Triple

T3822606
Position Surface form Disambiguated ID Type / Status
Subject Lincoln's Inn Fields E88608 entity
Predicate near P350 FINISHED
Object Chancery Lane E306904 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: Chancery Lane | Statement: [Lincoln's Inn Fields, near, Chancery Lane]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chancery Lane
Context triple: [Lincoln's Inn Fields, near, Chancery Lane]
  • A. Chancery Lane chosen
    Chancery Lane is a historic street in central London traditionally associated with the legal profession and home to many legal institutions and chambers.
  • B. Farringdon Street
    Farringdon Street was the original London terminus of the Metropolitan Railway, playing a key role in the early development of the city's underground rail network.
  • C. Caxton Street
    Caxton Street is a street in Westminster, central London, known for housing the historic Caxton Hall building.
  • D. Old Street
    Old Street is a major road and surrounding area in central London, known as a key hub for technology companies and startups within the city's "Silicon Roundabout" district.
  • E. Tottenham Court Road
    Tottenham Court Road is a major shopping and entertainment street in central London, known for its electronics stores, proximity to the West End, and busy Underground station.
  • 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_69aed9538cf881909d9ce8ca4ac7c18c completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeea63fe2c8190825f6e9451f6aa50 completed March 9, 2026, 3:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69bd7f58290881908c7622616a829c75 completed March 20, 2026, 5:09 p.m.
Created at: March 9, 2026, 3:17 p.m.