Triple

T21151032
Position Surface form Disambiguated ID Type / Status
Subject Poitou E521187 entity
Predicate followedBy P78 FINISHED
Object Poitou-Charentes NE NERFINISHED

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: Poitou-Charentes | Statement: [Poitou, followedBy, Poitou-Charentes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Poitou-Charentes
Context triple: [Poitou, followedBy, Poitou-Charentes]
  • A. Poitou chosen
    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.
  • B. Mayenne
    Mayenne is a department in northwestern France known for its rural landscapes, historic towns, and location within the former province of Maine.
  • C. 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.
  • D. Maine-et-Loire
    Maine-et-Loire is a department in western France known for its historic towns, châteaux, and vineyards along the Loire River.
  • 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 (2 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_69e0b50c6a848190a4e525a77a319b8a completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e72401830c8190a2008c40c4174d97 completed April 21, 2026, 7:15 a.m.
Created at: April 16, 2026, 2:58 p.m.