Triple

T16053980
Position Surface form Disambiguated ID Type / Status
Subject Sir Thomas White E389427 entity
Predicate placeOfDeath 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: [Sir Thomas White, placeOfDeath, Oxford, England]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oxford, England
Context triple: [Sir Thomas White, placeOfDeath, 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. Oxford
    Oxford is a small city in northeastern Alabama known for its location in the Anniston–Oxford metropolitan area and proximity to the Talladega National Forest.
  • D. Oxford
    Oxford is a small Mississippi city best known as the home of the University of Mississippi and for its rich literary and cultural heritage.
  • E. Oxford
    Oxford is a small borough in southeastern Pennsylvania known for its historic downtown and proximity to several colleges and rural communities.
  • 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_69d86dae698881908327ef2d67706cb9 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e183642420819088b03f613ee65851 completed April 17, 2026, 12:48 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffeb8b1b2c8190949943b20f2f8574 completed May 10, 2026, 2:20 a.m.
Created at: April 10, 2026, 4:56 a.m.