Triple

T4587929
Position Surface form Disambiguated ID Type / Status
Subject Innherred E103413 entity
Predicate borders P224 FINISHED
Object inner Trondheimsfjord E128059 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: inner Trondheimsfjord | Statement: [Innherred, borders, inner Trondheimsfjord]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: inner Trondheimsfjord
Context triple: [Innherred, borders, inner Trondheimsfjord]
  • A. Trondheimsfjord chosen
    Trondheimsfjord is a major Norwegian fjord on the central coast, known for its deep waters, rich marine life, and the city of Trondheim along its shores.
  • B. Oslofjord
    Oslofjord is a large inlet in southeastern Norway known for its islands, coastal towns, and role as the maritime gateway to Oslo.
  • C. Ofotfjord
    Ofotfjord is a dramatic fjord in northern Norway near Narvik, known for its strategic importance and as a key site of naval operations during World War II.
  • D. Romsdalsfjorden
    Romsdalsfjorden is a scenic fjord in Møre og Romsdal county, Norway, known for its dramatic landscapes, coastal towns, and role as a key waterway in the Romsdal region.
  • E. Hardangerfjord
    Hardangerfjord is one of Norway’s longest and most scenic fjords, renowned for its dramatic mountains, waterfalls, and fruit orchards.
  • 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_69bd43dccaf08190aa89e9991a289719 completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd591fc20481908d8d4b71d055ae8c completed March 20, 2026, 2:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69bde0b1b014819085543bd297f925c1 completed March 21, 2026, 12:05 a.m.
Created at: March 20, 2026, 1:11 p.m.