Triple
T12337533
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Faculty of Engineering, University of New South Wales |
E294128
|
entity |
| Predicate | hasDepartment |
P35
|
FINISHED |
| Object |
School of Minerals and Energy Resources Engineering, UNSW
The School of Minerals and Energy Resources Engineering at UNSW is an academic unit specializing in education and research in mining, petroleum, and energy resources engineering.
|
E978496
|
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 Minerals and Energy Resources Engineering, UNSW | Statement: [Faculty of Engineering, University of New South Wales, hasDepartment, School of Minerals and Energy Resources Engineering, UNSW]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: School of Minerals and Energy Resources Engineering, UNSW Context triple: [Faculty of Engineering, University of New South Wales, hasDepartment, School of Minerals and Energy Resources Engineering, UNSW]
-
A.
School of Mineral Resources Engineering
The School of Mineral Resources Engineering is an academic unit of the Technical University of Crete specializing in the study and engineering of mineral resources, including their exploration, extraction, and sustainable management.
-
B.
School of Energy Resources
The School of Energy Resources is a University of Wyoming academic and research unit focused on energy-related education, innovation, and industry collaboration, particularly in areas like fossil fuels, renewables, and energy policy.
-
C.
School of Energy and Mining Engineering
The School of Energy and Mining Engineering is an academic unit of the China University of Mining and Technology specializing in education and research related to energy resources, mining engineering, and associated technologies.
-
D.
School of Mines and Geoscience
The School of Mines and Geoscience is a Curtin University academic unit specializing in mining engineering, geology, and related earth sciences, supporting education and research for the resources sector.
-
E.
Faculty of Georesources and Materials Engineering
The Faculty of Georesources and Materials Engineering is a specialized division of RWTH Aachen University focused on education and research in raw materials, earth sciences, and materials engineering.
- 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 Minerals and Energy Resources Engineering, UNSW Triple: [Faculty of Engineering, University of New South Wales, hasDepartment, School of Minerals and Energy Resources Engineering, UNSW]
Generated description
The School of Minerals and Energy Resources Engineering at UNSW is an academic unit specializing in education and research in mining, petroleum, and energy resources engineering.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: School of Minerals and Energy Resources Engineering, UNSW Target entity description: The School of Minerals and Energy Resources Engineering at UNSW is an academic unit specializing in education and research in mining, petroleum, and energy resources engineering.
-
A.
School of Mineral Resources Engineering
The School of Mineral Resources Engineering is an academic unit of the Technical University of Crete specializing in the study and engineering of mineral resources, including their exploration, extraction, and sustainable management.
-
B.
School of Energy Resources
The School of Energy Resources is a University of Wyoming academic and research unit focused on energy-related education, innovation, and industry collaboration, particularly in areas like fossil fuels, renewables, and energy policy.
-
C.
School of Energy and Mining Engineering
The School of Energy and Mining Engineering is an academic unit of the China University of Mining and Technology specializing in education and research related to energy resources, mining engineering, and associated technologies.
-
D.
School of Mines and Geoscience
The School of Mines and Geoscience is a Curtin University academic unit specializing in mining engineering, geology, and related earth sciences, supporting education and research for the resources sector.
-
E.
Faculty of Georesources and Materials Engineering
The Faculty of Georesources and Materials Engineering is a specialized division of RWTH Aachen University focused on education and research in raw materials, earth sciences, and materials engineering.
- 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_69d6ab6ae0dc8190b1522a9c1c55c114 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93f678698819091462b44ff3435f6 |
completed | April 10, 2026, 6:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f62aa5f21c8190bcb32a078a2f7ebb |
completed | May 2, 2026, 4:47 p.m. |
| NEDg | Description generation | batch_69f62c54e6b08190bdae0ec35cc1c48d |
completed | May 2, 2026, 4:54 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f62d13237881908b7c2dca173e20cf |
completed | May 2, 2026, 4:57 p.m. |
Created at: April 8, 2026, 9:53 p.m.