqn): links coordinate zoological names, different from
3. coordinates of depicted place, also known as depicted item geolocation, geolocation of object, object geolocation (wd:P9149 as pqv/wdtn/psv/p/prv/prn/pr/ps/wdt/pq/psn/pqn): coordinates of the place depicted in the work (or Commons image)
4. coordinates of geographic center, also known as coordinates of geographic centre, geographic centre, geographic center, geographical midpoint, geographical centre (wd:P5140 as pqv/wdtn/psv/p/prv/prn/pr/ps/wdt/pq/psn/pqn): coordinates of the center of an area. Use qualifier "determination method" (P459) to indicate how, coordinate location
5. time index, also known as time coordinate, timestamp, temporal coordinate, relative time (wd:P4895 as pqv/wdtn/psv/p/prv/prn/pr/ps/wdt/pq/psn/pqn): indicate when something happens relative to its beginning
6. genomic start, also known as start coordinate, genomic from, Genloc From, from, Genloc Start (wd:P644 as pqv/wdtn/psv/p/prv/prn/pr/ps/wdt/pq/psn/pqn): genomic starting coordinate of the biological sequence (e.g. a gene)
7. spatial reference system, also known as coordinate reference system, CRS, SRS (wd:P3037 as pqv/wdtn/psv/p/prv/prn/pr/ps/wdt/pq/psn/pqn): frame of reference used to produce a map
8. coordinates of the point of view, also known as camera location, camera coordinates, viewpoint coordinates, coordinates of point of view, coordinates of pov (wd:P1259 as pqv/wdtn/psv/p/prv/prn/pr/ps/wdt/pq/psn/pqn): point from which the scene depicted by the element is seen (element can be a photo, a painting, etc.)
9. occupant, also known as tenant, resident, renter, occupiers, lessee (wd:P466 as pqv/wdtn/psv/p/prv/prn/pr/ps/wdt/pq/psn/pqn): person or organization occupying property, used by
10. named place on map, also known as name on map, place on map (wd:P9664 as pqv/wdtn/psv/p/prv/prn/pr/ps/wdt/pq/psn/pqn): property linking a map to a place named on it

No other items found

[Assistant]
From the search results, the property that indicates the coordinates of an item is `wdt:P625` (coordinate location).

Next, let's search for the property that indicates a route is a pilgrims' way.

### Step 3: Identify the Property for Being a Pilgrims' Way
We will search for the property that indicates a route is a pilgrims' way.

Let's start by searching for the property that indicates a route is a pilgrims' way.

[Tool]
Falling back to an unconstrained search on the full precomputed search indices:
SPARQL query contains no IRIs to constrain with

Top 10 property alternatives:
1. destination point, also known as stopping at, to, journey destination, finish, end point (journey) (wd:P1444 as pqv/wdtn/psv/p/prv/prn/pr/ps/wdt/pq/psn/pqn): destination for this route (journey, flight, sailing, exploration, migration, etc.), destination of transfer, location
2. OpenStreetMap way ID, also known as OSM way ID, OSM way, Open Street Map way ID, OSM line ID (wd:P10689 as pqv/wdtn/psv/p/prv/prn/pr/ps/wdt/pq/psn/pqn): identifier for a way in OpenStreetMap
3. route map, also known as schema, street map, railway map, subway map, transit map (wd:P15 as pqv/wdtn/psv/p/prv/prn/pr/ps/wdt/pq/psn/pqn): image of route map at Wikimedia Commons, locator map image
4. via, also known as waystation, journey via, route via, routing point, stopover (wd:P2825 as pqv/wdtn/psv/p/prv/prn/pr/ps/wdt/pq/psn/pqn): intermediate point on a journey - stopover location, waystation or routing point, location
5. start point, also known as start location, launch pad, launch site, starting place, starting point (wd:P1427 as pqv/wdtn/psv/p/prv/prn/pr/ps/wdt/pq/psn/pqn): starting place of this journey, flight, voyage, trek, migration etc., source of transfer, location
6. traffic sign, also known as road sign, trail blazer, shield, route shield, route marker (wd:P14 as pqv/wdtn/psv/p/prv/prn/pr/ps/wdt/pq/psn/pqn): graphic symbol describing the item, used at the side of or above roads to give instructions or provide information to road users, logo image
7. transport network, also known as transport network, transit network, tram network, trail system, system of routes (wd:P16 as pqv/wdtn/psv/p/prv/prn/pr/ps/wdt/pq/psn/pqn): network the infrastructure is a part of, part of
8. bases on balls, also known as BB, walks total, walks career total, walks, number of walks (wd:P9188 as pqv/wdtn/psv/p/prv/prn/pr/ps/wdt/pq/psn/pqn): number of walks in a baseball career or game(s)
9. located on street, also known as on street, street address, street, square, road (wd:P669 as pqv/wdtn/psv/p/prv/prn/pr/ps/wdt/pq/psn/pqn): street, road, or square, where the item is located. To add the n...perty P6375 "street address", if there is no item for the street, location, part of
10. in operation on service, also known as transport route of vehicle, transport route operated, transport route served, transport route serviced, used on route (wd:P10788 as pqv/wdtn/psv/p/prv/prn/pr/ps/wdt/pq/psn/pqn): service that a vehicle is operating on

No other items found

[Assistant]
From the search results, there is no direct property that indicates a route is a pilgrims' way. However, we can use the property `wdt:P31` (instance of) to check if a route is an instance of a pilgrims' way. We will need to find the entity for "pilgrims' way" first.

Let's search for the entity for "pilgrims' way".

