Triple
T4301258
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lauragais |
E99840
|
entity |
| Predicate | hasCulinarySpeciality |
P17971
|
FINISHED |
| Object | cassoulet (notably in Castelnaudary) |
—
|
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: cassoulet (notably in Castelnaudary) | Statement: [Lauragais, hasCulinarySpeciality, cassoulet (notably in Castelnaudary)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCulinarySpeciality Context triple: [Lauragais, hasCulinarySpeciality, cassoulet (notably in Castelnaudary)]
-
A.
hasSpecialtyFood
chosen
Indicates that an entity offers, serves, or is associated with a particular type of specialty food.
-
B.
hasCuisineItem
Indicates that a particular cuisine includes, features, or is associated with a specific food item.
-
C.
cuisineFeature
Indicates a characteristic, quality, or notable aspect that describes or distinguishes a particular cuisine.
-
D.
hasStapleFood
Indicates that an entity’s primary or regularly consumed basic food item is another specified entity.
-
E.
isCookedBy
Indicates that something has been prepared or made ready for eating through cooking by a particular agent.
- 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_69b345528ebc8190b5abc7e95094792d |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3509fb2b88190a13ab88a5b924052 |
completed | March 12, 2026, 11:47 p.m. |
| PD | Predicate disambiguation | batch_69b347fe55a88190b77bab0c0f38e1aa |
completed | March 12, 2026, 11:10 p.m. |
Created at: March 12, 2026, 11:08 p.m.