PREFIX orkgp: <http://orkg.org/orkg/predicate/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT DISTINCT ?model ?modelLabel WHERE {
  ?benchmark orkgp:HAS_DATASET <http://orkg.org/orkg/resource/R121031> .
  ?benchmark orkgp:HAS_EVALUATION ?evaluation .
  ?evaluation orkgp:HAS_MODEL ?model .
  OPTIONAL {
    ?model rdfs:label ?modelLabel .
  }
}

The SPARQL query is correct for retrieving models evaluated on the Penn Treebank (Character Level) dataset, following the expected schema (benchmark → dataset, benchmark → evaluation, evaluation → model). However, the query returned no results. This likely means that the ORKG knowledge graph currently does not contain any models evaluated on this dataset, or the relevant data is incomplete or uses different properties. You may consider checking for alternative properties linking evaluations to models, or for alternative identifiers for the dataset, as a refinement.

[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:
orkg at http://localhost:7054

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

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

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

[User] What models are being evaluated on the Penn Treebank (Character Level) dataset?

[Assistant]
Let's break down the question:

1. We are looking for "models" (probably machine learning models or algorithms).
2. These models are being "evaluated on" a specific dataset: "Penn Treebank (Character Level)".

First, I need to identify the entity for the "Penn Treebank (Character Level)" dataset in the ORKG knowledge graph. Then, I need to find models that are evaluated on this dataset. This likely involves finding a property that connects models to datasets they are evaluated on.

I'll start by searching for the "Penn Treebank (Character Level)" entity.

[Tool]
Top 10 entity alternatives:
1. Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R121031>): has type Dataset
2. Benchmark Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R130721>): has type Benchmark
3. Benchmark Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R130550>): has type Benchmark
4. Benchmark Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R130730>): has type Benchmark
5. Benchmark Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R130952>): has type Benchmark
6. Benchmark Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R130915>): has type Benchmark
7. Benchmark Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R130849>): has type Benchmark
8. Benchmark Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R130783>): has type Benchmark
9. Benchmark Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R130765>): has type Benchmark
10. Benchmark Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R130761>): has type Benchmark

[Assistant]
I found several entities related to "Penn Treebank (Character Level)" in the ORKG knowledge graph. The most direct match is:

- Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R121031>) with type Dataset.

There are also several entities with the type Benchmark, but for now, I will focus on the main dataset entity.

Next, I need to find which models are evaluated on this dataset. This likely involves finding a property such as "evaluated on", "tested on", or "uses dataset". I'll search for properties related to "evaluation" to find the correct connection.

[Tool]
Top 10 property alternatives:
1. Evaluated on (orkgp:P41838)
2. evaluates (orkgp:P37290)
3. evaluation (orkgp:P5091)
4. evaluation (orkgp:P34)
5. evaluation (orkgp:HAS_EVALUATION)
6. evaluate (orkgp:P20041)
7. evaluate on (orkgp:P20042)
8. Has evaluation (orkgp:HasEvaluation)
9. method evaluated (orkgp:P82000)
10. Means of evaluation (orkgp:P36082)

[Assistant]
The most relevant property for connecting models to datasets they are evaluated on appears to be "Evaluated on" (orkgp:P41838).

Now, I will look for triples where the object is the Penn Treebank (Character Level) dataset (http://orkg.org/orkg/resource/R121031) and the property is "Evaluated on" (orkgp:P41838). This should give me the models evaluated on this dataset.

[Tool] Got no rows and 3 columns

[Assistant]
It appears that there are no direct triples using the "Evaluated on" property (orkgp:P41838) with the Penn Treebank (Character Level) dataset as the object. However, there are several entities with the type "Benchmark" for the Penn Treebank (Character Level). It's possible that models are evaluated on these benchmark entities instead of the dataset entity.

Next, I will try the same approach but use one of the "Benchmark Penn Treebank (Character Level)" entities (for example, the first one: http://orkg.org/orkg/resource/R130721) as the object.

[Tool] Got no rows and 3 columns

[Assistant]
There are still no results when using the "Evaluated on" property with the first "Benchmark Penn Treebank (Character Level)" entity. Since there are multiple benchmark entities, it's possible that models are linked to other benchmark variants.

To be thorough, I will try listing all subjects that use the "Evaluated on" property with any of the top benchmark entities. I'll try the next benchmark entity: http://orkg.org/orkg/resource/R130550.

[Tool] Got no rows and 3 columns

[Assistant]
Again, there are no results for the "Evaluated on" property with this benchmark entity. It is possible that a different property is used to link models to datasets or benchmarks in the ORKG knowledge graph.

To investigate further, I will search for properties related to "dataset" to see if another property is used to indicate that a model is evaluated on a dataset.

[Tool]
Top 10 property alternatives:
1. Dataset (orkgp:P96045)
2. dataset (orkgp:P2005)
3. Dataset used (orkgp:P25063)
4. Datasets (orkgp:P44054)
5. Uses dataset (orkgp:P18087)
6. dataset description (orkgp:P16037)
7. Datasets used (orkgp:P58072)
8. dataset format (orkgp:P62072)
9. Dataset name (orkgp:P34063)
10. Experimental Dataset (orkgp:P15096)

[Assistant]
Several properties could be relevant, such as:

- "Dataset used" (orkgp:P25063)
- "Uses dataset" (orkgp:P18087)
- "Datasets used" (orkgp:P58072)

I will try listing triples where the object is the Penn Treebank (Character Level) dataset (http://orkg.org/orkg/resource/R121031) and the property is "Dataset used" (orkgp:P25063).

[Tool] Got no rows and 3 columns

[Assistant] There are no results for the "Dataset used" property either. Since there are multiple dataset-related properties, I will try the next most likely one: "Uses dataset" (orkgp:P18087) with the Penn Treebank (Character Level) dataset as the object.

[Tool] Got no rows and 3 columns

[Assistant]
There are still no results for the "Uses dataset" property. Since none of the direct dataset or evaluation properties are yielding results, it's possible that the relationship is modeled differently in ORKG, perhaps through a more complex structure such as a "comparison" or "benchmarking" resource that links models and datasets together.

To investigate further, I will search for entities related to "model" and see how they are typically linked to datasets or benchmarks.

[Tool]
Top 10 entity alternatives:
1. Model (<http://orkg.org/orkg/resource/R150425>): has type Contribution Template
2. Model (<http://orkg.org/orkg/resource/R44212>)
3. Model (<http://orkg.org/orkg/resource/R150408>): has type Contribution Template
4. Model (<http://orkg.org/orkg/resource/R50465>): has type Sentence, has type Model
5. Model (<http://orkg.org/orkg/resource/R50479>): has type Sentence, has type Model
6. Model (<http://orkg.org/orkg/resource/R69780>)
7. Model (<http://orkg.org/orkg/resource/R50384>): has type Sentence, has type Model
8. Model (<http://orkg.org/orkg/resource/R44256>)
9. Model (<http://orkg.org/orkg/resource/R50367>): has type Sentence, has type Model
10. Model (<http://orkg.org/orkg/resource/R50366>): has type Sentence, has type Model

[Assistant]
I found several entities labeled "Model" with different IRIs and types, including "Contribution Template," "Sentence," and "Model." To understand how these models are linked to datasets or benchmarks, I will examine the properties associated with one of these model entities, for example, http://orkg.org/orkg/resource/R50465.

I'll search for properties of this entity to see if there is a connection to datasets or benchmarks.

[Tool]
Top 10 property alternatives:
1. has content (orkgp:hasContent)

No other items found

[Assistant]
The only property found for this model entity related to "dataset" is "has content" (orkgp:hasContent), which does not seem directly relevant to dataset evaluation.

Given that direct links are not found, it is possible that the relationship between models and datasets is captured within a "comparison" or "benchmark" resource, where models and datasets are both listed as part of an evaluation or experiment.

To explore this, I will look for properties related to "has model" or "model" within the "Benchmark Penn Treebank (Character Level)" entity (for example, http://orkg.org/orkg/resource/R130721).

[Tool]
Top 10 property alternatives:
1. has dataset (orkgp:HAS_DATASET)
2. evaluation (orkgp:HAS_EVALUATION)

No other items found

[Assistant]
For the "Benchmark Penn Treebank (Character Level)" entity, I found the properties "has dataset" (orkgp:HAS_DATASET) and "evaluation" (orkgp:HAS_EVALUATION). The "evaluation" property seems promising, as it might link to evaluation results or models.

I will now list triples where the subject is the benchmark entity (http://orkg.org/orkg/resource/R130721) and the property is "evaluation" (orkgp:HAS_EVALUATION) to see what objects are linked and if they represent models or evaluation results.

[Tool]
Got 2 rows and 3 columns:
| subject                                                                             | property                          | object                                                                             |
| ----------------------------------------------------------------------------------- | --------------------------------- | ---------------------------------------------------------------------------------- |
| Benchmark Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R130721>) | evaluation (orkgp:HAS_EVALUATION) | Evaluation Bit per Character (BPC)_1.175 (<http://orkg.org/orkg/resource/R130722>) |
| Benchmark Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R130721>) | evaluation (orkgp:HAS_EVALUATION) | Evaluation Number of params_13.8M (<http://orkg.org/orkg/resource/R130723>)        |

[Assistant]
The "evaluation" property links the benchmark entity to two evaluation result entities:

1. Evaluation Bit per Character (BPC)_1.175 (<http://orkg.org/orkg/resource/R130722>)
2. Evaluation Number of params_13.8M (<http://orkg.org/orkg/resource/R130723>)

These evaluation result entities may contain information about the model being evaluated. I will now check the properties of the first evaluation result entity (http://orkg.org/orkg/resource/R130722) to see if it links to a model.

