FEATURES IN OPTIMALITY THEORY A COMPUTATIONAL MODEL

FEATURES IN OPTIMALITY THEORY: A COMPUTATIONAL MODEL by Andrea Jeanine Heiberg Copyright © Andrea Jeanine Heiberg 1999 A Dissertation Submitted to the Faculty of the DEPARTMENT OF LINGUISTICS In Partial Fulfillment of the Requirements For the Degree of DOCTOR OF PHILOSOPHY In the Graduate College THE UNIVERSITY OF ARIZONA 1999 THE UNIVERSITY OF ARIZONA GRADUATE COLLEGE As members of the Final Examination Committee, we certify that we have read the dissertation prepared by Andrea Jeanine Heiberg entitled FEATURES IN OPTIMALITY THEORY: A COMPUTATIONAL MODEL and recommend that it be accepted as fulfilling the dissertation requirement for the Degree of Doctor of Philosophy Diana Archangeli Date Michael Hammond Date Richard Demers Date D Terence Langendoen Date Final approval and acceptance of this dissertation is contingent upon the candidate's submission of the final copy of the dissertation to the Graduate College I hereby certify that I have read the dissertation as prepared under my direction and recommend that it be accepted as fulfilling the dissertation requirement Dissertation Director Diana Archangeli Date STATEMENT BY AUTHOR This dissertation has been submitted in partial fulfillment of requirements for an advanced degree at The University of Arizona and is deposited in the University Library to be made available to borrowers under rules of the Library Brief quotations from this dissertation are allowable without special permission, provided that accurate acknowledgment of source is made Requests for permission for extended quotation from or reproduction of this manuscript in whole or in part may be granted by the copyright holder SIGNED: _ ACKNOWLEDGEMENTS First and foremost, thank you to Diana Archangeli, my advisor and the chair of my committee, for all her encouragement and sound advice throughout my years at the University of Arizona, and especially during the process of writing this dissertation Thank you, Diana, for also opening your home life to me Thanks to Mike Hammond for enthusiastic discussions of phonology and computational linguistics, and for asking tough questions that greatly improved this dissertation To my whole committee, Diana Archangeli, Mike Hammond, Terry Langendoen, and Dick Demers, thank you for your persistence in drawing out the interesting points in this work (and for sometimes convincing me that they really were interesting!) Thank you to Rosemary Emery for being a friend, and for always keeping on top of things Thanks to my colleagues and friends at the University of Arizona, especially Colleen Fitzgerald, Sue Lorenson, Peg Lewis, and Carol Webster, for making graduate school enjoyable Thanks to my friends, coworkers, and supervisors at Motorola, Jessie Burciaga, Hart Switzer, Dan Griffith, Maurice Allen, Ray Embry, and Mike Mikac, for your support, patience, and flexibility, particularly at the end of this project To my husband, Francisco Espinosa, thank you for patiently waiting the many years it took to finish my degree Finally, thanks to my family for all your encouragement, interest in what I was doing, and support through the years TABLE OF CONTENTS STATEMENT BY AUTHOR ACKNOWLEDGEMENTS TABLE OF CONTENTS ABSTRACT INTRODUCTION 10 1.1 Why build a computational model? .13 1.2 Other work in computational Optimality Theory 16 1.3 Organization of dissertation 22 AUTOSEGMENTAL THEORY 23 2.1 Primitives .27 2.2 Properties of representations 32 2.3 Restrictions on representations 41 2.4 Possible representations .44 2.5 Summary 50 OPTIMALITY THEORY 52 3.1 Constraints 55 3.2 Candidate generation (Gen) 70 3.3 Case studies 73 THE MODEL 101 4.1 Object-oriented concepts 102 4.2 Autosegmental representations 105 4.3 Candidate generation (Gen) .116 4.4 Constraint hierarchy (Con) 138 4.5 Naïve algorithm 150 4.6 Proposed algorithm (Gen-Eval loop) 154 4.7 Sample run 168 4.8 Gen-Eval loop pseudocode 187 4.9 Performance .189 4.10 Summary 205 CONCLUSION 206 APPENDIX A: SAMPLE OUTPUT SCREEN 211 APPENDIX B: SAMPLE FEATURE TYPE SET 212 APPENDIX D: SAMPLE INPUT .214 APPENDIX E: SAMPLE CONSTRAINT HIERARCHY 217 APPENDIX G: SAMPLE RUN 219 APPENDIX I: JAVA CODE 228 A.1 Class hierarchy 228 A.2 Align 229 A.4 AlignFeature 230 A.6 AlignPrwd 232 A.8 Anchor .233 