Triple

T30786213
Position Surface form Disambiguated ID Type / Status
Subject 若尾文子 E783960 entity
Predicate 監督と協働 P38701 FINISHED
Object 増村保造
増村保造は、大映を代表する日本の映画監督で、鋭い人間描写とスタイリッシュな演出で知られ、特に女優・若尾文子を起用した作品群で高く評価されている人物である。
E1930368 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: 増村保造 | Statement: [若尾文子, 監督と協働, 増村保造]
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: 増村保造
Triple: [若尾文子, 監督と協働, 増村保造]
Generated description
増村保造は、大映を代表する日本の映画監督で、鋭い人間描写とスタイリッシュな演出で知られ、特に女優・若尾文子を起用した作品群で高く評価されている人物である。

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_69f224b213c8819083886073f90b647e completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f690097c9c81909858e7d8c15474da completed May 3, 2026, midnight
NED1 Entity disambiguation (via context triple) batch_6a28b0a7a9988190892052e9d99f13a9 completed June 10, 2026, 12:32 a.m.
NEDg Description generation batch_6a28b1ecd9448190a88b0f465f97a8ba completed June 10, 2026, 12:38 a.m.
NED2 Entity disambiguation (via description) batch_6a28b28f98288190af9d9c0ea08b4254 completed June 10, 2026, 12:40 a.m.
Created at: April 29, 2026, 8:41 p.m.