Triple

T10707010
Position Surface form Disambiguated ID Type / Status
Subject Pori E252433 entity
Predicate hasNeighbouringMunicipality P224 FINISHED
Object Nakkila E777392 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: Nakkila | Statement: [Pori, hasNeighbouringMunicipality, Nakkila]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nakkila
Context triple: [Pori, hasNeighbouringMunicipality, Nakkila]
  • A. Nakkila chosen
    Nakkila is a small municipality in western Finland known for its rural landscapes and location along the Kokemäki River.
  • B. Keilaniemi
    Keilaniemi is a coastal district in Espoo, Finland, known as a major business hub hosting numerous corporate headquarters and high-rise office buildings.
  • C. Kallio
    Kallio is a Finnish surname most notably borne by Kyösti Kallio, who served as the fourth President of Finland.
  • D. Lapua
    Lapua is a small town in western Finland known for its historical significance, including a former state cartridge factory and its role in the Lapua Movement.
  • E. Nayki
    Nayki is an island located within Lake Rakshastal in the Tibet Autonomous Region of China.
  • 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_69d6aa5cbabc8190973e683950d89faf completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6fddfbed48190810bb3faee473fde completed April 9, 2026, 1:16 a.m.
NED1 Entity disambiguation (via context triple) batch_69d9990760b48190a05753974cdf556c completed April 11, 2026, 12:42 a.m.
Created at: April 8, 2026, 9:12 p.m.