A.10 Association 233 A.12 AssociationOperation 234 A.14 AssociationSet 235 A.16 Constraint 236 A.18 Correspond 238 A.20 CorrespondAssociation 239 A.22 CorrespondFeature 240 A.24 DataFile 241 A.26 Debug 243 A.28 DeleteAssociation 244 A.30 DeleteFeature 245 A.32 DepA .247 A.34 DepF 248 A.36 Edge 248 A.38 Feature .249 A.40 FeatureLinearity 250 A.42 FeatureOperation .252 A.43 FeatureTokenSet 252 A.45 FeatureType .253 A.46 FeatureTypeSet 254 A.48 Foot 254 A.50 Gen 255 A.52 GenEval 258 A.53 Ground 265 A.55 GroundNegative 266 A.57 GroundPositive 267 A.59 Hierarchy 269 A.61 InsertAssociation .271 A.63 InsertFeature 272 A.65 LanguageFeatureTypeSet 273 A.67 MaxA 277 A.69 MaxF .278 A.71 Mora 279 A.73 Node 279 A.75 NodeSet 280 A.77 NoFloat 282 A.79 Operation 284 A.81 ProsodicNode 284 A.83 PrWd .285 A.85 RepPanel 285 A.87 Representation 291 A.89 Root 312 A.91 Single 313 A.93 Syllable 325 A.95 TableauPanel 326 REFERENCES 328 ABSTRACT This dissertation presents a computational model of Optimality Theory (OT) (Prince and Smolensky 1993) The model provides an efficient solution to the problem of candidate generation and evaluation, and is demonstrated for the realm of phonological features Explicit object-oriented implementations are proposed for autosegmental representations (Goldsmith 1976 and many others) and violable OT constraints and Gen operations on autosegmental representations Previous computational models of OT (Ellison 1995, Tesar 1995, Eisner 1997, Hammond 1997, Karttunen 1998) have not dealt in depth with autosegmental representations The proposed model provides a full treatment of autosegmental representations and constraints on autosegmental representations (Akinlabi 1996, Archangeli and Pulleyblank 1994, Itô, Mester, and Padgett 1995, Kirchner 1993, Padgett 1995, Pulleyblank 1993, 1996, 1998) Implementing Gen, the candidate generation component of OT, is a seemingly intractable problem Gen in principle performs unlimited insertion; therefore, it may produce an infinite candidate set For autosegmental representations, however, it is not necessary to think of Gen as infinite The Obligatory Contour Principle (Leben 1973, McCarthy 1979, 1986) restricts the number of tokens of any one feature type in a single representation; hence, Gen for autosegmental features is finite However, a finite Gen may produce a candidate set of exponential size Consider an input representation with four anchors for each of five features: there are (24 + 1)5, more than one million, candidates for such an input The proposed model implements a method for significantly reducing the exponential size of the candidate set Instead of first creating all candidates (Gen) and then evaluating them against the constraint hierarchy (Eval), candidate creation and evaluation are interleaved (cf Eisner 1997, Hammond 1997) in a Gen-Eval loop At each pass through the Gen-Eval loop, Gen operations apply to create the minimal number of candidates needed for constraint evaluation; this candidate set is evaluated and culled, and the set of Gen operations is reduced The loop continues until the hierarchy is exhausted; the remaining candidate(s) are optimal In providing explicit implementations of autosegmental representations, constraints, and Gen operations, the model provides a coherent view of autosegmental theory, Optimality Theory, and the interaction between the two 10 INTRODUCTION This dissertation presents a computational model of Optimality Theory (OT) (Prince and Smolensky 1993, McCarthy and Prince 1993) The model provides an efficient solution to the problem of candidate generation and evaluation The model is demonstrated for the realm of phonological features; explicit implementations are proposed for autosegmental representations (Goldsmith 1976 and many others), constraints on autosegmental representations, and operations on autosegmental features This work contributes to the fields of OT, autosegmental phonology, and computational linguistics The primitives of autosegmental representations, the basic data structure of the model, are enumerated and provided with an object-oriented implementation The properties of the generation component of OT, Gen, are explicitly stated in terms of those primitives, and also receive an object-oriented implementation