Triple

T8100885

Position	Surface form	Disambiguated ID	Type / Status
Subject	Lazaridis School of Business and Economics	`E189107`	entity
Predicate	hasDepartment	`P35`	FINISHED
Object	Department of Operations and Decision Sciences The Department of Operations and Decision Sciences is an academic unit specializing in operations management, business analytics, and quantitative decision-making within the Lazaridis School of Business and Economics.	`E711493`	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 Operations and Decision Sciences | Statement: [Lazaridis School of Business and Economics, hasDepartment, Department of Operations and Decision Sciences]

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

Target entity: Department of Operations and Decision Sciences
Context triple: [Lazaridis School of Business and Economics, hasDepartment, Department of Operations and Decision Sciences]

A. Department of Operations Research and Statistics
The Department of Operations Research and Statistics is an academic unit specializing in quantitative decision-making, optimization, and statistical analysis within the Faculty of Organizational Sciences at the University of Belgrade.
B. Information Systems and Decision Sciences Department
The Information Systems and Decision Sciences Department is an academic unit specializing in information technology, analytics, and data-driven decision-making within the Muma College of Business.
C. Department of Social and Decision Sciences
The Department of Social and Decision Sciences is an interdisciplinary academic unit at Carnegie Mellon University that focuses on the study of human behavior, decision-making, and public policy using methods from psychology, economics, and related social sciences.
D. Department of Operations Research and Financial Engineering
The Department of Operations Research and Financial Engineering is an academic department specializing in quantitative methods for decision-making, optimization, and financial modeling, typically housed within a university’s engineering school.
E. Department of Data Sciences and Operations
The Department of Data Sciences and Operations is an academic unit at the USC Marshall School of Business that focuses on research and education in data analytics, statistics, information systems, and operations management.
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 Operations and Decision Sciences
Triple: [Lazaridis School of Business and Economics, hasDepartment, Department of Operations and Decision Sciences]

Generated description

The Department of Operations and Decision Sciences is an academic unit specializing in operations management, business analytics, and quantitative decision-making within the Lazaridis School of Business and Economics.

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

Target entity: Department of Operations and Decision Sciences
Target entity description: The Department of Operations and Decision Sciences is an academic unit specializing in operations management, business analytics, and quantitative decision-making within the Lazaridis School of Business and Economics.

A. Department of Operations Research and Statistics
The Department of Operations Research and Statistics is an academic unit specializing in quantitative decision-making, optimization, and statistical analysis within the Faculty of Organizational Sciences at the University of Belgrade.
B. Information Systems and Decision Sciences Department
The Information Systems and Decision Sciences Department is an academic unit specializing in information technology, analytics, and data-driven decision-making within the Muma College of Business.
C. Department of Social and Decision Sciences
The Department of Social and Decision Sciences is an interdisciplinary academic unit at Carnegie Mellon University that focuses on the study of human behavior, decision-making, and public policy using methods from psychology, economics, and related social sciences.
D. Department of Operations Research and Financial Engineering
The Department of Operations Research and Financial Engineering is an academic department specializing in quantitative methods for decision-making, optimization, and financial modeling, typically housed within a university’s engineering school.
E. Department of Data Sciences and Operations
The Department of Data Sciences and Operations is an academic unit at the USC Marshall School of Business that focuses on research and education in data analytics, statistics, information systems, and operations management.
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_69ca82b886d88190a9cba0d5a4a27521`	completed	March 30, 2026, 2:03 p.m.
NER	Named-entity recognition	`batch_69cb42bbf20c8190aa8c272b5c39002d`	completed	March 31, 2026, 3:42 a.m.
NED1	Entity disambiguation (via context triple)	`batch_69cc641d96e88190adee974b79d5fc05`	completed	April 1, 2026, 12:17 a.m.
NEDg	Description generation	`batch_69cc68d9032c8190af6c5ff64fe46aff`	completed	April 1, 2026, 12:37 a.m.
NED2	Entity disambiguation (via description)	`batch_69cc69f6bb308190a95df95d1a67cfec`	completed	April 1, 2026, 12:42 a.m.

Created at: March 30, 2026, 5:31 p.m.