Triple
T13343713
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Faculty of Engineering, Hosei University |
E317890
|
entity |
| Predicate | hasDepartment |
P35
|
FINISHED |
| Object |
Department of Advanced Science and Engineering, Hosei University
The Department of Advanced Science and Engineering at Hosei University is an academic unit focused on cutting-edge research and education in science and engineering disciplines within the university’s engineering faculty.
|
E1035606
|
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 Advanced Science and Engineering, Hosei University | Statement: [Faculty of Engineering, Hosei University, hasDepartment, Department of Advanced Science and Engineering, Hosei University]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Department of Advanced Science and Engineering, Hosei University Context triple: [Faculty of Engineering, Hosei University, hasDepartment, Department of Advanced Science and Engineering, Hosei University]
-
A.
Faculty of Science and Engineering, Waseda University
The Faculty of Science and Engineering at Waseda University is a major academic division that encompasses a wide range of science, technology, and engineering disciplines, offering research-oriented and professionally focused programs.
-
B.
Graduate School of Advanced Science and Engineering
The Graduate School of Advanced Science and Engineering is a research-focused graduate school at Hiroshima University specializing in cutting-edge science and engineering education and innovation.
-
C.
School of Advanced Science and Engineering
The School of Advanced Science and Engineering is a graduate and undergraduate academic unit of Waseda University in Japan specializing in cutting-edge research and education across science, technology, and engineering fields.
-
D.
Research Center for Advanced Science and Technology, University of Tokyo
The Research Center for Advanced Science and Technology at the University of Tokyo is a leading interdisciplinary institute focused on pioneering research and innovation across cutting-edge fields in science and technology.
-
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 Advanced Science and Engineering, Hosei University Triple: [Faculty of Engineering, Hosei University, hasDepartment, Department of Advanced Science and Engineering, Hosei University]
Generated description
The Department of Advanced Science and Engineering at Hosei University is an academic unit focused on cutting-edge research and education in science and engineering disciplines within the university’s engineering faculty.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Department of Advanced Science and Engineering, Hosei University Target entity description: The Department of Advanced Science and Engineering at Hosei University is an academic unit focused on cutting-edge research and education in science and engineering disciplines within the university’s engineering faculty.
-
A.
Faculty of Science and Engineering, Waseda University
The Faculty of Science and Engineering at Waseda University is a major academic division that encompasses a wide range of science, technology, and engineering disciplines, offering research-oriented and professionally focused programs.
-
B.
Graduate School of Advanced Science and Engineering
The Graduate School of Advanced Science and Engineering is a research-focused graduate school at Hiroshima University specializing in cutting-edge science and engineering education and innovation.
-
C.
School of Advanced Science and Engineering
The School of Advanced Science and Engineering is a graduate and undergraduate academic unit of Waseda University in Japan specializing in cutting-edge research and education across science, technology, and engineering fields.
-
D.
Research Center for Advanced Science and Technology, University of Tokyo
The Research Center for Advanced Science and Technology at the University of Tokyo is a leading interdisciplinary institute focused on pioneering research and innovation across cutting-edge fields in science and technology.
-
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.