Triple
T32788072
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deauville-Clairefontaine Racecourse |
E838550
|
entity |
| Predicate | nearbyRacecourse |
P98305
|
FINISHED |
| Object | Deauville-La Touques 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: Deauville-La Touques Racecourse | Statement: [Deauville-Clairefontaine Racecourse, nearbyRacecourse, Deauville-La Touques Racecourse]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearbyRacecourse Context triple: [Deauville-Clairefontaine Racecourse, nearbyRacecourse, Deauville-La Touques Racecourse]
-
A.
hasNearbyRacetrack
chosen
Indicates that one entity is located close to or in the vicinity of a racetrack.
-
B.
racecourseRegion
Indicates that a racecourse is located within, or associated with, a particular geographic or administrative region.
-
C.
nearbyEventDate
Indicates that one event’s date occurs close in time to another event’s date.
-
D.
nearbyEvent
Indicates that one event occurs close in space or time to another event.
-
E.
nearbyLocation
Indicates that one location is situated close to another location in physical space.
- 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_69f3493b83f48190be335cd42465cecf |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fddac4e2f48190a9301d3422658b29 |
completed | May 8, 2026, 12:44 p.m. |
| PD | Predicate disambiguation | batch_69fdda06969c8190b5d033964ea2a690 |
completed | May 8, 2026, 12:41 p.m. |
Created at: May 1, 2026, 1:14 a.m.