Triple

T24147822
Position Surface form Disambiguated ID Type / Status
Subject Tōkyū Ikegami Line E598434 entity
Predicate usesRollingStock P5426 FINISHED
Object Tokyu 1000 series EMU
The Tokyu 1000 series EMU is a Japanese electric multiple unit train type operated by Tokyu Corporation, known for serving busy commuter lines in the Tokyo area with modernized, efficient suburban rail services.
E1625315 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: Tokyu 1000 series EMU | Statement: [Tōkyū Ikegami Line, usesRollingStock, Tokyu 1000 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: Tokyu 1000 series EMU
Triple: [Tōkyū Ikegami Line, usesRollingStock, Tokyu 1000 series EMU]
Generated description
The Tokyu 1000 series EMU is a Japanese electric multiple unit train type operated by Tokyu Corporation, known for serving busy commuter lines in the Tokyo area with modernized, efficient suburban rail services.

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_69e288c9e488819093dd1acd91b08b8a completed April 17, 2026, 7:23 p.m.
NER Named-entity recognition batch_69f1e00c42288190843962f9476a94a1 completed April 29, 2026, 10:40 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0fbd061520819091366de6290e7b26 completed May 22, 2026, 2:18 a.m.
NEDg Description generation batch_6a0fc0ac654c81908e3b8af4d47b0245 completed May 22, 2026, 2:34 a.m.
NED2 Entity disambiguation (via description) batch_6a0fc18011c48190bad1e30c2ef39b34 completed May 22, 2026, 2:37 a.m.
Created at: April 17, 2026, 11:30 p.m.