Triple
T1580418
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gell-Mann matrices |
E33749
|
entity |
| Predicate | usedToRepresent |
P6726
|
FINISHED |
| Object | color charge operators |
—
|
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: color charge operators | Statement: [Gell-Mann matrices, usedToRepresent, color charge operators]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedToRepresent Context triple: [Gell-Mann matrices, usedToRepresent, color charge operators]
-
A.
usedFor
Indicates that one entity serves a purpose, function, or role in accomplishing, enabling, or supporting another entity or activity.
-
B.
canRepresent
chosen
Indicates that one entity is capable of serving as a valid stand-in, proxy, or expression for another entity in a given context.
-
C.
usedToBe
Indicates that something held a particular state, role, or property in the past but no longer does in the present.
-
D.
usedToExplain
Indicates that one entity serves as an explanation or clarification for another entity.
-
E.
hasRepresentationIn
Indicates that one entity is represented, depicted, or encoded within another entity, such as a concept, object, or data structure having a corresponding representation in a specific medium or context.
- 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_69a885f27a4c8190a4622252cdf54c00 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69abacfb1144819080c5687175aba1e1 |
completed | March 7, 2026, 4:43 a.m. |
| PD | Predicate disambiguation | batch_69aa61b0f5bc8190b1dc272990a59c13 |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:27 p.m.