Triple

T9191257
Position Surface form Disambiguated ID Type / Status
Subject Dauphiné E220592 entity
Predicate containsRegion P285 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: [Dauphiné, containsRegion, Hautes-Alpes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hautes-Alpes
Context triple: [Dauphiné, containsRegion, 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_69ca83e7ba70819088b74866d9da2c30 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69ccd5bf25c081909e651b67ef8ecc33 completed April 1, 2026, 8:22 a.m.
NED1 Entity disambiguation (via context triple) batch_69d077797be081908300a5baa0041ce5 completed April 4, 2026, 2:29 a.m.
Created at: March 30, 2026, 7:24 p.m.