Triple

T12049152
Position Surface form Disambiguated ID Type / Status
Subject Henri Harpignies E286867 entity
Predicate placeOfActivity P1527 FINISHED
Object Nivernais E150661 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: Nivernais | Statement: [Henri Harpignies, placeOfActivity, Nivernais]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nivernais
Context triple: [Henri Harpignies, placeOfActivity, Nivernais]
  • A. Nivernais chosen
    Nivernais is a historic province in central France, centered around the town of Nevers and known for its rural landscapes and traditional agriculture.
  • B. Tournaisis
    Tournaisis is a historical region in present-day Belgium centered around the city of Tournai, known for its medieval political significance and rich cultural heritage.
  • C. Vendômois
    Vendômois is the French demonym referring to inhabitants or natives of the town of Vendôme in central France.
  • D. Vosgien
    Vosgien is a regional dialect of the Lorrain language spoken in the Vosges area of northeastern France.
  • E. Montévrain
    Montévrain is a suburban commune in the eastern outskirts of Paris, France, known for its proximity to Disneyland Paris and its role in the Marne-la-Vallée new town development.
  • 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_69d6ab4780948190bdb9f7620c2ac27e completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d904227958819084dbd5eb2566c735 completed April 10, 2026, 2:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69f49dc459308190bc88cb550e1d5b86 completed May 1, 2026, 12:34 p.m.
Created at: April 8, 2026, 9:47 p.m.