Triple
T36308034
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mauritius Turf Club |
E893992
|
entity |
| Predicate | hasNotableRacecourse |
P16266
|
FINISHED |
| Object | Champ de Mars Racecourse |
E257988
|
NE 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: Champ de Mars Racecourse | Statement: [Mauritius Turf Club, hasNotableRacecourse, Champ de Mars Racecourse]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableRacecourse Context triple: [Mauritius Turf Club, hasNotableRacecourse, Champ de Mars Racecourse]
-
A.
hasRacecourse
chosen
Indicates that an entity possesses, contains, or is associated with a racecourse facility or track.
-
B.
notableRaceTrackDepicted
Indicates that a work or representation depicts a race track that is considered notable or significant.
-
C.
hasRacecourseFeature
Indicates that something possesses or includes a specific feature or characteristic related to a racecourse.
-
D.
hasNotableRace
Indicates that an entity is associated with a race or competition that is considered notable or significant.
-
E.
notableRaceMeeting
Indicates that there is a race meeting or event that is particularly notable or significant in relation to the subject.
- F. None of above.
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_69f76e4c1b248190b10667d0213537fe |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a037c8d06cc8190ab6a5e18d9d2571e |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a39c3f6a7c48190a32781e71cbe8a97 |
completed | June 22, 2026, 11:23 p.m. |
| PD | Predicate disambiguation | batch_6a037a0a54cc8190868c1bfa1590d1a6 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:09 p.m.