Triple

T3984449
Position Surface form Disambiguated ID Type / Status
Subject BMT Broadway Line E86837 entity
Predicate formerServices P43939 FINISHED
Object M E187451 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: M | Statement: [BMT Broadway Line, formerServices, M]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: M
Context triple: [BMT Broadway Line, formerServices, M]
  • A. M
    M is a functional data mashup and query language used in Microsoft Power BI and related tools for data transformation and preparation.
  • B. M
    M is the codename for James Bond’s stern and authoritative superior who heads the British Secret Service in the 007 franchise.
  • C. M
    "M" is a 1951 American crime thriller film directed by Joseph Losey, adapted from Fritz Lang’s 1931 classic, in which David Wayne portrays a hunted child murderer.
  • D. M chosen
    M is a New York City Subway service that runs along the IND Sixth Avenue Line in Manhattan and connects Brooklyn and Queens.
  • E. M
    M is the New York Stock Exchange ticker symbol for Macy's, Inc., a major American department store chain.
  • 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_69aed93fd9d4819085d3b2137d2346cb completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af0197a0a0819085d746f51c7fc51b completed March 9, 2026, 5:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69b540284d548190821d37b68974a2d2 completed March 14, 2026, 11:02 a.m.
Created at: March 9, 2026, 3:33 p.m.