Triple
T9918621
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Faculty of Engineering, The University of Tokyo |
E185932
|
entity |
| Predicate | hasAcademicUnit |
P1488
|
FINISHED |
| Object |
Department of Civil Engineering, The University of Tokyo
The Department of Civil Engineering at the University of Tokyo is a leading academic department in Japan specializing in education and research on infrastructure, urban and environmental systems, and disaster prevention engineering.
|
E185932
|
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 Civil Engineering, The University of Tokyo | Statement: [Faculty of Engineering, The University of Tokyo, hasAcademicUnit, Department of Civil Engineering, The University of Tokyo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Department of Civil Engineering, The University of Tokyo Context triple: [Faculty of Engineering, The University of Tokyo, hasAcademicUnit, Department of Civil Engineering, The University of Tokyo]
-
A.
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.
-
B.
Graduate School of Engineering, The University of Tokyo
The Graduate School of Engineering at the University of Tokyo is a leading Japanese engineering institution renowned for its advanced research and education across a wide range of engineering and technology disciplines.
-
C.
Graduate School of Architecture, University of Tokyo
The Graduate School of Architecture at the University of Tokyo is a leading Japanese institution for advanced architectural education and research, known for producing influential architects and scholars.
-
D.
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.
-
E.
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.
- 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 Civil Engineering, The University of Tokyo Triple: [Faculty of Engineering, The University of Tokyo, hasAcademicUnit, Department of Civil Engineering, The University of Tokyo]
Generated description
The Department of Civil Engineering at the University of Tokyo is a leading academic department in Japan specializing in education and research on infrastructure, urban and environmental systems, and disaster prevention engineering.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Department of Civil Engineering, The University of Tokyo Target entity description: The Department of Civil Engineering at the University of Tokyo is a leading academic department in Japan specializing in education and research on infrastructure, urban and environmental systems, and disaster prevention engineering.
-
A.
Faculty of Engineering, The University of Tokyo
chosen
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.
-
B.
Graduate School of Engineering, The University of Tokyo
The Graduate School of Engineering at the University of Tokyo is a leading Japanese engineering institution renowned for its advanced research and education across a wide range of engineering and technology disciplines.
-
C.
Graduate School of Architecture, University of Tokyo
The Graduate School of Architecture at the University of Tokyo is a leading Japanese institution for advanced architectural education and research, known for producing influential architects and scholars.
-
D.
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.
-
E.
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.
- F. None of above.
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_69ca829b45f481909040f7b99a1976ed |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cdb5685a908190ab3e55b9bf9613f6 |
completed | April 2, 2026, 12:16 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d20dec42848190ab9f8663155df83f |
completed | April 5, 2026, 7:23 a.m. |
| NEDg | Description generation | batch_69d20ef343a4819093b915a66c63fbaa |
completed | April 5, 2026, 7:27 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d212d0ed108190bbde23439734618a |
completed | April 5, 2026, 7:44 a.m. |
Created at: March 30, 2026, 8:42 p.m.