Triple

T16762197
Position Surface form Disambiguated ID Type / Status
Subject Normandy waterways network E407373 entity
Predicate hasPart P35 FINISHED
Object River 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: River Seine | Statement: [Normandy waterways network, hasPart, River Seine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: River Seine
Context triple: [Normandy waterways network, hasPart, River Seine]
  • A. 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.
  • B. Source-Seine
    Source-Seine is the small commune in eastern France where the River Seine originates.
  • C. Front de Seine
    Front de Seine is a modern high-rise residential and commercial district in Paris known for its distinctive towers and redevelopment along the Left Bank of the Seine.
  • D. 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.
  • E. Essonne River
    The Essonne River is a tributary of the Seine in northern France, flowing through the Île-de-France region and giving its name to the Essonne department.
  • 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_69d8839174188190909f190097207065 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e3abed67f88190afb1d392ff01a5e7 completed April 18, 2026, 4:06 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00a52d077081908080c61da67e0032 completed May 10, 2026, 3:33 p.m.
Created at: April 10, 2026, 5:21 a.m.