Triple

T13676369
Position Surface form Disambiguated ID Type / Status
Subject Mini Coupé E327888 entity
Predicate assemblyLocation P40 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: [Mini Coupé, assemblyLocation, Oxford, England]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oxford, England
Context triple: [Mini Coupé, assemblyLocation, 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 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_69d8076f1fa8819094664a59b55010df completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbc65c04988190b675e6fb7241e53c completed April 12, 2026, 4:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7a838581c819092a195f60673b743 completed May 3, 2026, 7:55 p.m.
Created at: April 9, 2026, 9:53 p.m.