Triple

T22265280
Position Surface form Disambiguated ID Type / Status
Subject Austro-Hungarian North Pole expedition E550334 entity
Predicate departurePort P1521 FINISHED
Object Tromsø NE NERFINISHED

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: Tromsø | Statement: [Austro-Hungarian North Pole expedition, departurePort, Tromsø]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tromsø
Context triple: [Austro-Hungarian North Pole expedition, departurePort, Tromsø]
  • A. Tromsø chosen
    Tromsø is a city in northern Norway known for its Arctic location, vibrant cultural scene, and prominence as a viewing spot for the Northern Lights.
  • B. Bodø
    Bodø is a coastal city in northern Norway known as a regional hub for culture, transport, and access to Arctic nature.
  • C. Hanøy
    Hanøy is a small Norwegian island that forms part of Askøy Municipality in Vestland county.
  • D. Alsvåg
    Alsvåg is a small coastal village in Nordland county, Norway, known for its fishing industry and scenic location within the municipality of Øksnes.
  • E. Trondheim
    Trondheim is a historic Norwegian city in Trøndelag county, known for its medieval Nidaros Cathedral and role as a former capital of Norway.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e11e43d8208190aff4f9cf7f2c2a8a completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f141bb850881908f5e9c37afb52ca8 completed April 28, 2026, 11:24 p.m.
Created at: April 16, 2026, 8:39 p.m.