Triple

T37060605
Position Surface form Disambiguated ID Type / Status
Subject 大東市 E917312 entity
Predicate hasEducationalInstitution P113 FINISHED
Object 大阪産業大学
大阪産業大学は、大阪府にキャンパスを置き、経営・工学・スポーツ健康など幅広い分野の学部を持つ私立大学です。
E2211438 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: 大阪産業大学 | Statement: [大東市, hasEducationalInstitution, 大阪産業大学]
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: 大阪産業大学
Triple: [大東市, hasEducationalInstitution, 大阪産業大学]
Generated description
大阪産業大学は、大阪府にキャンパスを置き、経営・工学・スポーツ健康など幅広い分野の学部を持つ私立大学です。

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_69f76e95fa40819091e14681087ae5e4 completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69fb2f6caa1c8190ae3f88df531481e4 completed May 6, 2026, 12:09 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3e8c53fd988190aaf6521e5984470b completed June 26, 2026, 2:27 p.m.
NEDg Description generation batch_6a3e943fdef48190b1487178b6dbe237 completed June 26, 2026, 3:01 p.m.
NED2 Entity disambiguation (via description) batch_6a3eedfa8f3481908950dbde596ea364 completed June 26, 2026, 9:24 p.m.
Created at: May 3, 2026, 4:14 p.m.