Triple
T7423268
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | JSON-LD |
E171299
|
entity |
| Predicate | relatedTo |
P37
|
FINISHED |
| Object | N-Triples |
E171297
|
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: N-Triples | Statement: [JSON-LD, relatedTo, N-Triples]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: N-Triples Context triple: [JSON-LD, relatedTo, N-Triples]
-
A.
N-Triples
chosen
N-Triples is a line-based, plain-text format for encoding RDF graphs as a sequence of subject–predicate–object statements.
-
B.
RDF 1.1 N-Quads
RDF 1.1 N-Quads is a W3C serialization format for RDF datasets that extends N-Triples by supporting named graphs through four-part statements.
-
C.
RDF 1.1 TriG – RDF Dataset Language
RDF 1.1 TriG – RDF Dataset Language is a W3C specification that defines a compact, textual syntax for representing RDF datasets, including multiple named graphs, as an extension of Turtle.
-
D.
RDF 1.1 Concepts and Abstract Syntax
RDF 1.1 Concepts and Abstract Syntax is a W3C specification that defines the core data model, terminology, and abstract syntax for the Resource Description Framework (RDF).
-
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_69c68a625d048190af70eb8b63bec5a0 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f2eece588190905774e7151edcb8 |
completed | March 27, 2026, 9:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c83c51901081908ad8513c860408eb |
completed | March 28, 2026, 8:38 p.m. |
Created at: March 27, 2026, 3:12 p.m.