Triple

T680139
Position Surface form Disambiguated ID Type / Status
Subject Gardon River E13163 entity
Predicate flowsThrough P225 FINISHED
Object Cévennes E56142 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: Cévennes | Statement: [Gardon River, flowsThrough, Cévennes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cévennes
Context triple: [Gardon River, flowsThrough, Cévennes]
  • A. Cévennes chosen
    The Cévennes is a rugged mountainous region in south-central France known for its dramatic landscapes, chestnut forests, and historical role as a refuge for Protestant Huguenots.
  • B. Massif Central
    The Massif Central is a vast highland region in south-central France characterized by ancient volcanic mountains, plateaus, and deep river valleys.
  • C. Drôme
    Drôme is a department in southeastern France known for its diverse landscapes, historic towns, and location between the Alps and the Rhône Valley.
  • D. Grands Causses
    Grands Causses is a rugged limestone plateau region in southern France known for its deep gorges, dramatic cliffs, and pastoral landscapes within the broader Massif Central.
  • E. Haute-Loire
    Haute-Loire is a rural department in south-central France, known for its volcanic landscapes, the upper Loire River valley, and historic towns such as Le Puy-en-Velay.
  • 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_69a4933d3bf88190972041cd8cf143b9 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a4a04f4efc819082767a7517fa760a completed March 1, 2026, 8:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69a5dc9f5f7c8190a766c6b545d1abd8 completed March 2, 2026, 6:53 p.m.
Created at: March 1, 2026, 7:36 p.m.