Triple

T2149286
Position Surface form Disambiguated ID Type / Status
Subject Hauts-de-France E47141 entity
Predicate contains P35 FINISHED
Object Arras E187526 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: Arras | Statement: [Hauts-de-France, contains, Arras]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Arras
Context triple: [Hauts-de-France, contains, Arras]
  • A. Arras chosen
    Arras is a historic city in northern France renowned for its Flemish-Baroque architecture, grand squares, and role as a strategic site in both World Wars.
  • B. Saint-Omer
    Saint-Omer is a historic town in northern France known for its medieval architecture, strategic military importance, and role in Franco-Spanish conflicts.
  • C. Cambrai
    Cambrai is a historic city in northern France known for its medieval heritage, role in World War I, and traditional confectionery.
  • D. Valenciennes
    Valenciennes is a historic industrial city in northern France near the Belgian border, known for its former coal and steel industries and its rich artistic and architectural heritage.
  • E. Cambrésis
    Cambrésis is a historic region in northern France centered around the city of Cambrai, known for its medieval bishopric and strategic importance in European conflicts.
  • 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_69a88a1933e0819094f18426ed74180f completed March 4, 2026, 7:38 p.m.
NER Named-entity recognition batch_69abbe44d2608190986467d43ee224d4 completed March 7, 2026, 5:57 a.m.
NED1 Entity disambiguation (via context triple) batch_69b01cf667bc81909d1de1542d53076a completed March 10, 2026, 1:30 p.m.
Created at: March 4, 2026, 7:44 p.m.