Triple

T2936583
Position Surface form Disambiguated ID Type / Status
Subject Jean-Baptiste Carpeaux E79283 entity
Predicate birthPlace P1 FINISHED
Object Valenciennes E112910 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: Valenciennes | Statement: [Jean-Baptiste Carpeaux, birthPlace, Valenciennes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Valenciennes
Context triple: [Jean-Baptiste Carpeaux, birthPlace, Valenciennes]
  • A. Valenciennes chosen
    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.
  • B. Villeneuve d’Ascq
    Villeneuve d’Ascq is a suburban city in northern France near Lille, known for its universities, technology parks, and modernist urban planning.
  • C. 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.
  • D. Houilles
    Houilles is a suburban commune in north-central France, located in the western outskirts of Paris within the Yvelines department.
  • E. Arras
    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.
  • 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_69ad8b0fbab081908f6a61567c045d8d completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad983df5e08190939cd8acf8ad5b55 completed March 8, 2026, 3:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69b34ba8e6b081908866127ff3da46e0 completed March 12, 2026, 11:26 p.m.
Created at: March 8, 2026, 2:56 p.m.