[Tool]
Top 10 property alternatives:
1. value (orkgp:HAS_VALUE)
2. metric (orkgp:HAS_METRIC)

No other items found

[Assistant]
The evaluation result entity has properties "value" and "metric," but nothing directly referencing a "model." It's possible that the model information is stored under a different property or in a related entity.

To explore further, I'll list all properties for this evaluation result entity to see if any property links to a model or method.

[Tool]
Got 5 rows and 3 columns:
| subject                                                                            | property                  | object                                                            |
| ---------------------------------------------------------------------------------- | ------------------------- | ----------------------------------------------------------------- |
| Evaluation Bit per Character (BPC)_1.175 (<http://orkg.org/orkg/resource/R130722>) | value (orkgp:HAS_VALUE)   | 1.175 (xsd:string)                                                |
| Evaluation Bit per Character (BPC)_1.175 (<http://orkg.org/orkg/resource/R130722>) | metric (orkgp:HAS_METRIC) | Bit per Character (BPC) (<http://orkg.org/orkg/resource/R116794>) |
| Evaluation Bit per Character (BPC)_1.175 (<http://orkg.org/orkg/resource/R130722>) | rdf:type                  | Evaluation (orkgc:Evaluation)                                     |
| Evaluation Bit per Character (BPC)_1.175 (<http://orkg.org/orkg/resource/R130722>) | rdfs:label                | Evaluation Bit per Character (BPC)_1.175 (xsd:string)             |
| Evaluation Bit per Character (BPC)_1.175 (<http://orkg.org/orkg/resource/R130722>) | rdf:type                  | orkgc:Resource                                                    |

[Assistant]
The evaluation result entity does not directly reference a model. Since the evaluation entity is linked to the benchmark, and the benchmark is for a specific dataset, it's possible that the model is referenced elsewhere in the structure, perhaps in a higher-level comparison or experiment entity.

Given this, I will try searching for entities that mention both "Penn Treebank (Character Level)" and "model" in their labels or descriptions, as these might represent such comparison or experiment entities.

[Tool]
Top 10 entity alternatives:
1. Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R121031>): has type Dataset
2. Benchmark Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R130721>): has type Benchmark
3. Benchmark Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R130550>): has type Benchmark
4. Benchmark Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R130730>): has type Benchmark
5. Benchmark Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R130952>): has type Benchmark
6. Benchmark Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R130915>): has type Benchmark
7. Benchmark Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R130849>): has type Benchmark
8. Benchmark Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R130783>): has type Benchmark
9. Benchmark Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R130765>): has type Benchmark
10. Benchmark Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R130761>): has type Benchmark

[Assistant]
The search did not return any new entities that combine both "Penn Treebank (Character Level)" and "model" in their labels or descriptions—just the dataset and benchmark entities already found.

Given the structure observed, it seems that the models being evaluated may be referenced indirectly, possibly through the provenance of the evaluation results or in the context of a comparison resource.

As a next step, I will search for properties related to "method" or "approach" for the evaluation result entity (http://orkg.org/orkg/resource/R130722), as models are sometimes referenced as methods in such graphs.

[Tool]
Top 10 property alternatives:
1. metric (orkgp:HAS_METRIC)
2. value (orkgp:HAS_VALUE)

No other items found

[Assistant]
No properties related to "method" are found for the evaluation result entity. Since the direct approach is not yielding results, I will try a broader approach: searching for all entities that are linked to the Penn Treebank (Character Level) dataset (http://orkg.org/orkg/resource/R121031) via any property, to see if any of them represent models or experiments.

This may help uncover indirect relationships.

[Tool]
Got 12 rows and 3 columns, showing the first 10 rows below:
| subject                                                                             | property                        | object                                                                    |
| ----------------------------------------------------------------------------------- | ------------------------------- | ------------------------------------------------------------------------- |
| Benchmark Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R130550>) | has dataset (orkgp:HAS_DATASET) | Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R121031>) |
| Benchmark Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R130721>) | has dataset (orkgp:HAS_DATASET) | Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R121031>) |
| Benchmark Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R130730>) | has dataset (orkgp:HAS_DATASET) | Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R121031>) |
| Benchmark Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R130761>) | has dataset (orkgp:HAS_DATASET) | Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R121031>) |
| Benchmark Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R130765>) | has dataset (orkgp:HAS_DATASET) | Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R121031>) |
| Benchmark Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R130783>) | has dataset (orkgp:HAS_DATASET) | Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R121031>) |
| Benchmark Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R130849>) | has dataset (orkgp:HAS_DATASET) | Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R121031>) |
| Benchmark Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R130915>) | has dataset (orkgp:HAS_DATASET) | Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R121031>) |
| Benchmark Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R130952>) | has dataset (orkgp:HAS_DATASET) | Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R121031>) |
| Benchmark Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R130988>) | has dataset (orkgp:HAS_DATASET) | Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R121031>) |
| ...                                                                                | ...                             | ...                                                                       |

[Assistant]
All the entities linked to the Penn Treebank (Character Level) dataset are "Benchmark Penn Treebank (Character Level)" entities via the "has dataset" property. These benchmarks may aggregate evaluations for different models.

Given this, the best approach is to query for all models that are evaluated in the context of any of these benchmark entities. Since the evaluation results are linked to benchmarks, and the model might be referenced in the evaluation result or in a related structure, I will look for any "has model" or similar property in the context of these benchmarks.

I'll search for properties related to "model" for one of the benchmark entities, for example, http://orkg.org/orkg/resource/R130721.

[Tool]
Top 10 property alternatives:
1. has dataset (orkgp:HAS_DATASET)
2. evaluation (orkgp:HAS_EVALUATION)

No other items found

[Assistant]
No direct "has model" property is found for the benchmark entity. Since the benchmark links to evaluation result entities, and those do not directly reference models either, it is possible that the model is encoded in the label of the evaluation result or in a related entity.

Given this, I will construct a SPARQL query that retrieves all evaluation results linked to any "Benchmark Penn Treebank (Character Level)" entity, and for each evaluation result, attempts to retrieve any associated model entity or, if not available, the label of the evaluation result (which may contain the model name).

This approach will provide a comprehensive list of models (or at least their names as found in evaluation result labels) evaluated on the Penn Treebank (Character Level) dataset.

Here is the SPARQL query:

```sparql
SELECT DISTINCT ?evaluation ?evaluationLabel
WHERE {
  ?benchmark orkgp:HAS_DATASET <http://orkg.org/orkg/resource/R121031> .
  ?benchmark orkgp:HAS_EVALUATION ?evaluation .
  OPTIONAL { ?evaluation rdfs:label ?evaluationLabel. }
}
```

This will return all evaluation result entities for benchmarks of the Penn Treebank (Character Level) dataset, along with their labels, which may indicate the models being evaluated.

[Tool]
Got 21 rows and 2 columns, showing the first 5 and last 5 rows below:
| evaluation                                                                         | evaluationLabel                                       |
| ---------------------------------------------------------------------------------- | ----------------------------------------------------- |
| Evaluation Bit per Character (BPC)_1.160 (<http://orkg.org/orkg/resource/R130551>) | Evaluation Bit per Character (BPC)_1.160 (xsd:string) |
| Evaluation Number of params_10.7M (<http://orkg.org/orkg/resource/R130552>)        | Evaluation Number of params_10.7M (xsd:string)        |
| Evaluation Bit per Character (BPC)_1.175 (<http://orkg.org/orkg/resource/R130722>) | Evaluation Bit per Character (BPC)_1.175 (xsd:string) |
| Evaluation Number of params_13.8M (<http://orkg.org/orkg/resource/R130723>)        | Evaluation Number of params_13.8M (xsd:string)        |
| Evaluation Bit per Character (BPC)_1.187 (<http://orkg.org/orkg/resource/R130731>) | Evaluation Bit per Character (BPC)_1.187 (xsd:string) |
| ...                                                                                | ...                                                   |
| Evaluation Bit per Character (BPC)_1.214 (<http://orkg.org/orkg/resource/R130953>) | Evaluation Bit per Character (BPC)_1.214 (xsd:string) |
| Evaluation Number of params_16.3M (<http://orkg.org/orkg/resource/R130954>)        | Evaluation Number of params_16.3M (xsd:string)        |
| Evaluation Bit per Character (BPC)_1.31 (<http://orkg.org/orkg/resource/R130989>)  | Evaluation Bit per Character (BPC)_1.31 (xsd:string)  |
| Evaluation Bit per Character (BPC)_1.24 (<http://orkg.org/orkg/resource/R131007>)  | Evaluation Bit per Character (BPC)_1.24 (xsd:string)  |
| Evaluation Bit per Character (BPC)_1.38 (<http://orkg.org/orkg/resource/R131088>)  | Evaluation Bit per Character (BPC)_1.38 (xsd:string)  |

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The current SPARQL query retrieves evaluation results associated with benchmarks on the Penn Treebank (Character Level) dataset, but it does not directly answer the user's question about which models are being evaluated. The query should be refined to explicitly retrieve the models (entities) that are evaluated on this dataset. This likely requires identifying the property that links benchmarks or evaluations to models (e.g., orkgp:HAS_MODEL or similar) and including it in the SELECT clause. The answer should list the IRIs of the models, optionally with their labels. Please refine the query to directly return the models being evaluated.

[Assistant]
Thank you for the feedback. You are correct: the previous query only retrieved evaluation results, not the models themselves. To refine the query, I need to identify the property that links evaluation results (or benchmarks) to models—likely something like orkgp:HAS_MODEL or a similar property.

Step 1: Search for properties related to "model" that might connect evaluation results or benchmarks to model entities.

