Triple

T11067008
Position Surface form Disambiguated ID Type / Status
Subject Seine at Charenton-le-Pont E261650 entity
Predicate receivesWaterFrom P415 FINISHED
Object Marne River 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 River | Statement: [Seine at Charenton-le-Pont, receivesWaterFrom, Marne River]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Marne River
Context triple: [Seine at Charenton-le-Pont, receivesWaterFrom, Marne River]
  • 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. Marne
    Marne is a small city located in Cass County in the southwestern part of the U.S. state of Iowa.
  • C. Aube River
    The Aube River is a major waterway in northeastern France that flows through the Champagne region before joining the Seine.
  • 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. Aisne
    Aisne is a department in northern France known for its historic towns, World War I battlefields, and rural landscapes.
  • 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_69d6aa98650481908609c7c56bfa7902 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d79920428c81908db824ab54e08e8d completed April 9, 2026, 12:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69f49c59538081909102a6954f564e46 completed May 1, 2026, 12:28 p.m.
Created at: April 8, 2026, 9:26 p.m.