Triple
T14130589
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christiaan Bezuidenhout |
E350152
|
entity |
| Predicate | hasWonProfessionalTitleCount |
P25122
|
FINISHED |
| Object | multiple European Tour titles |
—
|
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: multiple European Tour titles | Statement: [Christiaan Bezuidenhout, hasWonProfessionalTitleCount, multiple European Tour titles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWonProfessionalTitleCount Context triple: [Christiaan Bezuidenhout, hasWonProfessionalTitleCount, multiple European Tour titles]
-
A.
numberOfTitleDefenses
Indicates the number of times an entity has successfully defended a previously won title or championship.
-
B.
careerWins
Indicates the total number of wins an individual or entity has accumulated over the course of their entire career.
-
C.
numberOfProfessionalFights
Indicates the total count of professional-level fights associated with an entity (such as a person or competitor).
-
D.
worldChampionshipTitles
Indicates the number of world championship titles an entity has won.
-
E.
winnerTitleCount
chosen
Indicates the number of titles or championships an entity has won.
- 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_69d827865f608190b311820428ae027b |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de610aa434819096671c5aabb9134a |
completed | April 14, 2026, 3:45 p.m. |
| PD | Predicate disambiguation | batch_69de05b5e7a08190a16be9ad8b92b80c |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 9, 2026, 10:47 p.m.