Triple
T9770365
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | neutrino hypothesis |
E237108
|
entity |
| Predicate | introducesConceptOf |
P201
|
FINISHED |
| Object | neutral elementary particle |
—
|
LITERAL 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: neutral elementary particle | Statement: [neutrino hypothesis, introducesConceptOf, neutral elementary particle]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: introducesConceptOf Context triple: [neutrino hypothesis, introducesConceptOf, neutral elementary particle]
-
A.
introducedConcept
chosen
Indicates that one entity is responsible for presenting, defining, or bringing a new concept into use or awareness for another entity or context.
-
B.
demonstratedConcept
Indicates that an entity has shown, illustrated, or made evident a particular concept through example, explanation, or action.
-
C.
exportsConcept
Indicates that one entity sends or supplies a concept, idea, or abstract knowledge resource from itself to another entity or context.
-
D.
featuredConcept
Indicates that one concept is highlighted or given special prominence relative to others in a particular context.
-
E.
trainingConcept
Indicates that one entity serves as a concept, topic, or subject matter that is being taught or trained on in relation to another entity.
- F. None of above.
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_69ca84d831b8819090322686b47887ce |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cda0f1dea08190b89bcc192b068c66 |
completed | April 1, 2026, 10:49 p.m. |
| PD | Predicate disambiguation | batch_69cd03d3b68c81909e570401a891b9f2 |
completed | April 1, 2026, 11:38 a.m. |
Created at: March 30, 2026, 8:26 p.m.