Triple

T2122452
Position Surface form Disambiguated ID Type / Status
Subject Langres Plateau E43955 entity
Predicate sourceRegionOf P410 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: [Langres Plateau, sourceRegionOf, Marne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Marne
Context triple: [Langres Plateau, sourceRegionOf, 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. 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.
  • D. Aube River
    The Aube River is a major waterway in northeastern France that flows through the Champagne region before joining the Seine.
  • E. Somme River
    The Somme River is a waterway in northern France that became historically significant as the site of one of World War I’s largest and bloodiest battles.
  • 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_69a88717cfe48190b7ecdd68c824848a completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abbdc3a12081908e95ae870207367f completed March 7, 2026, 5:55 a.m.
NED1 Entity disambiguation (via context triple) batch_69b324b9ba9c8190bfba5d7539cffeb2 completed March 12, 2026, 8:40 p.m.
Created at: March 4, 2026, 7:44 p.m.