Triple

T4099066

Position	Surface form	Disambiguated ID	Type / Status
Subject	Faculty of Engineering, University of Sheffield	`E87893`	entity
Predicate	hasPart	`P35`	FINISHED
Object	Department of Automatic Control and Systems Engineering, University of Sheffield The Department of Automatic Control and Systems Engineering at the University of Sheffield is a leading UK academic department specializing in control, systems engineering, and related interdisciplinary research and education.	`E412750`	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 Automatic Control and Systems Engineering, University of Sheffield | Statement: [Faculty of Engineering, University of Sheffield, hasPart, Department of Automatic Control and Systems Engineering, University of Sheffield]

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

Target entity: Department of Automatic Control and Systems Engineering, University of Sheffield
Context triple: [Faculty of Engineering, University of Sheffield, hasPart, Department of Automatic Control and Systems Engineering, University of Sheffield]

A. Department of Engineering, Lancaster University
The Department of Engineering at Lancaster University is a multidisciplinary engineering school known for its research and teaching in areas such as mechanical, electronic, chemical, and nuclear engineering.
B. Department of Engineering, University of Cambridge
The Department of Engineering at the University of Cambridge is one of the world’s leading engineering schools, renowned for its cutting-edge research, broad range of engineering disciplines, and rigorous undergraduate and postgraduate programs.
C. Faculty of Engineering and Mathematical Sciences
The Faculty of Engineering and Mathematical Sciences is a major academic division of the University of Western Australia that focuses on engineering disciplines, computer science, and the mathematical sciences in teaching and research.
D. School of Mechanical Science and Engineering
The School of Mechanical Science and Engineering is a major academic unit of Huazhong University of Science and Technology specializing in mechanical engineering education and research.
E. Faculty of Engineering and Design
The Faculty of Engineering and Design is Carleton University's academic division specializing in engineering, architecture, industrial design, and related technological 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 Automatic Control and Systems Engineering, University of Sheffield
Triple: [Faculty of Engineering, University of Sheffield, hasPart, Department of Automatic Control and Systems Engineering, University of Sheffield]

Generated description

The Department of Automatic Control and Systems Engineering at the University of Sheffield is a leading UK academic department specializing in control, systems engineering, and related interdisciplinary research and education.

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

Target entity: Department of Automatic Control and Systems Engineering, University of Sheffield
Target entity description: The Department of Automatic Control and Systems Engineering at the University of Sheffield is a leading UK academic department specializing in control, systems engineering, and related interdisciplinary research and education.

A. Department of Engineering, Lancaster University
The Department of Engineering at Lancaster University is a multidisciplinary engineering school known for its research and teaching in areas such as mechanical, electronic, chemical, and nuclear engineering.
B. Department of Engineering, University of Cambridge
The Department of Engineering at the University of Cambridge is one of the world’s leading engineering schools, renowned for its cutting-edge research, broad range of engineering disciplines, and rigorous undergraduate and postgraduate programs.
C. Faculty of Engineering and Mathematical Sciences
The Faculty of Engineering and Mathematical Sciences is a major academic division of the University of Western Australia that focuses on engineering disciplines, computer science, and the mathematical sciences in teaching and research.
D. School of Mechanical Science and Engineering
The School of Mechanical Science and Engineering is a major academic unit of Huazhong University of Science and Technology specializing in mechanical engineering education and research.
E. Faculty of Engineering and Design
The Faculty of Engineering and Design is Carleton University's academic division specializing in engineering, architecture, industrial design, and related technological 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_69aed94564cc8190a9c1457daedb6e7f`	completed	March 9, 2026, 2:29 p.m.
NER	Named-entity recognition	`batch_69aefd0bdea48190805a79515ee92709`	completed	March 9, 2026, 5:02 p.m.
NED1	Entity disambiguation (via context triple)	`batch_69b56b7585bc81909dc2c02e60a55def`	completed	March 14, 2026, 2:06 p.m.
NEDg	Description generation	`batch_69b56c3a4b708190a55027fd3b2b76e0`	completed	March 14, 2026, 2:10 p.m.
NED2	Entity disambiguation (via description)	`batch_69b56cc5c704819083dac59bf7b3cb83`	completed	March 14, 2026, 2:12 p.m.

Created at: March 9, 2026, 3:40 p.m.