Triple

T30245738
Position Surface form Disambiguated ID Type / Status
Subject Tokyo Metro 16000 series E769046 entity
Predicate designedToReplace P101 FINISHED
Object Tokyo Metro 6000 series
The Tokyo Metro 6000 series is an older generation of electric multiple unit trains that formerly operated on Tokyo’s subway network, particularly the Chiyoda Line.
E1911871 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: Tokyo Metro 6000 series | Statement: [Tokyo Metro 16000 series, designedToReplace, Tokyo Metro 6000 series]
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: Tokyo Metro 6000 series
Triple: [Tokyo Metro 16000 series, designedToReplace, Tokyo Metro 6000 series]
Generated description
The Tokyo Metro 6000 series is an older generation of electric multiple unit trains that formerly operated on Tokyo’s subway network, particularly the Chiyoda Line.

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_69f224831dc08190b2e569b987264057 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f68075a5f881908cd5d5eaddfb2b91 completed May 2, 2026, 10:53 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2789277b4081909483f31a40503794 completed June 9, 2026, 3:31 a.m.
NEDg Description generation batch_6a27899e1e608190ab47ff85d1a25738 completed June 9, 2026, 3:33 a.m.
NED2 Entity disambiguation (via description) batch_6a2789f2f6f0819099891123a61feb50 completed June 9, 2026, 3:35 a.m.
Created at: April 29, 2026, 7:39 p.m.