[Tool]
Top 10 property alternatives:
1. model (orkgp:P20072)
2. model (orkgp:P1004)
3. models (orkgp:P71209)
4. Models (orkgp:P43024)
5. model type (orkgp:P71176)
6. Proposed model (orkgp:P59015)
7. Mathematical model (orkgp:P41907)
8. has model (orkgp:hasModel)
9. Has model (orkgp:P9018)
10. has model (orkgp:HAS_MODEL)

[Assistant]
There are several promising properties for linking to models, including:

- has model (orkgp:hasModel)
- Has model (orkgp:P9018)
- has model (orkgp:HAS_MODEL)
- model (orkgp:P20072), etc.

Step 2: Check which of these properties are actually used in the context of evaluation results or benchmarks for the Penn Treebank (Character Level) dataset. I will list triples for one of the evaluation result entities (e.g., http://orkg.org/orkg/resource/R130722) using any of these "has model" properties to see if a model is linked.

[Tool]
Got 5 rows and 3 columns:
| subject                                                                            | property                  | object                                                            |
| ---------------------------------------------------------------------------------- | ------------------------- | ----------------------------------------------------------------- |
| Evaluation Bit per Character (BPC)_1.175 (<http://orkg.org/orkg/resource/R130722>) | value (orkgp:HAS_VALUE)   | 1.175 (xsd:string)                                                |
| Evaluation Bit per Character (BPC)_1.175 (<http://orkg.org/orkg/resource/R130722>) | metric (orkgp:HAS_METRIC) | Bit per Character (BPC) (<http://orkg.org/orkg/resource/R116794>) |
| Evaluation Bit per Character (BPC)_1.175 (<http://orkg.org/orkg/resource/R130722>) | rdf:type                  | Evaluation (orkgc:Evaluation)                                     |
| Evaluation Bit per Character (BPC)_1.175 (<http://orkg.org/orkg/resource/R130722>) | rdfs:label                | Evaluation Bit per Character (BPC)_1.175 (xsd:string)             |
| Evaluation Bit per Character (BPC)_1.175 (<http://orkg.org/orkg/resource/R130722>) | rdf:type                  | orkgc:Resource                                                    |

[Assistant]
None of the "has model" properties are present for this evaluation result entity. Since the evaluation result does not directly link to a model, it's possible that the benchmark entity itself might link to a model, or that another property is used.

Next, I will list all triples for one of the benchmark entities (e.g., http://orkg.org/orkg/resource/R130721) to see if any of the "has model" properties are used there.

[Tool]
Got 6 rows and 3 columns:
| subject                                                                             | property                          | object                                                                             |
| ----------------------------------------------------------------------------------- | --------------------------------- | ---------------------------------------------------------------------------------- |
| Benchmark Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R130721>) | evaluation (orkgp:HAS_EVALUATION) | Evaluation Bit per Character (BPC)_1.175 (<http://orkg.org/orkg/resource/R130722>) |
| Benchmark Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R130721>) | has dataset (orkgp:HAS_DATASET)   | Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R121031>)          |
| Benchmark Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R130721>) | rdf:type                          | Benchmark (orkgc:Benchmark)                                                        |
| Benchmark Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R130721>) | rdfs:label                        | Benchmark Penn Treebank (Character Level) (xsd:string)                             |
| Benchmark Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R130721>) | evaluation (orkgp:HAS_EVALUATION) | Evaluation Number of params_13.8M (<http://orkg.org/orkg/resource/R130723>)        |
| Benchmark Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R130721>) | rdf:type                          | orkgc:Resource                                                                     |

[Assistant]
No "has model" property is present on the benchmark entity either. Since neither the evaluation result nor the benchmark directly links to a model, it's possible that the model is referenced in a different way, perhaps as a subject of the evaluation or through another related entity.

To be thorough, I will check if any of the evaluation result entities are the object of a "has model" property. I will list triples where the property is "has model" (orkgp:HAS_MODEL).

[Tool]
Got 658 rows and 3 columns, showing the first 10 rows below:
| subject                                                                   | property                    | object                                                      |
| ------------------------------------------------------------------------- | --------------------------- | ----------------------------------------------------------- |
| Contribution  DDQN (tuned) hs (<http://orkg.org/orkg/resource/R132605>)   | has model (orkgp:HAS_MODEL) | DDQN (tuned) hs (<http://orkg.org/orkg/resource/R124898>)   |
| Contribution  DQN hs (<http://orkg.org/orkg/resource/R132805>)            | has model (orkgp:HAS_MODEL) | DQN hs (<http://orkg.org/orkg/resource/R124911>)            |
| Contribution  Prior+Duel hs (<http://orkg.org/orkg/resource/R132906>)     | has model (orkgp:HAS_MODEL) | Prior+Duel hs (<http://orkg.org/orkg/resource/R124919>)     |
| Contribution  DQN noop (<http://orkg.org/orkg/resource/R132706>)          | has model (orkgp:HAS_MODEL) | DQN noop (<http://orkg.org/orkg/resource/R124908>)          |
| Contribution  Prior hs (<http://orkg.org/orkg/resource/R132500>)          | has model (orkgp:HAS_MODEL) | Prior hs (<http://orkg.org/orkg/resource/R124895>)          |
| Contribution  Prior noop (<http://orkg.org/orkg/resource/R132401>)        | has model (orkgp:HAS_MODEL) | Prior noop (<http://orkg.org/orkg/resource/R124894>)        |
| Contribution  A3C FF hs (<http://orkg.org/orkg/resource/R133504>)         | has model (orkgp:HAS_MODEL) | A3C FF hs (<http://orkg.org/orkg/resource/R124913>)         |
| Contribution  A3C FF (1 day) hs (<http://orkg.org/orkg/resource/R133605>) | has model (orkgp:HAS_MODEL) | A3C FF (1 day) hs (<http://orkg.org/orkg/resource/R124914>) |
| Contribution  A3C LSTM hs (<http://orkg.org/orkg/resource/R133706>)       | has model (orkgp:HAS_MODEL) | A3C LSTM hs (<http://orkg.org/orkg/resource/R124921>)       |
| Contribution  Duel noop (<http://orkg.org/orkg/resource/R131981>)         | has model (orkgp:HAS_MODEL) | Duel noop (<http://orkg.org/orkg/resource/R124891>)         |
| ...                                                                       | ...                         | ...                                                         |

[Assistant]
The "has model" property (orkgp:HAS_MODEL) links "Contribution" entities to model entities. This suggests that the structure is: Contribution → has model → Model.

To connect this to the Penn Treebank (Character Level) dataset, I need to check if these "Contribution" entities are also linked to the dataset, either directly or via a benchmark.

I'll check if any "Contribution" entities are linked to the Penn Treebank (Character Level) dataset via a property such as "has dataset" (orkgp:HAS_DATASET).

[Tool]
Got 12 rows and 3 columns, showing the first 10 rows below:
| subject                                                                             | property                        | object                                                                    |
| ----------------------------------------------------------------------------------- | ------------------------------- | ------------------------------------------------------------------------- |
| Benchmark Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R130550>) | has dataset (orkgp:HAS_DATASET) | Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R121031>) |
| Benchmark Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R130721>) | has dataset (orkgp:HAS_DATASET) | Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R121031>) |
| Benchmark Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R130730>) | has dataset (orkgp:HAS_DATASET) | Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R121031>) |
| Benchmark Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R130761>) | has dataset (orkgp:HAS_DATASET) | Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R121031>) |
| Benchmark Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R130765>) | has dataset (orkgp:HAS_DATASET) | Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R121031>) |
| Benchmark Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R130783>) | has dataset (orkgp:HAS_DATASET) | Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R121031>) |
| Benchmark Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R130849>) | has dataset (orkgp:HAS_DATASET) | Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R121031>) |
| Benchmark Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R130915>) | has dataset (orkgp:HAS_DATASET) | Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R121031>) |
| Benchmark Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R130952>) | has dataset (orkgp:HAS_DATASET) | Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R121031>) |
| Benchmark Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R130988>) | has dataset (orkgp:HAS_DATASET) | Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R121031>) |
| ...                                                                                | ...                             | ...                                                                       |

[Assistant]
Only "Benchmark Penn Treebank (Character Level)" entities are linked to the dataset via "has dataset." Since "Contribution" entities are not directly linked, perhaps the connection is: Benchmark → has evaluation → Contribution → has model → Model.

Let me check if "Benchmark Penn Treebank (Character Level)" entities link to "Contribution" entities via the "evaluation" property, and if those contributions then link to models. I'll list the objects of the "evaluation" property for a benchmark and see if they are "Contribution" entities.

[Tool]
Got 2 rows and 3 columns:
| subject                                                                             | property                          | object                                                                             |
| ----------------------------------------------------------------------------------- | --------------------------------- | ---------------------------------------------------------------------------------- |
| Benchmark Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R130721>) | evaluation (orkgp:HAS_EVALUATION) | Evaluation Bit per Character (BPC)_1.175 (<http://orkg.org/orkg/resource/R130722>) |
| Benchmark Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R130721>) | evaluation (orkgp:HAS_EVALUATION) | Evaluation Number of params_13.8M (<http://orkg.org/orkg/resource/R130723>)        |

[Assistant]
The "evaluation" property links benchmarks to evaluation result entities, not directly to contributions. However, since "Contribution" entities use the "has model" property, perhaps the evaluation results are linked to contributions in another way.

To check this, I will see if the evaluation result entity (e.g., http://orkg.org/orkg/resource/R130722) is linked to a contribution entity via any property.

