Triple

T9838688
Position Surface form Disambiguated ID Type / Status
Subject Marta Kwiatkowska E239165 entity
Predicate workLocation P7 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: [Marta Kwiatkowska, workLocation, Oxford]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oxford
Context triple: [Marta Kwiatkowska, workLocation, 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_69ca84e314108190978324a4bdb959f8 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb34921b881909836ba0f5b42a27b completed April 2, 2026, 12:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69d1d5c066a08190baabf3141c10d9f3 completed April 5, 2026, 3:23 a.m.
Created at: March 30, 2026, 8:33 p.m.