Triple
T32669273
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AEVB |
E835244
|
entity |
| Predicate | typicalLikelihood |
P12230
|
FINISHED |
| Object | neural network likelihood model |
—
|
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: neural network likelihood model | Statement: [AEVB, typicalLikelihood, neural network likelihood model]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalLikelihood Context triple: [AEVB, typicalLikelihood, neural network likelihood model]
-
A.
typicalIn
chosen
Indicates that something commonly occurs, appears, or is found within a given context, category, or environment.
-
B.
likelyBehavior
Indicates the behavior or action that an entity is expected or predicted to exhibit under given circumstances.
-
C.
typicalConsistency
Indicates that one entity characteristically maintains a regular or expected level of consistency in relation to another entity or context.
-
D.
typicalAssumption
Indicates that something is taken as a standard or default assumption that generally holds in typical or normal circumstances.
-
E.
likelyIndicates
Indicates that one fact, observation, or condition serves as probabilistic evidence suggesting, but not guaranteeing, the presence or truth of another.
- 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_69f349303ccc8190a70d0f6e8a21d3fb |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_6a037cad051c8190b28b354b89208574 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a0379f0cbe481909b4b8fc6cbe297f0 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:08 a.m.