[Tool]
Falling back to an unconstrained search on the full precomputed search indices:
SPARQL query contains no IRIs to constrain with

Top 10 entity alternatives:
1. pilgrims' way, also known as pilgrimage route, Pilgrim Path, pilgrim way (wd:Q337912): a standard route that pilgrims take
2. Pilgrims' Way (wd:Q2095007): historic route in England
3. Pilgrims Way (wd:Q108837890): 1988 novel by Abdulrazak Gurnah
4. Pilgrims' Way (wd:Q7193974): English folk band
5. Xemxija Heritage Trail, also known as Pilgrims Way, The Roman Way (wd:Q124424370): Hiking heritage trail in St. Paul's Bay, Malta
6. Pilgrims Way (wd:Q26633201): architectural structure in Stock and Bradley, Wychavon, Worcestershire, England, UK
7. Pilgrims Way Cottage (wd:Q26483917): cottage in Puttenham, Guildford, Surrey, England, UK
8. Pilgrims Way Surgery (wd:Q131525168): doctors surgery in Dartford, Kent, United Kingdom
9. The Pilgrims' Way (wd:Q119756170): painting by Joseph Longhurst (1874–1922), Brighton & Hove Museums
10. Pilgrims way of Epidaurus, also known as Epidaurus Sacred Way (wd:Q80844127): ancient sacred road connecting Epidaurus to the Asclepieion

No other items found

[Assistant]
From the search results, the entity for "pilgrims' way" is `wd:Q337912`.

Now we have all the necessary components to construct the SPARQL query:
- The entity for the Camino de Santiago (Way of Saint James) is `wd:Q41150`.
- The property for being part of a route is `wdt:P16`.
- The property for coordinates is `wdt:P625`.
- The property for being an instance of a pilgrims' way is `wdt:P31` with the value `wd:Q337912`.

Let's construct the SPARQL query to find the items that are part of the Camino de Santiago, their coordinates, and the routes they are part of, where those routes are instances of a pilgrims' way.

[Tool] Got no rows and 5 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 structured in the way we expected or the properties and entities not being correctly linked.

Let's refine our approach:

1. **Check if the Camino de Santiago has any parts or components**: We will list the triples where the Camino de Santiago is the subject to see if there are any relevant properties and objects.
2. **Check if there are any routes that are instances of a pilgrims' way**: We will list the triples where the object is `wd:Q337912` to see if there are any relevant routes.

Let's start by listing the triples where the Camino de Santiago is the subject.

[Tool]
Got 490 rows and 3 columns, showing the first 10 rows below:
| subject                        | property                                                  | object                                                                                |
| ------------------------------ | --------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------- |
| Way of Saint James (wd:Q41150) | instance of (wdt:P31)                                     | trail system (wd:Q67179750)                                                                                |
| Way of Saint James (wd:Q41150) | country (wdt:P17)                                         | Spain (wd:Q29)                                                                                |
| Way of Saint James (wd:Q41150) | located in the administrative territorial entity (p:P131) | s:Q41150-d7dcc26b-43f9-d6e4-129f-43b16304a8d8                                                                                |
| Way of Saint James (wd:Q41150) | coordinate location (wdt:P625)                            | POINT(-8.543889 42.880561)                                                                                |
| Way of Saint James (wd:Q41150) | Commons category (wdt:P373)                               | Way of Saint James                                                                                |
| Way of Saint James (wd:Q41150) | image (wdt:P18)                                           | <http://commons.wikimedia.org/wiki/Special:FilePath/Catedral%20de%20Santiago%20de%20Compostela%20agosto%202018%20%28cropped%29.jpg> |
| Way of Saint James (wd:Q41150) | heritage designation (wdt:P1435)                          | Bien de Interés Cultural (wd:Q23712)                                                                                |
| Way of Saint James (wd:Q41150) | has part(s) (wdt:P527)                                    | Routes of Santiago de Compostela...cés and Routes of Northern Spain (wd:Q39081159)                                                  |
| Way of Saint James (wd:Q41150) | on focus list of Wikimedia project (wdt:P5008)            | wd:Q6173448                                                                                |
| Way of Saint James (wd:Q41150) | different from (wdt:P1889)                                | Way of St. James (wd:Q475699)                                                                                |
| ...                            | ...                                                       | ...                                                                                |

[Assistant]
From the list of triples, we can see that the Camino de Santiago (Way of Saint James) has several parts, as indicated by the `wdt:P527` (has part) property. This suggests that we should look for items that are part of the Camino de Santiago using this property.

Additionally, we can see that the Camino de Santiago is an instance of a trail system (`wd:Q67179750`), which might be a more general category than a pilgrims' way.

Let's refine our query to use the `wdt:P527` property to find the parts of the Camino de Santiago and their coordinates. We will also check if these parts are part of any routes that are instances of a pilgrims' way.

### Step 4: Construct the SPARQL Query
We will use the `wdt:P527` property to find the parts of the Camino de Santiago, their coordinates, and the routes they are part of, where those routes are instances of a pilgrims' way.

Here is the refined SPARQL query:

[Tool] Got no rows and 5 columns

[Assistant]
It seems that the query still did not return any results. This suggests that the parts of the Camino de Santiago might not be directly linked to routes that are instances of a pilgrims' way using the `wdt:P16` property.

Let's take a different approach:
1. **Find the parts of the Camino de Santiago** using the `wdt:P527` property.
2. **Find the coordinates of these parts** using the `wdt:P625` property.
3. **Find the routes these parts are part of** using the `wdt:P16` property.
4. **Check if these routes are instances of a pilgrims' way** using the `wdt:P31` property.

We will break this down into smaller steps to ensure we are capturing the correct data.

### Step 1: Find the Parts of the Camino de Santiago
Let's start by finding the parts of the Camino de Santiago using the `wdt:P527` property.

### Step 2: Find the Coordinates of These Parts
We will then find the coordinates of these parts using the `wdt:P625` property.

### Step 3: Find the Routes These Parts Are Part Of
We will find the routes these parts are part of using the `wdt:P16` property.

### Step 4: Check if These Routes Are Instances of a Pilgrims' Way
Finally, we will check if these routes are instances of a pilgrims' way using the `wdt:P31` property.

Let's start with the first step.

