Triple

T2678649
Position Surface form Disambiguated ID Type / Status
Subject Battle of Seneffe E56519 entity
Predicate historicalRegion P915 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: [Battle of Seneffe, historicalRegion, Hainaut]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hainaut
Context triple: [Battle of Seneffe, historicalRegion, 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. Dombes
    Dombes is a historic rural region in eastern France known for its many ponds, wetlands, and traditional fish farming.
  • D. Champagne province
    Champagne province was a historic region in northeastern France known for its medieval fairs, viticulture, and role in the development of the Champagne wine industry.
  • E. Langogne
    Langogne is a small historic town in south-central France, known for its picturesque setting in the Gévaudan region and its traditional rural character.
  • 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_69ab4a4b13fc81909dfdb3f23da46832 completed March 6, 2026, 9:42 p.m.
NER Named-entity recognition batch_69abd9d141888190bbd63e7a2b970fa0 completed March 7, 2026, 7:54 a.m.
NED1 Entity disambiguation (via context triple) batch_69afaf57675c8190a0c4a5fb674c4df6 completed March 10, 2026, 5:42 a.m.
Created at: March 6, 2026, 9:54 p.m.