Triple

T8445652
Position Surface form Disambiguated ID Type / Status
Subject Östersund Municipal Council E199667 entity
Predicate meetsIn P40 FINISHED
Object Östersund E38859 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: Östersund | Statement: [Östersund Municipal Council, meetsIn, Östersund]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Östersund
Context triple: [Östersund Municipal Council, meetsIn, Östersund]
  • A. Östersund chosen
    Östersund is a city in central Sweden known for its strong winter sports tradition and repeated bids to host the Winter Olympics.
  • B. Örnsköldsvik
    Örnsköldsvik is a coastal town in northern Sweden known for its strong ice hockey tradition and as the hometown of several prominent NHL players.
  • C. Karlskoga
    Karlskoga is an industrial town in central Sweden known for its historical association with Alfred Nobel and its role in the country’s arms and engineering industries.
  • D. Sundsvall
    Sundsvall is a coastal city in central Sweden known as an important industrial and commercial center on the Gulf of Bothnia.
  • E. Skellefteå
    Skellefteå is a city in northern Sweden known for its growing high-tech and green industry sector, particularly in battery manufacturing, as well as its ice hockey tradition.
  • 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_69ca83170f9081909cd98f55614c6476 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe3138ee08190918cd82adbe2d9a1 completed March 31, 2026, 3:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69cfb9f030fc8190961bcb067350e3e6 completed April 3, 2026, 1 p.m.
Created at: March 30, 2026, 6:09 p.m.