Triple

T15345163
Position Surface form Disambiguated ID Type / Status
Subject European route E39 E366897 entity
Predicate passesThrough P225 FINISHED
Object Kristiansund E76076 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: Kristiansund | Statement: [European route E39, passesThrough, Kristiansund]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kristiansund
Context triple: [European route E39, passesThrough, Kristiansund]
  • A. Kristiansund chosen
    Kristiansund is a coastal city in western Norway known for its historic clipfish industry, distinctive layout across several islands, and picturesque harbor.
  • B. Kristiansand
    Kristiansand is a coastal city in southern Norway known for its harbor, beaches, and role as a regional cultural and economic center.
  • C. Egersund
    Egersund is a coastal town in southwestern Norway known for its fishing industry, historic wooden architecture, and scenic harbor.
  • D. Florø
    Florø is a coastal town in western Norway known as the country’s westernmost town and a traditional center for fishing and maritime industries.
  • E. Ålesund
    Ålesund is a coastal Norwegian city renowned for its distinctive Art Nouveau architecture and location across several islands in Western Norway.
  • 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_69d85a1355608190a6673ddb67231d54 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03e163a3c8190ab933411372c1573 completed April 16, 2026, 1:40 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0007757ed48190813f6ab839240a15 completed May 10, 2026, 4:20 a.m.
Created at: April 10, 2026, 3:17 a.m.