Triple

T15216746
Position Surface form Disambiguated ID Type / Status
Subject Sogn region E363655 entity
Predicate borders P224 FINISHED
Object Hallingsdal region E107387 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: Hallingsdal region | Statement: [Sogn region, borders, Hallingsdal region]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hallingsdal region
Context triple: [Sogn region, borders, Hallingsdal region]
  • A. Hallingdal chosen
    Hallingdal is a major valley and traditional district in southeastern Norway, known for its river, ski resorts, and rich folk culture.
  • B. Hadeland district
    Hadeland district is a traditional rural region in southeastern Norway known for its historic farms, forests, and lakes north of Oslo.
  • C. Sunnfjord region
    The Sunnfjord region is a coastal district in western Norway known for its deep fjords, rugged mountains, and traditional rural communities.
  • D. Dovre region
    The Dovre region is a mountainous area in central Norway known for its rugged landscapes, national parks, and rich wildlife, including wild reindeer.
  • E. Ringerike district
    Ringerike district is a historic region in southeastern Norway known for its cultural heritage, distinctive landscape, and early medieval significance.
  • 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_69d85a0ce24c81909c4d3b6475548c95 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e0076f90c481909989befe031a2cae completed April 15, 2026, 9:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69ff0b37e4388190b748e884b3ba7568 completed May 9, 2026, 10:23 a.m.
Created at: April 10, 2026, 3:11 a.m.