Triple
T16711059
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Driffield |
E406106
|
entity |
| Predicate | DriffieldShowType |
P15144
|
FINISHED |
| Object | agricultural show |
—
|
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: agricultural show | Statement: [Driffield, DriffieldShowType, agricultural show]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: DriffieldShowType Context triple: [Driffield, DriffieldShowType, agricultural show]
-
A.
driftType
Indicates the manner or category of deviation or change from an expected or original state.
-
B.
showType
chosen
Indicates the category or format in which something is presented or displayed (e.g., type of show, presentation, or display mode).
-
C.
theatreType
Indicates the specific category or kind of theatre associated with an entity, such as its format, style, or operational model.
-
D.
Typer
Indicates that one entity serves as the type or classification for another entity.
-
E.
theaterType
Indicates the specific kind or category of theater associated with an entity (e.g., cinema, opera house, drama theater).
- 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_69d8838db21081909589220fd71440a4 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e386523fc08190a13a4232af191992 |
completed | April 18, 2026, 1:25 p.m. |
| PD | Predicate disambiguation | batch_69e319c379f88190ac0adf812486f598 |
completed | April 18, 2026, 5:42 a.m. |
Created at: April 10, 2026, 5:20 a.m.