Triple
T25050419
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AOC Bresse chicken |
E627361
|
entity |
| Predicate | meatCategory |
P51949
|
FINISHED |
| Object | poultry |
—
|
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: poultry | Statement: [AOC Bresse chicken, meatCategory, poultry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: meatCategory Context triple: [AOC Bresse chicken, meatCategory, poultry]
-
A.
meatType
chosen
Indicates the specific category or kind of meat associated with an entity.
-
B.
typicalMeat
Indicates that something is commonly or characteristically used or regarded as meat in a given context.
-
C.
meatContent
Indicates that one entity has a specified amount, proportion, or presence of meat contained within it.
-
D.
commonMeatCut
Indicates that two items are the same or equivalent cut of meat, or that an item belongs to a standard, commonly recognized meat cut category.
-
E.
notableMeatProduct
Indicates that one entity is a meat-based product that is especially prominent, well-known, or significant in relation to the other 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_69e2ff2b4c80819087c916b2b16241b9 |
completed | April 18, 2026, 3:48 a.m. |
| NER | Named-entity recognition | batch_69f454a02ac88190ae0a2ac9071622eb |
completed | May 1, 2026, 7:22 a.m. |
| PD | Predicate disambiguation | batch_69f442c861188190967655c6d8012380 |
completed | May 1, 2026, 6:06 a.m. |
Created at: April 18, 2026, 6:09 a.m.