[Tool]
Got 16 rows and 2 columns, showing the first 5 and last 5 rows below:
| ?part                                                                              | ?partLabel                                                          |
| ---------------------------------------------------------------------------------- | ------------------------------------------------------------------- |
| Way of Saint James in Austria (wd:Q1250609)                                        | Way of Saint James in Austria                                       |
| Routes of Santiago de Compostela...cés and Routes of Northern Spain (wd:Q39081159) | Routes of Santiago de Compostela...cés and Routes of Northern Spain |
| Way of Saint James in Spain (wd:Q64866310)                                         | Way of Saint James in Spain                                         |
| Way of Saint James in Czechia (wd:Q64866320)                                       | Way of Saint James in Czechia                                       |
| Way of Saint James in Italy (wd:Q64866323)                                         | Way of Saint James in Italy                                         |
| ...                                                                                | ...                                                                 |
| Way of Saint James in Luxemburg (wd:Q64866405)                                     | Way of Saint James in Luxemburg                                     |
| Way of Saint James in Belgium (wd:Q64866573)                                       | Way of Saint James in Belgium                                       |
| Way of Saint James in Slovenia (wd:Q64866723)                                      | Way of Saint James in Slovenia                                      |
| Way of Saint James in Hungary (wd:Q64866724)                                       | Way of Saint James in Hungary                                       |
| ViaJacobi (wd:Q7924357)                                                            | ViaJacobi                                                           |

[Assistant]
We have successfully found the parts of the Camino de Santiago. Now, let's find the coordinates of these parts using the `wdt:P625` property.

### Step 2: Find the Coordinates of These Parts
We will execute a query to find the coordinates of the parts of the Camino de Santiago.

Here is the SPARQL query for this step:

[Tool]
Got 2 rows and 3 columns:
| ?part                                                                              | ?partLabel                                                          | ?coordinates               |
| ---------------------------------------------------------------------------------- | ------------------------------------------------------------------- | -------------------------- |
| Routes of Santiago de Compostela...cés and Routes of Northern Spain (wd:Q39081159) | Routes of Santiago de Compostela...cés and Routes of Northern Spain | POINT(-6.414722 43.335000) |
| Way of Saint James in Czechia (wd:Q64866320)                                       | Way of Saint James in Czechia                                       | POINT(15.124914 49.808510) |

[Assistant]
We have found the coordinates for some of the parts of the Camino de Santiago. Next, we need to find the routes these parts are part of using the `wdt:P16` property.

### Step 3: Find the Routes These Parts Are Part Of
We will execute a query to find the routes these parts are part of.

Here is the SPARQL query for this step:

[Tool] Got no rows and 5 columns

[Assistant]
It seems that the parts of the Camino de Santiago are not directly linked to routes using the `wdt:P16` property. This suggests that the relationship might be more complex or the data might not be structured in the way we expected.

Let's take a different approach:
1. **Find the parts of the Camino de Santiago** using the `wdt:P527` property.
2. **Find the coordinates of these parts** using the `wdt:P625` property.
3. **Find the routes these parts are part of** using a broader search, possibly using the `wdt:P31` property to check if they are instances of a pilgrims' way.

### Step 3: Find the Routes These Parts Are Part Of
We will use a broader search to find the routes these parts are part of and check if they are instances of a pilgrims' way.

Here is the SPARQL query for this step:

[Tool]
Got 1 row and 5 columns:
| ?part                                        | ?partLabel                    | ?coordinates               | ?route                        | ?routeLabel      |
| -------------------------------------------- | ----------------------------- | -------------------------- | ----------------------------- | ---------------- |
| Way of Saint James in Czechia (wd:Q64866320) | Way of Saint James in Czechia | POINT(15.124914 49.808510) | Way of St. James (wd:Q475699) | Way of St. James |

[Assistant]
We have found one part of the Camino de Santiago, its coordinates, and the route it is part of, which is an instance of a pilgrims' way.

### Final SPARQL Query
Based on the results, we can finalize the SPARQL query to find the items that are part of the Camino de Santiago, their coordinates, and the routes they are part of, where those routes are instances of a pilgrims' way.

Here is the final SPARQL query:

```sparql
SELECT ?part ?partLabel ?coordinates ?route ?routeLabel
WHERE {
  wd:Q41150 wdt:P527 ?part .
  ?part wdt:P625 ?coordinates .
  ?part wdt:P31 ?route .
  ?route wdt:P31 wd:Q337912 .
  OPTIONAL { ?part rdfs:label ?partLabel . FILTER(LANG(?partLabel) = 'en') }
  OPTIONAL { ?route rdfs:label ?routeLabel . FILTER(LANG(?routeLabel) = 'en') }
}
```

This query returns the following results:
- `?part`: The part of the Camino de Santiago.
- `?partLabel`: The label of the part.
- `?coordinates`: The coordinates of the part.
- `?route`: The route the part is part of.
- `?routeLabel`: The label of the route.

Let's provide the final answer based on this query.

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX xsd: <http://www.w3.org/2001/XMLSchema#>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?ship ?shipLabel ?serviceEntryDate WHERE {
  ?ship wdt:P31 wd:Q11446 .
  ?ship wdt:P729 ?serviceEntryDate .
  FILTER ( ?serviceEntryDate >= '1939-01-01' ^^ xsd:date && ?serviceEntryDate <= '1946-12-31' ^^ xsd:date ) .
  {
    ?ship wdt:P17 wd:Q20
  } UNION {
    ?ship wdt:P137 wd:Q20
  }
  .
  OPTIONAL {
    ?ship rdfs:label ?shipLabel .
    FILTER ( LANG( ?shipLabel ) = 'en' )
  }
}

The Norwegian ship that entered operational service between 1939 and 1946, along with its service entry date, is: - **Ship**: Lindenes - **Service Entry Date**: 1943-01-01

[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 Norwegian ships entered operational service between 1939 and 1946, along with their service entry dates?

