Triple
T8272709
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | tabbouleh |
E193466
|
entity |
| Predicate | usesDressing |
P82438
|
FINISHED |
| Object | lemon juice and olive oil dressing |
—
|
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: lemon juice and olive oil dressing | Statement: [tabbouleh, usesDressing, lemon juice and olive oil dressing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesDressing Context triple: [tabbouleh, usesDressing, lemon juice and olive oil dressing]
-
A.
alsoWornIn
Indicates that an item of clothing or accessory is additionally worn in another context, location, or time beyond the primary one mentioned.
-
B.
wornAs
Indicates that one entity is used or put on as clothing, an accessory, or a wearable item by another entity.
-
C.
typicallyWornWith
Indicates that one item of clothing or accessory is commonly or customarily worn together with another.
-
D.
hasGarment
Indicates that one entity possesses, wears, or is associated with a particular garment.
-
E.
wears
Indicates that one entity is dressed in, or has on its body, a particular item such as clothing or accessories.
- F. None of above. chosen
Provenance (4 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_69ca82e14ae481908ffdb822cd2192bc |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb798878988190a5f63c854aa070f2 |
completed | March 31, 2026, 7:36 a.m. |
| PD | Predicate disambiguation | batch_69cb70a4525481909399d313a6247ace |
completed | March 31, 2026, 6:58 a.m. |
| PDg | Predicate description generation | batch_69cb76d648988190ab0669cc0592e827 |
completed | March 31, 2026, 7:25 a.m. |
Created at: March 30, 2026, 5:50 p.m.