Triple

T2866124
Position Surface form Disambiguated ID Type / Status
Subject Cavendish Hotel E63441 entity
Predicate nearby P350 FINISHED
Object Oxford Street E78234 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 Street | Statement: [Cavendish Hotel, nearby, Oxford Street]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Oxford Street
Context triple: [Cavendish Hotel, nearby, 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 (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_69ab4c42fb8c8190b36e161d47c03b81 completed March 6, 2026, 9:50 p.m.
NER Named-entity recognition batch_69abdfbb7ed4819096ca65391077e2af completed March 7, 2026, 8:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69b4c358374c819089e8c16d4115c409 completed March 14, 2026, 2:09 a.m.
Created at: March 6, 2026, 10:02 p.m.