Triple

T33372003
Position Surface form Disambiguated ID Type / Status
Subject 第1次安倍内閣 E854515 entity
Predicate 内閣府特命担当大臣 P134220 FINISHED
Object 山本有二
山本有二は、自民党所属の日本の政治家で、衆議院議員として金融・農政分野などで要職を歴任してきた人物である。
E2046996 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: 山本有二 | Statement: [第1次安倍内閣, 内閣府特命担当大臣, 山本有二]
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: 山本有二
Triple: [第1次安倍内閣, 内閣府特命担当大臣, 山本有二]
Generated description
山本有二は、自民党所属の日本の政治家で、衆議院議員として金融・農政分野などで要職を歴任してきた人物である。

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_69f3496ca10c8190908640d18fa00832 completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6e3dcad948190b0ab0de6f9d18a3e completed May 3, 2026, 5:57 a.m.
NED1 Entity disambiguation (via context triple) batch_6a35521d10fc8190bc7a6f5801a3c7d6 completed June 19, 2026, 2:28 p.m.
NEDg Description generation batch_6a3553e4829c8190bbb62bb63b8d488f completed June 19, 2026, 2:36 p.m.
NED2 Entity disambiguation (via description) batch_6a3554a6e0ec819099dac83f8f062643 completed June 19, 2026, 2:39 p.m.
Created at: May 1, 2026, 1:35 a.m.