Triple
T6438901
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Heisman Trophy |
E129967
|
entity |
| Predicate | notableFemaleWinner |
P70629
|
FINISHED |
| Object | none as of 2024 |
—
|
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: none as of 2024 | Statement: [Heisman Trophy, notableFemaleWinner, none as of 2024]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableFemaleWinner Context triple: [Heisman Trophy, notableFemaleWinner, none as of 2024]
-
A.
notableCoWinnersExample
Indicates that the related entities are notable examples of co-winners who shared the same award or recognition.
-
B.
notableWinner
Indicates that the subject is a particularly distinguished or prominent winner of the referenced competition, award, or contest.
-
C.
notableAwardWon
Indicates that an entity has received a specific notable award as a winner.
-
D.
notableAwardedFor
Indicates that an award is notable specifically for being given in recognition of a particular work, achievement, or contribution.
-
E.
notableMultipleWinners
Indicates that the subject has achieved multiple wins or repeated successes in a notable event, competition, or award.
- 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_69c0084caac48190a7bc2ad8ba44536f |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c06965a5d48190a5860da9e22dc6e0 |
completed | March 22, 2026, 10:12 p.m. |
| PD | Predicate disambiguation | batch_69c060f96980819091bab9335922a457 |
completed | March 22, 2026, 9:36 p.m. |
| PDg | Predicate description generation | batch_69c0623e3cd48190929b0e3cba013909 |
completed | March 22, 2026, 9:42 p.m. |
Created at: March 22, 2026, 4:45 p.m.