Triple

T15845003
Position Surface form Disambiguated ID Type / Status
Subject Helgeland coast E384191 entity
Predicate hasTown P847 FINISHED
Object Mo i Rana E74442 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: Mo i Rana | Statement: [Helgeland coast, hasTown, Mo i Rana]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mo i Rana
Context triple: [Helgeland coast, hasTown, Mo i Rana]
  • A. Mo i Rana chosen
    Mo i Rana is an industrial town in Nordland county, Norway, known for its steel industry, proximity to the Arctic Circle, and role as a regional hub in Northern Norway.
  • B. Rannungen
    Rannungen is a small municipality in the Bavarian region of Germany, situated within the rural district of Rhön-Grabfeld.
  • C. Dovrebanen
    Dovrebanen is a major Norwegian railway line connecting Oslo and Trondheim across the Dovrefjell mountain area.
  • D. Loggal Oya
    Loggal Oya is a river in Sri Lanka that serves as one of the tributaries feeding the country’s longest river system.
  • E. Runhällen
    Runhällen is a small locality in central Sweden situated within Heby Municipality in Uppsala County.
  • 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_69d86da422088190aac39e32e6c68429 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e142eb20088190bb45e37ce3291ef2 completed April 16, 2026, 8:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffa1412c9481909808473e14058033 completed May 9, 2026, 9:04 p.m.
Created at: April 10, 2026, 4:50 a.m.