Triple
T21426131
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Forez province |
E528558
|
entity |
| Predicate | borders |
P224
|
FINISHED |
| Object | Velay |
—
|
NE NERFINISHED |
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: Velay | Statement: [Forez province, borders, Velay]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Velay Context triple: [Forez province, borders, Velay]
-
A.
Velay
chosen
Velay is a historical and geographical region in south-central France, known for its volcanic landscapes, traditional agriculture, and medieval heritage within the broader Massif Central area.
-
B.
Miradoux
Miradoux is a small commune in the Gers department of southwestern France, known for its rural charm and traditional Gascon countryside.
-
C.
Vavin
Vavin is a Paris Métro station in the 6th arrondissement, serving the Montparnasse and Jardin du Luxembourg area.
-
D.
Gissac
Gissac is a small rural commune in the Aveyron department of southern France, known for its scenic countryside and traditional agricultural character.
-
E.
Patouès
Patouès is a regional Romance dialect of the Franco-Provençal language traditionally spoken in parts of France, Switzerland, and Italy.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0c455f3688190810bc96365791b0f |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ee813c7a048190a400e364c8df1dcf |
completed | April 26, 2026, 9:18 p.m. |
Created at: April 16, 2026, 5:48 p.m.