Triple

T4725800
Position Surface form Disambiguated ID Type / Status
Subject Sèvres E104880 entity
Predicate river P165 FINISHED
Object Seine E6962 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: Seine | Statement: [Sèvres, river, Seine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Seine
Context triple: [Sèvres, river, Seine]
  • A. Rhine
    The Rhine is one of Europe's most important rivers, historically serving as a vital trade route and cultural boundary from the Alps through Germany to the North Sea.
  • B. River Seine chosen
    The River Seine is a major waterway in northern France that flows through the heart of Paris and is central to the city's history, culture, and landscape.
  • C. Meuse
    Meuse is a department in northeastern France known for its rural landscapes and significant World War I battlefields, including Verdun.
  • D. Meuse
    The Meuse is a major European river flowing through France, Belgium, and the Netherlands, historically important for transport, trade, and the development of surrounding regions.
  • E. 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.
  • 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_69bd43ed84648190ae0b7ee8e8d00482 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6446b42081908e023979c9685730 completed March 20, 2026, 3:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69bea45c53908190af21d54dbf9550f0 completed March 21, 2026, 1:59 p.m.
Created at: March 20, 2026, 1:18 p.m.