Triple

T5599710
Position Surface form Disambiguated ID Type / Status
Subject 神戸大学 E147086 entity
Predicate hasFaculty P141 FINISHED
Object 法学部
法学部は、法律や政治などに関する専門的知識と法的思考力を養成することを目的とした大学の学部である。
 E528900 NE FINISHED

How this triple was built (4 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: 法学部 | Statement: [神戸大学, hasFaculty, 法学部]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: 法学部
Context triple: [神戸大学, hasFaculty, 法学部]
  • A. 法学研究科
    法学研究科は、東北大学に設置された法学分野の高度な専門教育と研究を行う大学院組織である。
  • B. Faculty of Political Science and Law
    The Faculty of Political Science and Law is an academic division of the Université du Québec à Montréal specializing in education and research in political science, public affairs, and legal studies.
  • C. Faculty of Law and Political Science
    The Faculty of Law and Political Science is an academic division of Lumière University Lyon 2 specializing in legal studies and political science education and research.
  • D. Faculty of Law and Political Science
    The Faculty of Law and Political Science is an academic division of the University of Reims Champagne-Ardenne specializing in legal and political studies and research.
  • E. Faculty of Law and Political Science
    The Faculty of Law and Political Science is an academic unit of Kabul University that provides higher education and research in legal studies, governance, and political affairs in Afghanistan.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: 法学部
Triple: [神戸大学, hasFaculty, 法学部]
Generated description
法学部は、法律や政治などに関する専門的知識と法的思考力を養成することを目的とした大学の学部である。
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: 法学部
Target entity description: 法学部は、法律や政治などに関する専門的知識と法的思考力を養成することを目的とした大学の学部である。
  • A. 法学研究科
    法学研究科は、東北大学に設置された法学分野の高度な専門教育と研究を行う大学院組織である。
  • B. Faculty of Political Science and Law
    The Faculty of Political Science and Law is an academic division of the Université du Québec à Montréal specializing in education and research in political science, public affairs, and legal studies.
  • C. Faculty of Law and Political Science
    The Faculty of Law and Political Science is an academic division of Lumière University Lyon 2 specializing in legal studies and political science education and research.
  • D. Faculty of Law and Political Science
    The Faculty of Law and Political Science is an academic division of the University of Reims Champagne-Ardenne specializing in legal and political studies and research.
  • E. Faculty of Law and Political Science
    The Faculty of Law and Political Science is an academic unit of Kabul University that provides higher education and research in legal studies, governance, and political affairs in Afghanistan.
  • F. None of above. chosen

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_69c009043d648190a7af89698ccf1e3e completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c020d936dc8190a2e599f1df9fdd91 completed March 22, 2026, 5:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0287139508190aa646918228cfdc0 completed March 22, 2026, 5:35 p.m.
NEDg Description generation batch_69c0350eb53081909dc573fefa3e7f0a completed March 22, 2026, 6:29 p.m.
NED2 Entity disambiguation (via description) batch_69c036ee4e1c8190b9e60655d72407ff completed March 22, 2026, 6:37 p.m.
Created at: March 22, 2026, 3:38 p.m.