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Thesis

Deep neural open information extraction with background knowledge

Abstract:

Natural language text, which exists in unstructured format, has a vast amount of knowledge about the world we live in. With the ever-increasing volume of natural language literature, it has become an incredibly time consuming effort to analyse text and extract important knowledge buried within it. This has resulted in the emergence of information extraction (IE) and natural language processing (NLP) methodologies and tools. IE focuses on the automatic extraction of structured semantic informa...

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Division:
MPLS
Department:
Computer Science
Role:
Author

Contributors

Role:
Supervisor
ORCID:
0000-0002-7644-1668
Role:
Examiner
ORCID:
0000-0003-4558-2457
Institution:
University of Cambridge
Role:
Examiner


Type of award:
DPhil
Level of award:
Doctoral
Awarding institution:
University of Oxford


Deposit date:
2022-09-23

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