Triple
T10891789
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kurobuta Berkshire pork |
E257194
|
entity |
| Predicate | hasMeatType |
P51949
|
FINISHED |
| Object | pork |
—
|
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: pork | Statement: [Kurobuta Berkshire pork, hasMeatType, pork]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMeatType Context triple: [Kurobuta Berkshire pork, hasMeatType, pork]
-
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.
isNonVegetarian
Indicates that an entity consumes or includes meat or animal-based products, and therefore does not follow a vegetarian diet.
-
D.
hasMealType
Indicates that an entity is associated with a specific category or type of meal (such as breakfast, lunch, or dinner).
-
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_69d6aa8550c8819095508a2ed9acf3db |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d75206354881908b148f2df3938513 |
completed | April 9, 2026, 7:15 a.m. |
| PD | Predicate disambiguation | batch_69d70d3943c881908895397eccc3e415 |
completed | April 9, 2026, 2:21 a.m. |
Created at: April 8, 2026, 9:21 p.m.