Triple

T25369687
Position Surface form Disambiguated ID Type / Status
Subject Ohara Museum of Art E632896 entity
Predicate exhibitsWorkBy P5419 FINISHED
Object Kuroda Seiki
Kuroda Seiki was a pioneering Japanese Western-style (yōga) painter of the Meiji era, often credited with introducing and popularizing modern Western painting techniques in Japan.
E1904021 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: Kuroda Seiki | Statement: [Ohara Museum of Art, exhibitsWorkBy, Kuroda Seiki]
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: Kuroda Seiki
Triple: [Ohara Museum of Art, exhibitsWorkBy, Kuroda Seiki]
Generated description
Kuroda Seiki was a pioneering Japanese Western-style (yōga) painter of the Meiji era, often credited with introducing and popularizing modern Western painting techniques in Japan.

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_69e75a90c0dc819092f928b6ea0ecc72 completed April 21, 2026, 11:08 a.m.
NER Named-entity recognition batch_69f4a110e8148190883924cfb6b242c4 completed May 1, 2026, 12:48 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2757c7d1d88190aa97fa19408a2151 completed June 9, 2026, 12:01 a.m.
NEDg Description generation batch_6a275a7d33848190ba11aeb45c7e8b83 completed June 9, 2026, 12:12 a.m.
NED2 Entity disambiguation (via description) batch_6a275b11987081908ec648ce1eeceed3 completed June 9, 2026, 12:15 a.m.
Created at: April 21, 2026, 1:38 p.m.