Triple
T3957590
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pecorino Sardo |
E85818
|
entity |
| Predicate | milkTreatment |
P53129
|
FINISHED |
| Object | pasteurized or raw depending on producer |
—
|
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: pasteurized or raw depending on producer | Statement: [Pecorino Sardo, milkTreatment, pasteurized or raw depending on producer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: milkTreatment Context triple: [Pecorino Sardo, milkTreatment, pasteurized or raw depending on producer]
-
A.
milkComposition
Indicates the specific nutrients and components that make up a given sample of milk.
-
B.
feedingType
Indicates the manner or method by which one entity provides nourishment or food to another.
-
C.
treats
Indicates that one entity provides medical care or therapeutic intervention to another entity.
-
D.
ruminantType
Indicates that one entity is classified as a type or category within the group of ruminant animals in relation to another entity.
-
E.
traditionalCheese
Indicates that something is recognized as a cheese made according to established, customary, or historically rooted methods or styles.
- 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_69aed93a96908190bcbdbfa718f155bd |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefaa5afdc8190b709af2473d75d02 |
completed | March 9, 2026, 4:51 p.m. |
| PD | Predicate disambiguation | batch_69aef8ed04e4819096bced8971cd888d |
completed | March 9, 2026, 4:44 p.m. |
| PDg | Predicate description generation | batch_69aefaa3c6a08190bfe76629c7c98eea |
completed | March 9, 2026, 4:51 p.m. |
Created at: March 9, 2026, 3:31 p.m.