Triple
T20096820
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ubaye River |
E496420
|
entity |
| Predicate | hasCityOnBank |
P7935
|
FINISHED |
| Object | Barcelonnette |
—
|
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: Barcelonnette | Statement: [Ubaye River, hasCityOnBank, Barcelonnette]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Barcelonnette Context triple: [Ubaye River, hasCityOnBank, Barcelonnette]
-
A.
Barcelonnette
chosen
Barcelonnette is a small Alpine town in southeastern France known for its picturesque valley setting and historical ties to Mexican emigration.
-
B.
Briançon
Briançon is a fortified alpine town in southeastern France, known as one of the highest cities in Europe and a key historical stronghold near the Italian border.
-
C.
Vert-le-Grand
Vert-le-Grand is a small commune in the Essonne department in the Île-de-France region of northern France.
-
D.
Maurienne
Maurienne is a valley and historic region in the French Alps, known for its mountain landscapes, ski resorts, and role as a major route through the Alps.
-
E.
Bilhères
Bilhères is a small mountain village in southwestern France, situated in the Ossau Valley of the Pyrenees.
- 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_69da626eee3881909f3454986d4a6511 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6666d83448190b3ade3f5b855e820 |
completed | April 20, 2026, 5:46 p.m. |
Created at: April 11, 2026, 11:25 p.m.