Triple

T21057684

Position	Surface form	Disambiguated ID	Type / Status
Subject	Program in Applied and Computational Mathematics, Princeton University	`E518761`	entity
Predicate	isInterdisciplinaryWith	`P592`	FINISHED
Object	Department of Operations Research and Financial Engineering, Princeton University	`—`	NE NERFINISHED

How this triple was built (2 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 Research and Financial Engineering, Princeton University | Statement: [Program in Applied and Computational Mathematics, Princeton University, isInterdisciplinaryWith, Department of Operations Research and Financial Engineering, Princeton University]

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

Target entity: Department of Operations Research and Financial Engineering, Princeton University
Context triple: [Program in Applied and Computational Mathematics, Princeton University, isInterdisciplinaryWith, Department of Operations Research and Financial Engineering, Princeton University]

A. Department of Operations Research and Financial Engineering chosen
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.
B. Department of Industrial Engineering and Operations Research, UC Berkeley
The Department of Industrial Engineering and Operations Research at UC Berkeley is a leading academic department specializing in optimization, stochastic processes, data analytics, and systems engineering for complex decision-making in industry and society.
C. 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.
D. 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.
E. Department of Management Science and Engineering at Stanford University
The Department of Management Science and Engineering at Stanford University is an interdisciplinary academic department that integrates engineering, business, and policy to study and improve complex systems in areas such as operations, decision analysis, information technology, and organizational strategy.
F. None of above.
G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b5053ac48190921529544959e906`	completed	April 16, 2026, 10:08 a.m.
NER	Named-entity recognition	`batch_69e6fd81434c8190aedfddf937f82322`	completed	April 21, 2026, 4:30 a.m.

Created at: April 16, 2026, 2:37 p.m.