Triple

T15647828
Position Surface form Disambiguated ID Type / Status
Subject Volda E376225 entity
Predicate hasNeighbouringMunicipality P224 FINISHED
Object Ulstein E494783 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: Ulstein | Statement: [Volda, hasNeighbouringMunicipality, Ulstein]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ulstein
Context triple: [Volda, hasNeighbouringMunicipality, Ulstein]
  • A. Ulstein chosen
    Ulstein is a coastal municipality in western Norway known for its maritime industry and shipbuilding.
  • B. MS Vesterålen
    MS Vesterålen is a Norwegian coastal passenger and cargo ship operated on the Hurtigruten coastal route, known for its intimate size and classic working-ship character.
  • C. SS Gotenland
    SS Gotenland was a German transport ship used by the Nazis during World War II to deport Jews and other prisoners to concentration and extermination camps.
  • D. Gjøa
    Gjøa is the historic Norwegian polar exploration ship used by Roald Amundsen to complete the first successful navigation of the Northwest Passage.
  • E. Aero O/Y
    Aero O/Y was the original Finnish airline that later evolved into the national carrier Finnair.
  • 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_69d85cd1564c8190991adda63bfab4b0 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04ed7212c8190be6ff76afa25f7ca completed April 16, 2026, 2:52 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff67936e388190913c9060194e5b53 completed May 9, 2026, 4:57 p.m.
Created at: April 10, 2026, 4:15 a.m.