Triple
T3768155
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | L’Auto |
E82729
|
entity |
| Predicate | mainCoverage |
P41336
|
FINISHED |
| Object | cycling |
—
|
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: cycling | Statement: [L’Auto, mainCoverage, cycling]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainCoverage Context triple: [L’Auto, mainCoverage, cycling]
-
A.
primaryCoverage
Indicates that one entity serves as the main or principal source of coverage (such as insurance or protection) for another entity.
-
B.
coverageScope
Indicates the extent or range of entities, conditions, or situations that are included under a particular coverage or applicability.
-
C.
providesCoverage
Indicates that one entity supplies protection, insurance, or service coverage to another entity or for a specified risk or scope.
-
D.
keyCoverage
Indicates that one entity provides coverage, protection, or applicability for another in a way that is essential or central to its function or requirements.
-
E.
typicallyCovers
chosen
Indicates that one entity is the kind of thing that usually or normally includes, addresses, or encompasses 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_69ad8b207b0081909d2b48843fbd8795 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcc2bdf6c819088d3c6ace83ca5ea |
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.