Triple
T25336854
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roquefort-sur-Soulzon caves |
E635299
|
entity |
| Predicate | cheesePlacedOn |
P140336
|
FINISHED |
| Object | wooden shelves during maturation |
—
|
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: wooden shelves during maturation | Statement: [Roquefort-sur-Soulzon caves, cheesePlacedOn, wooden shelves during maturation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cheesePlacedOn Context triple: [Roquefort-sur-Soulzon caves, cheesePlacedOn, wooden shelves during maturation]
-
A.
typicalCheesePlacement
chosen
Indicates the usual or most common spatial position or arrangement of cheese relative to other items or in a given context.
-
B.
cheeseType
Indicates that one entity is a specific type or variety of cheese in relation to another entity.
-
C.
cheeseSpeciality
Indicates that one entity is known for or specializes in producing or offering a particular type of cheese.
-
D.
cheeseMadeFrom
Indicates that one entity is produced or derived as cheese from another entity (typically a source ingredient such as milk).
-
E.
effectOnCheese
Indicates the influence or impact that one entity or action has on the state, quality, or characteristics of cheese.
- 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_69e75a99bd6481909476115b35b9a8e4 |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f498b39adc8190b0fc4925ce0769ed |
completed | May 1, 2026, 12:12 p.m. |
| PD | Predicate disambiguation | batch_69f4683b34748190818428489a226124 |
completed | May 1, 2026, 8:45 a.m. |
Created at: April 21, 2026, 1:32 p.m.