Triple
T1807303
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bayesian inference |
E40249
|
entity |
| Predicate | interpretsProbabilityAs |
P4529
|
FINISHED |
| Object | degree of belief |
—
|
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: degree of belief | Statement: [Bayesian inference, interpretsProbabilityAs, degree of belief]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: interpretsProbabilityAs Context triple: [Bayesian inference, interpretsProbabilityAs, degree of belief]
-
A.
definesProbability
Indicates that one entity specifies or assigns the probability value associated with another entity or event.
-
B.
interpretedAs
chosen
Indicates that something is understood, perceived, or taken to mean something else, often based on context or subjective judgment.
-
C.
interpretedInCase
Indicates that something is understood, analyzed, or given meaning within the context of a particular case or specific situational scenario.
-
D.
interpretationMethod
Indicates the method, technique, or process used to interpret or derive meaning from something.
-
E.
isInterpretedDifferentlyIn
Indicates that the same item, event, or expression is understood or construed in a different way within a specified context, group, or setting.
- 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_69a88643a3388190a612f2ebe1fb29e7 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69ab694d75ac8190a4d61399c04b9fb9 |
completed | March 6, 2026, 11:54 p.m. |
| PD | Predicate disambiguation | batch_69aa61d6b8ec8190a1597b2e44ea6534 |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:32 p.m.