Triple

T34158917
Position Surface form Disambiguated ID Type / Status
Subject House of Councillors constituencies of Japan E876219 entity
Predicate includes P1393 FINISHED
Object Hyogo at-large constituency
Hyogo at-large constituency is an electoral district in Japan that represents Hyogo Prefecture in the national House of Councillors.
E2085022 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: Hyogo at-large constituency | Statement: [House of Councillors constituencies of Japan, includes, Hyogo 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: Hyogo at-large constituency
Triple: [House of Councillors constituencies of Japan, includes, Hyogo at-large constituency]
Generated description
Hyogo at-large constituency is an electoral district in Japan that represents Hyogo 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_6a36c1d188a08190acf117c920fdf470 completed June 20, 2026, 4:37 p.m.
NEDg Description generation batch_6a36c63dd5e48190b456b5a95e6f7a93 completed June 20, 2026, 4:56 p.m.
NED2 Entity disambiguation (via description) batch_6a36c799cbc881908eb4e74997355460 completed June 20, 2026, 5:02 p.m.
Created at: May 1, 2026, 1:54 a.m.