Triple
T1188206
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Byron Nelson |
E25295
|
entity |
| Predicate | tourWins |
P8292
|
FINISHED |
| Object | 52 PGA Tour wins (commonly credited) |
—
|
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: 52 PGA Tour wins (commonly credited) | Statement: [Byron Nelson, tourWins, 52 PGA Tour wins (commonly credited)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tourWins Context triple: [Byron Nelson, tourWins, 52 PGA Tour wins (commonly credited)]
-
A.
wonTournament
Indicates that an entity emerged as the overall victor in a tournament competition.
-
B.
careerWins
chosen
Indicates the total number of wins an individual or entity has accumulated over the course of their entire career.
-
C.
gamesWonBy
Indicates the number of games that have been won by a particular entity in a given context.
-
D.
winnerCount
Indicates the number of entities that are designated as winners in a given context or event.
-
E.
winnerPlaysIn
Indicates that the entity identified as the winner of a contest or match participates in a subsequent game, round, or event.
- 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_69a49427d98881908646d6c63b8cea1e |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bd568cf481908d10cf19a3ce28f3 |
completed | March 1, 2026, 10:27 p.m. |
| PD | Predicate disambiguation | batch_69a4bb5bacc481909e8dfd5215e4711a |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:45 p.m.