Triple

T5159506
Position Surface form Disambiguated ID Type / Status
Subject Soignies municipality E116399 entity
Predicate contains P35 FINISHED
Object Soignies E452605 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: Soignies | Statement: [Soignies municipality, contains, Soignies]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Soignies
Context triple: [Soignies municipality, contains, Soignies]
  • A. Soignies chosen
    Soignies is a historic town and municipality in the province of Hainaut in Wallonia, Belgium, known for its medieval collegiate church and blue limestone industry.
  • B. Saintois
    A Saintois is a resident or native of the coastal commune of Saintes-Maries-de-la-Mer in southern France.
  • C. Fougères
    Fougères is a historic town in Brittany, northwestern France, known for its impressive medieval castle and well-preserved old quarter.
  • D. Remigny
    Remigny is a small wine-producing village in the Burgundy region of eastern France, situated near the renowned appellation of Santenay.
  • E. Dreux
    Dreux is a historic town in northern France known for its royal chapel and role as a regional center in the Eure-et-Loir department.
  • 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_69bd445edb3881909b93b34d260717fc completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd790613bc819084765cd4ea648dc9 completed March 20, 2026, 4:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69bfabe6de448190a4e0c2e537a2e045 completed March 22, 2026, 8:44 a.m.
Created at: March 20, 2026, 1:44 p.m.