Triple
T19050761
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dirichlet distribution |
E466249
|
entity |
| Predicate | normalizingConstant |
P118900
|
FINISHED |
| Object | multivariate beta function |
—
|
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: multivariate beta function | Statement: [Dirichlet distribution, normalizingConstant, multivariate beta function]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: normalizingConstant Context triple: [Dirichlet distribution, normalizingConstant, multivariate beta function]
-
A.
normalizationInvolves
chosen
Indicates that a normalization process includes or makes use of a particular component, step, or element as part of its execution.
-
B.
normalizationType
Indicates the specific method or scheme used to normalize or standardize data, values, or representations within a given context.
-
C.
normIs
Indicates that something conforms to, or is characterized by, a particular standard, rule, or norm.
-
D.
decayConstant
Indicates the proportional rate at which a quantity undergoing exponential decay decreases per unit time.
-
E.
oftenNormalizedTo
Indicates that one entity is frequently converted, mapped, or standardized into the form or representation of 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_69d8dd040fb881909af2a964f65ad208 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5dc02597c8190b39fd2c7b7e42258 |
completed | April 20, 2026, 7:55 a.m. |
| PD | Predicate disambiguation | batch_69e4b99633c8819097988608c278ecf8 |
completed | April 19, 2026, 11:16 a.m. |
Created at: April 10, 2026, 12:03 p.m.