Triple

T4348115
Position Surface form Disambiguated ID Type / Status
Subject Trøndersk dialect E97954 entity
Predicate spokenIn P2266 FINISHED
Object Trøndelag E17971 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: Trøndelag | Statement: [Trøndersk dialect, spokenIn, Trøndelag]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Trøndelag
Context triple: [Trøndersk dialect, spokenIn, Trøndelag]
  • A. Trøndelag chosen
    Trøndelag is a central region of Norway known for its historic city of Trondheim, coastal landscapes, and strong cultural traditions.
  • B. Buskerud
    Buskerud is a former county in southeastern Norway known for its varied landscape of forests, rivers, and mountains, including parts of the Hallingdal valley and Hardangervidda plateau.
  • C. Møre og Romsdal
    Møre og Romsdal is a coastal county in western Norway known for its dramatic fjords, islands, and mountainous landscapes.
  • D. Hedmarken
    Hedmarken is a traditional district in Innlandet county in eastern Norway, known for its agricultural landscapes and its central town, Hamar.
  • E. Hedmark
    Hedmark is a former county in eastern Norway known for its vast forests, agriculture, and inland landscapes along the Swedish border.
  • 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_69b34548402c819085ab68b27c235a87 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b351a5559c819081608b0aaf6a0e66 completed March 12, 2026, 11:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69be921df91881909c257fbd3c46073c completed March 21, 2026, 12:42 p.m.
Created at: March 12, 2026, 11:15 p.m.