Triple

T1781356
Position Surface form Disambiguated ID Type / Status
Subject Paris Métro Line 4 E39297 entity
Predicate runsUnder P23495 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 Métro Line 4, runsUnder, River Seine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: River Seine
Context triple: [Paris Métro Line 4, runsUnder, 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. Rive Droite
    Rive Droite is the northern, historically affluent bank of the Seine in Paris, known for its grand boulevards, major museums, and iconic landmarks.
  • D. Baie de Seine
    Baie de Seine is a coastal bay in northern France where the Seine River meets the English Channel, known for its maritime traffic and proximity to ports like Le Havre.
  • E. Loire
    The Loire is the longest river in France, renowned for its scenic valley dotted with historic châteaux and vineyards.
  • 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_69a88630519c8190a17addd83c4a3ef4 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa64e22d6881909ba6ec120b320918 completed March 6, 2026, 5:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69af174f97248190817a64dfbf98c360 completed March 9, 2026, 6:54 p.m.
Created at: March 4, 2026, 7:31 p.m.