Triple
T35330823
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trackhouse Racing Team |
E1020310
|
entity |
| Predicate | hasDriverNationality |
P99870
|
FINISHED |
| Object | Mexican driver Daniel Suárez |
—
|
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: Mexican driver Daniel Suárez | Statement: [Trackhouse Racing Team, hasDriverNationality, Mexican driver Daniel Suárez]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDriverNationality Context triple: [Trackhouse Racing Team, hasDriverNationality, Mexican driver Daniel Suárez]
-
A.
hasTrainerNationality
Indicates that the nationality of a trainer is associated with a particular entity (such as a person, team, or athlete).
-
B.
isByNationality
Indicates that one entity has a specified nationality or originates from the country represented by the other entity.
-
C.
hasParticipantNationality
chosen
Indicates that a participant in an event, activity, or relation has a specific nationality.
-
D.
hasOwnerNationalityStereotype
Indicates that an entity is associated with a stereotype about the nationality of its owner.
-
E.
hasCompilerNationality
Indicates that the compiler of a work or collection has a specific nationality.
- 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_69f76deacf4481908e7735a5a7715b0a |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f79da9f80c8190b0afd8509f28747b |
completed | May 3, 2026, 7:10 p.m. |
| PD | Predicate disambiguation | batch_69f79617d40481909ba372f94209c08b |
completed | May 3, 2026, 6:38 p.m. |
Created at: May 3, 2026, 4:03 p.m.