Triple

T15244682
Position Surface form Disambiguated ID Type / Status
Subject Richard With E364348 entity
Predicate placeOfBirth P1 FINISHED
Object Tromsø, Norway E56624 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: Tromsø, Norway | Statement: [Richard With, placeOfBirth, Tromsø, Norway]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tromsø, Norway
Context triple: [Richard With, placeOfBirth, Tromsø, Norway]
  • 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. Rosendal, Norway
    Rosendal, Norway is a small village in Kvinnherad municipality in Vestland county, known for its dramatic fjord landscape and the historic Barony Rosendal manor.
  • C. Bodø
    Bodø is a coastal city in northern Norway known as a regional hub for culture, transport, and access to Arctic nature.
  • D. Hamar, Norway
    Hamar, Norway is a town in southeastern Norway known for its prominent ice sports facilities and role as a major venue for international speed skating competitions.
  • E. Horten, Norway
    Horten, Norway is a coastal town and municipality in Vestfold known for its maritime heritage, naval history, and ferry link across the Oslofjord.
  • 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_69d85a0dde7481908fc64d1e82d5d20d completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e007f306f08190be448b215d6c9b6c completed April 15, 2026, 9:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69fedd461cf08190a506aac2f0cec83a completed May 9, 2026, 7:07 a.m.
Created at: April 10, 2026, 3:13 a.m.