Triple
T24611191
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Barbera |
E609117
|
entity |
| Predicate | typicalOakInfluence |
P31348
|
FINISHED |
| Object | vanilla when oak-aged |
—
|
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: vanilla when oak-aged | Statement: [Barbera, typicalOakInfluence, vanilla when oak-aged]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalOakInfluence Context triple: [Barbera, typicalOakInfluence, vanilla when oak-aged]
-
A.
typicalLevelOfInfluence
Indicates the usual degree or strength of influence one entity exerts over another or within a given context.
-
B.
typeOfInfluence
chosen
Indicates the specific nature or category of influence that one entity exerts on another.
-
C.
placeOfInfluence
Indicates the location or area where an entity exerts significant impact, authority, or cultural, social, or intellectual influence.
-
D.
typicalIn
Indicates that something commonly occurs, appears, or is found within a given context, category, or environment.
-
E.
influencesThrough
Indicates that one entity affects or alters another entity indirectly by means of an intermediate factor, channel, or mechanism.
- 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_69e2c4d1140081909c58667bf68f80c3 |
completed | April 17, 2026, 11:40 p.m. |
| NER | Named-entity recognition | batch_69f2be044d4c819094e14eda28d371a7 |
completed | April 30, 2026, 2:27 a.m. |
| PD | Predicate disambiguation | batch_69f2a6ca751c8190a040c10d701ecf3a |
completed | April 30, 2026, 12:48 a.m. |
Created at: April 18, 2026, 2:31 a.m.