Triple
T3768382
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Flèche Wallonne |
E82735
|
entity |
| Predicate | safetySupervision |
P30182
|
FINISHED |
| Object | UCI regulations |
—
|
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: UCI regulations | Statement: [La Flèche Wallonne, safetySupervision, UCI regulations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: safetySupervision Context triple: [La Flèche Wallonne, safetySupervision, UCI regulations]
-
A.
safety
Indicates that an entity provides, ensures, or is associated with protection from harm, danger, or risk for another entity or within a given context.
-
B.
constructionSupervision
Indicates that one entity oversees, manages, or inspects the construction activities or process of another entity or project.
-
C.
supervisionModel
Indicates that one entity oversees, directs, or manages the work, behavior, or performance of another entity.
-
D.
safetyRelevant
chosen
Indicates that the associated entity, condition, or information has a direct impact on safety or is critical for preventing harm or accidents.
-
E.
safetyRegulationEffect
Indicates how a safety regulation influences or changes the conditions, behaviors, or outcomes associated with the regulated entities.
- 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_69ad8b207b0081909d2b48843fbd8795 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcc2d4b848190bf63fb3ed5d3b2d9 |
completed | March 8, 2026, 7:21 p.m. |
| PD | Predicate disambiguation | batch_69adc04ec36c8190bd5b944d4f4d32aa |
completed | March 8, 2026, 6:30 p.m. |
Created at: March 8, 2026, 3:35 p.m.