Triple

T12787874
Position Surface form Disambiguated ID Type / Status
Subject Monts du Lyonnais E305677 entity
Predicate hasViewOf P854 FINISHED
Object Lyonnais plain E567748 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: Lyonnais plain | Statement: [Monts du Lyonnais, hasViewOf, Lyonnais plain]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lyonnais plain
Context triple: [Monts du Lyonnais, hasViewOf, Lyonnais plain]
  • A. Montpellier plain
    The Montpellier plain is a low-lying area surrounding the city of Montpellier in southern France, characterized by its agricultural landscapes and Mediterranean climate.
  • B. Alsace plain
    The Alsace plain is a broad, fertile lowland region in northeastern France, lying between the Vosges Mountains and the Rhine River and known for its agriculture, vineyards, and picturesque villages.
  • C. Béziers plain
    The Béziers plain is a fertile lowland region in southern France known for its vineyards, agriculture, and proximity to the Mediterranean coast.
  • D. Plaine de France
    Plaine de France is a fertile agricultural plain and historical region in northern Île-de-France, just north of Paris.
  • E. Rhône plain chosen
    The Rhône plain is a broad, fertile lowland region in southeastern France shaped by the Rhône River, known for its agriculture, vineyards, and historic settlements.
  • 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_69d7bdf366888190a8cccb982606889c completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96e5dbdb88190a1b06721ada51627 completed April 10, 2026, 9:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69f69b925b3c81909f5e604c0f457645 completed May 3, 2026, 12:49 a.m.
Created at: April 9, 2026, 5:29 p.m.