Natural Language Analysis of Patent Claims

1. Natural Language Analysis of Patent Claims Svetlana Sheremetyeva Department of Computational Linguistics Copenhagen Business School Denmark lanaconsult@mail.dk

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

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. lanaconsult@mail.dk

4. No existing NLP system, can process patent texts (claims) adequately. Example of a US Patent Claim 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 slotsformedin said cover part, said slots beingapproximatelyradially directed, guide members disposed on said cover part, a splice holder mountedon said cover part to form a rotatable splice holder. lanaconsult@mail.dk

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 lanaconsult@mail.dk

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 lanaconsult@mail.dk

7. A claim text chunked into phrases lanaconsult@mail.dk

8. Final parse as a set of predicate-argument structures lanaconsult@mail.dk

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 lanaconsult@mail.dk

10. A screenshot of the AutoRead prototype interface lanaconsult@mail.dk

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 lanaconsult@mail.dk