Triple

T3891151
Position Surface form Disambiguated ID Type / Status
Subject Chapter of Canterbury Cathedral E88063 entity
Predicate hasSeatIn P3522 FINISHED
Object Canterbury E72201 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: Canterbury | Statement: [Chapter of Canterbury Cathedral, hasSeatIn, Canterbury]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Canterbury
Context triple: [Chapter of Canterbury Cathedral, hasSeatIn, Canterbury]
  • A. Canterbury chosen
    Canterbury is a historic cathedral city in Kent, England, renowned for its medieval architecture and status as a major center of Christian pilgrimage.
  • B. Canterbury
    Canterbury is a large region on New Zealand’s South Island, centered on the city of Christchurch and known for its expansive plains, alpine scenery, and diverse communities.
  • C. Bristol
    Bristol is a city in central Connecticut known for being the home of ESPN and for its historic clock-making industry.
  • D. Bristol
    Bristol is a city in central Connecticut known historically for its clock-making industry and as the longtime home of ESPN’s headquarters.
  • E. Bristol
    Bristol is a small town located in Dane County in the U.S. state of Wisconsin.
  • 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_69aed9466d548190939f5217a23ed4ac completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeecb0ba448190aa076865b7762002 completed March 9, 2026, 3:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69b51c91d41c8190868ce530d58b5516 completed March 14, 2026, 8:30 a.m.
Created at: March 9, 2026, 3:21 p.m.