Triple
T4939487
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Langres |
E110891
|
entity |
| Predicate | cheeseType |
P60147
|
FINISHED |
| Object | soft washed-rind cow’s milk cheese |
—
|
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: soft washed-rind cow’s milk cheese | Statement: [Langres, cheeseType, soft washed-rind cow’s milk cheese]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cheeseType Context triple: [Langres, cheeseType, soft washed-rind cow’s milk cheese]
-
A.
traditionalCheese
Indicates that something is recognized as a cheese made according to established, customary, or historically rooted methods or styles.
-
B.
curdType
Indicates the specific kind or category of curd associated with an entity.
-
C.
isMeltingCheese
Indicates that one entity is causing cheese to transition from a solid to a softened or liquid state through heating or similar means.
-
D.
hasCheeseVarietyNamedAfterIt
Indicates that something has a type or variety of cheese that is named after it.
-
E.
milkType
Indicates the specific kind or category of milk associated with an entity (e.g., whole, skim, plant-based).
- 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_69bd4415eee08190bdce70276e56a5b4 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd7088f6e48190bf09e58ab053a4d1 |
completed | March 20, 2026, 4:06 p.m. |
| PD | Predicate disambiguation | batch_69bd6c389b9881908ad7fb1c5393c1b1 |
completed | March 20, 2026, 3:48 p.m. |
| PDg | Predicate description generation | batch_69bd6ff85b50819081d78087caa6b473 |
completed | March 20, 2026, 4:04 p.m. |
Created at: March 20, 2026, 1:31 p.m.