Triple
T1492041
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Semantic Web |
E29601
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | knowledge representation framework |
C7267
|
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: knowledge representation framework Context triple: [Semantic Web, instanceOf, knowledge representation framework]
-
A.
Knowledge representation language
A knowledge representation language is a formal system used to encode information about the world in a structured, machine-interpretable way so that computers can reason about it.
-
B.
open knowledge organization
An open knowledge organization is a collaborative, transparent system for structuring, connecting, and sharing information that allows broad participation in creating, maintaining, and reusing knowledge resources.
-
C.
framework in generative grammar
A framework in generative grammar is a theoretical system of principles and formal mechanisms used to model and explain the innate structure and rules underlying human language.
-
D.
machine learning framework
A machine learning framework is a software library or platform that provides tools, abstractions, and workflows to design, train, evaluate, and deploy machine learning models efficiently.
-
E.
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.
- 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_69a498dba1d8819093b46a3a8d2485f1 |
completed | March 1, 2026, 7:51 p.m. |
Created at: March 1, 2026, 8:12 p.m.