Triple

T17620691
Position Surface form Disambiguated ID Type / Status
Subject New Technology Train E429699 entity
Predicate successorTo P78 FINISHED
Object R40
The R40 was a class of New York City Subway cars built in the late 1960s, notable for their futuristic slanted-end design and service on B Division lines.
 E1279454 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: R40 | Statement: [New Technology Train, successorTo, R40]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: R40
Context triple: [New Technology Train, successorTo, R40]
  • A. R40
    R40 is a regional commuter rail line in Catalonia, Spain, operating as part of the Rodalies de Catalunya network.
  • B. R45
    R45 is the internal station code used by the New York City Subway to identify the Bay Ridge–95th Street station on the R line in Brooklyn.
  • C. R-4
    The R-4 is a World War II–era Sikorsky helicopter recognized as the first mass-produced helicopter and the first to be used operationally by the U.S. military.
  • D. R4
    R4 is a government office building in Oslo that forms part of Norway’s central Regjeringskvartalet complex.
  • E. R4
    R4 is a commuter rail line in the Rodalies de Catalunya network serving key suburban and regional routes 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: R40
Triple: [New Technology Train, successorTo, R40]
Generated description
The R40 was a class of New York City Subway cars built in the late 1960s, notable for their futuristic slanted-end design and service on B Division lines.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: R40
Target entity description: The R40 was a class of New York City Subway cars built in the late 1960s, notable for their futuristic slanted-end design and service on B Division lines.
  • A. R40
    R40 is a regional commuter rail line in Catalonia, Spain, operating as part of the Rodalies de Catalunya network.
  • B. R45
    R45 is the internal station code used by the New York City Subway to identify the Bay Ridge–95th Street station on the R line in Brooklyn.
  • C. R-4
    The R-4 is a World War II–era Sikorsky helicopter recognized as the first mass-produced helicopter and the first to be used operationally by the U.S. military.
  • D. R4
    R4 is a government office building in Oslo that forms part of Norway’s central Regjeringskvartalet complex.
  • E. R4
    R4 is a commuter rail line in the Rodalies de Catalunya network serving key suburban and regional routes 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.