Families of violable OT constraints and their methods of evaluation are precisely defined in terms of autosegmental primitives, and an object-oriented implementation of constraints is provided The proposals for representations, Gen, and constraints together form a coherent view of autosegmental theory under Optimality Theory The proposed implementations of OT constraints and Gen are inextricably tied to that of autosegmental representations The model takes advantage of the interplay among these 322 candidatePanel.add("North", candidateControlPanel); candidatePanel.add("Center", candidateCardPanel); //end candidate flipper rightPanel = new Panel(); rightPanel.setLayout(new BorderLayout(0,0)); rightPanel.add("South", hierarchyPanel); rightPanel.add("Center", candidatePanel); TableauPanel tableauPanel = new TableauPanel(candidates, constraintHierarchy); Panel statsPanel = new Panel(); statsPanel.setLayout(new BorderLayout(0,0)); Label statsTitle = new Label("Number of Candidates", Label.CENTER); statsTitle.setFont(new Font(getFont().getName(), Font.BOLD, getFont().getSize())); statsPanel.add("North", statsTitle); TextArea statsTextArea = new TextArea(4,40); statsTextArea.appendText(stat + "\n"); statsPanel.add("South", statsTextArea); leftPanel = new Panel(); leftPanel.setLayout(new BorderLayout(0,0)); Label tableauTitle = new Label("Tableau", Label.CENTER); tableauTitle.setFont(new Font(getFont().getName(), Font.BOLD, getFont().getSize())); leftPanel.add("North", tableauTitle); leftPanel.add("Center", tableauPanel); leftPanel.add("South", statsPanel); add("West", leftPanel); add("Center", rightPanel); message("Done # of candidates produced=" + candidates.size()); validate(); } //end display public boolean action(Event e, Object arg) { if (e.target instanceof Checkbox) { if (e.target.equals(drawInertCheckbox)) { drawInert = drawInertCheckbox.getState(); } else if (e.target.equals(drawColorCheckbox)) { drawColor = drawColorCheckbox.getState(); } else if (e.target.equals(drawTokensCheckbox)) { drawTokens = drawTokensCheckbox.getState(); } else if (e.target.equals(drawHeadsCheckbox)) { drawHeads = drawHeadsCheckbox.getState(); } //end if 323 } else { int newIndex = 0; int lastIndex = 0; String s = (String)arg; if (e.target.equals(computeButton)) { inputFileName = new String(inputPath + inputChoice.getSelectedItem() + ".txt"); try { appletCleanup(); inputURL = new URL(base, inputFileName); //get URL to data file inputURL.openStream(); //test featureURL = new URL(base, featureFileName); //get URL to language feature type file featureURL.openStream(); //test hierarchyURL = new URL(base, constraintFileName); //get URL to constraint file hierarchyURL.openStream(); //test getData(); process(); display(); } catch (Exception ex) { String st = "action:"+ex.toString(); message(st); System.out.println(st); } //end try } else if (e.target instanceof Choice) { if (e.target.equals(candidateChoice)) { ((CardLayout)candidateCardPanel.getLayout()).show(candidateCardPanel,s ); } else if (e.target.equals(hierarchyChoice)) { ((CardLayout)hierarchyCardPanel.getLayout()).show(hierarchyCardPanel,s ); } //end if } else { if (e.target.equals(optimalButton)) { s = candidateChoice.getItem(optimal); ((CardLayout)candidateCardPanel.getLayout()).show(candidateCardPanel,s ); candidateChoice.select(s); } else if (e.target.equals(firstCandidateButton)) { s = candidateChoice.getItem(0); 324 ((CardLayout)candidateCardPanel.getLayout()).first(candidateCardPanel) ; candidateChoice.select(s); } else if (e.target.equals(nextCandidateButton)) { lastIndex = candidateChoice.countItems()-1; newIndex = candidateChoice.getSelectedIndex()+1; if (newIndex > lastIndex) { s = candidateChoice.getItem(0); } else { s = candidateChoice.getItem(newIndex); } //end if ((CardLayout)candidateCardPanel.getLayout()).next(candidateCardPanel); candidateChoice.select(s); } else if (e.target.equals(previousCandidateButton)) { lastIndex = candidateChoice.countItems()-1; newIndex = candidateChoice.getSelectedIndex()-1; if (newIndex < 0) { s = candidateChoice.getItem(lastIndex); } else { s = candidateChoice.getItem(newIndex); } //end if ((CardLayout)candidateCardPanel.getLayout()).previous(candidateCardPan el); candidateChoice.select(s); } else if (e.target.equals(lastCandidateButton)) { lastIndex = candidateChoice.countItems()-1; s = candidateChoice.getItem(lastIndex); ((CardLayout)candidateCardPanel.getLayout()).last(candidateCardPanel); candidateChoice.select(s); } else if (e.target.equals(firstHierarchyButton)) { s = hierarchyChoice.getItem(0); ((CardLayout)hierarchyCardPanel.getLayout()).first(hierarchyCardPanel) ; hierarchyChoice.select(s); } else if (e.target.equals(nextHierarchyButton)) { lastIndex = hierarchyChoice.countItems()-1; newIndex = hierarchyChoice.getSelectedIndex()+1; if (newIndex > lastIndex) { s = hierarchyChoice.getItem(0); } else { s = hierarchyChoice.getItem(newIndex); 325 } //end if ((CardLayout)hierarchyCardPanel.getLayout()).next(hierarchyCardPanel); hierarchyChoice.select(s); } else if (e.target.equals(previousHierarchyButton)) { lastIndex = hierarchyChoice.countItems()-1; newIndex = hierarchyChoice.getSelectedIndex()-1; if (newIndex < 0) { s = hierarchyChoice.getItem(lastIndex); } else { s = hierarchyChoice.getItem(newIndex); } //end if ((CardLayout)hierarchyCardPanel.getLayout()).previous(hierarchyCardPan el); hierarchyChoice.select(s); } else if (e.target.equals(lastHierarchyButton)) { lastIndex = hierarchyChoice.countItems()-1; s = hierarchyChoice.getItem(lastIndex); ((CardLayout)hierarchyCardPanel.getLayout()).last(hierarchyCardPanel); hierarchyChoice.select(s); } //end if } //end if } //end if } return true; } //end action A.92 A.93 Syllable package OT; /** * Represents phonological syllable node * @version 1998-11-22 * @author Andrea Heiberg, University of Arizona */ public class Syllable extends ProsodicNode { public Syllable (String token) { 326 super(token); } //end constructor public String toString () { return "syllable(" + super.token + ")"; } //end toString public Syllable copy () { Syllable s = new Syllable(token); s.head = head; return s; } //end copy } A.94 A.95 TableauPanel package OT; import java.awt.*; import java.applet.*; import java.util.*; /** * Tableau * @version 1998-9-26 * @author Andrea Heiberg, University of Arizona */ public class TableauPanel extends Panel { public TableauPanel(RepresentationSet reps, Hierarchy hierarchy) { Label l; setFont(new Font("Courier", Font.PLAIN, 11)); TextArea t = new TextArea(19,45); t.setEditable(false); StringBuffer h = new StringBuffer(); //constraint hierarchy h.append(" "); Representation rep = (Representation)reps.get(new Integer(1)); for (int p=rep.toOrthography().length(); p>=0; p ) { h.append(" "); } //end for int n=1; for (Enumeration e=hierarchy.elements(); e.hasMoreElements();) { 327 Constraint c = (Constraint)e.nextElement(); h.append(new Integer(n).toString()); if (n>=10) { h.append(" "); } else { h.append(" "); } //end if n++; } //end for h.append("\n"); t.appendText(h.toString()); int sorted[] = reps.sort(); for (int i=0; i=1; j ) { b.append(" "); } //end for b.append(k); t.appendText(b.toString() + " " + rep.toOrthography() + " " + rep.printViolations(hierarchy) + "\n"); } //end for } add(t); } //end constructor 328 REFERENCES Akinlabi, Akinbiyi (1997) Featural affixation Journal of Linguistics 32.239-289 ROA-185-0397, Rutgers Optimality Archive, http://ruccs.rutgers.edu/roa.html Andrews, Avery (1994) OT for Windows 1.1 Australian National University ROA-910000, Rutgers Optimality Archive, http://ruccs.rutgers.edu/roa.html Archangeli, Diana and Douglas Pulleyblank (1993) Optimality, Grounding Theory, and rule parameters University of Arizona and University of British Columbia manuscript Archangeli, Diana and Douglas Pulleyblank (1994a) Grounded Phonology Cambridge, Massachusetts: MIT Press Archangeli, Diana and Douglas Pulleyblank (1994b) Kinande vowel harmony: Domains, grounded conditions, and one-sided alignment University of Arizona and University of British Columbia manuscript Beckman, Jill, Laura Walsh Dickey, and Suzanne Urbanczyk (1995) University of Massachusetts Occasional Papers in Linguistics 18: Papers in Optimality Theory Amherst, Massachusetts: University of Massachusetts GLSA Bickmore, Lee S (1996) Bantu tone spreading and displacement as alignment and minimal misalignment ROA-161-1196, Rutgers Optimality Archive, http://ruccs.rutgers.edu/roa.html Bird, Steven (1990) Constraint-based phonology University of Edinburgh Ph.D dissertation Bird, Steven (1995) Computational Phonology: A