Triple

T37061787
Position Surface form Disambiguated ID Type / Status
Subject 学校法人常翔学園 E917341 entity
Predicate 設置校 P98664 FINISHED
Object 常翔啓光学園中学校・高等学校
常翔啓光学園中学校・高等学校は、大阪府に所在し中高一貫教育を行う私立の進学校です。
 E2209941 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: 常翔啓光学園中学校・高等学校 | Statement: [学校法人常翔学園, 設置校, 常翔啓光学園中学校・高等学校]
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: 常翔啓光学園中学校・高等学校
Triple: [学校法人常翔学園, 設置校, 常翔啓光学園中学校・高等学校]
Generated description
常翔啓光学園中学校・高等学校は、大阪府に所在し中高一貫教育を行う私立の進学校です。

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_69fb35c058a881909b7ffc2258a656ff completed May 6, 2026, 12:36 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3e8c5715e8819082c99d589abd3baa completed June 26, 2026, 2:27 p.m.
NEDg Description generation batch_6a3e95ede37c8190976559fecd7917b3 completed June 26, 2026, 3:08 p.m.
NED2 Entity disambiguation (via description) batch_6a3e9914a3e48190bf59606bacf80c87 completed June 26, 2026, 3:21 p.m.
Created at: May 3, 2026, 4:14 p.m.