Triple

T37062009
Position Surface form Disambiguated ID Type / Status
Subject 大工大枚方キャンパス E917346 entity
Predicate 関連組織 P629 FINISHED
Object 大阪工業大学工学部
大阪工業大学工学部は、大阪工業大学において工学分野の専門教育と研究を担う主要な学部です。
 E917345 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: 大阪工業大学工学部 | Statement: [大工大枚方キャンパス, 関連組織, 大阪工業大学工学部]
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: 大阪工業大学工学部
Triple: [大工大枚方キャンパス, 関連組織, 大阪工業大学工学部]
Generated description
大阪工業大学工学部は、大阪工業大学において工学分野の専門教育と研究を担う主要な学部です。

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_69fb2f6dbc6881908dd57563630fe776 completed May 6, 2026, 12:09 p.m.
NED1 Entity disambiguation (via context triple) batch_6a402b9b5bc0819080b43e2c49bb4703 completed June 27, 2026, 7:59 p.m.
NEDg Description generation batch_6a402c5380008190b33806706655f030 completed June 27, 2026, 8:02 p.m.
NED2 Entity disambiguation (via description) batch_6a402e678e10819081e8b6b5bf2f233d completed June 27, 2026, 8:11 p.m.
Created at: May 3, 2026, 4:14 p.m.