Triple

T17620660
Position Surface form Disambiguated ID Type / Status
Subject New Technology Train E429699 entity
Predicate hasPart P35 FINISHED
Object R262
R262 is a model of New Technology Train subway car used in the New York City Transit system.
 E1279452 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: R262 | Statement: [New Technology Train, hasPart, R262]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: R262
Context triple: [New Technology Train, hasPart, R262]
  • A. R24
    R24 is a regional commuter rail line in Catalonia, Spain, operating within the Rodalies de Catalunya network to connect towns and cities in the area.
  • B. R27
    R27 is the internal station code used by the New York City Subway for the Broad Street station on the BMT Nassau Street Line.
  • C. R27
    R27 is a regional commuter rail line in Catalonia that forms part of the Rodalies de Catalunya network.
  • D. R62
    The R62 is a class of New York City Subway rolling stock built in the 1980s for use on A Division (numbered) lines.
  • E. R28
    R28 is a regional commuter rail line within the Rodalies de Catalunya network serving passengers in Catalonia, Spain.
  • 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: R262
Triple: [New Technology Train, hasPart, R262]
Generated description
R262 is a model of New Technology Train subway car used in the New York City Transit system.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: R262
Target entity description: R262 is a model of New Technology Train subway car used in the New York City Transit system.
  • A. R24
    R24 is a regional commuter rail line in Catalonia, Spain, operating within the Rodalies de Catalunya network to connect towns and cities in the area.
  • B. R27
    R27 is the internal station code used by the New York City Subway for the Broad Street station on the BMT Nassau Street Line.
  • C. R27
    R27 is a regional commuter rail line in Catalonia that forms part of the Rodalies de Catalunya network.
  • D. R62
    The R62 is a class of New York City Subway rolling stock built in the 1980s for use on A Division (numbered) lines.
  • E. R28
    R28 is a regional commuter rail line within the Rodalies de Catalunya network serving passengers in Catalonia, Spain.
  • F. None of above. chosen

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_69d889e37f308190a6aa0a69daff86c7 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e46d36074481909ee79e238841edf2 completed April 19, 2026, 5:50 a.m.
NED1 Entity disambiguation (via context triple) batch_6a020a9553f08190a4cd8fea76f016df completed May 11, 2026, 4:57 p.m.
NEDg Description generation batch_6a020bec249c81909148778f348fb1b4 completed May 11, 2026, 5:03 p.m.
NED2 Entity disambiguation (via description) batch_6a020ce0cc0081909e9e90b9067e3f01 completed May 11, 2026, 5:07 p.m.
Created at: April 10, 2026, 5:51 a.m.