Triple
T2127814
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | baba ghanoush |
E46463
|
entity |
| Predicate | commonGarnish |
P32595
|
FINISHED |
| Object | olive oil drizzle |
—
|
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: olive oil drizzle | Statement: [baba ghanoush, commonGarnish, olive oil drizzle]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: commonGarnish Context triple: [baba ghanoush, commonGarnish, olive oil drizzle]
-
A.
commonIn
Indicates that something frequently occurs, appears, or is found within a specified context, group, or environment.
-
B.
commonFor
chosen
Indicates that something is typical, usual, or frequently occurring for a given entity or context.
-
C.
culinaryUse
Indicates that one entity is used in the preparation, flavoring, or serving of food or drink for another entity.
-
D.
usesIngredient
Indicates that one entity employs or incorporates another entity as an ingredient in its composition or creation.
-
E.
cuisine
Indicates the type or style of food traditionally associated with or served by an entity (such as a restaurant or region).
- 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_69a88a1626548190ae59a5028c3baa8e |
completed | March 4, 2026, 7:37 p.m. |
| NER | Named-entity recognition | batch_69abbb75033881909b16659fc73945ef |
completed | March 7, 2026, 5:45 a.m. |
| PD | Predicate disambiguation | batch_69abb7bd86cc8190938ef06c1ed6d969 |
completed | March 7, 2026, 5:29 a.m. |
Created at: March 4, 2026, 7:44 p.m.