[Tool]
Got 1 row and 3 columns:
| subject                                                                             | property                          | object                                                                             |
| ----------------------------------------------------------------------------------- | --------------------------------- | ---------------------------------------------------------------------------------- |
| Benchmark Penn Treebank (Character Level) (<http://orkg.org/orkg/resource/R130721>) | evaluation (orkgp:HAS_EVALUATION) | Evaluation Bit per Character (BPC)_1.175 (<http://orkg.org/orkg/resource/R130722>) |

[Assistant]
The only link to the evaluation result entity is from the benchmark via the "evaluation" property. There is no direct link to a contribution entity.

Given this, it appears that the ORKG knowledge graph does not directly link models to benchmarks or evaluation results for the Penn Treebank (Character Level) dataset using the "has model" property or similar. The structure seems to lack an explicit connection between models and the evaluation results for this dataset.

Therefore, I cannot construct a SPARQL query that directly returns the models evaluated on the Penn Treebank (Character Level) dataset, as the necessary links are not present in the current data.

Here is my best attempt at a query that would work if such links existed:

```sparql
SELECT DISTINCT ?model ?modelLabel WHERE {
  ?benchmark orkgp:HAS_DATASET <http://orkg.org/orkg/resource/R121031> .
  ?benchmark orkgp:HAS_EVALUATION ?evaluation .
  ?evaluation orkgp:HAS_MODEL ?model .
  OPTIONAL { ?model rdfs:label ?modelLabel. }
}
```

But based on the data, this query will not return any results.

I will now provide this explanation and my best attempt at a query.

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The explanation is partially correct: the query structure is logical and follows the expected relationships (benchmark → dataset, benchmark → evaluation, evaluation → model). However, the query itself is a valid attempt and should have been executed and its result reported, which it was (no rows). The explanation should clarify that the query is correct given the schema, but the lack of results likely means that the knowledge graph does not contain any models evaluated on the Penn Treebank (Character Level) dataset, or that the data is incomplete or uses different properties. The answer should emphasize that the query is correct, but the data is missing or incomplete, rather than implying that such a query cannot be constructed at all. Suggest checking for alternative properties or dataset identifiers as a refinement.

[Tool] Got no rows and 2 columns

[Tool] Stopped generation process


PREFIX orkgp: <http://orkg.org/orkg/predicate/>
SELECT DISTINCT ?metric WHERE {
  ?benchmark orkgp:HAS_DATASET <http://orkg.org/orkg/resource/R124960> .
  ?benchmark orkgp:HAS_EVALUATION ?eval .
  ?eval orkgp:HAS_METRIC ?metric .
}

The commonly used evaluation metric for benchmarking models on the Atari 2600 Berzerk dataset is 'Score' (http://orkg.org/orkg/resource/R119875).

[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:
orkg at http://localhost:7054

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

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

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

[User] What evaluation metrics are commonly used when benchmarking models on the Atari 2600 Berzerk dataset?

[Assistant]
First, I need to identify the relevant entities and properties in the question:

- "evaluation metrics": likely entities or classes representing metrics or measures.
- "benchmarking models": possibly related to evaluation, experiments, or tasks.
- "Atari 2600 Berzerk dataset": a specific dataset, so I need to find its entity.

My plan:
1. Search for the "Atari 2600 Berzerk" dataset entity.
2. Search for properties related to "evaluation metrics" or "metrics" in the context of datasets or benchmarks.
3. Combine these to find which metrics are associated with benchmarking models on this dataset.

Step 1: Search for the "Atari 2600 Berzerk" dataset entity.

[Tool]
Top 10 entity alternatives:
1. Atari 2600 Berzerk (<http://orkg.org/orkg/resource/R124960>): has type Dataset
2. Benchmark Atari 2600 Berzerk (<http://orkg.org/orkg/resource/R132626>): has type Benchmark
3. Benchmark Atari 2600 Berzerk (<http://orkg.org/orkg/resource/R132521>): has type Benchmark
4. Benchmark Atari 2600 Berzerk (<http://orkg.org/orkg/resource/R132422>): has type Benchmark
5. Benchmark Atari 2600 Berzerk (<http://orkg.org/orkg/resource/R132303>): has type Benchmark
6. Benchmark Atari 2600 Berzerk (<http://orkg.org/orkg/resource/R132204>): has type Benchmark
7. Benchmark Atari 2600 Berzerk (<http://orkg.org/orkg/resource/R132103>): has type Benchmark
8. Benchmark Atari 2600 Berzerk (<http://orkg.org/orkg/resource/R132002>): has type Benchmark
9. Benchmark Atari 2600 Berzerk (<http://orkg.org/orkg/resource/R131899>): has type Benchmark
10. Benchmark Atari 2600 Berzerk (<http://orkg.org/orkg/resource/R132727>): has type Benchmark

[Assistant]
I found several relevant entities:
- "Atari 2600 Berzerk" dataset: <http://orkg.org/orkg/resource/R124960>
- Multiple "Benchmark Atari 2600 Berzerk" entities, each likely representing a specific benchmark instance.

To answer the question about evaluation metrics commonly used for benchmarking models on this dataset, I should focus on the dataset entity and its associated benchmarks.

Next, I need to identify properties related to "evaluation metrics" or "metrics" that are used in the context of these benchmarks.

Step 2: Search for properties related to "evaluation metric" in ORKG.

[Tool]
Top 10 property alternatives:
1. Evaluation metrics (orkgp:P41532)
2. Has evaluation metrics (orkgp:P35217)
3. Performance metric (orkgp:P5003)
4. Automatic Evaluation Metrics (orkgp:P37517)
5. evaluation (orkgp:P5091)
6. evaluation (orkgp:P34)
7. evaluation (orkgp:HAS_EVALUATION)
8. Evaluation method (orkgp:P59089)
9. Performance metrics (orkgp:P49059)
10. Evaluation results (orkgp:P25064)

[Assistant]
I found several relevant properties:
- Evaluation metrics (orkgp:P41532)
- Has evaluation metrics (orkgp:P35217)
- Performance metric (orkgp:P5003)
- Automatic Evaluation Metrics (orkgp:P37517)
- Performance metrics (orkgp:P49059)

To determine which metrics are commonly used, I should look for connections between the Atari 2600 Berzerk dataset (or its benchmarks) and these properties.

Step 3: List triples where the subject is the Atari 2600 Berzerk dataset and the property is any of the evaluation metric properties. I'll start with "Evaluation metrics" (orkgp:P41532).

[Tool] Got no rows and 3 columns

[Assistant]
There are no direct triples linking the Atari 2600 Berzerk dataset entity to evaluation metrics via the "Evaluation metrics" property. Since benchmarks are often modeled as separate entities, and there are many "Benchmark Atari 2600 Berzerk" entities, I should check if these benchmarks are linked to evaluation metrics.

Step 4: List triples where the subject is one of the "Benchmark Atari 2600 Berzerk" entities and the property is "Evaluation metrics" (orkgp:P41532). I'll start with the first benchmark entity: <http://orkg.org/orkg/resource/R132626>.

[Tool] Got no rows and 3 columns

[Assistant]
There are no direct triples linking the first benchmark entity to evaluation metrics via "Evaluation metrics" (orkgp:P41532). I should try another common property, such as "Has evaluation metrics" (orkgp:P35217), with the same benchmark entity.

Step 5: List triples where the subject is <http://orkg.org/orkg/resource/R132626> and the property is "Has evaluation metrics" (orkgp:P35217).

[Tool] Got no rows and 3 columns

[Assistant]
There are still no direct links using "Has evaluation metrics". It's possible that the metrics are linked via another property, or that they are associated with results or performance metrics.

Step 6: Try the "Performance metric" property (orkgp:P5003) with the same benchmark entity.

[Tool] Got no rows and 3 columns

[Assistant]
There are still no direct links using "Performance metric". Since there are multiple benchmark entities, and the metrics might be linked to other benchmark instances, I should try listing all properties for one of the benchmark entities to see how metrics might be represented.

Step 7: List all properties for the benchmark entity <http://orkg.org/orkg/resource/R132626>.

[Tool]
Got 5 rows and 3 columns:
| subject                                                                | property                          | object                                                            |
| ---------------------------------------------------------------------- | --------------------------------- | ----------------------------------------------------------------- |
| Benchmark Atari 2600 Berzerk (<http://orkg.org/orkg/resource/R132626>) | evaluation (orkgp:HAS_EVALUATION) | Evaluation Score_1011.1 (<http://orkg.org/orkg/resource/R132627>) |
| Benchmark Atari 2600 Berzerk (<http://orkg.org/orkg/resource/R132626>) | has dataset (orkgp:HAS_DATASET)   | Atari 2600 Berzerk (<http://orkg.org/orkg/resource/R124960>)      |
| Benchmark Atari 2600 Berzerk (<http://orkg.org/orkg/resource/R132626>) | rdf:type                          | Benchmark (orkgc:Benchmark)                                       |
| Benchmark Atari 2600 Berzerk (<http://orkg.org/orkg/resource/R132626>) | rdfs:label                        | Benchmark Atari 2600 Berzerk (xsd:string)                         |
| Benchmark Atari 2600 Berzerk (<http://orkg.org/orkg/resource/R132626>) | rdf:type                          | orkgc:Resource                                                    |

[Assistant]
The benchmark entity is linked to an "Evaluation Score" entity via the property "evaluation" (orkgp:HAS_EVALUATION). This suggests that evaluation metrics might be associated with these "Evaluation Score" entities.

Step 8: List all properties for the "Evaluation Score_1011.1" entity (<http://orkg.org/orkg/resource/R132627>) to see if it specifies which metric is used.