[Assistant]
To answer this question, we need to identify the relevant entities and properties in the knowledge graph. We are looking for ships that are:

1. Norwegian (i.e., they belong to Norway).
2. Entered operational service between 1939 and 1946.
3. Have a known service entry date.

Let's start by searching for the property that represents the service entry date of a ship. We can also look for the entity representing Norway and the class of ships.

[Tool]
Falling back to an unconstrained search on the full precomputed search indices:
SPARQL query contains no IRIs to constrain with

Top 10 entity alternatives:
1. service entry, also known as in service, time of service entry, service introduction, launch date, first light (wd:P729): date or point in time on which a piece or class of equipment entered operational service
2. service entry, also known as beginning-of-life phase, commissioning, entry into service, placing in service, project commissioning (wd:Q29933828): act of placing in active service
3. service retirement, also known as date of service retirement, time of service retirement, retirement, retired, out of service (wd:P730): date or point in time on which a piece or class of equipment was...from operational service ; use P2669 for end of a public service
4. effective date, also known as Effective Date, date of entry into force, date of commencement, commencement date, as of date (wd:Q5347252): the date upon which something is considered to take effect
5. How Service Is Dated (wd:Q42350647): scientific article published on July 1867
6. How Service Is Dated (wd:Q42424281): scientific article published on April 1867
7. inferred from date of position held, also known as deduced from date of position held, deduced from date of service, inferred from date of service (wd:Q108479125): heuristic for sourcing Wikidata statements by estimating the approximate date of activity
8. Brightline slates fares and service date (wd:Q110987241)
9. Date of Service for Pension Grievance (wd:Q42360403): scientific article published on December 1909
10. Datek Online, also known as Datek Online Brokerage Services, Datek Online Holdings Corporation (wd:Q56816206)

No other items found

[Assistant]
From the search results, the property `service entry` (wd:P729) seems to be the most relevant for our query. It represents the date or point in time on which a piece or class of equipment entered operational service.

Next, let's search for the entity representing Norway and the class of ships.

[Tool]
Falling back to an unconstrained search on the full precomputed search indices:
SPARQL query contains no IRIs to constrain with

Top 10 entity alternatives:
1. Norway, also known as Kingdom of Norway (wd:Q20): country in Northern Europe
2. Norway, also known as Norway, Iowa, Norway, IA (wd:Q1913264): city in Iowa, United States
3. Norway, also known as Norway, MI, Norway, Michigan (wd:Q2480177): city in Dickinson County, Michigan, United States
4. Norway, also known as Norway, SC, Norway, South Carolina (wd:Q3243583): town in South Carolina
5. Kingdom of Norway, also known as Norway, Norwegian Empire (wd:Q2196956): former Kingdom from 872 to 1397
6. Norway, also known as Norway, Maine, Norway, ME (wd:Q2734330): town in Maine, USA
7. Norway, also known as Norway, IN, Norway, Indiana (wd:Q2118814): census-designated place in Indiana
8. Kingdom of Norway, also known as Norway, Norwegian Kingdom (wd:Q2597352): short-lived monarchy in Northern Europe (1814)
9. Norway, also known as Norway, New York, Norway, NY (wd:Q944765): town in New York, USA
10. Norway, also known as Norway, WI (wd:Q3046928): town in Wisconsin, USA

No other items found

[Assistant]
The entity representing Norway (the country) is `wd:Q20`.

Now, let's search for the class of ships. We can use a broader term like "ship" and then filter for Norwegian ships later.

[Tool]
Falling back to an unconstrained search on the full precomputed search indices:
SPARQL query contains no IRIs to constrain with

Top 10 entity alternatives:
1. ship, also known as water vessel, vessel, marine vessel, ships (wd:Q11446): large buoyant watercraft
2. Shippensburg University of Pennsylvania, also known as Ship, ship.edu, Shipenburg, Shipensburg, Shippenburg (wd:Q7498066): public university in Shippensburg, Pennsylvania, United States
3. INPP5D, also known as hp51CN, inositol polyphosphate-5-phosphatase D, p150Ship, SHIP, SHIP-1 (wd:Q18027947): protein-coding gene in the species Homo sapiens
4. Morena Ship, also known as Ship (wd:Q21472350): hill in Antarctica
5. The Ship, also known as Ship, The Ship, Fitzrovia (wd:Q24022978): public house in New Cavendish Street, London, UK
6. The Ship, also known as Ship (wd:Q7763836): episode of Star Trek: Deep Space Nine (S5 E2)
7. 🚢, also known as SHIP, U+1F6A2, ship emoji (wd:Q87581923): Unicode character
8. 𐇨, also known as 𐇨, U+101E8, ship, PHAISTOS DISC SIGN SHIP (wd:Q87545964): Phaistos disc sign ship (U+101E8), 25th sign
9. Search for Hidden Particles, also known as SHiP (wd:Q108443828): Particle physics experiment at CERN
10. The Ship Public House, also known as Ship (wd:Q26666058): pub in Plymouth, Devon, England, UK

No other items found

[Assistant]
The entity representing the class of ships is `wd:Q11446`.

Now that we have the relevant entities and properties, we can start building our SPARQL query. We need to find ships that are instances of `wd:Q11446` (ships), have a service entry date between 1939 and 1946, and are associated with Norway (`wd:Q20`).

Let's write a basic query to find these ships and their service entry dates.

[Tool]
SPARQL execution failed:
Error while executing a SERVICE request to <http://wikiba.se:80/ontology#label>: SERVICE responded with HTTP status code: 301, Moved Permanently. First 100 bytes of the response: '<html>
<head><title>301 Moved Permanently</title></head>
<body>
<center><h1>301 Moved Permanently'

[Assistant]
It looks like the `SERVICE wikibase:label` is causing an issue. As per the rules, we should avoid using it and instead use `rdfs:label` to get the labels.

Let's modify the query to use `rdfs:label` and re-execute it.

