Triple

T8445381
Position Surface form Disambiguated ID Type / Status
Subject Östersund Ski Stadium E199660 entity
Predicate operator P179 FINISHED
Object City of 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: City of Östersund | Statement: [Östersund Ski Stadium, operator, City of Östersund]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: City of Östersund
Context triple: [Östersund Ski Stadium, operator, City of 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. Strömstad
    Strömstad is a coastal town and municipality in western Sweden, near the Norwegian border, known for its archipelago, tourism, and ferry connections.
  • 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. 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.
  • E. Ystad
    Ystad is a historic coastal town in southern Sweden known for its medieval architecture and as the setting of Henning Mankell’s Kurt Wallander crime novels.
  • 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_69ce88bc6b008190a93fbd41089d6c72 completed April 2, 2026, 3:18 p.m.
Created at: March 30, 2026, 6:09 p.m.