Triple

T3504140
Position Surface form Disambiguated ID Type / Status
Subject Somme E74035 entity
Predicate borderedBy P224 FINISHED
Object Oise E326194 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: [Somme, borderedBy, Oise]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oise
Context triple: [Somme, borderedBy, Oise]
  • A. Oise
    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. Oise River chosen
    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.
  • C. 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.
  • D. Aisne
    Aisne is a department in northern France known for its historic towns, World War I battlefields, and rural landscapes.
  • E. Aisne
    Aisne is a river in northeastern France that flows through the Champagne and Picardy regions before joining the Oise River.
  • 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_69ad85ce7a9c81909ddc5cf0cb67a6e3 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adbbf22b1c8190956141d8fb924210 completed March 8, 2026, 6:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdb8e6b8848190a2b7951638f53465 completed March 20, 2026, 9:15 p.m.
Created at: March 8, 2026, 3:18 p.m.