Triple
T17495961
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blanquette de Limoux |
E426059
|
entity |
| Predicate | bubbleCharacteristic |
P127670
|
FINISHED |
| Object | fine mousse |
—
|
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: fine mousse | Statement: [Blanquette de Limoux, bubbleCharacteristic, fine mousse]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bubbleCharacteristic Context triple: [Blanquette de Limoux, bubbleCharacteristic, fine mousse]
-
A.
bubbleState
Indicates the current status or condition of a bubble within a process, system, or environment (e.g., whether it exists, is active, stable, or has changed).
-
B.
bubbleLocation
Indicates the spatial position or area where a bubble is situated or occurs.
-
C.
bounceCharacteristics
Indicates the specific way in which something bounces, such as its rebound height, frequency, or pattern of motion after impact.
-
D.
confluenceCharacteristic
Indicates a characteristic or property that specifically pertains to the confluence or merging point of two or more entities.
-
E.
densityCharacteristic
Indicates that one entity specifies or characterizes the density property or density-related attribute of 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_69d889dccf7481909264a1844a2e9100 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e4520e9c8c8190aa955766bc915d26 |
completed | April 19, 2026, 3:54 a.m. |
| PD | Predicate disambiguation | batch_69e3b4f5fbcc8190a6ea9639bf5650da |
completed | April 18, 2026, 4:44 p.m. |
| PDg | Predicate description generation | batch_69e3bbb37d148190b7f38599c06594ee |
completed | April 18, 2026, 5:13 p.m. |
Created at: April 10, 2026, 5:48 a.m.