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Funded PhD Opportunity

Automated fact checking of legal documents using computational intelligence techniques

Subjects: Computer Science and Informatics and Law


Summary

This PhD is aligned with the vision of Legal Innovation Centre to promote and support the use of technology in legal services aiding social renewal. This has already led to impact on policy & culture with the Chief Lord Justice of Northern Ireland in a recent announcement referring to our Visual Law Project output.

A prospectus is a document by a corporation containing information on the character, nature, and purpose of an issue of shares, debentures, or other corporate Securities that extends an invitation to the public to purchase the securities.  It must contain all material facts relating to the company and its operations so that a prospective investor can make an informed decision as to the merit of the investment. An important aspect of a law firm’s work is the verification of the facts of each prospectus.

Currently, this is an intensive manual task. Given the large volume of data available in many of these prospectuses, the manual validation of facts can become unfeasible. This supports the requirement for research into tools to enable rapid accurate fact checking and contribute to time-savings in legal fact checking [1]. This proposal comes from members of the Legal Innovation Centre at Ulster University which brings together research into the application and impact of new legal technology and opportunities for the education and training of current and future lawyers in essential legal tech skills.

The aim is to extract and verify each fact in these legal texts and to create a broad set of enabling tools to assist legal workers in the verification of relevant facts. Knowledge acquisition rules based on the linguistic treatment of specific aspects of legal documents will be key to improving the results in this task. Additionally, domain knowledge representation can provide an even broader set of possibilities.

This research will create language models for addressing Information Extraction from texts in the legal domain combined with external publicly accessible document silos to verify statements. Automatic fact checking of legal documents allows for improvements in legal information retrieval system effectiveness [2-4]. However, there are still important issues to overcome so that these tools can fully meet their initial demands.

One of these issues is related to the correct identification and representation of legal statements. Previous work is limited by an approach based on text processing without using important relationship descriptions available in the domain knowledge of the legal context and linguistic information. Even with initiatives, whose approach incorporates linguistic aspects in their design, it can be noted, however, that domain knowledge has not been incorporated.


Essential criteria

  • Upper Second Class Honours (2:1) Degree or equivalent from a UK institution (or overseas award deemed to be equivalent via UK NARIC)
  • Experience using research methods or other approaches relevant to the subject domain

Desirable Criteria

If the University receives a large number of applicants for the project, the following desirable criteria may be applied to shortlist applicants for interview.

  • First Class Honours (1st) Degree
  • Completion of Masters at a level equivalent to commendation or distinction at Ulster
  • Research project completion within taught Masters degree or MRES
  • Practice-based research experience and/or dissemination
  • Work experience relevant to the proposed project
  • Publications - peer-reviewed
  • Use of personal initiative as evidenced by record of work above that normally expected at career stage.

Funding

    DFE

    The scholarship will cover tuition fees at the Home rate and a maintenance allowance of £ 14,777 per annum for three years. EU applicants will only be eligible for the fees component of the studentship (no maintenance award is provided).  For Non EU nationals the candidate must be "settled" in the UK.


Other information


The Doctoral College at Ulster University


Reviews

As Senior Engineering Manager of Analytics at Seagate Technology I utilise the learning from my PhD ever day

Adrian Johnston - PhD in Informatics

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Key dates

Submission deadline
Monday 18 February 2019

Interview Date
Mid March 2019


Contact supervisor

Professor Kevin Curran


Other supervisors


Applying

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