Triple
T23012928
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Andretti Green Racing |
E572954
|
entity |
| Predicate | notableRaceEngineer |
P150660
|
FINISHED |
| Object | Eric Bretzman |
—
|
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: Eric Bretzman | Statement: [Andretti Green Racing, notableRaceEngineer, Eric Bretzman]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableRaceEngineer Context triple: [Andretti Green Racing, notableRaceEngineer, Eric Bretzman]
-
A.
notableFormerDriver
Indicates that a person was previously a prominent or distinguished driver for the referenced entity (such as a team, organization, or company).
-
B.
raceComponent
Indicates that one entity is a constituent part, segment, or stage within a larger race or racing event involving another entity.
-
C.
motorsportRole
Indicates the specific function or position an entity holds within the context of motorsport activities or events.
-
D.
notableRaceStyle
Indicates that an entity is particularly recognized for competing in, specializing in, or being associated with a specific style or category of racing.
-
E.
racedAs
Indicates that one entity participated in a race or competition under the identity, name, or classification of another entity.
- F. None of above. chosen
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_69e245b764cc8190a51be76f1d9611e1 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f183e300008190bb12c6388a8b3280 |
completed | April 29, 2026, 4:06 a.m. |
| PD | Predicate disambiguation | batch_69ef3b9cd5488190bcd23183179f48cd |
completed | April 27, 2026, 10:34 a.m. |
| PDg | Predicate description generation | batch_69ef538b29c081908fa56ee35a1dcee7 |
completed | April 27, 2026, 12:16 p.m. |
Created at: April 17, 2026, 3:51 p.m.