Triple
T6611636
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seve Ballesteros |
E149250
|
entity |
| Predicate | wonOpenChampionshipYear |
P31224
|
FINISHED |
| Object | 1979 |
—
|
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: 1979 | Statement: [Seve Ballesteros, wonOpenChampionshipYear, 1979]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wonOpenChampionshipYear Context triple: [Seve Ballesteros, wonOpenChampionshipYear, 1979]
-
A.
yearOfWin
chosen
Indicates the specific calendar year in which an entity achieved a particular victory or win.
-
B.
firstWinnerYear
Indicates the year in which an entity first won a particular competition, award, or title.
-
C.
numberOfOpenChampionshipsWon
Indicates the total count of Open Championships that an entity has won.
-
D.
championPreviousTitleYear
Indicates the year in which the current champion previously held the same title.
-
E.
mostWinsYears
Indicates the years during which an entity achieved the highest number of wins compared to others or compared to its own performance in other years.
- 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_69c687ebc680819094caf71faba2efe2 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6cf3796d08190a26e988386089447 |
completed | March 27, 2026, 6:40 p.m. |
| PD | Predicate disambiguation | batch_69c6acfed25481909cac74c84a9fe088 |
completed | March 27, 2026, 4:14 p.m. |
Created at: March 27, 2026, 1:57 p.m.