Triple

T18535104
Position Surface form Disambiguated ID Type / Status
Subject Tooley Street E452943 entity
Predicate hasBuilding P105 FINISHED
Object More London 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: More London | Statement: [Tooley Street, hasBuilding, More London]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: More London
Context triple: [Tooley Street, hasBuilding, More London]
  • A. More London chosen
    More London is a modern riverside business and leisure development on the south bank of the River Thames in central London, known for its offices, public spaces, and views of Tower Bridge.
  • B. London Particular
    London Particular is a classic British crime novel by Christianna Brand, featuring her recurring detective Inspector Cockrill in a fog-shrouded murder mystery.
  • C. Londiani
    Londiani is a town in Kenya’s Rift Valley region, known as a local commercial and transport hub within Kericho County.
  • D. Metropolis (London)
    Metropolis (London) is the historic core area of Greater London that served as the primary urban and administrative center of the city during the 19th century.
  • E. "London"
    London is the capital and largest city of the United Kingdom, renowned as a global center for finance, culture, and history.
  • 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_69d8d387b5548190aa030dad2cb4947e completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e5340193588190ace2c09c6a94cf81 completed April 19, 2026, 7:58 p.m.
Created at: April 10, 2026, 11:37 a.m.