Triple
T1492054
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Semantic Web |
E29601
|
entity |
| Predicate | basedOnStandard |
P1587
|
FINISHED |
| Object | SKOS |
E40098
|
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: SKOS | Statement: [Semantic Web, basedOnStandard, SKOS]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SKOS Context triple: [Semantic Web, basedOnStandard, SKOS]
-
A.
SKOS
chosen
SKOS (Simple Knowledge Organization System) is a W3C standard model for representing and sharing knowledge organization systems such as thesauri, classification schemes, and subject headings on the Semantic Web.
-
B.
OWL
OWL (Web Ontology Language) is a W3C-recommended semantic web language used to define and share rich, machine-interpretable ontologies on the web.
-
C.
Dublin Core
Dublin Core is a widely used standard for describing digital resources through a simple, generic set of metadata elements to support discovery and interoperability across systems.
-
D.
RDFS
RDFS (RDF Schema) is a semantic web vocabulary language used to define the structure, classes, and properties of RDF data.
-
E.
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.
- 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_69a498dba1d8819093b46a3a8d2485f1 |
completed | March 1, 2026, 7:51 p.m. |
| NER | Named-entity recognition | batch_69a4c6c4f0c88190a97ba4910c1a5d85 |
completed | March 1, 2026, 11:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad1ca98e64819097916eb7717e6364 |
completed | March 8, 2026, 6:52 a.m. |
Created at: March 1, 2026, 8:12 p.m.