Triple

T18312969
Position Surface form Disambiguated ID Type / Status
Subject Thorbjörn Fälldin E438675 entity
Predicate residence P75 FINISHED
Object Ångermanland NE NERFINISHED

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: Ångermanland | Statement: [Thorbjörn Fälldin, residence, Ångermanland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ångermanland
Context triple: [Thorbjörn Fälldin, residence, Ångermanland]
  • A. Ångermanland chosen
    Ångermanland is a historical province in northern Sweden known for its deep river valleys, forested landscapes, and coastal areas along the Gulf of Bothnia.
  • B. Jämtland region
    Jämtland region is a sparsely populated county in central Sweden known for its lakes, forests, mountains, and outdoor recreation tourism.
  • C. Norrbotten County
    Norrbotten County is Sweden’s northernmost and largest county, known for its Arctic climate, vast wilderness, and sparsely populated landscapes.
  • D. Södermanland
    Södermanland is a historical province in eastern Sweden, located south of Lake Mälaren and west of the Baltic Sea, known for its castles, lakes, and early Swedish cultural heritage.
  • E. Dalsland
    Dalsland is a historical province in western Sweden known for its forests, lakes, and rural landscapes.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b916a2d081909e249e4902f6aad9 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e5021a96b48190976273be3ff3e5c6 completed April 19, 2026, 4:26 p.m.
Created at: April 10, 2026, 10:36 a.m.