Triple

T13343709
Position Surface form Disambiguated ID Type / Status
Subject Faculty of Engineering, Hosei University E317890 entity
Predicate hasDepartment P35 FINISHED
Object Department of Mechanical Engineering, Hosei University
The Department of Mechanical Engineering at Hosei University is an academic unit specializing in education and research in mechanical engineering and related technologies.
E1035602 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: Department of Mechanical Engineering, Hosei University | Statement: [Faculty of Engineering, Hosei University, hasDepartment, Department of Mechanical Engineering, Hosei University]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Department of Mechanical Engineering, Hosei University
Context triple: [Faculty of Engineering, Hosei University, hasDepartment, Department of Mechanical Engineering, Hosei University]
  • A. Faculty of Engineering, Tohoku University
    The Faculty of Engineering at Tohoku University is a major academic division of the university in Sendai, Japan, renowned for its research and education in engineering and applied sciences.
  • B. Department of Mechanical Engineering, Johns Hopkins University
    The Department of Mechanical Engineering at Johns Hopkins University is a leading academic and research unit specializing in areas such as fluid mechanics, robotics, and materials science within the university’s Whiting School of Engineering.
  • C. Faculty of Mechanical Science and Engineering
    The Faculty of Mechanical Science and Engineering is a major academic division of the Dresden University of Technology specializing in mechanical engineering education and research.
  • D. Faculty of Engineering, Hokkaido University
    The Faculty of Engineering at Hokkaido University is a major academic division that provides undergraduate engineering education and supports advanced research and graduate programs across a wide range of engineering disciplines.
  • E. Department of Mechanical Engineering, Ege University
    The Department of Mechanical Engineering at Ege University is an academic unit that offers undergraduate and graduate education and conducts research in core areas of mechanical engineering within the university’s Faculty of Engineering.
  • 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: Department of Mechanical Engineering, Hosei University
Triple: [Faculty of Engineering, Hosei University, hasDepartment, Department of Mechanical Engineering, Hosei University]
Generated description
The Department of Mechanical Engineering at Hosei University is an academic unit specializing in education and research in mechanical engineering and related technologies.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Department of Mechanical Engineering, Hosei University
Target entity description: The Department of Mechanical Engineering at Hosei University is an academic unit specializing in education and research in mechanical engineering and related technologies.
  • A. Faculty of Engineering, Tohoku University
    The Faculty of Engineering at Tohoku University is a major academic division of the university in Sendai, Japan, renowned for its research and education in engineering and applied sciences.
  • B. Department of Mechanical Engineering, Johns Hopkins University
    The Department of Mechanical Engineering at Johns Hopkins University is a leading academic and research unit specializing in areas such as fluid mechanics, robotics, and materials science within the university’s Whiting School of Engineering.
  • C. Faculty of Mechanical Science and Engineering
    The Faculty of Mechanical Science and Engineering is a major academic division of the Dresden University of Technology specializing in mechanical engineering education and research.
  • D. Faculty of Engineering, Hokkaido University
    The Faculty of Engineering at Hokkaido University is a major academic division that provides undergraduate engineering education and supports advanced research and graduate programs across a wide range of engineering disciplines.
  • E. Department of Mechanical Engineering, Ege University
    The Department of Mechanical Engineering at Ege University is an academic unit that offers undergraduate and graduate education and conducts research in core areas of mechanical engineering within the university’s Faculty of Engineering.
  • 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_69d806b5a3c08190b42c267fb092f98a completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d99e8839b48190b164414b418e756c completed April 11, 2026, 1:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69f71f417e4081908ab2025a313bfad1 completed May 3, 2026, 10:11 a.m.
NEDg Description generation batch_69f7204ac36c8190a04e921442489e9c completed May 3, 2026, 10:15 a.m.
NED2 Entity disambiguation (via description) batch_69f7221887208190ac98945a023bc496 completed May 3, 2026, 10:23 a.m.
Created at: April 9, 2026, 9:31 p.m.