Triple
T6653853
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | bagna càuda |
E150890
|
entity |
| Predicate | hasPreparation |
P47540
|
FINISHED |
| Object | garlic is sliced or pounded |
—
|
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: garlic is sliced or pounded | Statement: [bagna càuda, hasPreparation, garlic is sliced or pounded]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPreparation Context triple: [bagna càuda, hasPreparation, garlic is sliced or pounded]
-
A.
preparationInvolved
chosen
Indicates that a particular preparation, process, or setup is involved in enabling or carrying out an action, event, or relationship.
-
B.
preparationBy
Indicates that one entity is created, assembled, or made ready through the actions or processes performed by another entity.
-
C.
preparedAt
Indicates the time or place at which something was prepared or made ready.
-
D.
preparesFor
Indicates that one entity is used, designed, or undertaken in order to get another entity ready for a future event, state, or activity.
-
E.
preparedFor
Indicates that one entity has been made ready, equipped, or arranged in anticipation of use by or in connection with 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_69c687f2c9508190a60b9aad31d3f358 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6cc9c6cb0819084fec8e0beb430de |
completed | March 27, 2026, 6:29 p.m. |
| PD | Predicate disambiguation | batch_69c6ad071b0081909b96dd4b93414bd1 |
completed | March 27, 2026, 4:15 p.m. |
Created at: March 27, 2026, 2:01 p.m.