Triple
T6482584
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gamma function |
E146428
|
entity |
| Predicate | normalizationConstantFor |
P70383
|
FINISHED |
| Object | gamma distribution density |
—
|
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: gamma distribution density | Statement: [Gamma function, normalizationConstantFor, gamma distribution density]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: normalizationConstantFor Context triple: [Gamma function, normalizationConstantFor, gamma distribution density]
-
A.
usesNormalization
Indicates that one entity applies or relies on a normalization process or technique in relation to another entity or data.
-
B.
normalizationAttempt
Indicates an effort to convert something into a standard or consistent form according to defined rules or criteria.
-
C.
isProportionalityFactorIn
chosen
Indicates that one quantity serves as the proportionality factor (constant of proportionality) in a specified proportional relationship or equation.
-
D.
normIs
Indicates that something conforms to, or is characterized by, a particular standard, rule, or norm.
-
E.
normType
Indicates the specific category or classification of a norm that governs or constrains an entity or situation.
- 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_69c0090158c08190af0df9a2348d2d52 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c06a6cd0c4819085a921e6a361d91c |
completed | March 22, 2026, 10:17 p.m. |
| PD | Predicate disambiguation | batch_69c0673f6d48819080e10c85155c7195 |
completed | March 22, 2026, 10:03 p.m. |
Created at: March 22, 2026, 4:51 p.m.