Triple
T424886
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chablis |
E8184
|
entity |
| Predicate | typicalServingTemperature |
P4459
|
FINISHED |
| Object | well chilled |
—
|
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: well chilled | Statement: [Chablis, typicalServingTemperature, well chilled]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalServingTemperature Context triple: [Chablis, typicalServingTemperature, well chilled]
-
A.
hasTemperature
chosen
Indicates that an entity possesses or is characterized by a specific temperature value.
-
B.
requiresCookingTemperature
Indicates that performing the action or preparing the item necessitates reaching or maintaining a specific cooking temperature.
-
C.
servesAgeRange
Indicates that a service, product, or offering is intended for or applicable to entities within a specified age range.
-
D.
servesDish
Indicates that one entity prepares and presents a specific dish as food for another entity.
-
E.
typicalFlavor
Indicates that something characteristically has or is associated with a particular flavor.
- 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_69a2e7f1d1bc81909cf2dc9754a3c334 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2eed56ab481909eec289075496260 |
completed | Feb. 28, 2026, 1:34 p.m. |
| PD | Predicate disambiguation | batch_69a2edd6736c81909a6ca549f77b4345 |
completed | Feb. 28, 2026, 1:29 p.m. |
Created at: Feb. 28, 2026, 1:11 p.m.