Triple
T28968387
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1986 NCAA Division I-A football championship |
E732102
|
entity |
| Predicate | decidingGameLoserScore |
P157899
|
FINISHED |
| Object | 10 |
—
|
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: 10 | Statement: [1986 NCAA Division I-A football championship, decidingGameLoserScore, 10]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: decidingGameLoserScore Context triple: [1986 NCAA Division I-A football championship, decidingGameLoserScore, 10]
-
A.
decidingGameLoser
chosen
Indicates that the referenced entity is the loser in the decisive or final game that determines the overall outcome of a series or competition.
-
B.
decidingGameWinner
Indicates that an event, action, or process determines which participant is the winner of a game.
-
C.
decidingSeriesLoser
Indicates that one entity is the loser in a game or match that determines the outcome of a series between competitors.
-
D.
tiebreakerGameLoser
Indicates the player or team that lost a specific tiebreaker game used to resolve a tie in a competition or match.
-
E.
decisivePenaltyScorer
Indicates that an entity scores a crucial penalty that decisively determines the outcome of a match or competition.
- 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_69f043ee242c8190b063248b417c5a69 |
completed | April 28, 2026, 5:21 a.m. |
| NER | Named-entity recognition | batch_69f67257b0448190a13011af81c81449 |
completed | May 2, 2026, 9:53 p.m. |
| PD | Predicate disambiguation | batch_69f66ec5bf508190ad088b89455252bd |
completed | May 2, 2026, 9:38 p.m. |
Created at: April 28, 2026, 8:53 a.m.