Triple

T17605379
Position Surface form Disambiguated ID Type / Status
Subject Portman Square E428817 entity
Predicate near P350 FINISHED
Object Oxford Street — 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 Street | Statement: [Portman Square, near, Oxford Street]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Oxford Street
Context triple: [Portman Square, near, Oxford Street]
  • A. Oxford Street chosen
    Oxford Street is one of London’s busiest and most famous shopping streets, known for its major retail stores and central West End location.
  • B. Oxford Street
    Oxford Street is a major thoroughfare in central Manchester, England, known for its theatres, entertainment venues, and busy city-centre traffic.
  • C. New Oxford Street
    New Oxford Street is a major shopping and traffic thoroughfare in central London that forms part of the West End’s principal east–west route.
  • D. Marylebone High Street
    Marylebone High Street is a prominent central London shopping street known for its mix of upscale boutiques, independent shops, cafés, and restaurants in the Marylebone district.
  • E. Regent Street
    Regent Street is a major shopping and commercial thoroughfare in London’s West End, renowned for its elegant architecture and flagship retail stores.
  • 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_69d889e1c6148190ba76241e74688f8b completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e46c4c06a88190a0be2dec3d6056c4 completed April 19, 2026, 5:46 a.m.
Created at: April 10, 2026, 5:51 a.m.