Triple

T13861473
Position Surface form Disambiguated ID Type / Status
Subject Belle (2013 film) E333205 entity
Predicate filmingLocation P40 FINISHED
Object Oxford 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 | Statement: [Belle (2013 film), filmingLocation, Oxford]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oxford
Context triple: [Belle (2013 film), filmingLocation, Oxford]
  • A. Oxford chosen
    Oxford is a historic English city renowned for its prestigious university, distinctive architecture, and long-standing academic and cultural influence.
  • B. 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.
  • C. Oxford
    Oxford is a small town in New Haven County, Connecticut, known for its suburban-rural character and growing residential communities.
  • D. Oxford
    Oxford is a small borough in southeastern Pennsylvania known for its historic downtown and proximity to several colleges and rural communities.
  • E. Oxford
    Oxford is a small rural town in New Zealand’s Canterbury region, known for its farming community and proximity to the Southern Alps.
  • 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_69d81c5ced9c8190b0e9bcc6effe5959 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de05c20db88190acb842748aa01039 completed April 14, 2026, 9:15 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7c70c41f081908b6af3f419d8468d completed May 3, 2026, 10:07 p.m.
Created at: April 9, 2026, 10:14 p.m.