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Natural Language to Natural Language to Machine Readable Machine Readable Format Format By: Damian Tamayo By: Damian Tamayo Presentation 1 – Oct. 12, Presentation 1 – Oct. 12, 2009 2009 CIS 895 – MSE Project CIS 895 – MSE Project

Natural Language to Machine Readable Format

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Natural Language to Machine Readable Format. By: Damian Tamayo Presentation 1 – Oct. 12, 2009 CIS 895 – MSE Project. Documentation. cis.ksu.edu/~dtamayo What I want to do, Where I want to go Vision Document – Project Overview My plan to get there Project Plan Gantt Chart - PowerPoint PPT Presentation

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Page 1: Natural Language to Machine Readable Format

Natural Language to Machine Natural Language to Machine Readable FormatReadable Format

By: Damian TamayoBy: Damian Tamayo

Presentation 1 – Oct. 12, 2009Presentation 1 – Oct. 12, 2009

CIS 895 – MSE ProjectCIS 895 – MSE Project

Page 2: Natural Language to Machine Readable Format

DocumentationDocumentation

cis.ksu.edu/~dtamayocis.ksu.edu/~dtamayo What I want to do, Where I want to goWhat I want to do, Where I want to go

Vision Document – Project OverviewVision Document – Project Overview

My plan to get thereMy plan to get there Project PlanProject Plan Gantt ChartGantt Chart

Standards/Guidelines Standards/Guidelines SQA PlanSQA Plan

Page 3: Natural Language to Machine Readable Format

OverviewOverview Project OverviewProject Overview

The GoalThe Goal

Project RequirementsProject Requirements Examples – Simulated outputExamples – Simulated output

ParsingParsing Logical OutputLogical Output SemanticsSemantics PPOSPPOS

SQASQA

Cost EstimationCost Estimation

Project ScheduleProject Schedule

QuestionsQuestions

Page 4: Natural Language to Machine Readable Format

Project Overview - GoalProject Overview - Goal

Employ natural language processing to Employ natural language processing to detect structure and semantics of a detect structure and semantics of a sentence in order to output correct logic so sentence in order to output correct logic so that it can be in machine readable format that it can be in machine readable format accurately represent the inputted text accurately represent the inputted text understand the parsed structure that is understand the parsed structure that is

represented represented Ex: Two cars entered the same intersection from Ex: Two cars entered the same intersection from

different roadwaysdifferent roadways

Page 5: Natural Language to Machine Readable Format

Project RequirementsProject Requirements

Program RequirementsProgram Requirements Main focus of MSE projectMain focus of MSE project

Proprietary POS TaggerProprietary POS Tagger Ensure correct InputEnsure correct Input

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Program Requirements Program Requirements

Req1 (Critical) GUIReq1 (Critical) GUI A.)POS tagger output tabA.)POS tagger output tab B.(Critical) User input (ui) tab/process -> split B.(Critical) User input (ui) tab/process -> split

sentences tabsentences tab C.) Split sentences tab -> hold process uiC.) Split sentences tab -> hold process ui D.(Critical) tab for internal representationD.(Critical) tab for internal representation E.(Critical) ontology tab for showing logicE.(Critical) ontology tab for showing logic F.(Critical)PPOS tagger – ensure inputF.(Critical)PPOS tagger – ensure input

Page 7: Natural Language to Machine Readable Format

Program Reqs (cont)Program Reqs (cont)

Req2 – error messages/servers not Req2 – error messages/servers not runningrunning

Req3 – UI free from grammatical errorsReq3 – UI free from grammatical errors

Req4 – UI not ambigousReq4 – UI not ambigous

Req5 – UI can be multiple sentencesReq5 – UI can be multiple sentences

Page 8: Natural Language to Machine Readable Format

Program Reqs (cont)Program Reqs (cont)

Req6 – Dynamic UIReq6 – Dynamic UI

Req7 – Correct punctuation Req7 – Correct punctuation

Req8 (Critical) – Internal Rep correct Req8 (Critical) – Internal Rep correct

Req9 – UI not use pronounsReq9 – UI not use pronouns

Req10 – UI not use inferenceReq10 – UI not use inference

Page 9: Natural Language to Machine Readable Format

PPOS ReqPPOS Req

PReq1 – PPOS tab -> UI manually tagPReq1 – PPOS tab -> UI manually tag A.) Supersedes other POS taggersA.) Supersedes other POS taggers B.) Return parse of sentenceB.) Return parse of sentence

