Triple

T268013

Position	Surface form	Disambiguated ID	Type / Status
Subject	Wuhan University	`E5774`	entity
Predicate	hasFaculty	`P141`	FINISHED
Object	School of Water Resources and Hydropower Engineering The School of Water Resources and Hydropower Engineering is a specialized faculty of Wuhan University focused on education and research in water resources management, hydropower engineering, and related environmental and civil engineering fields.	`E35610`	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: School of Water Resources and Hydropower Engineering | Statement: [Wuhan University, hasFaculty, School of Water Resources and Hydropower Engineering]

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

Target entity: School of Water Resources and Hydropower Engineering
Context triple: [Wuhan University, hasFaculty, School of Water Resources and Hydropower Engineering]

A. School of Civil Engineering and Architecture
The School of Civil Engineering and Architecture is a specialized academic unit of Wuhan University focused on education and research in civil engineering, architecture, and related built-environment disciplines.
B. School of Resources and Environmental Science
The School of Resources and Environmental Science is a specialized academic unit of Wuhan University focused on education and research in natural resources management, environmental science, and related interdisciplinary fields.
C. School of Power and Mechanical Engineering
The School of Power and Mechanical Engineering is an academic unit of Wuhan University specializing in mechanical engineering, energy and power engineering, and related technological research and education.
D. Faculty of Engineering
The Faculty of Engineering at McGill University is a leading academic division offering undergraduate and graduate programs in engineering and related applied sciences, known for its research, innovation, and professional training.
E. Faculty of Engineering
The Faculty of Engineering at the University of Tokyo is a leading academic division renowned for its cutting-edge research and education in engineering and technology in Japan and worldwide.
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: School of Water Resources and Hydropower Engineering
Triple: [Wuhan University, hasFaculty, School of Water Resources and Hydropower Engineering]

Generated description

The School of Water Resources and Hydropower Engineering is a specialized faculty of Wuhan University focused on education and research in water resources management, hydropower engineering, and related environmental and civil engineering fields.

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

Target entity: School of Water Resources and Hydropower Engineering
Target entity description: The School of Water Resources and Hydropower Engineering is a specialized faculty of Wuhan University focused on education and research in water resources management, hydropower engineering, and related environmental and civil engineering fields.

A. School of Civil Engineering and Architecture
The School of Civil Engineering and Architecture is a specialized academic unit of Wuhan University focused on education and research in civil engineering, architecture, and related built-environment disciplines.
B. School of Resources and Environmental Science
The School of Resources and Environmental Science is a specialized academic unit of Wuhan University focused on education and research in natural resources management, environmental science, and related interdisciplinary fields.
C. School of Power and Mechanical Engineering
The School of Power and Mechanical Engineering is an academic unit of Wuhan University specializing in mechanical engineering, energy and power engineering, and related technological research and education.
D. Faculty of Engineering
The Faculty of Engineering at McGill University is a leading academic division offering undergraduate and graduate programs in engineering and related applied sciences, known for its research, innovation, and professional training.
E. Faculty of Engineering
The Faculty of Engineering at the University of Tokyo is a leading academic division renowned for its cutting-edge research and education in engineering and technology in Japan and worldwide.
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_69a2587daeb081909591b9d30f80a271`	completed	Feb. 28, 2026, 2:52 a.m.
NER	Named-entity recognition	`batch_69a25dae4a0c8190a66cf6ed3889851c`	completed	Feb. 28, 2026, 3:14 a.m.
NED1	Entity disambiguation (via context triple)	`batch_69a38f4fa8908190961d1bc22a75a081`	completed	March 1, 2026, 12:58 a.m.
NEDg	Description generation	`batch_69a38fd6772081908bbaf308bdbcd5f6`	completed	March 1, 2026, 1:01 a.m.
NED2	Entity disambiguation (via description)	`batch_69a3908a50088190a7cea3de890a8e86`	completed	March 1, 2026, 1:04 a.m.

Created at: Feb. 28, 2026, 2:56 a.m.