Triple

T20184550
Position Surface form Disambiguated ID Type / Status
Subject Jean Racine E492819 entity
Predicate placeOfBirth P1 FINISHED
Object Aisne 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: Aisne | Statement: [Jean Racine, placeOfBirth, Aisne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Aisne
Context triple: [Jean Racine, placeOfBirth, Aisne]
  • A. Aisne chosen
    Aisne is a department in northern France known for its historic towns, World War I battlefields, and rural landscapes.
  • B. Aisne
    Aisne is a river in northeastern France that flows through the Champagne and Picardy regions before joining the Oise River.
  • C. Marne
    Marne is a department in northeastern France known for its Champagne-producing vineyards and historic towns such as Reims and Châlons-en-Champagne.
  • D. Marne
    The Marne is a major river in northeastern France that flows through the Île-de-France region before joining the Seine near Paris.
  • E. Marne
    Marne is a small city located in Cass County in the southwestern part of the U.S. state of Iowa.
  • 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_69da6268a034819081cbd9ea5a1c9475 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e668f199688190a42094cce220f6f2 completed April 20, 2026, 5:57 p.m.
Created at: April 11, 2026, 11:36 p.m.