Triple

T11312433
Position Surface form Disambiguated ID Type / Status
Subject Communauté urbaine du Grand Reims E267871 entity
Predicate department P1467 FINISHED
Object Marne E992253 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: [Communauté urbaine du Grand Reims, department, Marne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Marne
Context triple: [Communauté urbaine du Grand Reims, department, Marne]
  • A. Marne chosen
    Marne is a department in northeastern France known for its Champagne-producing vineyards and historic towns such as Reims and Châlons-en-Champagne.
  • B. Marne
    The Marne is a major river in northeastern France that flows through the Île-de-France region before joining the Seine near Paris.
  • C. Marne
    Marne is a small city located in Cass County in the southwestern part of the U.S. state of Iowa.
  • D. Aisne
    Aisne is a department in northern France known for its historic towns, World War I battlefields, and rural landscapes.
  • E. Aisne
    Aisne is a river in northeastern France that flows through the Champagne and Picardy regions before joining the Oise River.
  • 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_69d6aaca5c24819083db46a30d86cb34 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e9c1b7dc81908d8cc768c47390d3 completed April 9, 2026, 6:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69f671788ec88190852df74698bc4518 completed May 2, 2026, 9:49 p.m.
Created at: April 8, 2026, 9:32 p.m.