Triple
T37058234
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Shot |
E917251
|
entity |
| Predicate | finalScoreAfterShot |
P2625
|
FINISHED |
| Object | Duke 104–103 Kentucky |
—
|
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: Duke 104–103 Kentucky | Statement: [The Shot, finalScoreAfterShot, Duke 104–103 Kentucky]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: finalScoreAfterShot Context triple: [The Shot, finalScoreAfterShot, Duke 104–103 Kentucky]
-
A.
finalScore
chosen
Indicates the resulting or overall score achieved after all contributing actions, events, or evaluations are completed.
-
B.
finalReplayScore
Indicates the score or result achieved at the end of a replayed event, game, or scenario.
-
C.
penaltyShootoutScore
Indicates the number of goals each side scored during a penalty shootout used to decide a tied match.
-
D.
finalSecondLegScore
Indicates the score achieved in the second leg of a two-leg competition or matchup once that leg is completed.
-
E.
finalSetScore
Indicates the final score achieved in a particular set within a match or game.
- 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_69f76e95fa40819091e14681087ae5e4 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69ff0e9c75208190a4423261f00b79b3 |
completed | May 9, 2026, 10:38 a.m. |
| PD | Predicate disambiguation | batch_69ff0e07f08481909c4ae322632a6bf0 |
completed | May 9, 2026, 10:35 a.m. |
Created at: May 3, 2026, 4:14 p.m.