Triple
T30521260
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Troy Bayliss |
E776698
|
entity |
| Predicate | wonWorldSBKTitleInSeason |
P10823
|
FINISHED |
| Object | 2001 |
—
|
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: 2001 | Statement: [Troy Bayliss, wonWorldSBKTitleInSeason, 2001]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wonWorldSBKTitleInSeason Context triple: [Troy Bayliss, wonWorldSBKTitleInSeason, 2001]
-
A.
motoGPWorldChampionSeason
Indicates that a given MotoGP rider was the world champion for a specified racing season.
-
B.
wonChampionshipInSeason
chosen
Indicates that an entity secured a championship title during a specified season.
-
C.
wonWorldTitleIn
Indicates that an entity achieved victory in a world championship title in a specified competition or year.
-
D.
Moto2WorldChampion
Indicates that an entity is the rider who won the overall Moto2 World Championship title in a given season.
-
E.
wonDriversTitleFor
Indicates that one entity secured the drivers’ championship title while competing for, or representing, another entity.
- 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_69f2249b23c4819087fa85496d92f43f |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f68809fa4c8190b7477043dd360dc2 |
completed | May 2, 2026, 11:26 p.m. |
| PD | Predicate disambiguation | batch_69f67e42d6688190b60e91d2c388c555 |
completed | May 2, 2026, 10:44 p.m. |
Created at: April 29, 2026, 8:17 p.m.