Triple

T18367594
Position Surface form Disambiguated ID Type / Status
Subject Enstone Aerodrome E440088 entity
Predicate hasNearbyCity P350 FINISHED
Object Oxford NE NERFINISHED

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: [Enstone Aerodrome, hasNearbyCity, Oxford]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oxford
Context triple: [Enstone Aerodrome, hasNearbyCity, 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 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 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 (2 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_69d8b918221c8190a9f7b563d64ac677 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e5174f5f448190a1fc67d3039aadd9 completed April 19, 2026, 5:56 p.m.
Created at: April 10, 2026, 10:38 a.m.