[Tool]
Got 5 rows and 3 columns:
| subject                                                           | property                  | object                                          |
| ----------------------------------------------------------------- | ------------------------- | ----------------------------------------------- |
| Evaluation Score_1011.1 (<http://orkg.org/orkg/resource/R132627>) | value (orkgp:HAS_VALUE)   | 1011.1 (xsd:string)                             |
| Evaluation Score_1011.1 (<http://orkg.org/orkg/resource/R132627>) | metric (orkgp:HAS_METRIC) | Score (<http://orkg.org/orkg/resource/R119875>) |
| Evaluation Score_1011.1 (<http://orkg.org/orkg/resource/R132627>) | rdf:type                  | Evaluation (orkgc:Evaluation)                   |
| Evaluation Score_1011.1 (<http://orkg.org/orkg/resource/R132627>) | rdfs:label                | Evaluation Score_1011.1 (xsd:string)            |
| Evaluation Score_1011.1 (<http://orkg.org/orkg/resource/R132627>) | rdf:type                  | orkgc:Resource                                  |

[Tool]
Got 3 rows and 3 columns:
| subject                                         | property   | object                |
| ----------------------------------------------- | ---------- | --------------------- |
| Score (<http://orkg.org/orkg/resource/R119875>) | rdf:type   | Metric (orkgc:Metric) |
| Score (<http://orkg.org/orkg/resource/R119875>) | rdfs:label | Score (xsd:string)    |
| Score (<http://orkg.org/orkg/resource/R119875>) | rdf:type   | orkgc:Resource        |

[Assistant]
The "Evaluation Score" entity is linked to a metric called "Score" (<http://orkg.org/orkg/resource/R119875>), which is of type Metric.

To answer the question about "commonly used" metrics, I should check if other benchmarks for Atari 2600 Berzerk also use this metric or if there are additional metrics used.

Step 9: For all "Benchmark Atari 2600 Berzerk" entities, find the metrics used in their evaluations.

I will write a SPARQL query to:
- Find all benchmarks for Atari 2600 Berzerk.
- For each benchmark, get its evaluations and the associated metric.

This will help identify all metrics commonly used for benchmarking models on this dataset.

[Tool]
Got 1 row and 2 columns:
| metric                                          | metricLabel        |
| ----------------------------------------------- | ------------------ |
| Score (<http://orkg.org/orkg/resource/R119875>) | Score (xsd:string) |

[Tool] Stopped generation process

[User]
Feedback (status=done):
The SPARQL query correctly retrieves the identifiers of the evaluation metrics used for benchmarking models on the Atari 2600 Berzerk dataset. It follows the rules by returning the actual IRIs and not stopping early. The answer is accurate and complete based on the available data.


PREFIX orkgp: <http://orkg.org/orkg/predicate/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?contribution ?contributionLabel ?code_link ?benchmark ?benchmarkLabel WHERE {
  ?contribution orkgp:HAS_MODEL <http://orkg.org/orkg/resource/R124891> .
  ?contribution orkgp:HAS_BENCHMARK ?benchmark .
  ?contribution orkgp:HAS_SOURCE_CODE ?code_link .
  OPTIONAL {
    ?contribution rdfs:label ?contributionLabel .
  }
  OPTIONAL {
    ?benchmark rdfs:label ?benchmarkLabel .
  }
}
LIMIT 100

Got 100 rows and 5 columns, showing the first 5 and last 5 rows below:
| contribution                                                      | contributionLabel                    | code_link                                                                        | benchmark                                                                     | benchmarkLabel                                   |
| ----------------------------------------------------------------- | ------------------------------------ | -------------------------------------------------------------------------------- | ----------------------------------------------------------------------------- | ------------------------------------------------ |
| Contribution  Duel noop (<http://orkg.org/orkg/resource/R131981>) | Contribution 	Duel noop (xsd:string) | https://github.com/austinsilveria/Banana-Collection-DQN (xsd:string)             | Benchmark Atari 2600 Seaquest (<http://orkg.org/orkg/resource/R131982>)       | Benchmark Atari 2600 Seaquest (xsd:string)       |
| Contribution  Duel noop (<http://orkg.org/orkg/resource/R131981>) | Contribution 	Duel noop (xsd:string) | https://github.com/abryeemessi/Wednesday (xsd:string)                            | Benchmark Atari 2600 Seaquest (<http://orkg.org/orkg/resource/R131982>)       | Benchmark Atari 2600 Seaquest (xsd:string)       |
| Contribution  Duel noop (<http://orkg.org/orkg/resource/R131981>) | Contribution 	Duel noop (xsd:string) | https://github.com/cocolico14/N-step-Dueling-DDQN-PER-Pacman (xsd:string)        | Benchmark Atari 2600 Seaquest (<http://orkg.org/orkg/resource/R131982>)       | Benchmark Atari 2600 Seaquest (xsd:string)       |
| Contribution  Duel noop (<http://orkg.org/orkg/resource/R131981>) | Contribution 	Duel noop (xsd:string) | https://github.com/Adrelf/DRL-navigation (xsd:string)                            | Benchmark Atari 2600 Seaquest (<http://orkg.org/orkg/resource/R131982>)       | Benchmark Atari 2600 Seaquest (xsd:string)       |
| Contribution  Duel noop (<http://orkg.org/orkg/resource/R131981>) | Contribution 	Duel noop (xsd:string) | https://github.com/eddynelson/dqn (xsd:string)                                   | Benchmark Atari 2600 Seaquest (<http://orkg.org/orkg/resource/R131982>)       | Benchmark Atari 2600 Seaquest (xsd:string)       |
| ...                                                               | ...                                  | ...                                                                              | ...                                                                           | ...                                              |
| Contribution  Duel noop (<http://orkg.org/orkg/resource/R131981>) | Contribution 	Duel noop (xsd:string) | https://github.com/nbopardi/smb (xsd:string)                                     | Benchmark Atari 2600 Name This Game (<http://orkg.org/orkg/resource/R131984>) | Benchmark Atari 2600 Name This Game (xsd:string) |
| Contribution  Duel noop (<http://orkg.org/orkg/resource/R131981>) | Contribution 	Duel noop (xsd:string) | https://github.com/nathanin/pad (xsd:string)                                     | Benchmark Atari 2600 Name This Game (<http://orkg.org/orkg/resource/R131984>) | Benchmark Atari 2600 Name This Game (xsd:string) |
| Contribution  Duel noop (<http://orkg.org/orkg/resource/R131981>) | Contribution 	Duel noop (xsd:string) | https://github.com/manvibharat/S...ing-Deep-reienforcement-learning (xsd:string) | Benchmark Atari 2600 Name This Game (<http://orkg.org/orkg/resource/R131984>) | Benchmark Atari 2600 Name This Game (xsd:string) |
| Contribution  Duel noop (<http://orkg.org/orkg/resource/R131981>) | Contribution 	Duel noop (xsd:string) | https://github.com/MEOWMEOW114/nd893-p1-navigation-banana (xsd:string)           | Benchmark Atari 2600 Name This Game (<http://orkg.org/orkg/resource/R131984>) | Benchmark Atari 2600 Name This Game (xsd:string) |
| Contribution  Duel noop (<http://orkg.org/orkg/resource/R131981>) | Contribution 	Duel noop (xsd:string) | https://github.com/mohit8935/Deep-Q-Learning-Paper (xsd:string)                  | Benchmark Atari 2600 Name This Game (<http://orkg.org/orkg/resource/R131984>) | Benchmark Atari 2600 Name This Game (xsd:string) |

This optimized query retrieves up to 100 code links from contributions that use the Duel noop model in any benchmark, along with the IRIs and human-readable labels for the contributions and benchmarks (where available). This should help avoid memory issues while still providing readable and relevant 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:
orkg at http://localhost:7054

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

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

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

[User] List the code links in papers that use the Duel noop model in any benchmark?

[Assistant]
Let's break down the question:

1. Entities:
   - "Duel noop model": This is likely a specific model or method.
   - "papers": We are interested in papers that use this model.
   - "benchmark": The papers should use the model in the context of any benchmark.
   - "code links": We want the code links from those papers.

2. Properties:
   - "uses model" or "uses method"
   - "benchmark"
   - "code link"

Step 1: Search for the "Duel noop model" entity in ORKG.

[Tool]
Top 10 entity alternatives:
1. Duel noop (<http://orkg.org/orkg/resource/R124891>): has type Model
2. Contribution  Duel noop (<http://orkg.org/orkg/resource/R131981>): has type Contribution
3. Model (<http://orkg.org/orkg/resource/R150425>): has type Contribution Template
4. Model (<http://orkg.org/orkg/resource/R44212>)
5. Model (<http://orkg.org/orkg/resource/R150408>): has type Contribution Template
6. Model (<http://orkg.org/orkg/resource/R50465>): has type Sentence, has type Model
7. Model (<http://orkg.org/orkg/resource/R50479>): has type Sentence, has type Model
8. Model (<http://orkg.org/orkg/resource/R69780>)
9. Model (<http://orkg.org/orkg/resource/R50384>): has type Sentence, has type Model
10. Model (<http://orkg.org/orkg/resource/R44256>)

[Assistant]
The top result for "Duel noop model" is Duel noop (<http://orkg.org/orkg/resource/R124891>), which is of type Model. This is likely the entity we want.

Next, we need to find papers that use this model in any benchmark and retrieve their code links.

Step 2: Let's search for properties related to "uses model" or "uses method" to find how papers might be linked to the Duel noop model.

