Triple

T18456235
Position Surface form Disambiguated ID Type / Status
Subject Northern Ostrobothnia E450908 entity
Predicate hasMunicipality P847 FINISHED
Object Alavieska 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: Alavieska | Statement: [Northern Ostrobothnia, hasMunicipality, Alavieska]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alavieska
Context triple: [Northern Ostrobothnia, hasMunicipality, Alavieska]
  • A. Alavieska chosen
    Alavieska is a small rural municipality in Northern Ostrobothnia, Finland, known for its agricultural landscape and close-knit community.
  • B. Svaliava
    Svaliava is a small town in western Ukraine known for its scenic Carpathian surroundings and mineral springs.
  • C. Lopevi
    Lopevi is an Oceanic language of Vanuatu, traditionally spoken on Lopevi Island in the central part of the archipelago.
  • D. Altaelva
    Altaelva is a major river in northern Norway known for flowing through the Alta region and its surrounding Arctic landscapes.
  • E. Válega
    Válega is a civil parish located within the municipality of Ovar in northern Portugal, known for its traditional Portuguese architecture and regional cultural heritage.
  • 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_69d8d38345688190b565eac2e4cd7935 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e5264c10408190b2085ade88655c7d completed April 19, 2026, 7 p.m.
Created at: April 10, 2026, 11:31 a.m.