Triple

T3701737
Position Surface form Disambiguated ID Type / Status
Subject Nordland E80792 entity
Predicate hasRegion P285 FINISHED
Object Ofoten E322908 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: Ofoten | Statement: [Nordland, hasRegion, Ofoten]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ofoten
Context triple: [Nordland, hasRegion, Ofoten]
  • A. Ofoten chosen
    Ofoten is a district in Nordland county in northern Norway, known for its fjords, mountains, and the port town of Narvik.
  • B. Notodden
    Notodden is a town and municipality in Vestfold og Telemark county, Norway, known for its industrial heritage and annual blues festival.
  • C. Svolvær
    Svolvær is a coastal town in northern Norway that serves as a key fishing, tourism, and transport hub in the Lofoten archipelago.
  • D. Kristinestad
    Kristinestad is a small coastal town in western Finland known for its well-preserved wooden old town and historic maritime character.
  • E. Leknes
    Leknes is a small coastal town in Norway’s Lofoten archipelago, known for its dramatic mountain-and-sea landscapes and role as a regional commercial center.
  • 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_69ad8b1793888190a5f70e4b21dc05a1 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69adc547c1848190a1ece46c59b7c43d completed March 8, 2026, 6:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69b51c688e0c8190a7e9ea3fe010c361 completed March 14, 2026, 8:29 a.m.
Created at: March 8, 2026, 3:33 p.m.