Triple
T36492881
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tarrant Hinton |
E899097
|
entity |
| Predicate | GreatDorsetSteamFairType |
P185766
|
FINISHED |
| Object | steam and vintage vehicle 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: steam and vintage vehicle show | Statement: [Tarrant Hinton, GreatDorsetSteamFairType, steam and vintage vehicle show]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: GreatDorsetSteamFairType Context triple: [Tarrant Hinton, GreatDorsetSteamFairType, steam and vintage vehicle show]
-
A.
GreatDorsetSteamFairFounded
Indicates that an entity is the person or organization that founded the Great Dorset Steam Fair.
-
B.
worldsFairEdition
Indicates that one entity is a special edition of another that was produced or designated specifically for a World's Fair event.
-
C.
Pinner Fair
Indicates a fair or event taking place in, associated with, or named after Pinner.
-
D.
rollerCoasterType
Indicates that one entity is classified as a specific type or category of roller coaster in relation to another entity.
-
E.
partOfAttractionType
Indicates that one attraction type is a component or subset of a broader, more general attraction type.
- 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_69f76e5ad4588190bdbce60c52fbb785 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7c371931c8190afb1d4dd5157f92c |
completed | May 3, 2026, 9:51 p.m. |
| PD | Predicate disambiguation | batch_69f7c1b91fd88190ab85afd626603769 |
completed | May 3, 2026, 9:44 p.m. |
| PDg | Predicate description generation | batch_69f7c3705b5c81908c84004543a71c07 |
completed | May 3, 2026, 9:51 p.m. |
Created at: May 3, 2026, 4:10 p.m.