[Tool]
Got 590 rows and 3 columns, showing the first 5 and last 5 rows below:
| ?ship                      | ?shipLabel  | ?serviceEntryDate    |
| -------------------------- | ----------- | -------------------- |
| D'Arsonval (wd:Q101775168) | D'Arsonval  | 1941-01-01T00:00:00Z |
| Iran (wd:Q101778560)       | Iran        | 1941-01-01T00:00:00Z |
| Silva (wd:Q101778635)      | Silva       | 1939-01-01T00:00:00Z |
| Fangturm (wd:Q101793696)   | Fangturm    | 1944-01-01T00:00:00Z |
| wd:Q102189442              |             | 1939-01-01T00:00:00Z |
| ...                        | ...         | ...                  |
| Narew (wd:Q97992964)       | Narew       | 1939-01-01T00:00:00Z |
| Coast Angel (wd:Q97994341) | Coast Angel | 1945-01-01T00:00:00Z |
| Blue Gadus (wd:Q97995941)  | Blue Gadus  | 1944-01-01T00:00:00Z |
| BGM-H12 (wd:Q97999540)     | BGM-H12     | 1942-01-01T00:00:00Z |
| Kattenturm (wd:Q98003660)  | Kattenturm  | 1944-01-01T00:00:00Z |

[Assistant]
The query has returned a list of ships that entered operational service between 1939 and 1946, along with their service entry dates. However, we need to ensure that these ships are Norwegian. To do this, we need to filter the results to include only those ships that are associated with Norway.

We can use the `wdt:P36` property to check if the ship is associated with Norway (`wd:Q20`). Let's update the query to include this filter.

[Tool] Got no rows and 3 columns

[Assistant]
It appears that there are no ships in the knowledge graph that meet all the criteria: being a ship, entering operational service between 1939 and 1946, and being associated with Norway.

However, it's possible that the association with Norway might be represented differently. Instead of using `wdt:P36` (country), we can try using `wdt:P17` (country of origin) or `wdt:P137` (operator) to see if we can find any Norwegian ships.

Let's update the query to include these additional properties.

[Tool]
Got 1 row and 3 columns:
| ?ship                   | ?shipLabel | ?serviceEntryDate    |
| ----------------------- | ---------- | -------------------- |
| Lindenes (wd:Q20111712) | Lindenes   | 1943-01-01T00:00:00Z |

[Assistant]
The query has returned one Norwegian ship that entered operational service between 1939 and 1946, along with its service entry date. The ship is `Lindenes`, which entered service on January 1, 1943.

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

```sparql
SELECT ?ship ?shipLabel ?serviceEntryDate WHERE {
  ?ship wdt:P31 wd:Q11446 .
  ?ship wdt:P729 ?serviceEntryDate .
  FILTER(?serviceEntryDate >= '1939-01-01'^^xsd:date && ?serviceEntryDate <= '1946-12-31'^^xsd:date) .
  { ?ship wdt:P17 wd:Q20 } UNION { ?ship wdt:P137 wd:Q20 } .
  OPTIONAL { ?ship rdfs:label ?shipLabel . FILTER(LANG(?shipLabel) = 'en') }
}
```

The Norwegian ship that entered operational service between 1939 and 1946, along with its service entry date, is:

- **Ship**: Lindenes
- **Service Entry Date**: 1943-01-01

[Tool] Stopped generation process


PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX wd: <http://www.wikidata.org/entity/>
SELECT ?poem WHERE {
  ?poem wdt:P31 wd:Q5185279 .
  ?poem wdt:P6216 wd:Q19652 .
  OPTIONAL {
    ?poem wdt:P407 ?language .
  }
  FILTER ( ?language = wd:Q1860 || ! BOUND( ?language ) ) .
  FILTER NOT EXISTS {
    ?poem wdt:P51 ?audio .
  }
}
LIMIT 10

The poems in the public domain, either in English or with no specified language, and without an audio recording are:
- Death’s Ramble (wd:Q100774453)
- No one knows me (wd:Q100923811)
- Gerontion (wd:Q10289249)
- Endimion & Phœbe (wd:Q104450438)
- Junior Yell (wd:Q104451306)
- Philadelphia Rosary (wd:Q104591336)
- Casabianca (wd:Q1046613)
- wd:Q10556773
- instructiones 2 (wd:Q106048798)
- exodus (wd:Q106065164)

[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 poems are in the public domain, either in English or with no specified language, and do not have an audio recording?

[Assistant]
To construct a SPARQL query that answers the user's question, I need to identify the relevant entities and properties. The key elements are:

1. Poems (items that are instances of poem)
2. Public domain status (license or copyright status)
3. Language (English or unspecified)
4. Audio recordings (absence of audio recordings)

I'll start by searching for the entity representing "poem" and the property for "instance of".

[Tool]
Falling back to an unconstrained search on the full precomputed search indices:
SPARQL query contains no IRIs to constrain with

Top 10 entity alternatives:
1. poem, also known as poems, poetry (wd:Q5185279): form of literature, work of poetry, often composed of verses
2. long poem, also known as poem (wd:Q1782649): poetry genre, poetic form
3. NPNT, also known as EGFL6L, nephronectin, POEM (wd:Q18053814): protein-coding gene in the species Homo sapiens
4. poem (wd:Q19415001): poem written by Mostafa Saadeq Al-Rafe'ie
5. Poem, also known as Poetry (wd:Q19423189): Poem written by Abdullah ibn al-Mu'tazz
6. Poem (wd:Q7207343): song by nu metal band Taproot
7. Poem (wd:Q7207339): album by industrial/electronic music group Delerium
8. Poem (wd:Q56525947): Greek band
9. Poem (wd:Q2893205): 1981 album by Bridges
10. The Summer Moon, also known as Poem (wd:Q19100286): 1912

No other items found

[Assistant] From the search results, the most appropriate entity for "poem" is `wd:Q5185279`. Next, I need to find the property for "instance of". I will search for this property now.

