Triple

T19151310

Position	Surface form	Disambiguated ID	Type / Status
Subject	University of Pittsburgh School of Medicine	`E468813`	entity
Predicate	hasAcademicDepartment	`P589`	FINISHED
Object	Department of Biomedical Informatics The Department of Biomedical Informatics is an academic unit specializing in the research and education of computational and data-driven methods to advance biomedical science and healthcare.	`E441458`	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 Biomedical Informatics | Statement: [University of Pittsburgh School of Medicine, hasAcademicDepartment, Department of Biomedical Informatics]

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

Target entity: Department of Biomedical Informatics
Context triple: [University of Pittsburgh School of Medicine, hasAcademicDepartment, Department of Biomedical Informatics]

A. Department of Biomedical Informatics
The Department of Biomedical Informatics is an academic division specializing in the application of information science, data analysis, and computational methods to biomedical and clinical research within Osaka University's Graduate School of Medicine.
B. Department of Medical Informatics
The Department of Medical Informatics is an academic division at Kobe University's Graduate School of Medicine that focuses on the research and education of information technologies and data management in healthcare and medical science.
C. Department of Medical Informatics
The Department of Medical Informatics is an academic unit at Tohoku University's Faculty of Medicine that focuses on the application of information science and technology to healthcare, clinical practice, and biomedical research.
D. Department of Medical Informatics
The Department of Medical Informatics is an academic unit at the University of Tokyo’s Faculty of Medicine that focuses on the research and education of information technologies and data science in healthcare and medical practice.
E. Department of Computer Science and Biomedical Informatics
The Department of Computer Science and Biomedical Informatics is an academic unit at the University of Thessaly in Greece that focuses on education and research at the intersection of computing and biomedical sciences.
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 Biomedical Informatics
Triple: [University of Pittsburgh School of Medicine, hasAcademicDepartment, Department of Biomedical Informatics]

Generated description

The Department of Biomedical Informatics is an academic unit specializing in the research and education of computational and data-driven methods to advance biomedical science and healthcare.

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

Target entity: Department of Biomedical Informatics
Target entity description: The Department of Biomedical Informatics is an academic unit specializing in the research and education of computational and data-driven methods to advance biomedical science and healthcare.

A. Department of Biomedical Informatics chosen
The Department of Biomedical Informatics is an academic division specializing in the application of information science, data analysis, and computational methods to biomedical and clinical research within Osaka University's Graduate School of Medicine.
B. Department of Medical Informatics
The Department of Medical Informatics is an academic unit at Tohoku University's Faculty of Medicine that focuses on the application of information science and technology to healthcare, clinical practice, and biomedical research.
C. Department of Medical Informatics
The Department of Medical Informatics is an academic division at Kobe University's Graduate School of Medicine that focuses on the research and education of information technologies and data management in healthcare and medical science.
D. Department of Medical Informatics
The Department of Medical Informatics is an academic unit at the University of Tokyo’s Faculty of Medicine that focuses on the research and education of information technologies and data science in healthcare and medical practice.
E. Department of Computer Science and Biomedical Informatics
The Department of Computer Science and Biomedical Informatics is an academic unit at the University of Thessaly in Greece that focuses on education and research at the intersection of computing and biomedical sciences.
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_69d8dd084ff48190ac0f8c46ee722629`	completed	April 10, 2026, 11:20 a.m.
NER	Named-entity recognition	`batch_69e5e97cfaa08190b7085d28fe970108`	completed	April 20, 2026, 8:53 a.m.
NED1	Entity disambiguation (via context triple)	`batch_6a06f25476488190aa7dd874a54ecb91`	completed	May 15, 2026, 10:15 a.m.
NEDg	Description generation	`batch_6a06f41269748190b6fa6301d8eb4f4f`	completed	May 15, 2026, 10:23 a.m.
NED2	Entity disambiguation (via description)	`batch_6a06f4da6b04819084dab89e9b3c5d3e`	completed	May 15, 2026, 10:26 a.m.

Created at: April 10, 2026, 12:06 p.m.