Triple

T15248338

Position	Surface form	Disambiguated ID	Type / Status
Subject	Tokyo University of Marine Science and Technology	`E364444`	entity
Predicate	hasDepartment	`P35`	FINISHED
Object	Department of Logistics and Information Engineering The Department of Logistics and Information Engineering is an academic unit at Tokyo University of Marine Science and Technology focused on education and research in logistics systems, information technology, and related engineering fields.	`E1145716`	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 Logistics and Information Engineering | Statement: [Tokyo University of Marine Science and Technology, hasDepartment, Department of Logistics and Information Engineering]

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

Target entity: Department of Logistics and Information Engineering
Context triple: [Tokyo University of Marine Science and Technology, hasDepartment, Department of Logistics and Information Engineering]

A. Department of Logistics, Business and Public Policy
The Department of Logistics, Business and Public Policy is an academic unit at the University of Maryland’s Robert H. Smith School of Business that focuses on supply chain management, transportation, and the intersection of business strategy and public policy.
B. School of Transportation and Logistics Engineering
The School of Transportation and Logistics Engineering is an academic unit of Wuhan University of Technology specializing in education and research on transportation systems, logistics management, and related engineering disciplines.
C. Faculty of Logistics and Crisis Management
The Faculty of Logistics and Crisis Management is a specialized unit of Tomas Bata University in Zlín focused on education and research in logistics, emergency response, and the management of critical situations.
D. Technology and Logistics Directorate
The Technology and Logistics Directorate is the Israel Defense Forces’ branch responsible for military logistics, technological support, maintenance, and supply systems that enable the IDF’s operational readiness.
E. School of Transport and Logistics
The School of Transport and Logistics is an academic faculty of Lagos State University specializing in education and research on transportation systems, logistics management, and related infrastructure.
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 Logistics and Information Engineering
Triple: [Tokyo University of Marine Science and Technology, hasDepartment, Department of Logistics and Information Engineering]

Generated description

The Department of Logistics and Information Engineering is an academic unit at Tokyo University of Marine Science and Technology focused on education and research in logistics systems, information technology, and related engineering fields.

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

Target entity: Department of Logistics and Information Engineering
Target entity description: The Department of Logistics and Information Engineering is an academic unit at Tokyo University of Marine Science and Technology focused on education and research in logistics systems, information technology, and related engineering fields.

A. Department of Logistics, Business and Public Policy
The Department of Logistics, Business and Public Policy is an academic unit at the University of Maryland’s Robert H. Smith School of Business that focuses on supply chain management, transportation, and the intersection of business strategy and public policy.
B. School of Transportation and Logistics Engineering
The School of Transportation and Logistics Engineering is an academic unit of Wuhan University of Technology specializing in education and research on transportation systems, logistics management, and related engineering disciplines.
C. Faculty of Logistics and Crisis Management
The Faculty of Logistics and Crisis Management is a specialized unit of Tomas Bata University in Zlín focused on education and research in logistics, emergency response, and the management of critical situations.
D. Technology and Logistics Directorate
The Technology and Logistics Directorate is the Israel Defense Forces’ branch responsible for military logistics, technological support, maintenance, and supply systems that enable the IDF’s operational readiness.
E. School of Transport and Logistics
The School of Transport and Logistics is an academic faculty of Lagos State University specializing in education and research on transportation systems, logistics management, and related infrastructure.
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_69d85a0dde7481908fc64d1e82d5d20d`	completed	April 10, 2026, 2:01 a.m.
NER	Named-entity recognition	`batch_69e007f4f9d48190b96a7e0c6993cd69`	completed	April 15, 2026, 9:49 p.m.
NED1	Entity disambiguation (via context triple)	`batch_69fedd491cd881908bad9660af9b6b8f`	completed	May 9, 2026, 7:07 a.m.
NEDg	Description generation	`batch_69fedf6ee3f081909553078cd3e9d243`	completed	May 9, 2026, 7:17 a.m.
NED2	Entity disambiguation (via description)	`batch_69fee0016a088190ad87268e035f677e`	completed	May 9, 2026, 7:19 a.m.

Created at: April 10, 2026, 3:13 a.m.