Triple
T25526659
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chester May Festival |
E639792
|
entity |
| Predicate | racecourseUsed |
P157863
|
FINISHED |
| Object | Chester Racecourse |
—
|
NE NERFINISHED |
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: Chester Racecourse | Statement: [Chester May Festival, racecourseUsed, Chester Racecourse]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: racecourseUsed Context triple: [Chester May Festival, racecourseUsed, Chester Racecourse]
-
A.
racecourseUsed
chosen
Indicates that a particular racecourse is utilized or employed for a given event, activity, or purpose.
-
B.
racecourseFeature
Indicates that one entity is a physical or functional feature or component of a racecourse associated with the other entity.
-
C.
racecourseType
Indicates the specific kind or classification of a racecourse associated with an entity.
-
D.
racecourseManaged
Indicates that one entity is responsible for operating, organizing, or overseeing the management of a racecourse for another entity.
-
E.
racecourseCounty
Indicates the county in which a given racecourse is geographically located or administered.
- 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_69e75dbf3f9c8190b3f2a75d1b75d127 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f5f86073d0819093afb1d79b97bccc |
completed | May 2, 2026, 1:13 p.m. |
| PD | Predicate disambiguation | batch_69f468421ba08190880eac99135e5970 |
completed | May 1, 2026, 8:45 a.m. |
Created at: April 21, 2026, 3:11 p.m.