Triple

T19827971
Position Surface form Disambiguated ID Type / Status
Subject Viliya E476377 entity
Predicate alternativeName P39 FINISHED
Object Neris 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: Neris | Statement: [Viliya, alternativeName, Neris]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Neris
Context triple: [Viliya, alternativeName, Neris]
  • A. Neris River chosen
    The Neris River is a major river in Belarus and Lithuania that flows through the city of Kaunas before joining the Nemunas River.
  • B. Nemunas River
    The Nemunas River is the largest river in Lithuania, flowing through major cities like Kaunas and forming part of the country’s border before emptying into the Curonian Lagoon.
  • C. Akmena-Danė River
    The Akmena-Danė River is a waterway in western Lithuania that flows through the port city of Klaipėda before emptying into the Curonian Lagoon.
  • D. Baltiyskaya
    Baltiyskaya is a planned Moscow Metro station on the Bolshaya Koltsevaya line intended to serve the northwestern part of the city.
  • E. Gauja
    Gauja is the longest river entirely within Latvia, known for its scenic valley, sandstone cliffs, and the national park that bears its name.
  • 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_69d8e51c7c188190b926f3a2a7b5f881 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e656cc0f2c81908137caa4c2087027 completed April 20, 2026, 4:39 p.m.
Created at: April 10, 2026, 1:50 p.m.