Triple

T28249829
Position Surface form Disambiguated ID Type / Status
Subject R142 subway car class E712281 entity
Predicate designedToReplace P101 FINISHED
Object R36 subway cars
The R36 subway cars were a class of New York City Subway rolling stock built in the early 1960s, best known for serving the IRT lines for several decades and for their distinctive "Redbird" paint scheme in later years.
 E1819427 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: R36 subway cars | Statement: [R142 subway car class, designedToReplace, R36 subway cars]
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: R36 subway cars
Triple: [R142 subway car class, designedToReplace, R36 subway cars]
Generated description
The R36 subway cars were a class of New York City Subway rolling stock built in the early 1960s, best known for serving the IRT lines for several decades and for their distinctive "Redbird" paint scheme in later years.

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_69efb51fb98881909692421959ec0170 completed April 27, 2026, 7:12 p.m.
NER Named-entity recognition batch_69f643eecbe481908f4c9be0fa878f36 completed May 2, 2026, 6:35 p.m.
NED1 Entity disambiguation (via context triple) batch_6a164169c720819084b5b963b0f3b81c completed May 27, 2026, 12:57 a.m.
NEDg Description generation batch_6a1642a04a9c81908f196894b8f4bdf5 completed May 27, 2026, 1:02 a.m.
NED2 Entity disambiguation (via description) batch_6a164322f1148190b37794a5fc54f184 completed May 27, 2026, 1:04 a.m.
Created at: April 27, 2026, 11:04 p.m.