Triple
T35330100
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NASCAR Cup Series owners’ championship |
E1020293
|
entity |
| Predicate | pointsAccumulateFor |
P161848
|
FINISHED |
| Object | specific car entry |
—
|
LITERAL FINISHED |
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: specific car entry | Statement: [NASCAR Cup Series owners’ championship, pointsAccumulateFor, specific car entry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: pointsAccumulateFor Context triple: [NASCAR Cup Series owners’ championship, pointsAccumulateFor, specific car entry]
-
A.
pointsEarnedFrom
Indicates the number of points that an entity has received as a result of another specified source, action, or event.
-
B.
pointsAwarded
chosen
Indicates that a specified number of points has been granted to an entity as a result of some action or event.
-
C.
points
Indicates that one entity directs attention, focus, or a physical/abstract indication toward another entity or location.
-
D.
pointsForWin
Indicates the number of points awarded to an entity for achieving a win in a given context or competition.
-
E.
winnerPoints
Indicates the number of points earned by the winning participant or entity in a competition or event.
- 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_69f79533b88c8190934ec4cb21770e24 |
completed | May 3, 2026, 6:34 p.m. |
| PD | Predicate disambiguation | batch_69f79104f5b48190a496cdffde8472da |
completed | May 3, 2026, 6:16 p.m. |
Created at: May 3, 2026, 4:03 p.m.