Triple

T15805802
Position Surface form Disambiguated ID Type / Status
Subject New York City Subway M line E383212 entity
Predicate nomenclature P44079 FINISHED
Object M
M is a service designation used for one of the lines in the New York City Subway system.
E187451 NE FINISHED

How this triple was built (4 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: [New York City Subway M line, nomenclature, M]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: M
Context triple: [New York City Subway M line, nomenclature, 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 New York Stock Exchange ticker symbol for Macy's, Inc., a major American department store chain.
  • C. M
    M is an experimental musical composition by avant-garde American composer John Cage, reflecting his innovative approaches to sound and structure.
  • D. M
    M is a landmark 1931 German thriller film by Fritz Lang, renowned as an early and influential work in the serial killer and crime genre.
  • E. M
    M is a light rail line in San Francisco’s Muni Metro system that runs between the Embarcadero and the southwestern neighborhoods of the city.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: M
Triple: [New York City Subway M line, nomenclature, M]
Generated description
M is a service designation used for one of the lines in the New York City Subway system.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: M
Target entity description: M is a service designation used for one of the lines in the New York City Subway system.
  • A. 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.
  • B. M
    M is a light rail line in San Francisco’s Muni Metro system that runs between the Embarcadero and the southwestern neighborhoods of the city.
  • C. M
    M is the New York Stock Exchange ticker symbol for Macy's, Inc., a major American department store chain.
  • D. M
    M is the codename for James Bond’s stern and authoritative superior who heads the British Secret Service in the 007 franchise.
  • E. M
    M is the standard notation for the Monster group, the largest sporadic simple group in group theory and a central object in the study of finite simple groups and monstrous moonshine.
  • F. None of above.

Provenance (5 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_69d86da2858c819090cc8481e7207b6e completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e0b52682548190998d8b6a08982877 completed April 16, 2026, 10:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff998d17648190b9f020632461965f completed May 9, 2026, 8:31 p.m.
NEDg Description generation batch_69ff9dcbb36881909c4317f9031199b8 completed May 9, 2026, 8:49 p.m.
NED2 Entity disambiguation (via description) batch_69ff9e25b2f08190b519d61be3e2f2f6 completed May 9, 2026, 8:50 p.m.
Created at: April 10, 2026, 4:48 a.m.