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Artificial Intelligence Research Centre Program Systems Institute Russian Academy of Science

Artificial Intelligence Research Centre Program Systems Institute Russian Academy of Science. 152020 Pereslavl-Zalessky Russia. INEX: Tools for Information Extraction. Artificial Intelligence Research Centre Program Systems Institute Russian Academy of Science 152020 Pereslavl-Zalessky

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Artificial Intelligence Research Centre Program Systems Institute Russian Academy of Science

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  1. Artificial Intelligence Research CentreProgram Systems InstituteRussian Academy of Science 152020 Pereslavl-Zalessky Russia

  2. INEX: Tools for Information Extraction Artificial Intelligence Research CentreProgram Systems InstituteRussian Academy of Science 152020 Pereslavl-Zalessky Russia +7 48535 98065 inex@epk.botik.ru

  3. Information extraction Objective: • extract meaningful information of a pre-specified type from (typically large amounts of) texts for further analytical purposes Output: • data structures of a pre-specified format (filled scenario templates)

  4. Examples • Sports report: <winner>, <loser>, <score>, <location>, <date>… • Database on rental accommodation opportunities: <location>,<renting price>, <bedrooms number>, <phone number>…

  5. Possible IE application scenarios: • inference of new information (knowledge acquisition) • query formulation and answering in human-computer systems • automatic generation of abstracts and summaries • visualization of document content, etc.

  6. The `Newsmaking’ task • <newsmaker> • <type of newsmaker> (person or organization) • <message> • <type of message> (original, cited, a reference to another newsmaker)

  7. IE system architecture

  8. Tokenisation & sentence segmentation • Tokenisation identification of words, punctuation marks, delimiters, special characters • Sentence segmentation recognizing sentence boundaries

  9. Morphological analysis • maps every word-form of the input text to (a) canonical form(s) • recognizes the word's morphological properties Results are typically ambiguous.

  10. Filtering • reduces the text to be subjected to further processing to potentially relevant portions

  11. Disambiguation • a side effect of other processes (e.g., microsyntactic analysis) • a stand-alone stage

  12. Microsyntactic analysis • identifies noun phrases (NP) • identifies some regularly formed constructions (numbers, dates, personal proper names)

  13. Macrosyntactic analysis • identifies clause boundaries • constructs clause hierarchy within a sentence

  14. Named entity recognizer • identifies proper names • assigns semantic features to certain items

  15. Information extraction rules • a domain knowledge representation formalism (scenario templates) • a set of patterns to identify template elements in a text (covering the many possible ways to talk about the target event elements)

  16. IE pattern includes: • a set of rules that define how to retrieve this pattern in a text • a set of constraints imposed on textual elements to fit into a particular slot of the target

  17. Coreference Resolver • recognizes different occurrences of the same entity in a text

  18. Merging partial results • merging partially filled templates to produce a final, maximally filled template

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