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Language Resources and Tools For Supporting The System Engineering Process

Language Resources and Tools For Supporting The System Engineering Process. Onditi V. O. et. al. Computing Department Lancaster University. Overview. System Engineering is a collaborative process. The process is characterised by decisions: about the product about the process

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Language Resources and Tools For Supporting The System Engineering Process

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  1. Language Resources and Tools For Supporting The System Engineering Process Onditi V. O. et. al. Computing Department Lancaster University

  2. Overview • System Engineering is a collaborative process. • The process is characterised by decisions: • about the product • about the process • The decisions are used for estimating individual’s contribution, system maintenance and training NLDB 2004

  3. Challenges/Solutions • Challenges • Decisions aren’t adequately recorded • Use different strategies for recording decisions e.g. use both minutes and audio • Decisions are unstructured and therefore difficult to retrieve and use • Use formal representations during capture • Formalism introduces cognitive overload on decision makers NLDB 2004

  4. Challenges/Solutions (Cont’d) • Decisions are implicitly recorded • Discover decisions through actions • Solution • Use unstructured representation to create and share a structured representation NLDB 2004

  5. The architecture POS/Semantic Rules Indicator Words POS/Semantic Tagging Document Stream Tokenization Structure/Style Rules Extract Actions Sentences Syntactic Pattern Store Action & Context on DB Html derived document NLDB 2004

  6. Document tokenisation • Use document’s style and structure to break a document into paragraphs. • Use string patterns to tokenise the paragraphs into: • sentences, multi-word-expressions, and words NLDB 2004

  7. Analysing a document’s content • Analysis is done at two levels: • surface and • deep (syntactic/semantic) • In surface analysis: • choose and constrain indicator words. • use indicator words for identifying agenda items and minute items. NLDB 2004

  8. Analysing a document’s content (cont’d) • In deep analysis: • use part-of-speech (pos) attribute for selecting content words (nouns, pronouns, verbs, adjectives) • use a pos pattern for extracting action statements (actions) • use semantic attribute to associate action sentences NLDB 2004

  9. Template for action sentences • An action sentence comprises: • an object (action), a verb or verb phrase • a subject (agent), a noun or pronoun • Nouns and verb phrases are syntactically arranged: • the subject appears at the head • the object appears at the tail NLDB 2004

  10. Template for action sentences (cont’d) • a modal verb or function word ‘to’ ties the subject and object • An action sentence template is defined thus: • subject + modal verb/function word ‘to’ + object • the template = NP* + VM/TO + V* in CLAWS (Constituent Likelihood Automatic Word Tagging Systems) tag set. NLDB 2004

  11. Template for action sentences (cont’d) • NP* matches all proper nouns (subject) • VM/TO matches all modal verbs or function word ‘to’ • V* matches all verbs (object) • There are other ways to arrange a subject and an object in a sentence. • the subject can be at the head instead of the tail NLDB 2004

  12. Action template: An example NLDB 2004

  13. Action template: An example (cont’d) • In the example, the elements • <s> = sentence, <w> = word • Element <w> has attributes: • id (identity) - identifies the ordinal number of a sentence in a document and the ordinal number of a word in a sentence • pos = part-of-speech • sem = semantic category NLDB 2004

  14. Action template: An example (cont’d) • pos sequence from id 37.5 to 37.7: • is NP1, TO, VVI • matches the action template NP* + TO/VM + V* • The sentence is marked as an action NLDB 2004

  15. Action template: Results NLDB 2004

  16. Action template: Results (cont’d) • Three sets (1,2,3) of minutes from four organisations (A,B,C,D) were processed • Rel = relevant actions, Ret = actions retrieved by the tool, RelRet = relevant actions retrieved • Recall = RelRet/Rel, Precision = RelRet/Ret • Overall precision = 78, overall recall = 62 NLDB 2004

  17. Representing extracted information • Extracted information is represented in a structured format: • agenda items, minute items and actions are represented as database objects • associations between the objects are captured • associations between the objects and the minute documents are captured NLDB 2004

  18. Retrieving actions • Actions can be retrieved through: • browsing • query • The context of the actions can be retrieved by jumping into the minute document NLDB 2004

  19. Retrieving actions (cont’d) NLDB 2004

  20. Conclusion • Minute documents can be automatically structured and efficiently shared. • Actions sentences can be automatically extracted from minutes documents. • Process decisions can be tracked through actions. NLDB 2004

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