Triple

T11685349
Position Surface form Disambiguated ID Type / Status
Subject Northern France E277724 entity
Predicate hasMajorRiver P165 FINISHED
Object Oise E47853 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: Oise | Statement: [Northern France, hasMajorRiver, Oise]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oise
Context triple: [Northern France, hasMajorRiver, Oise]
  • A. Oise chosen
    Oise is a major river in northern France that flows through regions such as Picardy and Île-de-France before joining the Seine near Paris.
  • B. Vosgien
    Vosgien is a regional dialect of the Lorrain language spoken in the Vosges area of northeastern France.
  • C. Oise River
    The Oise River is a major waterway in northern France and southern Belgium that flows into the Seine and serves as an important route for inland navigation and commerce.
  • D. Vallée de la Marne
    Vallée de la Marne is a key subregion of France’s Champagne wine area, known for its vineyards along the Marne River and its significant production of Pinot Meunier–based sparkling wines.
  • E. Aisne
    Aisne is a department in northern France known for its historic towns, World War I battlefields, and rural landscapes.
  • 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_69d6aafe02d881909900d54ad7d4af84 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a463f6448190a4c8e1651a2bd905 completed April 10, 2026, 7:19 a.m.
NED1 Entity disambiguation (via context triple) batch_69f6a52fcfa081909cc312a56bf12693 completed May 3, 2026, 1:30 a.m.
Created at: April 8, 2026, 9:40 p.m.