Triple
T30521183
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | European Superstock 1000 Championship |
E776696
|
entity |
| Predicate | relationToWSBK |
P204064
|
FINISHED |
| Object | support class |
—
|
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: support class | Statement: [European Superstock 1000 Championship, relationToWSBK, support class]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationToWSBK Context triple: [European Superstock 1000 Championship, relationToWSBK, support class]
-
A.
relationToLeague
Indicates the type or nature of a team's or participant's association with a specific league (e.g., membership, affiliation, or standing).
-
B.
relationToWinner
Indicates the specific relationship or connection an entity has to the winner of a contest, competition, or event.
-
C.
relationToMainFestival
Indicates how a given event, activity, or element is connected or related to the main festival.
-
D.
relationToBPP
Indicates the specific type of relationship or association an entity has to a designated BPP (e.g., as owner, member, participant, or related party).
-
E.
relationshipToBond
Indicates the specific type of personal, familial, or professional relationship an entity has to the person named Bond.
- 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_69f2249b23c4819087fa85496d92f43f |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_6a0316136a14819085bb88563d5abc42 |
completed | May 12, 2026, 11:59 a.m. |
| PD | Predicate disambiguation | batch_6a03158a962c81909f17d58197f6ba00 |
completed | May 12, 2026, 11:56 a.m. |
| PDg | Predicate description generation | batch_6a0316129c9081908f01528f62fe8997 |
completed | May 12, 2026, 11:59 a.m. |
Created at: April 29, 2026, 8:17 p.m.