Triple
T32212190
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AdanaKebab |
E822836
|
entity |
| Predicate | traditionalMeatSource |
P85784
|
FINISHED |
| Object | male lamb |
—
|
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: male lamb | Statement: [AdanaKebab, traditionalMeatSource, male lamb]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: traditionalMeatSource Context triple: [AdanaKebab, traditionalMeatSource, male lamb]
-
A.
typicalMeat
Indicates that something is commonly or characteristically used or regarded as meat in a given context.
-
B.
notableMeatProduct
Indicates that one entity is a meat-based product that is especially prominent, well-known, or significant in relation to the other entity.
-
C.
meatType
Indicates the specific category or kind of meat associated with an entity.
-
D.
meatFlavor
Indicates that one entity has the taste quality or flavor characteristic associated with meat in relation to another entity.
-
E.
traditionalFoodBase
chosen
Indicates that one entity serves as the primary ingredient, staple, or foundational component of a traditional food associated 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_69f3490a3bec819097bc58d4731b9d08 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fea1f5d8c481908dc3351dc9ecef7f |
completed | May 9, 2026, 2:54 a.m. |
| PD | Predicate disambiguation | batch_69fea06b6fe0819095bf4c1bc9809927 |
completed | May 9, 2026, 2:48 a.m. |
Created at: May 1, 2026, 12:37 a.m.