Triple
T24791825
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GT Le Mans |
E620269
|
entity |
| Predicate | typicalRace |
P51003
|
FINISHED |
| Object | 24 Hours of Daytona GTLM class |
—
|
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: 24 Hours of Daytona GTLM class | Statement: [GT Le Mans, typicalRace, 24 Hours of Daytona GTLM class]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalRace Context triple: [GT Le Mans, typicalRace, 24 Hours of Daytona GTLM class]
-
A.
typicalRaceLengthCategory
Indicates the usual distance range or length classification that a race is most commonly run at.
-
B.
raceCategory
Indicates the classification of an entity into a specific race or racial group within a defined categorization system.
-
C.
racesAgainst
Indicates that one entity competes in a race directly against another entity.
-
D.
primaryRaceType
Indicates the main or predominant race category associated with an entity, as opposed to any secondary or additional race classifications.
-
E.
relatedRace
chosen
Indicates that there is a connection or association between two races, such as similarity, relevance, or contextual linkage.
- 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_69e2fabe77c8819085f7ce6486248139 |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f65f7731e4819099d5bd3d915ee266 |
completed | May 2, 2026, 8:32 p.m. |
| PD | Predicate disambiguation | batch_69f65c1f94ac8190bc6fbc7916fc0d82 |
completed | May 2, 2026, 8:18 p.m. |
Created at: April 18, 2026, 4:47 a.m.