Triple

T220754
Position Surface form Disambiguated ID Type / Status
Subject Thomas Cranmer E4207 entity
Predicate deathPlace P21 FINISHED
Object Oxford, England E19137 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: Oxford, England | Statement: [Thomas Cranmer, deathPlace, Oxford, England]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oxford, England
Context triple: [Thomas Cranmer, deathPlace, Oxford, England]
  • A. Cambridge, England
    Cambridge, England is a historic university city on the River Cam renowned for the University of Cambridge and its longstanding contributions to education, science, and culture.
  • B. Oxford chosen
    Oxford is a historic English city renowned for its prestigious university, distinctive architecture, and long-standing academic and cultural influence.
  • C. Lexington, England
    Lexington, England is a historic English locality whose name was later adopted by the American town of Lexington, Massachusetts.
  • D. Middlesex, England
    Middlesex, England is a historic county in southeast England that once encompassed much of what is now Greater London.
  • E. London, England
    London, England is the capital and largest city of the United Kingdom, renowned as a global center for finance, culture, and politics.
  • 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_69a2573508588190b522c2476d91acfe completed Feb. 28, 2026, 2:47 a.m.
NER Named-entity recognition batch_69a25c6e6fbc8190a8744e193df513e8 completed Feb. 28, 2026, 3:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69a38b8ac09c81908181fb0f15482e66 completed March 1, 2026, 12:42 a.m.
Created at: Feb. 28, 2026, 2:53 a.m.