Triple
T18291052
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bagnes |
E438114
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Versegères |
—
|
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: Versegères | Statement: [Bagnes, contains, Versegères]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Versegères Context triple: [Bagnes, contains, Versegères]
-
A.
Versegères
chosen
Versegères is a small village in the Swiss canton of Valais, situated within the alpine Val de Bagnes region.
-
B.
Ferrière
Ferrière is a French-language surname of Swiss origin borne by various notable individuals, including social worker and humanitarian Suzanne Ferrière.
-
C.
Gagnière
Gagnière is a French surname, likely of regional origin, associated with individuals such as Mahoudeau.
-
D.
Seytroux
Seytroux is a small mountain village and commune in the Haute-Savoie department of southeastern France, situated in the Chablais region of the French Alps.
-
E.
Bouvron
Bouvron is a small commune in western France, situated in the Loire-Atlantique department of the Pays de la Loire region.
- 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_69d8b914530c8190b4474d862a2b2a1b |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e500fee5248190928e68ddaa4d90d7 |
completed | April 19, 2026, 4:21 p.m. |
Created at: April 10, 2026, 10:35 a.m.