[Tool]
Falling back to an unconstrained search on the full precomputed search indices:
SPARQL query contains no IRIs to constrain with

Top 10 property alternatives:
1. instance of, also known as unitary element of class, has type, unique individual of, type, item of type (wd:P31 as pqv/wdtn/psv/p/prv/prn/pr/ps/wdt/pq/psn/pqn): that class of which this subject is a particular example and mem...is a subclass of mountain (and an instance of volcanic landform)
2. Wikidata property example, also known as e.g., Wikidata property sample, property sample, property example, for example (wd:P1855 as pqv/wdtn/psv/p/prv/prn/pr/ps/wdt/pq/psn/pqn): example where this Wikidata property is used; target item is one...ualifier the property being described given the associated value
3. quantity, also known as amount, total number, total, qty, occurrences (wd:P1114 as pqv/wdtn/psv/p/prv/prn/pr/ps/wdt/pq/psn/pqn): number of instances of this subject in the universe of the subje...e actual number of instances in Wikidata may be lower or higher)
4. subproperty of, also known as subclass of property, superproperty, subPropertyOf, rdfs:subPropertyOf, parent property (wd:P1647 as pqv/wdtn/psv/p/prv/prn/pr/ps/wdt/pq/psn/pqn): all resources related by this property are also related by that property, related property
5. partially coincident with, also known as intersecting with, has overlap with, has common parts with, has common members with, has common instances with (wd:P1382 as pqv/wdtn/psv/p/prv/prn/pr/ps/wdt/pq/psn/pqn): object that partially overlaps with the subject in its instances, parts, or members, different from
6. model item, also known as specimen, sample, featured item, example item, best example (wd:P5869 as pqv/wdtn/psv/p/prv/prn/pr/ps/wdt/pq/psn/pqn): defines which item is a best practice example of modelling a sub...lue of this property, usage instructions at Wikidata:Model items
7. permanent duplicated item, also known as same concept as, same as, duplicate of, permanently duplicated item, duplicate of item (wd:P2959 as pqv/wdtn/psv/p/prv/prn/pr/ps/wdt/pq/psn/pqn): this item duplicates another item and the two can't be merged, a... cdowiki, gomwiki, nanwiki).  Use P31=Q17362920 for other wikis.
8. exemplar of, also known as contains work, includes work, contents (wd:P1574 as pqv/wdtn/psv/p/prv/prn/pr/ps/wdt/pq/psn/pqn): Links an individual copy of a work to the item for that work or edition, instance of
9. usage example, also known as sentence, use in a sentence, example sentence (wd:P5831 as pqv/wdtn/psv/p/prv/prn/pr/ps/wdt/pq/psn/pqn): example of how a lexeme (sense) might be used
10. fictional or mythical analog of, also known as fictionalisation of, mythical analog of, fictional version of, fictionalization of, fictional analog of (wd:P1074 as pqv/wdtn/psv/p/prv/prn/pr/ps/wdt/pq/psn/pqn): used to link an entity or class of entities appearing in a creat...with the analogous entity or class of entities in the real world, inspired by

No other items found

[Assistant] The property for "instance of" is `wd:P31`. Now, I need to find the property for "public domain" or "copyright status". I will search for this property next.

[Tool]
Falling back to an unconstrained search on the full precomputed search indices:
SPARQL query contains no IRIs to constrain with

Top 10 property alternatives:
1. public domain date, also known as copyright end date, PD date (wd:P3893 as pqv/wdtn/psv/p/prv/prn/pr/ps/wdt/pq/psn/pqn): date the item enters into the public domain in a jurisdiction
2. copyright status, also known as copyrighted, copyright restriction (wd:P6216 as pqv/wdtn/psv/p/prv/prn/pr/ps/wdt/pq/psn/pqn): copyright status for intellectual creations like works of art, publications, software, etc.
3. after a work by, also known as inspirational artist, inspiring artist, copy of a work by, based on a work by, artist who inspired this (wd:P1877 as pqv/wdtn/psv/p/prv/prn/pr/ps/wdt/pq/psn/pqn): artist whose work strongly inspired / was copied in this item, significant person
4. notable work, also known as artwork, wrote, writer of, works, work (wd:P800 as pqv/wdtn/psv/p/prv/prn/pr/ps/wdt/pq/psn/pqn): notable scientific, artistic or literary work, or other work of significance among subject's works
5. copyright status as a creator, also known as statut des droits d'auteur du createur, copyright status of creator's works, copyright status as creator, copyright status of works (wd:P7763 as pqv/wdtn/psv/p/prv/prn/pr/ps/wdt/pq/psn/pqn): states if the body of work published during the lifetime of this creator is still copyrighted or in the public domain
6. copyright holder, also known as licensor, proprietor, copyright owner, copyright ‘owner’ (wd:P3931 as pqv/wdtn/psv/p/prv/prn/pr/ps/wdt/pq/psn/pqn): person or organisation who holds the copyright of a work according to the Berne Convention, owned by
7. catalog, also known as catalogue, registry, exhibition catalogue, cat. (wd:P972 as pqv/wdtn/psv/p/prv/prn/pr/ps/wdt/pq/psn/pqn): catalog for the item, or, as a qualifier of P528 – catalog for which the 'catalog code' is valid, part of
8. derivative work, also known as is source work of, is adapted as, is the basis for, iteration, reboot (wd:P4969 as pqv/wdtn/psv/p/prv/prn/pr/ps/wdt/pq/psn/pqn): new work of art (film, book, software, etc.) derived from major part of this work
9. LIBRIS editions (wd:P1182 as pqv/wdtn/psv/p/prv/prn/pr/ps/wdt/pq/psn/pqn): the identifier for the items in the LIBRIS-catalog of the Royal Swedish Library about specific publications
10. phonographic copyright, also known as ℗, (P) (wd:P12456 as pqv/wdtn/psv/p/prv/prn/pr/ps/wdt/pq/psn/pqn): person or organization that holds the phonographic copyright

No other items found

[Assistant] The property for "copyright status" is `wd:P6216`. Next, I need to find the value for "public domain" and the property for "language". I will search for these now.

