Triple
T1382132
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gaussian distribution |
E29361
|
entity |
| Predicate | cumulativeDistributionFunction |
P9754
|
FINISHED |
| Object | Φ((x−μ)/σ) |
—
|
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: Φ((x−μ)/σ) | Statement: [Gaussian distribution, cumulativeDistributionFunction, Φ((x−μ)/σ)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cumulativeDistributionFunction Context triple: [Gaussian distribution, cumulativeDistributionFunction, Φ((x−μ)/σ)]
-
A.
hasDistributionFunction
chosen
Indicates that an entity is associated with a specific distribution function that characterizes how its values or occurrences are probabilistically or statistically distributed.
-
B.
cumulativeProperty
Indicates that a property of a whole is derived by aggregating or summing corresponding properties of its parts or components.
-
C.
hasStatisticalFunctions
Indicates that one entity provides or supports statistical operations or capabilities for another entity.
-
D.
conclusionDistribution
Indicates how conclusions, outcomes, or end states are apportioned, spread, or assigned across different entities or categories.
-
E.
distribution
Indicates the act or pattern of giving, delivering, or spreading something from one source to multiple recipients or locations.
- 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_69a498d883a48190bfdca525296ef7ee |
completed | March 1, 2026, 7:51 p.m. |
| NER | Named-entity recognition | batch_69a4c3361bf08190b3f6bbf82e17685b |
completed | March 1, 2026, 10:52 p.m. |
| PD | Predicate disambiguation | batch_69a4befe343c81909f758440a531b5be |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:59 p.m.