Triple

T8135980
Position Surface form Disambiguated ID Type / Status
Subject West End of London E189969 entity
Predicate hasNickname P39 FINISHED
Object Theatreland E376835 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: Theatreland | Statement: [West End of London, hasNickname, Theatreland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Theatreland
Context triple: [West End of London, hasNickname, Theatreland]
  • A. Theatreland chosen
    Theatreland is the famous concentration of major commercial theatres in London’s West End, known for its long-running plays and musicals.
  • B. Westend
    Westend is a prominent and affluent district in Frankfurt am Main, Germany, known for its elegant residential areas and concentration of banks and corporate offices.
  • C. Broadway
    Broadway is a major thoroughfare in New York City famous for its historic theaters and role as the heart of American commercial theater.
  • D. Broadway
    Broadway is a major thoroughfare in Cambridge, Massachusetts, running through the city center and connecting key academic, residential, and commercial areas.
  • E. Broadway
    Broadway is a major east–west thoroughfare in Vancouver, British Columbia, known as one of the city’s primary commercial and transit corridors.
  • 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_69ca82bcb4848190a9a9d036ad768642 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb43fff6e0819086c95b571272b50c completed March 31, 2026, 3:48 a.m.
NED1 Entity disambiguation (via context triple) batch_69ccbed2abb881908107fdc5a8092aab completed April 1, 2026, 6:44 a.m.
Created at: March 30, 2026, 5:35 p.m.