Triple

T32495252
Position Surface form Disambiguated ID Type / Status
Subject Kinugawa limited express E830502 entity
Predicate rollingStock P1305 FINISHED
Object JR East 253 series EMU
The JR East 253 series EMU is a Japanese electric multiple unit train type originally introduced for Narita Express services and later used on various limited express routes.
E2014910 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: JR East 253 series EMU | Statement: [Kinugawa limited express, rollingStock, JR East 253 series EMU]
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: JR East 253 series EMU
Triple: [Kinugawa limited express, rollingStock, JR East 253 series EMU]
Generated description
The JR East 253 series EMU is a Japanese electric multiple unit train type originally introduced for Narita Express services and later used on various limited express routes.

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_69f34920aa4081908d8fb0277414b911 completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6c40e16d0819084ab23950b416eb6 completed May 3, 2026, 3:42 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3485f977388190bf3ab3ec66f9dc40 completed June 18, 2026, 11:57 p.m.
NEDg Description generation batch_6a3487b674c481908bc278d93694863c completed June 19, 2026, 12:05 a.m.
NED2 Entity disambiguation (via description) batch_6a348a5e05108190aa1a78461750b83a completed June 19, 2026, 12:16 a.m.
Created at: May 1, 2026, 12:59 a.m.