Triple
T484140
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hart Memorial Trophy |
E9836
|
entity |
| Predicate | mostWinsPlayerCount |
P12883
|
FINISHED |
| Object | 9 |
—
|
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: 9 | Statement: [Hart Memorial Trophy, mostWinsPlayerCount, 9]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mostWinsPlayerCount Context triple: [Hart Memorial Trophy, mostWinsPlayerCount, 9]
-
A.
mostWinsByPlayerCount
chosen
Indicates the maximum number of wins achieved by any single player within the considered set or context.
-
B.
mostOverallWinsHolder
Indicates that the subject is the entity holding the highest total number of wins overall, compared to all other relevant entities.
-
C.
mostOverallWinsRecord
Indicates that the subject holds the record for having the greatest total number of wins compared to all others in the relevant context.
-
D.
winnerCount
Indicates the number of entities that are designated as winners in a given context or event.
-
E.
hallOfFamePlayersCount
Indicates the number of players associated with an entity who have been inducted into a hall of fame.
- 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_69a2e802e2908190ab17c9479e0b6412 |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2f0ba310c81909645ef7e8a20b52f |
completed | Feb. 28, 2026, 1:42 p.m. |
| PD | Predicate disambiguation | batch_69a2edf48ec08190b85d07e194f99c49 |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.