Triple

T20707684
Position Surface form Disambiguated ID Type / Status
Subject Raumabanen E508946 entity
Predicate offersViewOf P3821 FINISHED
Object Rauma River NE NERFINISHED

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: Rauma River | Statement: [Raumabanen, offersViewOf, Rauma River]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rauma River
Context triple: [Raumabanen, offersViewOf, Rauma River]
  • A. Rauma River chosen
    The Rauma River is a scenic river in Norway renowned for its clear turquoise waters, dramatic valley landscapes, and popularity for salmon fishing and outdoor recreation.
  • B. Tuskora River
    The Tuskora River is a small waterway in western Russia that flows through the city of Kursk.
  • C. Seinäjoki River
    Seinäjoki River is a watercourse in western Finland that flows through and gives its name to the city of Seinäjoki.
  • D. Raisionjoki river
    Raisionjoki river is a small river in southwestern Finland that flows through the town of Raisio before emptying into the Archipelago Sea.
  • E. Kalajoki River
    The Kalajoki River is a watercourse in northern Finland that flows through the town of Ylivieska before emptying into the Gulf of Bothnia.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b4c40ad88190b81f77695366d328 completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6c1952e888190877b79933970f7b0 completed April 21, 2026, 12:15 a.m.
Created at: April 16, 2026, 12:14 p.m.