Triple
T1580413
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gell-Mann matrices |
E33749
|
entity |
| Predicate | normalization |
P27188
|
FINISHED |
| Object | Tr(λ_a λ_b) = 2 δ_{ab} |
—
|
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: Tr(λ_a λ_b) = 2 δ_{ab} | Statement: [Gell-Mann matrices, normalization, Tr(λ_a λ_b) = 2 δ_{ab}]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: normalization
Context triple: [Gell-Mann matrices, normalization, Tr(λ_a λ_b) = 2 δ_{ab}]
-
A.
normalizationAttempt
Indicates an effort to convert something into a standard or consistent form according to defined rules or criteria.
-
B.
normIs
chosen
Indicates that something conforms to, or is characterized by, a particular standard, rule, or norm.
-
C.
normType
Indicates the specific category or classification of a norm that governs or constrains an entity or situation.
-
D.
hasNorm
Indicates that an entity is associated with, governed by, or characterized through a particular norm, rule, or standard.
-
E.
regularization
Indicates the application of a constraint or penalty to a model or function to prevent overfitting and encourage simpler, more generalizable behavior.
- 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.