Triple

T4427702
Position Surface form Disambiguated ID Type / Status
Subject Charles Coulson E95247 entity
Predicate workLocation P7 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: [Charles Coulson, workLocation, Oxford, England]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oxford, England
Context triple: [Charles Coulson, workLocation, 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 town in New Haven County, Connecticut, known for its suburban-rural character and growing residential communities.
  • E. 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.
  • 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_69b3453c2a0c8190926b574c90766db9 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b355674d5481908bf2dfd611f3520f completed March 13, 2026, 12:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69b6136ac9c081908780783a27f66474 completed March 15, 2026, 2:03 a.m.
Created at: March 12, 2026, 11:30 p.m.