[Tool]
Top 10 property alternatives:
1. model (orkgp:P20072)
2. model (orkgp:P1004)
3. model type (orkgp:P71176)
4. models (orkgp:P71209)
5. Models (orkgp:P43024)
6. Proposed model (orkgp:P59015)
7. uses Micro-Models (orkgp:P44136)
8. has model (orkgp:hasModel)
9. Has model (orkgp:P9018)
10. has model (orkgp:HAS_MODEL)

[Assistant]
There are several properties related to "model", but the most generic and likely candidates are:
- model (orkgp:P20072)
- model (orkgp:P1004)
- has model (orkgp:hasModel)
- Has model (orkgp:P9018)
- has model (orkgp:HAS_MODEL)

To be thorough, let's check which of these properties link papers (or contributions) to the Duel noop model entity.

Step 3: List triples where the object is Duel noop (<http://orkg.org/orkg/resource/R124891>) to see which properties are used.

[Tool]
Got 1 row and 3 columns:
| subject                                                           | property                    | object                                              |
| ----------------------------------------------------------------- | --------------------------- | --------------------------------------------------- |
| Contribution  Duel noop (<http://orkg.org/orkg/resource/R131981>) | has model (orkgp:HAS_MODEL) | Duel noop (<http://orkg.org/orkg/resource/R124891>) |

[Assistant]
The property used to link to the Duel noop model is has model (orkgp:HAS_MODEL), and the subject is "Contribution Duel noop" (<http://orkg.org/orkg/resource/R131981>).

Next, we need to find papers (or their contributions) that use this model in any benchmark. Usually, contributions are linked to papers, and benchmarks may be linked via a property.

Step 4: Let's check what properties are associated with the "Contribution Duel noop" entity to see if there are links to papers, benchmarks, and code links.

[Tool]
Got 114 rows and 3 columns, showing the first 10 rows below:
| subject                                                           | property                                | object                                                                  |
| ----------------------------------------------------------------- | --------------------------------------- | ----------------------------------------------------------------------- |
| Contribution  Duel noop (<http://orkg.org/orkg/resource/R131981>) | research problem (orkgp:P32)            | Atari Games (<http://orkg.org/orkg/resource/R124884>)                   |
| Contribution  Duel noop (<http://orkg.org/orkg/resource/R131981>) | has source code (orkgp:HAS_SOURCE_CODE) | https://github.com/170928/-Review-Dueling-Deep-Q-Network (xsd:string)   |
| Contribution  Duel noop (<http://orkg.org/orkg/resource/R131981>) | has benchmark (orkgp:HAS_BENCHMARK)     | Benchmark Atari 2600 Seaquest (<http://orkg.org/orkg/resource/R131982>) |
| Contribution  Duel noop (<http://orkg.org/orkg/resource/R131981>) | has model (orkgp:HAS_MODEL)             | Duel noop (<http://orkg.org/orkg/resource/R124891>)                     |
| Contribution  Duel noop (<http://orkg.org/orkg/resource/R131981>) | rdf:type                                | Contribution (orkgc:Contribution)                                       |
| Contribution  Duel noop (<http://orkg.org/orkg/resource/R131981>) | rdfs:label                              | Contribution 	Duel noop (xsd:string)                                    |
| Contribution  Duel noop (<http://orkg.org/orkg/resource/R131981>) | has source code (orkgp:HAS_SOURCE_CODE) | https://github.com/1jsingh/rl_navigation (xsd:string)                   |
| Contribution  Duel noop (<http://orkg.org/orkg/resource/R131981>) | has source code (orkgp:HAS_SOURCE_CODE) | https://github.com/abryeemessi/Wednesday (xsd:string)                   |
| Contribution  Duel noop (<http://orkg.org/orkg/resource/R131981>) | has source code (orkgp:HAS_SOURCE_CODE) | https://github.com/Adrelf/DRL-navigation (xsd:string)                   |
| Contribution  Duel noop (<http://orkg.org/orkg/resource/R131981>) | has source code (orkgp:HAS_SOURCE_CODE) | https://github.com/alessandrositta/Flatland_challenge (xsd:string)      |
| ...                                                               | ...                                     | ...                                                                     |

[Assistant]
From the triples, we see that:
- The contribution "Contribution Duel noop" is linked to several code links via has source code (orkgp:HAS_SOURCE_CODE).
- It is also linked to benchmarks via has benchmark (orkgp:HAS_BENCHMARK).
- The contribution is likely associated with a paper, but the direct paper link is not shown in the first 10 rows.

Since the question asks for code links in papers that use the Duel noop model in any benchmark, and the contribution already links the model, benchmarks, and code links, we can retrieve all code links from contributions that use the Duel noop model and have any benchmark.

Step 5: Let's generalize the query to find all contributions that:
- have model Duel noop,
- have any benchmark,
- and have code links.

We will return the contribution, code link, and optionally the benchmark and paper if available.

Let's construct the SPARQL query.

[Tool]
Got 2,950 rows and 4 columns, showing the first 5 and last 5 rows below:
| contribution                                                      | code_link                                                                 | benchmark                                                                      | paper |
| ----------------------------------------------------------------- | ------------------------------------------------------------------------- | ------------------------------------------------------------------------------ | ----- |
| Contribution  Duel noop (<http://orkg.org/orkg/resource/R131981>) | https://github.com/170928/-Review-Dueling-Deep-Q-Network (xsd:string)     | Benchmark Atari 2600 Seaquest (<http://orkg.org/orkg/resource/R131982>)        |       |
| Contribution  Duel noop (<http://orkg.org/orkg/resource/R131981>) | https://github.com/170928/-Review-Dueling-Deep-Q-Network (xsd:string)     | Benchmark Atari 2600 Name This Game (<http://orkg.org/orkg/resource/R131984>)  |       |
| Contribution  Duel noop (<http://orkg.org/orkg/resource/R131981>) | https://github.com/170928/-Review-Dueling-Deep-Q-Network (xsd:string)     | Benchmark Atari 2600 Gopher (<http://orkg.org/orkg/resource/R131986>)          |       |
| Contribution  Duel noop (<http://orkg.org/orkg/resource/R131981>) | https://github.com/170928/-Review-Dueling-Deep-Q-Network (xsd:string)     | Benchmark Atari 2600 Crazy Climber (<http://orkg.org/orkg/resource/R131988>)   |       |
| Contribution  Duel noop (<http://orkg.org/orkg/resource/R131981>) | https://github.com/170928/-Review-Dueling-Deep-Q-Network (xsd:string)     | Benchmark Atari 2600 Double Dunk (<http://orkg.org/orkg/resource/R131990>)     |       |
| ...                                                               | ...                                                                       | ...                                                                            | ...   |
| Contribution  Duel noop (<http://orkg.org/orkg/resource/R131981>) | https://github.com/zynk13/dueling-dqn-Reinforcement-learning (xsd:string) | Benchmark Atari 2600 Video Pinball (<http://orkg.org/orkg/resource/R132072>)   |       |
| Contribution  Duel noop (<http://orkg.org/orkg/resource/R131981>) | https://github.com/zynk13/dueling-dqn-Reinforcement-learning (xsd:string) | Benchmark Atari 2600 Chopper Command (<http://orkg.org/orkg/resource/R132074>) |       |
| Contribution  Duel noop (<http://orkg.org/orkg/resource/R131981>) | https://github.com/zynk13/dueling-dqn-Reinforcement-learning (xsd:string) | Benchmark Atari 2600 Star Gunner (<http://orkg.org/orkg/resource/R132076>)     |       |
| Contribution  Duel noop (<http://orkg.org/orkg/resource/R131981>) | https://github.com/zynk13/dueling-dqn-Reinforcement-learning (xsd:string) | Benchmark Atari 2600 Gravitar (<http://orkg.org/orkg/resource/R132078>)        |       |
| Contribution  Duel noop (<http://orkg.org/orkg/resource/R131981>) | https://github.com/zynk13/dueling-dqn-Reinforcement-learning (xsd:string) | Benchmark Atari 2600 Robotank (<http://orkg.org/orkg/resource/R132080>)        |       |

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The SPARQL query is mostly correct and retrieves the relevant code links for contributions using the Duel noop model in any benchmark. However, the query currently returns only the IRIs of the contributions, benchmarks, and papers, but it does not include their human-readable labels, which would make the results more understandable. While labels are not strictly required unless requested, including them in OPTIONAL clauses would improve usability. Additionally, the query should ensure that it returns the actual IRIs for all entities, which it currently does. Therefore, the query is sensible but could be refined for better readability and completeness by including OPTIONAL { ?contribution rdfs:label ?contributionLabel } and similar for benchmarks and papers.

[Assistant]
Thank you for the feedback. To refine the query for better usability, I will add OPTIONAL clauses to retrieve human-readable labels for the contribution, benchmark, and paper entities, while still ensuring that the actual IRIs are returned. This will make the results more understandable without sacrificing completeness.

Here is the improved SPARQL query:

SELECT ?contribution ?contributionLabel ?code_link ?benchmark ?benchmarkLabel ?paper ?paperLabel WHERE {
  ?contribution orkgp:HAS_MODEL <http://orkg.org/orkg/resource/R124891> .
  ?contribution orkgp:HAS_BENCHMARK ?benchmark .
  ?contribution orkgp:HAS_SOURCE_CODE ?code_link .
  OPTIONAL { ?paper orkgp:hasContribution ?contribution . }
  OPTIONAL { ?contribution rdfs:label ?contributionLabel . }
  OPTIONAL { ?benchmark rdfs:label ?benchmarkLabel . }
  OPTIONAL { ?paper rdfs:label ?paperLabel . }
}

This query will return the IRIs and, where available, the labels for contributions, benchmarks, and papers, along with the code links.

Now, I will submit this refined query as the answer.

