Triple

T13413292
Position Surface form Disambiguated ID Type / Status
Subject Jules Renard E320144 entity
Predicate placeOfBirth P1 FINISHED
Object Mayenne E372757 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: Mayenne | Statement: [Jules Renard, placeOfBirth, Mayenne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mayenne
Context triple: [Jules Renard, placeOfBirth, Mayenne]
  • A. Mayenne
    Mayenne is a river in western France that flows through the regions of Normandy and Pays de la Loire before joining other waterways to form the Loire basin.
  • B. Mayenne chosen
    Mayenne is a department in northwestern France known for its rural landscapes, historic towns, and location within the former province of Maine.
  • C. Maine-et-Loire
    Maine-et-Loire is a department in western France known for its historic towns, châteaux, and vineyards along the Loire River.
  • D. Poitou
    Poitou is a historical region in western France that was a significant stronghold and cultural center for French Protestants (Huguenots) during the Reformation and subsequent religious conflicts.
  • E. Deux-Sèvres
    Deux-Sèvres is a department in western France known for its rural landscapes, historic towns such as Niort, and location within the Nouvelle-Aquitaine region.
  • 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_69d806b943cc8190b6af624d385d7e12 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69dbaeb556948190af008c88e5bbf051 completed April 12, 2026, 2:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69f75d86d32c8190a1d9ce72e99426e2 completed May 3, 2026, 2:36 p.m.
Created at: April 9, 2026, 9:35 p.m.