Triple
T7438342
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jim Barnes |
E171677
|
entity |
| Predicate | wonUSTournamentCount |
P76402
|
FINISHED |
| Object | 2 PGA Championships |
—
|
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: 2 PGA Championships | Statement: [Jim Barnes, wonUSTournamentCount, 2 PGA Championships]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wonUSTournamentCount Context triple: [Jim Barnes, wonUSTournamentCount, 2 PGA Championships]
-
A.
wonTournament
Indicates that an entity emerged as the overall victor in a tournament competition.
-
B.
numberOfUSOpenChampionshipsWon
Indicates the count of US Open Championship titles that an entity has won.
-
C.
NCAATournamentAppearancesApprox
Indicates that an entity has participated in the NCAA Tournament, with the count of appearances given as an approximate rather than an exact value.
-
D.
NCAATournamentAppearance
Indicates that an entity has participated in at least one NCAA basketball tournament.
-
E.
usOpenWinsCount
Indicates the number of times an entity has won the US Open tournament.
- 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_69c68a64228c8190affaec2a8127ce7b |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f34aa3388190ac300cf934042d78 |
completed | March 27, 2026, 9:14 p.m. |
| PD | Predicate disambiguation | batch_69c6f038582c8190bac77c9b5a34b862 |
completed | March 27, 2026, 9:01 p.m. |
| PDg | Predicate description generation | batch_69c6f0be2b1c8190bea06100a7caef2b |
completed | March 27, 2026, 9:03 p.m. |
Created at: March 27, 2026, 3:13 p.m.