[Tool] Stopped generation process

[User]
Feedback (status=retry):
The SPARQL query could not be executed due to a memory allocation error. This is not an issue with the query's logic, but rather with the system's resource limits. However, to improve the chances of successful execution, consider optimizing the query to reduce memory usage. For example, remove unnecessary OPTIONAL clauses or limit the number of returned results using LIMIT. Additionally, ensure that only the required variables are selected. Once the system resources are addressed or the query is optimized, retry the execution.

[Assistant]
Thank you for the feedback. To address the memory allocation error, I will optimize the query by:

- Removing the OPTIONAL label for the paper, since most results do not have a paper IRI.
- Keeping only the most relevant labels: contribution and benchmark.
- Adding a LIMIT clause to restrict the number of results (e.g., LIMIT 100), which should help with resource usage.

Here is the optimized query:

SELECT ?contribution ?contributionLabel ?code_link ?benchmark ?benchmarkLabel WHERE {
  ?contribution orkgp:HAS_MODEL <http://orkg.org/orkg/resource/R124891> .
  ?contribution orkgp:HAS_BENCHMARK ?benchmark .
  ?contribution orkgp:HAS_SOURCE_CODE ?code_link .
  OPTIONAL { ?contribution rdfs:label ?contributionLabel . }
  OPTIONAL { ?benchmark rdfs:label ?benchmarkLabel . }
}
LIMIT 100

I will now execute this optimized query.

[Tool]
Got 100 rows and 5 columns, showing the first 5 and last 5 rows below:
| contribution                                                      | contributionLabel                    | code_link                                                                        | benchmark                                                                     | benchmarkLabel                                   |
| ----------------------------------------------------------------- | ------------------------------------ | -------------------------------------------------------------------------------- | ----------------------------------------------------------------------------- | ------------------------------------------------ |
| Contribution  Duel noop (<http://orkg.org/orkg/resource/R131981>) | Contribution 	Duel noop (xsd:string) | https://github.com/austinsilveria/Banana-Collection-DQN (xsd:string)             | Benchmark Atari 2600 Seaquest (<http://orkg.org/orkg/resource/R131982>)       | Benchmark Atari 2600 Seaquest (xsd:string)       |
| Contribution  Duel noop (<http://orkg.org/orkg/resource/R131981>) | Contribution 	Duel noop (xsd:string) | https://github.com/abryeemessi/Wednesday (xsd:string)                            | Benchmark Atari 2600 Seaquest (<http://orkg.org/orkg/resource/R131982>)       | Benchmark Atari 2600 Seaquest (xsd:string)       |
| Contribution  Duel noop (<http://orkg.org/orkg/resource/R131981>) | Contribution 	Duel noop (xsd:string) | https://github.com/cocolico14/N-step-Dueling-DDQN-PER-Pacman (xsd:string)        | Benchmark Atari 2600 Seaquest (<http://orkg.org/orkg/resource/R131982>)       | Benchmark Atari 2600 Seaquest (xsd:string)       |
| Contribution  Duel noop (<http://orkg.org/orkg/resource/R131981>) | Contribution 	Duel noop (xsd:string) | https://github.com/Adrelf/DRL-navigation (xsd:string)                            | Benchmark Atari 2600 Seaquest (<http://orkg.org/orkg/resource/R131982>)       | Benchmark Atari 2600 Seaquest (xsd:string)       |
| Contribution  Duel noop (<http://orkg.org/orkg/resource/R131981>) | Contribution 	Duel noop (xsd:string) | https://github.com/eddynelson/dqn (xsd:string)                                   | Benchmark Atari 2600 Seaquest (<http://orkg.org/orkg/resource/R131982>)       | Benchmark Atari 2600 Seaquest (xsd:string)       |
| ...                                                               | ...                                  | ...                                                                              | ...                                                                           | ...                                              |
| Contribution  Duel noop (<http://orkg.org/orkg/resource/R131981>) | Contribution 	Duel noop (xsd:string) | https://github.com/nbopardi/smb (xsd:string)                                     | Benchmark Atari 2600 Name This Game (<http://orkg.org/orkg/resource/R131984>) | Benchmark Atari 2600 Name This Game (xsd:string) |
| Contribution  Duel noop (<http://orkg.org/orkg/resource/R131981>) | Contribution 	Duel noop (xsd:string) | https://github.com/nathanin/pad (xsd:string)                                     | Benchmark Atari 2600 Name This Game (<http://orkg.org/orkg/resource/R131984>) | Benchmark Atari 2600 Name This Game (xsd:string) |
| Contribution  Duel noop (<http://orkg.org/orkg/resource/R131981>) | Contribution 	Duel noop (xsd:string) | https://github.com/manvibharat/S...ing-Deep-reienforcement-learning (xsd:string) | Benchmark Atari 2600 Name This Game (<http://orkg.org/orkg/resource/R131984>) | Benchmark Atari 2600 Name This Game (xsd:string) |
| Contribution  Duel noop (<http://orkg.org/orkg/resource/R131981>) | Contribution 	Duel noop (xsd:string) | https://github.com/MEOWMEOW114/nd893-p1-navigation-banana (xsd:string)           | Benchmark Atari 2600 Name This Game (<http://orkg.org/orkg/resource/R131984>) | Benchmark Atari 2600 Name This Game (xsd:string) |
| Contribution  Duel noop (<http://orkg.org/orkg/resource/R131981>) | Contribution 	Duel noop (xsd:string) | https://github.com/mohit8935/Deep-Q-Learning-Paper (xsd:string)                  | Benchmark Atari 2600 Name This Game (<http://orkg.org/orkg/resource/R131984>) | Benchmark Atari 2600 Name This Game (xsd:string) |

[Tool] Stopped generation process


SELECT ?benchmark ?benchmarkLabel ?dataset ?evaluation ?evaluationLabel ?metric ?metricLabel ?score WHERE {
  ?benchmark orkgp:HAS_DATASET ?dataset ;
            orkgp:HAS_EVALUATION ?evaluation .
  FILTER(?dataset = <http://orkg.org/orkg/resource/R123966>)
  ?evaluation orkgp:HAS_VALUE ?scoreRaw ;
              orkgp:HAS_METRIC ?metric .
  BIND(xsd:float(?scoreRaw) AS ?score)
  FILTER(BOUND(?score) && !isNaN(?score))
  OPTIONAL { ?evaluation rdfs:label ?evaluationLabel }
  OPTIONAL { ?metric rdfs:label ?metricLabel }
  OPTIONAL { ?benchmark rdfs:label ?benchmarkLabel }
} ORDER BY DESC(?score) LIMIT 1

The highest benchmark result for the AAPD dataset is an F1 score of 72.9. The result comes from the benchmark http://orkg.org/orkg/resource/R134430, dataset http://orkg.org/orkg/resource/R123966, evaluation http://orkg.org/orkg/resource/R134431, and metric http://orkg.org/orkg/resource/R114483.

[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:
orkg at http://localhost:7054

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

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

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

[User] Can you provide the highest benchmark result, including the metric and score, for the AAPD dataset?

[Assistant]
Let's break down the question:

1. We need to identify the entity for the "AAPD dataset".
2. We need to find benchmark results related to this dataset.
3. For each result, we need to retrieve the metric and score.
4. We need to select the highest score among these results, along with its metric.

Let's start by searching for the "AAPD dataset" entity in the ORKG.

[Tool]
Top 10 entity alternatives:
1. Dataset (<http://orkg.org/orkg/resource/R178304>): has type Contribution Template
2. Dataset (<http://orkg.org/orkg/resource/R216575>): has type Contribution, has type R216526
3. Dataset (<http://orkg.org/orkg/resource/R182198>): has type Contribution
4. Dataset (<http://orkg.org/orkg/resource/R70898>): has type Contribution Template
5. Dataset (<http://orkg.org/orkg/resource/R11002>): has type Contribution
6. Dataset (<http://orkg.org/orkg/resource/R11006>): has type Contribution
7. Dataset (<http://orkg.org/orkg/resource/R12082>): has type Contribution
8. Dataset (<http://orkg.org/orkg/resource/R11015>): has type Contribution
9. Dataset (<http://orkg.org/orkg/resource/R11012>): has type Contribution
10. Dataset (<http://orkg.org/orkg/resource/R12102>): has type Contribution

[Assistant] There are several entities labeled as "Dataset" in the ORKG, but none are explicitly labeled "AAPD dataset" in the search results. To proceed, I will try searching for "AAPD" alone to see if there is a more specific match for the AAPD dataset.

[Tool]
Top 10 entity alternatives:
1. AAPD (<http://orkg.org/orkg/resource/R123966>): has type Dataset
2. AAPD (<http://orkg.org/orkg/resource/R218384>)
3. Benchmark AAPD (<http://orkg.org/orkg/resource/R134430>): has type Benchmark

[Assistant]
The entity "AAPD" with IRI <http://orkg.org/orkg/resource/R123966> is of type Dataset, which matches our target. Now, I need to find benchmark results related to this dataset.

Next, I'll search for properties related to "benchmark result" or similar for the AAPD dataset entity.

[Tool]
No property items found

No other items found

[Assistant]
It appears there are no direct properties labeled "benchmark" for the AAPD dataset entity. However, benchmarks are often represented as related resources or through contributions.

Next, I'll check for properties like "has benchmark", "evaluation", or "result" for the AAPD dataset entity to see if benchmark results are linked in another way.

[Tool]
No property items found

No other items found

[Assistant]
There are no direct "result" properties for the AAPD dataset entity either. Since benchmarks are often represented as contributions or as part of a benchmark entity, I'll check the "Benchmark AAPD" entity (<http://orkg.org/orkg/resource/R134430>) to see if it contains benchmark results or links to contributions with results.

I'll search for properties of the "Benchmark AAPD" entity.

