Triple
T22678665
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arena Racing Company |
E560417
|
entity |
| Predicate | hasNumberOfRacecourses |
P105773
|
FINISHED |
| Object | multiple racecourses across the UK |
—
|
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: multiple racecourses across the UK | Statement: [Arena Racing Company, hasNumberOfRacecourses, multiple racecourses across the UK]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfRacecourses Context triple: [Arena Racing Company, hasNumberOfRacecourses, multiple racecourses across the UK]
-
A.
hasRacecourse
Indicates that an entity possesses, contains, or is associated with a racecourse facility or track.
-
B.
racecoursesOperatedBy
chosen
Indicates that specific racecourses are managed, run, or operated by a particular organization or entity.
-
C.
numberOfRaces
Indicates the total count of races associated with a given entity or event.
-
D.
hasRacecourseFeature
Indicates that something possesses or includes a specific feature or characteristic related to a racecourse.
-
E.
racecourseFeature
Indicates that one entity is a physical or functional feature or component of a racecourse associated with the other entity.
- 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_69e2454bfd00819099115715a22cb057 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1785e4e7481909f1ebd6d8dbd6585 |
completed | April 29, 2026, 3:17 a.m. |
| PD | Predicate disambiguation | batch_69ee62a6245881909506ff502da14137 |
completed | April 26, 2026, 7:08 p.m. |
Created at: April 17, 2026, 3:11 p.m.