Triple
T3884624
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kac ring model |
E92908
|
entity |
| Predicate | analyzedUsing |
P30899
|
FINISHED |
| Object | probability theory |
—
|
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: probability theory | Statement: [Kac ring model, analyzedUsing, probability theory]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: analyzedUsing Context triple: [Kac ring model, analyzedUsing, probability theory]
-
A.
analyzes
Indicates that one entity systematically examines or evaluates another entity to understand its nature, structure, or components.
-
B.
helpsAnalyze
chosen
Indicates that one entity assists another in examining, interpreting, or understanding something in a more detailed or effective way.
-
C.
unitOfAnalysis
Indicates the primary entity, level, or component that is being examined or measured in a given analysis or study.
-
D.
usedInDetector
Indicates that something (e.g., a component, material, or method) is employed as part of a detector or detection system.
-
E.
difficultToAnalyzeAs
Indicates that one entity is hard to examine, interpret, or understand when considered in terms of, or compared to, 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_69aed9697de0819087c2559295ff3d12 |
completed | March 9, 2026, 2:30 p.m. |
| NER | Named-entity recognition | batch_69aeec92cc548190b88b899299e5ccdc |
completed | March 9, 2026, 3:51 p.m. |
| PD | Predicate disambiguation | batch_69aee759609c8190985e96ec6d96dedd |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:20 p.m.