Triple

T9841571
Position Surface form Disambiguated ID Type / Status
Subject Dalane district E239237 entity
Predicate borders P224 FINISHED
Object Jæren district E384979 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: Jæren district | Statement: [Dalane district, borders, Jæren district]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jæren district
Context triple: [Dalane district, borders, Jæren district]
  • A. Ryfylke district
    Ryfylke district is a traditional region in Rogaland county, southwestern Norway, known for its fjords, mountains, and scattered rural communities.
  • B. Jæren region chosen
    The Jæren region is a coastal area in southwestern Norway known for its flat, fertile farmland, long sandy beaches, and the city of Stavanger as its main urban center.
  • C. Ringerike district
    Ringerike district is a historic region in southeastern Norway known for its cultural heritage, distinctive landscape, and early medieval significance.
  • D. Sunnmøre district
    Sunnmøre district is a coastal region in the southwestern part of Møre og Romsdal county in Norway, known for its fjords, islands, and maritime communities.
  • E. Sogn og Fjordane
    Sogn og Fjordane was a former county in western Norway known for its dramatic fjords, mountains, and coastal landscapes.
  • 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_69ca84e3f0c48190ada72a65ebd50efd completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb34c920c81909b56ed9936b15f9b completed April 2, 2026, 12:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69d1d5d9673c8190ada27bef9220798d completed April 5, 2026, 3:24 a.m.
Created at: March 30, 2026, 8:33 p.m.