Triple

T4739222
Position Surface form Disambiguated ID Type / Status
Subject Schibsted E105196 entity
Predicate areaServed P82 FINISHED
Object Sweden E7489 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: Sweden | Statement: [Schibsted, areaServed, Sweden]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sweden
Context triple: [Schibsted, areaServed, Sweden]
  • A. Sweden chosen
    Sweden is a Nordic country in Northern Europe known for its high standard of living, strong welfare state, and long-standing policy of neutrality.
  • B. Finland
    Finland is a Nordic country in Northern Europe known for its extensive forests and lakes, high standard of living, strong welfare state, and history that includes fighting in World War II and maintaining a policy of military non-alignment during the Cold War.
  • C. Norway
    Norway is a Nordic country in Northern Europe known for its high standard of living, extensive welfare state, and dramatic natural landscapes of fjords, mountains, and coastline.
  • D. Swedavia
    Swedavia is a Swedish state-owned company that owns, operates, and develops several of Sweden’s major airports.
  • E. Denmark
    Denmark is a Nordic country in Northern Europe known for its high standard of living, strong welfare state, and role as a founding member of NATO and the United Nations.
  • 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_69bd43ef87a48190a5bc3600711aa032 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6485d690819098dc4a974516da6b completed March 20, 2026, 3:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69be1024cfec819089bd3a23325c9c13 completed March 21, 2026, 3:27 a.m.
Created at: March 20, 2026, 1:19 p.m.