Triple

T623200
Position Surface form Disambiguated ID Type / Status
Subject City of Westminster E14557 entity
Predicate contains P35 FINISHED
Object Marylebone E40485 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: Marylebone | Statement: [City of Westminster, contains, Marylebone]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Marylebone
Context triple: [City of Westminster, contains, Marylebone]
  • A. Marylebone chosen
    Marylebone is a central London district in the City of Westminster, known for its elegant Georgian architecture, upscale shopping streets, and cultural landmarks.
  • B. Hampstead
    Hampstead is a historic and affluent district in north London, England, known for its literary and artistic associations and the expansive Hampstead Heath.
  • C. Knightsbridge
    Knightsbridge is an affluent central London district renowned for its luxury shopping, upscale residences, and proximity to Hyde Park.
  • D. Kensington
    Kensington is a district in West London, England, known for its affluent residential areas, cultural institutions, and royal associations.
  • E. Hyde Park Corner
    Hyde Park Corner is a major road junction and public space in central London, situated near Hyde Park and known for its memorials and heavy traffic.
  • 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_69a4934b17c881909ace8270e8ddd202 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a49e41753881909f0faed720cc31bc completed March 1, 2026, 8:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69a56c4b64088190a033462dd923f5b2 completed March 2, 2026, 10:54 a.m.
Created at: March 1, 2026, 7:35 p.m.