Triple

T8403190
Position Surface form Disambiguated ID Type / Status
Subject W. E. H. Berwick E198426 entity
Predicate workLocation P7 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: [W. E. H. Berwick, workLocation, Bangor]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bangor
Context triple: [W. E. H. Berwick, workLocation, Bangor]
  • A. Bangor
    Bangor is a coastal town in Northern Ireland known for its marina, seaside resort heritage, and role as a commuter hub for nearby Belfast.
  • B. Bangor chosen
    Bangor is a historic cathedral city in northwest Wales, known for its university and scenic location near the Menai Strait.
  • C. 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.
  • D. 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.
  • E. Prestatyn
    Prestatyn is a seaside town in Denbighshire, North Wales, known for its sandy beaches, coastal tourism, and position near the Irish Sea.
  • 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_69ca8310df9c8190b25f16161cca3e41 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cb82505e0c81909549db59b7c4eb00 completed March 31, 2026, 8:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69ce1d2a17e481908c7eab4624903251 completed April 2, 2026, 7:39 a.m.
Created at: March 30, 2026, 6:04 p.m.