Triple

T2599513
Position Surface form Disambiguated ID Type / Status
Subject Gwynedd E58308 entity
Predicate hasLargestTown P847 FINISHED
Object Bangor E266539 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: Bangor | Statement: [Gwynedd, hasLargestTown, Bangor]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bangor
Context triple: [Gwynedd, hasLargestTown, Bangor]
  • A. Bangor chosen
    Bangor is a historic cathedral city in northwest Wales, known for its university and scenic location near the Menai Strait.
  • B. Bangor metropolitan area
    The Bangor metropolitan area is a regional urban and economic hub in central-eastern Maine centered on the city of Bangor and its surrounding communities.
  • C. Bangor, Maine
    Bangor, Maine is a small city in eastern Maine known as a regional commercial and cultural hub and famously associated with author Stephen King.
  • D. Prestatyn
    Prestatyn is a seaside town in Denbighshire, North Wales, known for its sandy beaches, coastal tourism, and position near the Irish Sea.
  • E. Colchester
    Colchester is a historic town in Essex, England, often cited as Britain’s oldest recorded town and known for its Roman heritage and medieval landmarks.
  • 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_69ab4ac14040819098b13f4a27d5c8ff completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abd457564c819080d8c8818c02545a completed March 7, 2026, 7:31 a.m.
NED1 Entity disambiguation (via context triple) batch_69af83cfdd6081908cdeb21243e73dda completed March 10, 2026, 2:37 a.m.
Created at: March 6, 2026, 9:49 p.m.