Triple
T11211625
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fête des Vignerons |
E265321
|
entity |
| Predicate | 2019EditionAudience |
P37957
|
FINISHED |
| Object | hundreds of thousands of spectators |
—
|
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: hundreds of thousands of spectators | Statement: [Fête des Vignerons, 2019EditionAudience, hundreds of thousands of spectators]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 2019EditionAudience Context triple: [Fête des Vignerons, 2019EditionAudience, hundreds of thousands of spectators]
-
A.
edition2019Host
Indicates that the subject served as the host of the 2019 edition of a particular event or series.
-
B.
relatesToAudience
Indicates a general relationship or relevance between something and a particular audience or group of recipients.
-
C.
audienceSetting
Indicates the context or environment in which an audience is situated or addressed.
-
D.
audienceAccess
Indicates that one entity has permission or ability to access, view, or engage with a particular audience associated with another entity.
-
E.
audienceScale
chosen
Indicates the relative size or reach of the audience associated with an entity, event, or communication.
- 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_69d6aac59460819089b9848b27f57848 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8d6f5d4819086dcb776a0d469e8 |
completed | April 9, 2026, 5:58 p.m. |
| PD | Predicate disambiguation | batch_69d75cfbbb188190861efd5d94fe27da |
completed | April 9, 2026, 8:02 a.m. |
Created at: April 8, 2026, 9:30 p.m.