Triple
T1451768
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | OWL 2 QL |
E31305
|
entity |
| Predicate | relatedTo |
P37
|
FINISHED |
| Object | SPARQL |
E29603
|
NE FINISHED |
How this triple was built (2 steps)
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.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: SPARQL | Statement: [OWL 2 QL, relatedTo, SPARQL]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SPARQL Context triple: [OWL 2 QL, relatedTo, SPARQL]
-
A.
SPARQL
chosen
SPARQL is a semantic query language and protocol used to retrieve and manipulate data stored in Resource Description Framework (RDF) format on the Semantic Web.
-
B.
OWL 2 QL
OWL 2 QL is a lightweight profile of the Web Ontology Language designed to enable efficient query answering over large datasets using standard relational database technologies.
-
C.
RDF
RDF (Resource Description Framework) is a standard model for data interchange on the Web that represents information as subject–predicate–object triples to enable structured, machine-readable metadata and knowledge graphs.
-
D.
OWL
OWL (Web Ontology Language) is a W3C-recommended semantic web language used to define and share rich, machine-interpretable ontologies on the web.
-
E.
RDFS
RDFS (RDF Schema) is a semantic web vocabulary language used to define the structure, classes, and properties of RDF data.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
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_69a499171a28819085b993a3ac78e363 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c57bc0908190a57e6bc3d20d5e3c |
completed | March 1, 2026, 11:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad08c6f7c881908d1ef9f7897895a6 |
completed | March 8, 2026, 5:27 a.m. |
Created at: March 1, 2026, 8 p.m.