Triple
T2175456
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Drôme |
E48515
|
entity |
| Predicate | borders |
P224
|
FINISHED |
| Object | Hautes-Alpes |
E99775
|
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: Hautes-Alpes | Statement: [Drôme, borders, Hautes-Alpes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hautes-Alpes Context triple: [Drôme, borders, Hautes-Alpes]
-
A.
Hautes-Alpes
chosen
Hautes-Alpes is a mountainous department in southeastern France known for its Alpine landscapes, ski resorts, and outdoor recreation.
-
B.
Alpes-de-Haute-Provence
Alpes-de-Haute-Provence is a mountainous department in southeastern France known for its Alpine landscapes, lavender fields, and picturesque Provençal villages.
-
C.
Haute-Savoie
Haute-Savoie is a department in the Auvergne-Rhône-Alpes region of southeastern France, renowned for its Alpine landscapes, ski resorts, and proximity to Mont Blanc and the Swiss and Italian borders.
-
D.
Savoie
Savoie is a mountainous department in southeastern France, known for its Alpine landscapes, ski resorts, and rich Savoyard cultural heritage.
-
E.
Alpes-Maritimes
Alpes-Maritimes is a department in southeastern France on the Mediterranean coast, known for the French Riviera cities of Nice and Cannes and its mix of coastal and Alpine landscapes.
- 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_69a88aa3faa48190995b233af6525815 |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abbece30888190936853740ff6cb02 |
completed | March 7, 2026, 5:59 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae5d9eff988190a02734bd73616cba |
completed | March 9, 2026, 5:41 a.m. |
Created at: March 4, 2026, 7:45 p.m.