Triple
T1422238
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | OWL Full |
E30248
|
entity |
| Predicate | lessRestrictiveThan |
P24324
|
FINISHED |
| Object | OWL Lite |
E4407
|
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: OWL Lite | Statement: [OWL Full, lessRestrictiveThan, OWL Lite]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: OWL Lite Context triple: [OWL Full, lessRestrictiveThan, OWL Lite]
-
A.
OWL
chosen
OWL (Web Ontology Language) is a W3C-recommended semantic web language used to define and share rich, machine-interpretable ontologies on the web.
-
B.
OWL Full
OWL Full is the most expressive and semantically unrestricted variant of the Web Ontology Language, allowing full RDF compatibility at the cost of computational decidability.
-
C.
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.
-
D.
OWL 2 EL
OWL 2 EL is a lightweight profile of the Web Ontology Language designed for efficient reasoning over large-scale ontologies, particularly in domains like biomedical terminologies.
-
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_69a498fb823c8190a67ce4c4837e641a |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c9df014081908a6e2f41ba012ecc |
completed | March 1, 2026, 11:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad08b09c948190a5ec17021299049e |
completed | March 8, 2026, 5:27 a.m. |
Created at: March 1, 2026, 8 p.m.