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Natural Language Analysis of Patent Claims

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Title: Natural Language Analysis of Patent Claims


1
Natural Language Analysis of Patent Claims
  • Svetlana Sheremetyeva
  • Department of Computational Linguistics
  • Copenhagen Business School
  • Denmark

2
Overview of the presentation
  • Why do we need NLP of patent claims
  • Natural language analyzer for patent claims
  • Examples of applications
  • Conclusions

3
Why NLP of patent claims
  • The claim is the focal point of a patent
    disclosure and the actual subject of legal
    protection
  • An optimistic view is that NLP of patent claims
    will raise a level of performance of patent
    related applications
  • Patent claims are particularly challenging for
    NLP as they are an ultimate example of extremely
    long sentences frequently including a lot of
    telescopically embedding clauses.

4
Example of a US Patent Claim
No existing NLP system, can process patent texts
(claims) adequately.
  • A cassette for holding excess lengths of light
    waveguides in a splice area comprising
  • a cover part and a pot-shaped bottom part
    having a bottom disk and a rim extending
    perpendicular to said bottom disk, said cover and
    bottom parts are superimposed to enclose
    jointly an area forming a magazine for excess
    lengths of light waveguides, said cover part
    being rotatable in said bottom part, two guide
    slots formed in said cover part, said slots being
    approximately radially directed, guide members
    disposed on said cover part, a splice holder
    mounted on said cover part to form a rotatable
    splice holder.

5
Natural language analyzer for patent claims
(knowledge)
  • Lexicons
  • shallow lexicon for supertagging
  • deep predicate lexicon
  • Grammar mixture of PHG and DG
  • Knowledge representation (final parse) in two
    formats
  • a set of individual predicate-argument structures
  • a tree of predicate argument structures

6
Natural language analyzer for patent claims
(analysis algorithm)
  • Tokenazation
  • Supertaging (shallow lexicon)
  • assignment of supertags, disambiguation
  • Chunking (keeps internal structure of chunks)
  • Determining dependencies (predicate lexicon)
  • case-role dependencies predicate disambiguation
  • predicate-argument structures

7
A claim text chunked into phrases
8
Final parse as a set of predicate-argument
structures
9
Examples of applications
  • Machine translation
  • Transfer of SL predicate-argument structures into
    TL predicate argument structures
  • Generation of TL claim with the generator of the
    application for authoring patent claims
    (Sheremetyeva, 2003)
  • AutoRead for improving the readability of claims
  • Generation of the simple sentences based on every
    predicate structure

10
A screenshot of the AutoRead prototype interface
11
Conclusions
  • Suggested methodology can be used in any patent
    related application including MT, IR, QA, etc. in
    multiple languages
  • We intend to
  • add an optional interactive module to the
    analyzer to improve the quality of analysis
  • integrate the analyzer into a number of
    applications, e.g., MT, AutoRead, IR, QA, etc.
  • develop such applications in multiple languages
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