Triple

T15471979
Position Surface form Disambiguated ID Type / Status
Subject Paris road network E376683 entity
Predicate crosses P416 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: [Paris road network, crosses, River Seine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: River Seine
Context triple: [Paris road network, crosses, 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_69d85cd21dcc81908646251b1c26ea00 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e03f6c57308190b4cfe661c26addd4 completed April 16, 2026, 1:46 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff454ac84c8190b1979e6caca3ee66 completed May 9, 2026, 2:31 p.m.
Created at: April 10, 2026, 3:33 a.m.