Triple

T4201233
Position Surface form Disambiguated ID Type / Status
Subject Dender E86069 entity
Predicate flowsThrough P225 FINISHED
Object Hainaut E86438 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: Hainaut | Statement: [Dender, flowsThrough, Hainaut]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hainaut
Context triple: [Dender, flowsThrough, Hainaut]
  • A. Hainaut chosen
    Hainaut is a historical region in western Europe, now divided between Belgium and France, known for its medieval heritage and role as a frequent battleground in European conflicts.
  • B. Brionnais
    Brionnais is a historic rural region in eastern France known for its Romanesque churches, traditional stone villages, and Charolais cattle farming.
  • C. Auberjonois
    Auberjonois is a surname most prominently associated with René Auberjonois, an American actor known for roles in film, television, and voice work.
  • D. Wattrelos
    Wattrelos is a commune in northern France near the Belgian border, known historically for its textile industry and cross-border cultural ties.
  • E. Dombes
    Dombes is a historic rural region in eastern France known for its many ponds, wetlands, and traditional fish farming.
  • 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_69aed93b89f48190a31f6d57c760e42f completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af037da30481908106b27a88d59140 completed March 9, 2026, 5:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69b58a14eda88190aaca14644c3e041a completed March 14, 2026, 4:17 p.m.
Created at: March 9, 2026, 3:49 p.m.