Triple

T3701503
Position Surface form Disambiguated ID Type / Status
Subject Harstad E78588 entity
Predicate partOf P40 FINISHED
Object Ofoten region E180868 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 region | Statement: [Harstad, partOf, Ofoten region]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ofoten region
Context triple: [Harstad, partOf, Ofoten region]
  • A. Ofoten district chosen
    Ofoten district is a traditional region in Nordland county in northern Norway, known for its fjords, mountains, and the town of Narvik as its main urban center.
  • B. Oslofjord region
    The Oslofjord region is a coastal area in southeastern Norway centered around the Oslofjord, known for its ports, maritime activities, and proximity to the capital city, Oslo.
  • C. Lillehammer region
    The Lillehammer region is an area in southeastern Norway known for its winter sports facilities, scenic landscapes, and role as host of the 1994 Winter Olympics.
  • D. Setesdal region
    The Setesdal region is a traditional valley area in southern Norway known for its distinctive folk culture, music, and well-preserved rural landscapes.
  • E. Romsdal
    Romsdal is a traditional district in Møre og Romsdal county in western Norway, known for its dramatic fjords, mountains, and the town of Molde.
  • 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_69ad85e3b1888190abc983e06968696d completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc547c1848190a1ece46c59b7c43d completed March 8, 2026, 6:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4cdf1b16081909b18af630d0b4817 completed March 14, 2026, 2:54 a.m.
Created at: March 8, 2026, 3:26 p.m.