Triple
T3791789
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Morzine |
E89667
|
entity |
| Predicate | nearestCity |
P350
|
FINISHED |
| Object | Thonon-les-Bains |
E79177
|
NE 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: Thonon-les-Bains | Statement: [Morzine, nearestCity, Thonon-les-Bains]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Thonon-les-Bains Context triple: [Morzine, nearestCity, Thonon-les-Bains]
-
A.
Thonon-les-Bains
chosen
Thonon-les-Bains is a French spa and resort town in the Haute-Savoie region, known for its lakeside setting on Lake Geneva and views of the Alps.
-
B.
Nyons
Nyons is a small town in southeastern France renowned for its olive production and picturesque setting in the Drôme Provençale region.
-
C.
Thônes
Thônes is a small Alpine town in southeastern France, known as a gateway to the Aravis mountains and for its traditional Reblochon cheese production.
-
D.
Bilhères
Bilhères is a small mountain village in southwestern France, situated in the Ossau Valley of the Pyrenees.
-
E.
Évian-les-Bains
Évian-les-Bains is a French spa and resort town in the Alps renowned worldwide for its mineral water and scenic lakeside setting.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69aed9597d6881909b6ee3b9de859223 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aee7687c4481908d5e6988e2638b68 |
completed | March 9, 2026, 3:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b53fde1998819088a4436f3ec7205a |
completed | March 14, 2026, 11 a.m. |
Created at: March 9, 2026, 3:15 p.m.