Mobile menu icon
Skip to navigation | Skip to main content | Skip to footer
Mobile menu icon Search iconSearch
Search type

Department of Computer Science


Reasoning with Natural Language

Primary supervisor

Contact admissions office

Other projects with the same supervisor

Funding

  • Competition Funded Project (Students Worldwide)

This research project is one of a number of projects at this institution. It is in competition for funding with one or more of these projects. Usually the project which receives the best applicant will be awarded the funding. Applications for this project are welcome from suitably qualified candidates worldwide. Funding may only be available to a limited set of nationalities and you should read the full department and project details for further information.

Project description

In recent years, there has been considerable interest in applying machine learning to tackle inferential problems in natural language. These include challenges such as, for example, recovering entailments from natural language text snippets, or constructing explanations and answering multiple-choice questions based on natural language resources. The emphasis here is on chaining together inferential steps in contexts featuring imprecision, uncertainty and ambiguity, perhaps with the aid of background knowledge. At the same time, there is a considerable body of theoretical knowledge concerning the computational complexity of solving logical problems involving specific fragments of natural language. For example, various grammatical constructions can be shown, on proof-theoretic, or even complexity-theoretic grounds, to generate entailments that cannot be retrieved using certain types of simple proof rules.

The aim of this project is to bring greater clarity to recent studies of entailment recognition using neural networks, by bringing to bear insights gained from the theoretical studies. The hypothesis under consideration is that neural networks are unable to replicate all but the simplest varieties of logical inference arising in natural language. We aim thereby to obtain more information on what, exactly, such techniques can and cannot do, and indeed, to what extent these limitations make a difference in respect of to practical tasks involving the processing of natural language.

Person specification

For information

Essential

Applicants will be required to evidence the following skills and qualifications.

  • This project requires mathematical engagement and ability substantially greater than for a typical Computer Science PhD. Give evidence for appropriate competence, as relevant to the project description.
  • You must be capable of performing at a very high level.
  • You must have a self-driven interest in uncovering and solving unknown problems and be able to work hard and creatively without constant supervision.

Desirable

Applicants will be required to evidence the following skills and qualifications.

  • You will have good time management.
  • You will possess determination (which is often more important than qualifications) although you'll need a good amount of both.

General

Applicants will be required to address the following.

  • Comment on your transcript/predicted degree marks, outlining both strong and weak points.
  • Discuss your final year Undergraduate project work - and if appropriate your MSc project work.
  • How well does your previous study prepare you for undertaking Postgraduate Research?
  • Why do you believe you are suitable for doing Postgraduate Research?