Triple

T7627277
Position Surface form Disambiguated ID Type / Status
Subject Lule River E172666 entity
Predicate region P40 FINISHED
Object Norrbotten E346158 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: Norrbotten | Statement: [Lule River, region, Norrbotten]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Norrbotten
Context triple: [Lule River, region, Norrbotten]
  • A. Ångermanland
    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. Norrbotten County chosen
    Norrbotten County is Sweden’s northernmost and largest county, known for its Arctic climate, vast wilderness, and sparsely populated landscapes.
  • C. Jämtland region
    Jämtland region is a sparsely populated county in central Sweden known for its lakes, forests, mountains, and outdoor recreation tourism.
  • D. Västernorrland County
    Västernorrland County is a coastal county in northern Sweden known for its forests, rivers, and towns such as Sundsvall and Härnösand.
  • E. Nordland
    Nordland is a long coastal county in northern Norway known for its dramatic fjords, islands like the Lofoten archipelago, and Arctic 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_69c699517e348190bd3348b6889200f2 completed March 27, 2026, 2:50 p.m.
NER Named-entity recognition batch_69c6fa8150ac8190908aec411b0f4e50 completed March 27, 2026, 9:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69c9162980708190be2a347b2322c09c completed March 29, 2026, 12:08 p.m.
Created at: March 27, 2026, 3:56 p.m.