[Tool]
No entity items found

No other items found

No literal items found

[Assistant]
It seems that there are no direct values for "public domain" linked to the `wd:P6216` property. However, I can try searching for the term "public domain" to see if it appears as an entity that might be used in this context.

I will also search for the property for "language" while I'm at it.

[Tool]
Falling back to an unconstrained search on the full precomputed search indices:
SPARQL query contains no IRIs to constrain with

Top 10 entity alternatives:
1. public domain, also known as 🅮, DP, out of copyright, PD (wd:Q19652): no exclusive intellectual property rights apply
2. public sphere, also known as public domain, publicity, public life (wd:Q17945): area in social life
3. public domain (wd:Q5871222): ปนัดดา คงหนองลาน มั่นหาญ
4. Public Domain (wd:Q7758689): online magazine
5. Public Domain (wd:Q20200052): British band
6. Public Domain (wd:Q20813938): 2000 album by Dave Alvin
7. Public Domain (wd:Q7257358): 2003 Canadian film about reality TV directed by Kris Lefcoe
8. The Public Domain, also known as Public Domain (wd:Q19824841): 2015 film
9. DP, also known as DOMAINE PUBLIC NON IDENTIFIE, dominio popular, D.P., DP DP, public domain (wd:Q59754537): special purpose artist used for songwriting credits in the public domain, composer, lyricist
10. public domain (wd:Q15687061): duplicate of Q19652 used to test workaround for QuickStatements limitations

No other items found

No literal items found

[Assistant] The entity for "public domain" is `wd:Q19652`. Now, I will search for the property for "language".

[Tool]
Falling back to an unconstrained search on the full precomputed search indices:
SPARQL query contains no IRIs to constrain with

Top 10 property alternatives:
1. programmed in, also known as language, programming language, written in (wd:P277 as pqv/wdtn/psv/p/prv/prn/pr/ps/wdt/pq/psn/pqn): the programming language(s) in which the software is developed
2. languages spoken, written or signed, also known as language of expression, language, wrote language, writes language, uses language (wd:P1412 as pqv/wdtn/psv/p/prv/prn/pr/ps/wdt/pq/psn/pqn): language(s) that a person or a people speaks, writes or signs, including the native language(s)
3. language of work or name, also known as language of the reference, language of URL, language of website, language of work, named in language (wd:P407 as pqv/wdtn/psv/p/prv/prn/pr/ps/wdt/pq/psn/pqn): language associated with this creative work (such as books, show...guage" (P103) and "languages spoken, written or signed" (P1412))
4. official language, also known as language spoken, spoken in, speaking, language official (wd:P37 as pqv/wdtn/psv/p/prv/prn/pr/ps/wdt/pq/psn/pqn): language designated as official by this item, language used
5. language used, also known as languages used, medium of instruction, used language, uses language, working language (wd:P2936 as pqv/wdtn/psv/p/prv/prn/pr/ps/wdt/pq/psn/pqn): language widely used (spoken or written) in this place or at this event or organisation
6. language style, also known as manner, term register, obsolete, register, sense register (wd:P6191 as pqv/wdtn/psv/p/prv/prn/pr/ps/wdt/pq/psn/pqn): to denote of the way a sense of a word is used, e.g., slang, vulgarism, babytalk, colloquialism, etc.
7. native language, also known as first language, L1 speaker of, language native, mother tongue (wd:P103 as pqv/wdtn/psv/p/prv/prn/pr/ps/wdt/pq/psn/pqn): language or languages a person has learned from early childhood, languages spoken, written or signed
8. writing language, also known as languages of writings, languages written, language written, writing languages, language of works (wd:P6886 as pqv/wdtn/psv/p/prv/prn/pr/ps/wdt/pq/psn/pqn): language in which the writer has written their work, languages spoken, written or signed
9. Ethnologue language status, also known as EGIDS, language status (wd:P3823 as pqv/wdtn/psv/p/prv/prn/pr/ps/wdt/pq/psn/pqn): language status identifier by Ethnologue.com using EGIDS scale
10. variety of lexeme, form or sense, also known as dialect, used in dialect, variety of form (wd:P7481 as pqv/wdtn/psv/p/prv/prn/pr/ps/wdt/pq/psn/pqn): dialect, graphic or phonetic variety that this lexeme, form or sense is used in

No other items found

[Assistant] The property for "language of work or name" is `wd:P407`. Now, I need to find the entity for "English" and the property for "audio recording". I will search for these now.

[Tool]
Falling back to an unconstrained search on the full precomputed search indices:
SPARQL query contains no IRIs to constrain with

Top 10 entity alternatives:
1. English, also known as English language, English-language, English the Global Language, English (language), The English language (wd:Q1860): West Germanic language
2. English, also known as English (language), The English language, English the Global Language, English-language, English language (wd:Q1860): West Germanic language
3. English people, also known as Englishmen, the English, people of England, English (wd:Q42406): citizens of England
4. English studies, also known as English philology, English major, English language and literature, English (academic discipline), English language (wd:Q27968): discipline that studies the English language and literature
5. English, also known as English, Indiana, English, IN (wd:Q2017605): town in and the county seat of Sterling Township, Crawford County, Indiana, United States
6. Aiden English, also known as English, Matt Rehwoldt (wd:Q3852026): American professional wrestler, professional wrestler, stage actor
7. English language in England, also known as Anglo-English, English English, English in England, English of England (wd:Q3312722): dialects of British English from England
8. UFC Fight Night: Thompson vs. Till, also known as English (wd:Q53831565): English
9. English, also known as AAE, Black English (wd:Q48767245): set of English dialects primarily spoken by most black people in the United States
10. English (wd:Q15924427): family name

No other items found

No literal items found

[Assistant] The entity for "English" is `wd:Q1860`. Now, I need to find the property for "audio recording". I will search for this property next.

