Triple
T10904301
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brighton Racecourse |
E257526
|
entity |
| Predicate | hasCourseDistance |
P82629
|
FINISHED |
| Object | 1 mile |
—
|
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: 1 mile | Statement: [Brighton Racecourse, hasCourseDistance, 1 mile]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCourseDistance Context triple: [Brighton Racecourse, hasCourseDistance, 1 mile]
-
A.
hasCourseLength
chosen
Indicates that an entity (such as a course) is associated with a specific duration or length.
-
B.
hasCyclingDistance
Indicates that there is a specified distance associated with traveling between entities by cycling.
-
C.
hasCoursePar
Indicates that one course is a parent or higher-level course in relation to another course, such as a prerequisite or overarching course.
-
D.
turfCourseDistance
Indicates the distance over which an event or action occurs on a turf (grass) course.
-
E.
mainTrackDistance
Indicates the distance measured along the primary or main track between two referenced points or entities.
- 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_69d6aa8550c8819095508a2ed9acf3db |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d761a5dffc8190927b0928978646a4 |
completed | April 9, 2026, 8:21 a.m. |
| PD | Predicate disambiguation | batch_69d70d3d69e08190bb369e9a7927142c |
completed | April 9, 2026, 2:21 a.m. |
Created at: April 8, 2026, 9:22 p.m.