Triple
T15914733
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mons-en-Pévèle |
E385939
|
entity |
| Predicate | impactOnRace |
P102027
|
FINISHED |
| Object | creates splits in the peloton |
—
|
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: creates splits in the peloton | Statement: [Mons-en-Pévèle, impactOnRace, creates splits in the peloton]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: impactOnRace Context triple: [Mons-en-Pévèle, impactOnRace, creates splits in the peloton]
-
A.
stanceOnRace
Indicates a subject’s expressed position, attitude, or viewpoint regarding race or racial issues.
-
B.
raceRole
Indicates the specific role, position, or function an entity holds within a race or racing event.
-
C.
relatedRace
Indicates that there is a connection or association between two races, such as similarity, relevance, or contextual linkage.
-
D.
impactOnSubject
chosen
Indicates the effect, influence, or consequence that one entity, event, or action has on a specified subject.
-
E.
civilRightsImpact
Indicates how an action, policy, or event affects the civil rights or civil liberties of individuals or groups.
- 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_69d86da686e4819097cbf3b1fc2d881d |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e172b48b308190bc430b2308cbc75b |
completed | April 16, 2026, 11:37 p.m. |
| PD | Predicate disambiguation | batch_69e142cf5c548190a931f7b58144cd31 |
completed | April 16, 2026, 8:13 p.m. |
Created at: April 10, 2026, 4:52 a.m.