[Tool]
Falling back to an unconstrained search on the full precomputed search indices:
SPARQL query contains no IRIs to constrain with

Top 10 property alternatives:
1. audio, also known as audio file, audio recording, audio sample, recording, song (wd:P51 as pqv/wdtn/psv/p/prv/prn/pr/ps/wdt/pq/psn/pqn): relevant sound. If available, use a more specific property. Samples: "spoken text audio" (P989), "pronunciation audio" (P443)
2. audio recording of the subject's spoken voice, also known as voice recording, audio clip, spoken voice, speaking voice, recording of the subject's spoken voice (wd:P990 as pqv/wdtn/psv/p/prv/prn/pr/ps/wdt/pq/psn/pqn): audio file representing the speaking voice of a person; or of an animated cartoon or other fictitious character, audio
3. recordist, also known as audio recorder, audio recordist, recorded by, video recorder, video recordist (wd:P10893 as pqv/wdtn/psv/p/prv/prn/pr/ps/wdt/pq/psn/pqn): the person or other agent who recorded the audio and/or video for this file
4. recording or performance of, also known as performance of, performance or recording of, recording of (wd:P2550 as pqv/wdtn/psv/p/prv/prn/pr/ps/wdt/pq/psn/pqn): item is a recording or release of this composition
5. performer, also known as actor, sung by, singer, recording by, recorded by (wd:P175 as pqv/wdtn/psv/p/prv/prn/pr/ps/wdt/pq/psn/pqn): actor, musician, band or other performer associated with this role or musical work, contributor to the creative work or subject
6. captured with, also known as camera used, taken with, recording device, recorded with, photographed with (wd:P4082 as pqv/wdtn/psv/p/prv/prn/pr/ps/wdt/pq/psn/pqn): equipment (e.g. model of camera, lens, microphone), used to capture this image, video, audio, or data
7. audio transcription, also known as transcription of audio (wd:P9533 as pqv/wdtn/psv/p/prv/prn/pr/ps/wdt/pq/psn/pqn): transcription of the word/text being spoken in this file
8. recording location, also known as recorded at (wd:P8546 as pqv/wdtn/psv/p/prv/prn/pr/ps/wdt/pq/psn/pqn): location where a media item (sound, video, etc.) was recorded, significant place
9. audio system, also known as audio format (wd:P7501 as pqv/wdtn/psv/p/prv/prn/pr/ps/wdt/pq/psn/pqn): audio system hardware used in the item
10. media legend, also known as video legend, video description, video caption, caption, media description (wd:P2096 as pqv/wdtn/psv/p/prv/prn/pr/ps/wdt/pq/psn/pqn): qualifier to describe the media of the statement. This avoids le...the media is defined at Wikidata. For the date, use P585 instead

No other items found

[Assistant]
The property for "audio recording" is `wd:P51`. Now, I have all the necessary components to construct the SPARQL query. Here is the breakdown:

1. **Poem**: `wd:Q5185279`
2. **Instance of**: `wd:P31`
3. **Public domain**: `wd:P6216` with value `wd:Q19652`
4. **Language**: `wd:P407` with value `wd:Q1860` (English) or no specified language
5. **Audio recording**: `wd:P51` should not exist

I will start by constructing a basic query to find poems that are in the public domain and either in English or have no specified language. Then, I will add the condition to exclude poems with audio recordings.

Let's start with the basic query and check the results.

[Tool]
Got 10 rows and 1 column:
| ?poem                               |
| ----------------------------------- |
| Death’s Ramble (wd:Q100774453)      |
| No one knows me (wd:Q100923811)     |
| Gerontion (wd:Q10289249)            |
| Endimion & Phœbe (wd:Q104450438)    |
| Junior Yell (wd:Q104451306)         |
| Philadelphia Rosary (wd:Q104591336) |
| Casabianca (wd:Q1046613)            |
| wd:Q10556773                        |
| instructiones 2 (wd:Q106048798)     |
| exodus (wd:Q106065164)              |

[Assistant]
The initial query returns a list of poems that are in the public domain and either in English or have no specified language. Now, I need to add the condition to exclude poems that have an audio recording (`wd:P51`). I will modify the query to include this condition and re-run it.

Here is the updated query:

[Tool]
Got 10 rows and 1 column:
| ?poem                               |
| ----------------------------------- |
| Death’s Ramble (wd:Q100774453)      |
| No one knows me (wd:Q100923811)     |
| Gerontion (wd:Q10289249)            |
| Endimion & Phœbe (wd:Q104450438)    |
| Junior Yell (wd:Q104451306)         |
| Philadelphia Rosary (wd:Q104591336) |
| Casabianca (wd:Q1046613)            |
| wd:Q10556773                        |
| instructiones 2 (wd:Q106048798)     |
| exodus (wd:Q106065164)              |

[Assistant]
The updated query successfully returns a list of poems that are in the public domain, either in English or with no specified language, and do not have an audio recording. The results look correct and meet the criteria specified in the user's question.

I will now provide the final SPARQL query and the answer to the user's question.

Here is the final SPARQL query:

```sparql
SELECT ?poem WHERE {
  ?poem wdt:P31 wd:Q5185279 .
  ?poem wdt:P6216 wd:Q19652 .
  OPTIONAL { ?poem wdt:P407 ?language . }
  FILTER(?language = wd:Q1860 || !BOUND(?language)) .
  FILTER NOT EXISTS { ?poem wdt:P51 ?audio . }
} LIMIT 10
```

And here is the answer to the user's question:

The poems in the public domain, either in English or with no specified language, and without an audio recording are:
- Death’s Ramble (wd:Q100774453)
- No one knows me (wd:Q100923811)
- Gerontion (wd:Q10289249)
- Endimion & Phœbe (wd:Q104450438)
- Junior Yell (wd:Q104451306)
- Philadelphia Rosary (wd:Q104591336)
- Casabianca (wd:Q1046613)
- wd:Q10556773
- instructiones 2 (wd:Q106048798)
- exodus (wd:Q106065164)

[Tool] Stopped generation process