Triple
T13266974
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dirichlet process models |
E315947
|
entity |
| Predicate | inferenceMethod |
P21759
|
FINISHED |
| Object | Gibbs sampling |
—
|
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: Gibbs sampling | Statement: [Dirichlet process models, inferenceMethod, Gibbs sampling]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: inferenceMethod Context triple: [Dirichlet process models, inferenceMethod, Gibbs sampling]
-
A.
supportsInferenceOf
Indicates that one entity provides a logical basis or justification for concluding or deriving another entity.
-
B.
interpretationMethod
chosen
Indicates the method, technique, or process used to interpret or derive meaning from something.
-
C.
usedToInfer
Indicates that one entity serves as a basis or source from which another entity is logically derived or concluded.
-
D.
reconstructionMethod
Indicates the technique or process used to reconstruct, restore, or rebuild something from its original or fragmented state.
-
E.
inferredType
Indicates that an entity has a type or category that has been deduced or derived rather than explicitly stated.
- 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_69d806b1d9ac8190852c5571d5bd5f0f |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99cfdc9388190af1fdd3cd4717bd8 |
completed | April 11, 2026, 12:59 a.m. |
| PD | Predicate disambiguation | batch_69d98f60911081909fa346a054f76c9f |
completed | April 11, 2026, 12:01 a.m. |
Created at: April 9, 2026, 9:25 p.m.