Triple

T6339169
Position Surface form Disambiguated ID Type / Status
Subject River Cherwell E142578 entity
Predicate flowsThrough P225 FINISHED
Object city of 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: city of Oxford | Statement: [River Cherwell, flowsThrough, city of Oxford]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: city of Oxford
Context triple: [River Cherwell, flowsThrough, city of 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 federal electoral district in Ontario, Canada, represented in the House of Commons.
  • C. 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.
  • D. 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.
  • E. Oxford
    Oxford is a small town in New Haven County, Connecticut, known for its suburban-rural character and growing residential 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_69c008d5ab108190b346c465696824a9 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c0654fb774819087bffb8b966a790a completed March 22, 2026, 9:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69c604352f148190b5accc28462256ad completed March 27, 2026, 4:14 a.m.
Created at: March 22, 2026, 4:30 p.m.