Triple

T20231407
Position Surface form Disambiguated ID Type / Status
Subject KooKoo E495533 entity
Predicate hasFanBaseLocation P897 FINISHED
Object Kouvola region 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: Kouvola region | Statement: [KooKoo, hasFanBaseLocation, Kouvola region]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kouvola region
Context triple: [KooKoo, hasFanBaseLocation, Kouvola region]
  • A. Kouvola region chosen
    The Kouvola region is an area in southeastern Finland centered around the city of Kouvola, known for its forests, lakes, and role as a regional transport and commercial hub.
  • B. Kuopio region
    The Kuopio region is a central area of Eastern Finland known for its lakes, forests, and the city of Kuopio as its main urban and economic hub.
  • C. Kainuu region
    Kainuu region is an eastern Finnish region known for its vast forests, numerous lakes, and sparsely populated rural landscapes.
  • D. Tampere region
    The Tampere region is a major urban and economic area in southern Finland centered on the city of Tampere, known for its industry, technology, and cultural life.
  • E. Jyväskylä region
    The Jyväskylä region is a central Finnish area known for its lakes, forests, and the city of Jyväskylä, a major hub of education, culture, and technology.
  • 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_69da626cff80819097b530718a7c98b6 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e66fddafac819089cef4158f5e0ab5 completed April 20, 2026, 6:26 p.m.
Created at: April 11, 2026, 11:39 p.m.