Constraint-Based Approach New York: Cambridge University Press Bird, Steven and T Mark Ellison (1995) One-level phonology: Autosegmental representations and rules as finite state automata Computational Linguistics 20:1.55-90 Bird, Steven and Ewan Klein (1990) Phonological events Journal of Linguistics 26.33-56 Bird, Steven and Ewan Klein (1995) Phonological analysis in typed feature systems Computational Linguistics 20 329 Chomsky, Noam and Morris Halle (1968) The Sound Pattern of English New York: Harper and Row Clements, G N (1985) The geometry of phonological features Phonology Yearbook 2.225-252 Clements, G N and K Ford (1979) Kikuyu tone shift and its synchronic consequences Linguistic Inquiry 10.179-210 Clements, G N and K Ford (1981) On the phonological status of downstep in Kikuyu In D Goyvaerts (ed.), Phonology in the 1980’s Ghent: Storia Scientia Clements, G N and J Goldsmith (1984) Autosegmental Studies in Bantu Tone Dordrecht: Foris Clements, G N and Elizabeth Hume (1995) The internal organization of speech sounds In John Goldsmith (ed.), The Handbook of Phonological Theory Cambridge, Massachusetts: Blackwell Clements, George N and Engin Sezer (1982) Vowel and consonant disharmony in Turkish In Harry van der Hulst and Norval Smith (eds.), The Structure of Phonological Representations, Part II Dordrecht: Foris Cole, Jennifer and Charles W Kisseberth (1994) An optimal domains theory of harmony Studies in the Linguistic Sciences 24 ROA-22-0894, Rutgers Optimality Archive, http://ruccs.rutgers.edu/roa.html Coleman, John and John Local (1991) The “no crossing constraint” in autosegmental phonology Linguistics and Philosophy 14:295-338 Crowhurst, Megan J and Mark Hewitt (1997) Boolean operations and constraint interactions in Optimality Theory ROA-229-1197, Rutgers Optimality Archive, http://ruccs.rutgers.edu/roa.html de Lacy, Paul (1997) Prosodic Categorization University of Auckland M.A thesis ROA-236-1297, Rutgers Optimality Archive, http://ruccs.rutgers.edu/roa.html Eisner, Jason (1997a) Efficient generation in primitive Optimality Theory University of Pennsylvania manuscript ROA-206-0797, Rutgers Optimality Archive, http://ruccs.rutgers.edu/roa.html 330 Eisner, Jason (1997b) What constraints should OT allow? 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dissertation ROA-281-0998, Rutgers Optimality Archive, http://ruccs.rutgers.edu/roa.html Tesar, Bruce (1995a) Computational Optimality Theory University of Colorado Ph.D dissertation ROA-90-0000, Rutgers Optimality Archive, http://ruccs.rutgers.edu/roa.html Tesar, Bruce (1995b) Computing optimal forms in Optimality Theory: Basic syllabification University of Colorado at Boulder manuscript ROA-52-0295, Rutgers Optimality Archive, http://ruccs.rutgers.edu/roa.html 336 Tesar, Bruce (1998) Robust interpretive parsing in metrical stress theory Rutgers University manuscript ROA-262-0598, Rutgers Optimality Archive, http://ruccs.rutgers.edu/roa.html Walther, Markus (1996) OT SIMPLE—A construction kit approach to Optimality Theory implementation Heinrich-Heine-Universität Düsseldorf manuscript ROA-152-1096, Rutgers Optimality Archive, http://ruccs.rutgers.edu/roa.html Yip, Moira (1994a) Morpheme-level features: Chaoyang syllable structure and nasalization ROA-81-0000, Rutgers Optimality Archive, http://ruccs.rutgers.edu/roa.html Yip, Moira (1994b) Repetition and its avoidance: The case of Javanese ROA-83-0000, Rutgers Optimality Archive, http://ruccs.rutgers.edu/roa.html Zoll, Cheryl (1996) A unified treatment of latent segments and floating features University of California, Berkeley, manuscript ROA-137-0996, Rutgers Optimality Archive, http://ruccs.rutgers.edu/roa.html ... Why build a computational model? A typical method of carrying out OT analyses involves hypothesizing a ranking of violable constraints for a language, and then testing the ranking on a handpicked... set of candidate representations Testing involves evaluating each candidate against the constraint hierarchy and finding the optimal candidate according to the evaluations; this process can be... candidates (Gen) and then evaluating them against the constraint hierarchy (Eval), candidate creation and evaluation are interleaved (cf Eisner 1997, Hammond 1997) in a Gen-Eval loop At each pass through