PReq2 – tag options similar to other POS PReq2 – tag options similar to other POS taggerstaggers

PReq3 – Dynamic taggingPReq3 – Dynamic tagging

Page 10: Natural Language to Machine Readable Format

Expected GUIExpected GUI

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Expected GUI – Split SentencesExpected GUI – Split Sentences

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Expected ParseExpected Parse

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Example Parse Output 2Example Parse Output 2

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Expected Internal RepresentationExpected Internal Representation

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Expected Logic OutputExpected Logic Output

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Expected Logical RepExpected Logical Rep If you are entering a through street or highway at which there are If you are entering a through street or highway at which there are

stop signs, you must stop completely and proceed when you can do stop signs, you must stop completely and proceed when you can do so without interfering with other traffic.so without interfering with other traffic.

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Expected PPOS Expected PPOS

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Expected PPOS Expected PPOS

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SQASQA

Supervisory CommitteeSupervisory Committee Attend presentationsAttend presentations Provide feedbackProvide feedback

Major ProfessorMajor Professor Meet with developer/weekly basisMeet with developer/weekly basis

DeveloperDeveloper Produce product in given timeframeProduce product in given timeframe Meet weekly w/ Major ProfessorMeet weekly w/ Major Professor

Page 20: Natural Language to Machine Readable Format

SQA (cont)SQA (cont)

Documentation and Coding StandardsDocumentation and Coding Standards Existing Project Existing Project

Adding ontoAdding onto Follow existing examplesFollow existing examples

MetricsMetrics COCOMO IICOCOMO II

Reviews AuditsReviews Audits Michael Marlen – chief advisor Michael Marlen – chief advisor

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SQA (cont)SQA (cont)

TestingTesting Dynamic Basis Dynamic Basis

As code is integrated As code is integrated

ToolsTools MS Visual Studio 2008MS Visual Studio 2008 TortoiseSVN TortoiseSVN

Source ControlSource Control

Page 22: Natural Language to Machine Readable Format

Cost EstimationCost Estimation

COCOMO IICOCOMO II Effort – 2.45 * EAF * (KSLOC) ^ 1.09Effort – 2.45 * EAF * (KSLOC) ^ 1.09

Time = 2.5 * (Effort) ^ 0.38Time = 2.5 * (Effort) ^ 0.38

26.8 = 2.45 * 0.89 * 10^1.09 26.8 = 2.45 * 0.89 * 10^1.09 8.7 = 2.5 * 26.8 ^0.388.7 = 2.5 * 26.8 ^0.38

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EAFEAF

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EAF EAF

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EAFEAF

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Cost EstimationCost Estimation

COCOMO IICOCOMO II Effort – 2.45 * EAF * (KSLOC) ^ 1.09Effort – 2.45 * EAF * (KSLOC) ^ 1.09

Time = 2.5 * (Effort) ^ 0.38Time = 2.5 * (Effort) ^ 0.38

26.8 = 2.45 * 0.89 * 10^1.09 26.8 = 2.45 * 0.89 * 10^1.09 8.7 = 2.5 * 26.8 ^0.388.7 = 2.5 * 26.8 ^0.38

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Gantt ChartGantt Chart

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MilestonesMilestones

Internal RepresentationInternal Representation

Logical RepresentationLogical Representation

PPOS TaggerPPOS Tagger

Page 29: Natural Language to Machine Readable Format

Project ScheduleProject Schedule

Presentation 1 – Oct 12, 2009Presentation 1 – Oct 12, 2009 Inception Phase Inception Phase

Presentation 2 – November 5, 2009 ?Presentation 2 – November 5, 2009 ? Elaboration PhaseElaboration Phase

Presentation 3 – December 3, 2009 ?Presentation 3 – December 3, 2009 ? Production Phase – Final Product Production Phase – Final Product

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Phase 2 DeliverablesPhase 2 Deliverables

Vision Plan 2.0Vision Plan 2.0 Project Plan 2.0Project Plan 2.0 Architectural Design DocumentArchitectural Design Document Software Test Plan 1.0Software Test Plan 1.0 Technical Inspection Technical Inspection Presentation 2Presentation 2

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To DoTo Do

Revise DocumentsRevise Documents

Build GUIBuild GUI

Implement Internal RepresentationImplement Internal Representation

Phase 2 DocumentsPhase 2 Documents

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