Triple
T13343712
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Faculty of Engineering, Hosei University |
E317890
|
entity |
| Predicate | hasDepartment |
P35
|
FINISHED |
| Object |
Department of Systems and Control Engineering, Hosei University
The Department of Systems and Control Engineering at Hosei University is an academic unit focused on the analysis, design, and optimization of complex engineering systems and control technologies.
|
E1035605
|
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 Systems and Control Engineering, Hosei University | Statement: [Faculty of Engineering, Hosei University, hasDepartment, Department of Systems and Control Engineering, Hosei University]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Department of Systems and Control Engineering, Hosei University Context triple: [Faculty of Engineering, Hosei University, hasDepartment, Department of Systems and Control Engineering, Hosei University]
-
A.
Department of Mathematical Engineering and Information Physics, The University of Tokyo
The Department of Mathematical Engineering and Information Physics at the University of Tokyo is an academic department specializing in the mathematical foundations of engineering, information science, and physical systems.
-
B.
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.
-
C.
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.
-
D.
Faculty of Engineering, Kyoto University
The Faculty of Engineering at Kyoto University is a major academic division renowned for its cutting-edge research and education across a wide range of engineering disciplines in one of Japan’s leading national universities.
-
E.
Faculty of Engineering, The University of Tokyo
The Faculty of Engineering at the University of Tokyo is a leading Japanese engineering faculty renowned for its cutting-edge research and education across a wide range of engineering disciplines.
- 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 Systems and Control Engineering, Hosei University Triple: [Faculty of Engineering, Hosei University, hasDepartment, Department of Systems and Control Engineering, Hosei University]
Generated description
The Department of Systems and Control Engineering at Hosei University is an academic unit focused on the analysis, design, and optimization of complex engineering systems and control technologies.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Department of Systems and Control Engineering, Hosei University Target entity description: The Department of Systems and Control Engineering at Hosei University is an academic unit focused on the analysis, design, and optimization of complex engineering systems and control technologies.
-
A.
Department of Mathematical Engineering and Information Physics, The University of Tokyo
The Department of Mathematical Engineering and Information Physics at the University of Tokyo is an academic department specializing in the mathematical foundations of engineering, information science, and physical systems.
-
B.
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.
-
C.
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.
-
D.
Faculty of Engineering, Kyoto University
The Faculty of Engineering at Kyoto University is a major academic division renowned for its cutting-edge research and education across a wide range of engineering disciplines in one of Japan’s leading national universities.
-
E.
Faculty of Engineering, The University of Tokyo
The Faculty of Engineering at the University of Tokyo is a leading Japanese engineering faculty renowned for its cutting-edge research and education across a wide range of engineering disciplines.
- 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.