Triple

T34158918
Position Surface form Disambiguated ID Type / Status
Subject House of Councillors constituencies of Japan E876219 entity
Predicate includes P1393 FINISHED
Object Kanagawa at-large constituency
Kanagawa at-large constituency is a multi-member electoral district in Japan that represents Kanagawa Prefecture in the national House of Councillors.
E2086924 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: Kanagawa at-large constituency | Statement: [House of Councillors constituencies of Japan, includes, Kanagawa at-large constituency]
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: Kanagawa at-large constituency
Triple: [House of Councillors constituencies of Japan, includes, Kanagawa at-large constituency]
Generated description
Kanagawa at-large constituency is a multi-member electoral district in Japan that represents Kanagawa Prefecture in the national House of Councillors.

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_69f349ac987481908a8e6053f665bc8b completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f70fb84a80819081183b5e56ab9a4f completed May 3, 2026, 9:04 a.m.
NED1 Entity disambiguation (via context triple) batch_6a36d5d468008190b568653cd5051703 completed June 20, 2026, 6:03 p.m.
NEDg Description generation batch_6a36d684ddb481909f1f147c4d0dfcd7 completed June 20, 2026, 6:05 p.m.
NED2 Entity disambiguation (via description) batch_6a36d7085f048190a542289f6535e8da completed June 20, 2026, 6:08 p.m.
Created at: May 1, 2026, 1:54 a.m.