Triple
T35332005
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Penske Racing |
E1020345
|
entity |
| Predicate | hasEnginePartner |
P194332
|
FINISHED |
| Object | Chevrolet |
—
|
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: Chevrolet | Statement: [Penske Racing, hasEnginePartner, Chevrolet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEnginePartner Context triple: [Penske Racing, hasEnginePartner, Chevrolet]
-
A.
hasPartner
Indicates that one entity is in a partner relationship (such as romantic, life, or business partnership) with another entity.
-
B.
hasNetworkPartner
Indicates that an entity is connected to another entity through a formal or recognized network partnership relationship.
-
C.
hasOnscreenPartner
Indicates that one entity appears together with another as a partner within the same onscreen context or scene.
-
D.
hasGlobalPartner
Indicates that an entity maintains a formal partnership or collaborative relationship with another entity at an international or worldwide level.
-
E.
hasExternalPartner
Indicates that an entity is engaged in a relationship, collaboration, or interaction with a partner organization or individual outside its own structure or system.
- 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_69f76deacf4481908e7735a5a7715b0a |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fd6a1c1c4881908090053bc359b181 |
completed | May 8, 2026, 4:44 a.m. |
| PD | Predicate disambiguation | batch_69fd696f24d8819091033afacbdaadc5 |
completed | May 8, 2026, 4:41 a.m. |
| PDg | Predicate description generation | batch_69fd6a1a38f081908c573aee4696de4f |
completed | May 8, 2026, 4:44 a.m. |
Created at: May 3, 2026, 4:03 p.m.