Triple
T24558140
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1992 Open Championship |
E607577
|
entity |
| Predicate | winnerRoundScores |
P156309
|
FINISHED |
| Object | 66-64-69-73 |
—
|
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: 66-64-69-73 | Statement: [1992 Open Championship, winnerRoundScores, 66-64-69-73]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: winnerRoundScores Context triple: [1992 Open Championship, winnerRoundScores, 66-64-69-73]
-
A.
winnerRound
Indicates that an entity is the one who won a particular round in a multi-round event or competition.
-
B.
finalScoreWinner
Indicates that the referenced entity is the winner as determined by the final score of a game, match, or competition.
-
C.
winnerCount
Indicates the number of entities that are designated as winners in a given context or event.
-
D.
winnerPoints
Indicates the number of points earned by the winning participant or entity in a competition or event.
-
E.
finalScore
Indicates the resulting or overall score achieved after all contributing actions, events, or evaluations are completed.
- 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_69e2c4cae1b88190825e88d5ce8aa61e |
completed | April 17, 2026, 11:39 p.m. |
| NER | Named-entity recognition | batch_69f2a8f3fa5481909af50dca4156a22f |
completed | April 30, 2026, 12:57 a.m. |
| PD | Predicate disambiguation | batch_69f2a6b99e7c8190ba7e2dc8729a314a |
completed | April 30, 2026, 12:47 a.m. |
| PDg | Predicate description generation | batch_69f2a846c5bc81909ba50cee483bea91 |
completed | April 30, 2026, 12:54 a.m. |
Created at: April 18, 2026, 2:27 a.m.