Triple
T25602182
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ontop |
E641815
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | Ontology-Based Data Access system |
C50510
|
CONCEPT FINISHED |
How this triple was built (1 step)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
CD
Concept disambiguation
gpt-5-mini-2025-08-07
Target class: Ontology-Based Data Access system Context triple: [Ontop, instanceOf, Ontology-Based Data Access system]
-
A.
Web ontology language
A web ontology language is a formal language designed for representing rich, machine-interpretable knowledge about concepts, relationships, and constraints on the web to enable automated reasoning and interoperability.
-
B.
Object-Document Mapper
An Object-Document Mapper is a software component that maps in-memory objects to document-oriented database representations and vice versa, handling persistence, retrieval, and schema translation between object models and document structures.
-
C.
SPARQL endpoint
A SPARQL endpoint is a web-accessible service that accepts SPARQL queries and returns results from an underlying RDF dataset.
-
D.
Object–relational mapping tool
An object–relational mapping tool is a software library or framework that automatically maps objects in application code to rows in a relational database, allowing developers to work with data using object-oriented paradigms instead of SQL.
-
E.
bibliographic data model
A bibliographic data model is a structured framework that defines how information about published and unpublished resources (such as books, articles, and digital media) is represented, organized, and related for purposes of description, discovery, and management.
- F. None of above. chosen
Provenance (1 batch)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69e75dc6ccf081908d49578fd36a76d5 |
completed | April 21, 2026, 11:21 a.m. |
Created at: April 21, 2026, 4:36 p.m.