Triple

T8518608
Position Surface form Disambiguated ID Type / Status
Subject Voss E201638 entity
Predicate formerCounty P1069 FINISHED
Object Hordaland E366605 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: Hordaland | Statement: [Voss, formerCounty, Hordaland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hordaland
Context triple: [Voss, formerCounty, Hordaland]
  • A. Hordaland chosen
    Hordaland was a former county in western Norway known for its fjords, coastal landscapes, and the city of Bergen.
  • B. Rogaland
    Rogaland is a county in southwestern Norway known for its rugged coastline, fjords, and the oil industry centered around the city of Stavanger.
  • C. Sogn og Fjordane
    Sogn og Fjordane was a former county in western Norway known for its dramatic fjords, mountains, and coastal landscapes.
  • D. Aust-Agder
    Aust-Agder was a former county in southern Norway known for its coastal towns, forests, and role in the country’s maritime and timber industries.
  • E. Agder
    Agder is a county in southern Norway known for its long coastline, maritime heritage, and popular coastal towns and islands.
  • 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_69ca8321bb44819081b74df0b710276d completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe627de908190b463da0f26da4ffb completed March 31, 2026, 3:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69cef30c02908190892234cab9a22ad4 completed April 2, 2026, 10:51 p.m.
Created at: March 30, 2026, 6:16 p.m.