Triple
T27928797
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clos de Tart |
E707917
|
entity |
| Predicate | hasVineTraining |
P175324
|
FINISHED |
| Object | Guyot (typical in region) |
—
|
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: Guyot (typical in region) | Statement: [Clos de Tart, hasVineTraining, Guyot (typical in region)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVineTraining Context triple: [Clos de Tart, hasVineTraining, Guyot (typical in region)]
-
A.
hasTrained
Indicates that one entity has provided training or instruction to another entity.
-
B.
hasTrainingFor
Indicates that an entity has received or possesses training that prepares it for performing a specific task, role, or function.
-
C.
hasTrainingTrack
Indicates that an entity is associated with or assigned to a specific training track or program.
-
D.
hasTrainingRole
Indicates that an entity holds or is assigned a specific role within a training or instructional context.
-
E.
hasTrainedAt
Indicates that an entity has received training, education, or instruction at a specified place or institution.
- 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_69ef96bbf2c48190a9d0e0291457aab6 |
completed | April 27, 2026, 5:02 p.m. |
| NER | Named-entity recognition | batch_69f6d1d916f881909575c2b22c416a5b |
completed | May 3, 2026, 4:40 a.m. |
| PD | Predicate disambiguation | batch_69f6cfe2183481908ae4e85a59c66f69 |
completed | May 3, 2026, 4:32 a.m. |
| PDg | Predicate description generation | batch_69f6d0d331dc8190be5aa6bfc6365e67 |
completed | May 3, 2026, 4:36 a.m. |
Created at: April 27, 2026, 7:01 p.m.