[Tool]
Top 10 property alternatives:
1. evaluation (orkgp:HAS_EVALUATION)
2. has dataset (orkgp:HAS_DATASET)

No other items found

[Tool]
Got 1 row and 3 columns:
| subject                                                  | property                          | object                                                       |
| -------------------------------------------------------- | --------------------------------- | ------------------------------------------------------------ |
| Benchmark AAPD (<http://orkg.org/orkg/resource/R134430>) | evaluation (orkgp:HAS_EVALUATION) | Evaluation F1_72.9 (<http://orkg.org/orkg/resource/R134431>) |

[Tool]
Got 5 rows and 3 columns:
| subject                                                      | property                  | object                                       |
| ------------------------------------------------------------ | ------------------------- | -------------------------------------------- |
| Evaluation F1_72.9 (<http://orkg.org/orkg/resource/R134431>) | value (orkgp:HAS_VALUE)   | 72.9 (xsd:string)                            |
| Evaluation F1_72.9 (<http://orkg.org/orkg/resource/R134431>) | metric (orkgp:HAS_METRIC) | F1 (<http://orkg.org/orkg/resource/R114483>) |
| Evaluation F1_72.9 (<http://orkg.org/orkg/resource/R134431>) | rdf:type                  | Evaluation (orkgc:Evaluation)                |
| Evaluation F1_72.9 (<http://orkg.org/orkg/resource/R134431>) | rdfs:label                | Evaluation F1_72.9 (xsd:string)              |
| Evaluation F1_72.9 (<http://orkg.org/orkg/resource/R134431>) | rdf:type                  | orkgc:Resource                               |

[Tool]
Got 1 row and 3 columns:
| subject                                                  | property                          | object                                                       |
| -------------------------------------------------------- | --------------------------------- | ------------------------------------------------------------ |
| Benchmark AAPD (<http://orkg.org/orkg/resource/R134430>) | evaluation (orkgp:HAS_EVALUATION) | Evaluation F1_72.9 (<http://orkg.org/orkg/resource/R134431>) |

[Tool]
Got 5 rows and 3 columns:
| subject                                                  | property                          | object                                                       |
| -------------------------------------------------------- | --------------------------------- | ------------------------------------------------------------ |
| Benchmark AAPD (<http://orkg.org/orkg/resource/R134430>) | evaluation (orkgp:HAS_EVALUATION) | Evaluation F1_72.9 (<http://orkg.org/orkg/resource/R134431>) |
| Benchmark AAPD (<http://orkg.org/orkg/resource/R134430>) | has dataset (orkgp:HAS_DATASET)   | AAPD (<http://orkg.org/orkg/resource/R123966>)               |
| Benchmark AAPD (<http://orkg.org/orkg/resource/R134430>) | rdf:type                          | Benchmark (orkgc:Benchmark)                                  |
| Benchmark AAPD (<http://orkg.org/orkg/resource/R134430>) | rdfs:label                        | Benchmark AAPD (xsd:string)                                  |
| Benchmark AAPD (<http://orkg.org/orkg/resource/R134430>) | rdf:type                          | orkgc:Resource                                               |

[Tool]
Got 1 row and 3 columns:
| subject                                                  | property                        | object                                         |
| -------------------------------------------------------- | ------------------------------- | ---------------------------------------------- |
| Benchmark AAPD (<http://orkg.org/orkg/resource/R134430>) | has dataset (orkgp:HAS_DATASET) | AAPD (<http://orkg.org/orkg/resource/R123966>) |

[Tool]
Got 3,717 rows and 3 columns, showing the first 10 rows below:
| subject                                                               | property                          | object                                                                                |
| --------------------------------------------------------------------- | --------------------------------- | ------------------------------------------------------------------------------------------------------------- |
| 1-SOTAB_description (<http://orkg.org/orkg/resource/R282239>)         | evaluation (orkgp:HAS_EVALUATION) | Using DoDuo (<http://orkg.org/orkg/resource/R286796>)                                                         |
| MammoTab (<http://orkg.org/orkg/resource/R282243>)                    | evaluation (orkgp:HAS_EVALUATION) | Evaluation using the MTab system...versions of the SemTab challenge (<http://orkg.org/orkg/resource/R287505>) |
| Contribution 1 (<http://orkg.org/orkg/resource/R136069>)              | evaluation (orkgp:HAS_EVALUATION) | Gold standard (<http://orkg.org/orkg/resource/R136078>)                                                       |
| Wikinary (<http://orkg.org/orkg/resource/R282241>)                    | evaluation (orkgp:HAS_EVALUATION) | Human evaluation (<http://orkg.org/orkg/resource/R273019>)                                                    |
| Genome Evolutionary Analysis (<http://orkg.org/orkg/resource/R75376>) | evaluation (orkgp:HAS_EVALUATION) | country of origin (<http://orkg.org/orkg/resource/R33266>)                                                    |
| FedX (<http://orkg.org/orkg/resource/R114017>)                        | evaluation (orkgp:HAS_EVALUATION) | FedBench8 (<http://orkg.org/orkg/resource/R114025>)                                                           |
| Contribution 1 (<http://orkg.org/orkg/resource/R136100>)              | evaluation (orkgp:HAS_EVALUATION) | true (xsd:string)                                                                                |
| SPARQL query optimization (<http://orkg.org/orkg/resource/R75313>)    | evaluation (orkgp:HAS_EVALUATION) | Online running time (xsd:string)                                                                              |
| Contribution 1 (<http://orkg.org/orkg/resource/R182425>)              | evaluation (orkgp:HAS_EVALUATION) | Link Prediction (xsd:string)                                                                                |
| (Main) Contribution (<http://orkg.org/orkg/resource/R76790>)          | evaluation (orkgp:HAS_EVALUATION) | Query performance (<http://orkg.org/orkg/resource/R113263>)                                                   |
| ...                                                                   | ...                               | ...                                                                                |

[Tool]
Got 1 row and 3 columns:
| subject                                                  | property                        | object                                         |
| -------------------------------------------------------- | ------------------------------- | ---------------------------------------------- |
| Benchmark AAPD (<http://orkg.org/orkg/resource/R134430>) | has dataset (orkgp:HAS_DATASET) | AAPD (<http://orkg.org/orkg/resource/R123966>) |

[Tool]
Got 1 row and 3 columns:
| subject                                                  | property                          | object                                                       |
| -------------------------------------------------------- | --------------------------------- | ------------------------------------------------------------ |
| Benchmark AAPD (<http://orkg.org/orkg/resource/R134430>) | evaluation (orkgp:HAS_EVALUATION) | Evaluation F1_72.9 (<http://orkg.org/orkg/resource/R134431>) |

[Tool]
Got 5 rows and 3 columns:
| subject                                                      | property                  | object                                       |
| ------------------------------------------------------------ | ------------------------- | -------------------------------------------- |
| Evaluation F1_72.9 (<http://orkg.org/orkg/resource/R134431>) | value (orkgp:HAS_VALUE)   | 72.9 (xsd:string)                            |
| Evaluation F1_72.9 (<http://orkg.org/orkg/resource/R134431>) | metric (orkgp:HAS_METRIC) | F1 (<http://orkg.org/orkg/resource/R114483>) |
| Evaluation F1_72.9 (<http://orkg.org/orkg/resource/R134431>) | rdf:type                  | Evaluation (orkgc:Evaluation)                |
| Evaluation F1_72.9 (<http://orkg.org/orkg/resource/R134431>) | rdfs:label                | Evaluation F1_72.9 (xsd:string)              |
| Evaluation F1_72.9 (<http://orkg.org/orkg/resource/R134431>) | rdf:type                  | orkgc:Resource                               |

[Tool] Stopped generation process

[User]
Feedback (status=refine):
The SPARQL query is mostly correct and retrieves the highest benchmark result for the AAPD dataset, including the metric and score. However, it does not return the actual IRIs of the benchmark or the dataset, which could be useful for traceability and completeness. Additionally, the query should ensure that the score is cast to a numeric type for proper ordering, as it currently assumes the score is always a string that can be cast to float. It would be more robust to filter out non-numeric scores or handle cases where the score is not a valid float. Also, the query could optionally include labels for the metric and evaluation using OPTIONAL clauses with rdfs:label, but this is not strictly necessary unless requested by the user. Overall, the answer is correct, but the query could be refined for completeness and robustness.

[Assistant]
Thank you for your feedback. Here’s how I’ll refine the query:

1. I will include the IRIs of the benchmark and dataset in the SELECT clause for traceability.
2. I will ensure that the score is cast to a float for proper ordering and filter out non-numeric scores using FILTER and BIND.
3. I will optionally include labels for the metric and evaluation using OPTIONAL clauses, but these will not be required fields.

Let me now construct the improved SPARQL query.

[Tool] Stopped generation process

[User]
Feedback (status=retry):
The SPARQL query uses the function TRY(), which is not standard SPARQL and is not supported by the QLever endpoint used here. This causes the query to fail to execute. To fix this, you should remove the TRY() function and instead use a standard SPARQL approach to handle type conversion and filtering. For example, you can use FILTER(datatype(?scoreRaw) = xsd:float) or attempt to cast with xsd:float directly, and filter out unbound or invalid values. Please rewrite the query using only standard SPARQL functions and retry.

[Assistant]
Thank you for pointing out the issue with the TRY() function. I will revise the query to use only standard SPARQL functions.

Here’s my plan:
- I will attempt to cast the score to xsd:float using BIND.
- I will filter to include only those scores where the cast is successful (i.e., the value is bound and not NaN).
- I will include the IRIs for benchmark, dataset, evaluation, and metric, and optionally their labels.

Let’s write the revised query.

[Tool] Stopped generation process