Triple

T1977093
Position Surface form Disambiguated ID Type / Status
Subject Nord (department) E42939 entity
Predicate containsCity P294 FINISHED
Object Maubeuge E228647 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: Maubeuge | Statement: [Nord (department), containsCity, Maubeuge]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maubeuge
Context triple: [Nord (department), containsCity, Maubeuge]
  • A. Maubeuge chosen
    Maubeuge is a fortified industrial town in northern France near the Belgian border, historically significant for its strategic military position.
  • B. Metz
    Metz is a historic city in northeastern France known for its Gothic Saint-Stephen Cathedral, Roman and medieval heritage, and role as the capital of the Moselle department in the Grand Est region.
  • C. Thionville
    Thionville is a town in northeastern France near the Luxembourg border, known historically as a strategic industrial and military center in the Moselle region.
  • D. Diekirch
    Diekirch is a town in northern Luxembourg known for its role in World War II, particularly during the country's liberation, and for its national military museum.
  • E. Reims
    Reims is a historic city in northeastern France known for its Gothic cathedral, role in French coronations, and significance during both World Wars.
  • 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_69a8871289048190b00b0d7744b7b2b1 completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abb3f9a87c8190816db3888787ad76 completed March 7, 2026, 5:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae95eb4db481909ab7507147f1d674 completed March 9, 2026, 9:42 a.m.
Created at: March 4, 2026, 7:36 p.m.