Triple
T9805804
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | American League Pitcher of the Month |
E237949
|
entity |
| Predicate | hasMultipleWinnersPossibleOverCareer |
P34452
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [American League Pitcher of the Month, hasMultipleWinnersPossibleOverCareer, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMultipleWinnersPossibleOverCareer Context triple: [American League Pitcher of the Month, hasMultipleWinnersPossibleOverCareer, yes]
-
A.
hasMultipleWinnersPossible
chosen
Indicates that a situation, event, or contest allows for more than one winner to be recognized or selected.
-
B.
hasWinnerEverySeason
Indicates that for every season in consideration, there exists a winner associated with that season.
-
C.
hasMultipleWinnersPerPositionInLeague
Indicates that, within a given league, a single position can be held or won by more than one winner simultaneously or in the same season.
-
D.
hasMultipleMedalsPerYear
Indicates that an entity has been awarded more than one medal within the same calendar year.
-
E.
careerWins
Indicates the total number of wins an individual or entity has accumulated over the course of their entire career.
- 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_69ca84dd4608819097ff4ed00feca280 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdab7b67748190ba16ce868f29d13e |
completed | April 1, 2026, 11:34 p.m. |
| PD | Predicate disambiguation | batch_69cd03dd2da881909052fbf29736a773 |
completed | April 1, 2026, 11:39 a.m. |
Created at: March 30, 2026, 8:29 p.m.