Triple

T4938877
Position Surface form Disambiguated ID Type / Status
Subject Varennes-en-Argonne E110879 entity
Predicate locatedInAdministrativeTerritorialEntity P40 FINISHED
Object Meuse E93477 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: Meuse | Statement: [Varennes-en-Argonne, locatedInAdministrativeTerritorialEntity, Meuse]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Meuse
Context triple: [Varennes-en-Argonne, locatedInAdministrativeTerritorialEntity, Meuse]
  • A. Meuse
    The Meuse is a major European river flowing through France, Belgium, and the Netherlands, historically important for transport, trade, and the development of surrounding regions.
  • B. Meuse chosen
    Meuse is a department in northeastern France known for its rural landscapes and significant World War I battlefields, including Verdun.
  • C. Sambre
    The Sambre is a major river in northern France and southern Belgium that flows through the Walloon region before joining the Meuse at Namur.
  • D. Rijn
    Rijn is the Dutch name for the major European river known in English as the Rhine.
  • E. Rhens
    Rhens is a historic town on the Rhine River in western Germany, known for its medieval role as a meeting place of the prince-electors of the Holy Roman Empire.
  • 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_69bd4415eee08190bdce70276e56a5b4 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd7088f6e48190bf09e58ab053a4d1 completed March 20, 2026, 4:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69bed90711188190942aefd5da31496d completed March 21, 2026, 5:44 p.m.
Created at: March 20, 2026, 1:31 p.m.