Triple

T9918629

Position	Surface form	Disambiguated ID	Type / Status
Subject	Faculty of Engineering, The University of Tokyo	`E185932`	entity
Predicate	hasAcademicUnit	`P1488`	FINISHED
Object	Department of Materials Engineering, The University of Tokyo The Department of Materials Engineering at the University of Tokyo is a leading academic department focused on the science, engineering, and innovation of advanced materials for technology and industry.	`E829498`	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 Materials Engineering, The University of Tokyo | Statement: [Faculty of Engineering, The University of Tokyo, hasAcademicUnit, Department of Materials Engineering, The University of Tokyo]

NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07

Target entity: Department of Materials Engineering, The University of Tokyo
Context triple: [Faculty of Engineering, The University of Tokyo, hasAcademicUnit, Department of Materials 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. Institute for Solid State Physics, University of Tokyo
The Institute for Solid State Physics at the University of Tokyo is a leading Japanese research institute specializing in condensed matter physics and related materials science.
D. Institute of Industrial Science, University of Tokyo
The Institute of Industrial Science at the University of Tokyo is a leading Japanese research institute dedicated to advanced science and engineering, spanning fields from information technology and robotics to materials and environmental studies.
E. Department of Materials Science and Engineering (University of Michigan)
The Department of Materials Science and Engineering at the University of Michigan is an academic department focused on research and education in the properties, design, and applications of materials for engineering and technology.
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 Materials Engineering, The University of Tokyo
Triple: [Faculty of Engineering, The University of Tokyo, hasAcademicUnit, Department of Materials Engineering, The University of Tokyo]

Generated description

The Department of Materials Engineering at the University of Tokyo is a leading academic department focused on the science, engineering, and innovation of advanced materials for technology and industry.

NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07

Target entity: Department of Materials Engineering, The University of Tokyo
Target entity description: The Department of Materials Engineering at the University of Tokyo is a leading academic department focused on the science, engineering, and innovation of advanced materials for technology and industry.

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. Institute for Solid State Physics, University of Tokyo
The Institute for Solid State Physics at the University of Tokyo is a leading Japanese research institute specializing in condensed matter physics and related materials science.
D. Institute of Industrial Science, University of Tokyo
The Institute of Industrial Science at the University of Tokyo is a leading Japanese research institute dedicated to advanced science and engineering, spanning fields from information technology and robotics to materials and environmental studies.
E. Department of Materials Science and Engineering (University of Michigan)
The Department of Materials Science and Engineering at the University of Michigan is an academic department focused on research and education in the properties, design, and applications of materials for engineering and technology.
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_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.