Triple

T10399563
Position Surface form Disambiguated ID Type / Status
Subject Oise E245108 entity
Predicate borders P224 FINISHED
Object Aisne E83838 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: Aisne | Statement: [Oise, borders, Aisne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Aisne
Context triple: [Oise, borders, 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
    The Marne is a major river in northeastern France that flows through the Île-de-France region before joining the Seine near Paris.
  • D. Marne
    Marne is a small city located in Cass County in the southwestern part of the U.S. state of Iowa.
  • E. Oise-Aisne
    Oise-Aisne is a region in northern France that was a major World War I battlefield, notably during the Aisne and Oise-Aisne offensives.
  • 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_69d381b5116081908d85227bab6d3c0c completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4e9d2e8488190b2bb8f8509903804 completed April 7, 2026, 11:26 a.m.
NED1 Entity disambiguation (via context triple) batch_69e4963545f481909ecc360480b1fc37 completed April 19, 2026, 8:45 a.m.
Created at: April 6, 2026, 12:07 p.m.