Triple
T33626315
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maisons-Laffitte |
E861413
|
entity |
| Predicate | horseRacingTrackType |
P69994
|
FINISHED |
| Object | flat racing track |
—
|
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: flat racing track | Statement: [Maisons-Laffitte, horseRacingTrackType, flat racing track]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: horseRacingTrackType Context triple: [Maisons-Laffitte, horseRacingTrackType, flat racing track]
-
A.
racecourseType
chosen
Indicates the specific kind or classification of a racecourse associated with an entity.
-
B.
raceTypeDetail
Indicates the specific category or classification of a race, providing detailed information about the type of race involved in the relationship.
-
C.
racecourseFeature
Indicates that one entity is a physical or functional feature or component of a racecourse associated with the other entity.
-
D.
racecourseUsed
Indicates that a particular racecourse is utilized or employed for a given event, activity, or purpose.
-
E.
notableRaceTrackDepicted
Indicates that a work or representation depicts a race track that is considered notable or significant.
- 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_69f34981c54c81909b33c3fa2208a52d |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6f85724048190be13f0503898a67e |
completed | May 3, 2026, 7:25 a.m. |
| PD | Predicate disambiguation | batch_69f6f6632dfc8190af85e258c8519207 |
completed | May 3, 2026, 7:16 a.m. |
Created at: May 1, 2026, 1:41 a.m.