Triple
T9843697
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cauchy distribution |
E239287
|
entity |
| Predicate | hasScaleParameter |
P90306
|
FINISHED |
| Object | γ |
—
|
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: γ | Statement: [Cauchy distribution, hasScaleParameter, γ]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasScaleParameter Context triple: [Cauchy distribution, hasScaleParameter, γ]
-
A.
hasScale
Indicates that one entity possesses or is characterized by a scale or graduated measurement system related to another entity.
-
B.
hasScales
Indicates that an entity possesses scales as a surface covering or body feature.
-
C.
hasScaleHeight
Indicates the characteristic vertical distance over which a quantity (such as pressure, density, or concentration) decreases by a fixed factor in a stratified medium.
-
D.
hasScaleFactorForm
Indicates that one entity is represented as a scaled version or proportional form of another, typically via a specific scale factor.
-
E.
scalesWith
Indicates that a change in one quantity is systematically associated with a proportional or otherwise dependent change in another quantity.
- F. None of above. chosen
Provenance (4 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_69ca84e3f0c48190ada72a65ebd50efd |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb35c8e348190aa090c71bf6f30eb |
completed | April 2, 2026, 12:07 a.m. |
| PD | Predicate disambiguation | batch_69cd03e57cac8190914bb5ae608a6e0e |
completed | April 1, 2026, 11:39 a.m. |
| PDg | Predicate description generation | batch_69cd06ace53081909b5f81f382f6591e |
completed | April 1, 2026, 11:51 a.m. |
Created at: March 30, 2026, 8:33 p.m.