Triple
T10331281
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TER Auvergne-Rhône-Alpes services |
E242878
|
entity |
| Predicate | connectsCity |
P4245
|
FINISHED |
| Object | Modane |
E55601
|
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: Modane | Statement: [TER Auvergne-Rhône-Alpes services, connectsCity, Modane]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Modane Context triple: [TER Auvergne-Rhône-Alpes services, connectsCity, Modane]
-
A.
Modane
chosen
Modane is a French Alpine town in the Savoie department known as a key transit point through the Fréjus Road and Rail Tunnels between France and Italy.
-
B.
Moreuil
Moreuil is a small commune in northern France, located in the Somme department in the Hauts-de-France region.
-
C.
Mouriès
Mouriès is a village in southern France’s Provence region, known for its olive oil production and location near the Alpilles hills.
-
D.
Malaucène
Malaucène is a picturesque Provençal village in southeastern France, known as a popular base for cyclists and tourists visiting and climbing Mont Ventoux.
-
E.
La Dôle
La Dôle is a prominent mountain peak in the Jura range of western Switzerland, known for its panoramic views over Lake Geneva and the Alps and for hosting telecommunications and weather facilities near its summit.
- 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_69d381af787481908bc401325c760a88 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d7fcaf4c8190bdcfcb953d88ea2f |
completed | April 7, 2026, 10:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d7504679ec8190926d2c5016653cea |
completed | April 9, 2026, 7:07 a.m. |
Created at: April 6, 2026, 11:52 a.m.