Triple
T23013255
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CART |
E572961
|
entity |
| Predicate | notableTeams |
P69211
|
FINISHED |
| Object | Team Penske |
—
|
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: Team Penske | Statement: [CART, notableTeams, Team Penske]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Team Penske Context triple: [CART, notableTeams, Team Penske]
-
A.
Team Penske
chosen
Team Penske is a prominent American auto racing organization best known for its successful teams in series such as IndyCar and NASCAR.
-
B.
Penske Racing
Penske Racing is a prominent American auto racing organization, best known for its success in IndyCar and NASCAR under the ownership of businessman Roger Penske.
-
C.
DS Penske
DS Penske is a professional Formula E racing team competing in the FIA electric single-seater championship.
-
D.
Chip Ganassi Racing
Chip Ganassi Racing is a prominent American auto racing organization that has fielded championship-winning teams across series such as IndyCar and NASCAR.
-
E.
Smith & Haas
Smith & Haas was an American publishing house known for issuing notable literary works in the early 20th century.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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. |
Created at: April 17, 2026, 3:51 p.m.