Triple
T20786446
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Camembert, Orne |
E511649
|
entity |
| Predicate | hasCheeseStyleOrigin |
P141539
|
FINISHED |
| Object | soft-ripened cheese style |
—
|
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-ripened cheese style | Statement: [Camembert, Orne, hasCheeseStyleOrigin, soft-ripened cheese style]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCheeseStyleOrigin Context triple: [Camembert, Orne, hasCheeseStyleOrigin, soft-ripened cheese style]
-
A.
hasCheeseVarietyNamedAfterIt
Indicates that something has a type or variety of cheese that is named after it.
-
B.
hasCheeseFactory
Indicates that an entity possesses, hosts, or contains a cheese-producing factory.
-
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.
cheeseType
Indicates that one entity is a specific type or variety of cheese in relation to another entity.
- 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_69e0b4cb83948190bd57bec21d78ed53 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c28c0d0c8190aa48e6fdfdaab750 |
completed | April 21, 2026, 12:19 a.m. |
| PD | Predicate disambiguation | batch_69e5c0550ec481908a0877fb2409d983 |
completed | April 20, 2026, 5:57 a.m. |
| PDg | Predicate description generation | batch_69e5c3cbe5788190b7ace43bfdac2ef6 |
completed | April 20, 2026, 6:12 a.m. |
Created at: April 16, 2026, 12:38 p.m.