Triple

T3750056
Position Surface form Disambiguated ID Type / Status
Subject Châlons Vatry Airport E81306 entity
Predicate locatedIn P40 FINISHED
Object Marne E46315 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: Marne | Statement: [Châlons Vatry Airport, locatedIn, Marne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Marne
Context triple: [Châlons Vatry Airport, locatedIn, Marne]
  • A. Marne chosen
    The Marne is a major river in northeastern France that flows through the Île-de-France region before joining the Seine near Paris.
  • B. Aisne
    Aisne is a department in northern France known for its historic towns, World War I battlefields, and rural landscapes.
  • C. Aisne
    Aisne is a river in northeastern France that flows through the Champagne and Picardy regions before joining the Oise River.
  • D. Vallée de la Marne
    Vallée de la Marne is a key subregion of France’s Champagne wine area, known for its vineyards along the Marne River and its significant production of Pinot Meunier–based sparkling wines.
  • E. Nièvre
    Nièvre is a rural department in central France’s Bourgogne-Franche-Comté region, known for its rolling countryside, the Loire River, and its capital city Nevers.
  • 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_69ad8b19b7b08190a6188804e99c53e9 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69adcb6d0ac4819092c9a41cc60f518d completed March 8, 2026, 7:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69be4379623c8190856b03238e3ef0dd completed March 21, 2026, 7:06 a.m.
Created at: March 8, 2026, 3:35 p.m.