Courtesy of 2013
|
|
- Marianna Bridges
- 6 years ago
- Views:
Transcription
1 Immediate Constituent Analysis (IC Analysis) Immediate Constituent Analysis is typically analytic and was developed with a view to working out a scientific discovery procedure to find out about the basic units of linguistics. The principle underlying theory is to cut a sentence into smaller parts till the smallest unit (ultimate constituent), the morpheme, is reached. The aim of Immediate Constituent Analysis is to analyse each utterance and each constituent into maximally independent sequences. The ultimate constituents are the smallest meaningful units which any given constriction can be broken down to, consisting of a morpheme at the morphological level and a word at the syntactic level. This term was introduced by Bloomfield, who illustrated the way in which it was possible to take a sentence (he chose Poor John and ran away) and split it up into two immediate constituents (Poor John and ran away), these being in turn analysable into further constituents (Poor and John, and ran away). In other words, a sentence is seen not as a sequence or a "string" of elements, Poor + John + ran + away, but as being made up of "layers" of constituents, each cutting point, or "node' in the diagram being given on identifying label. This was made clear in the form of a "tree diagram", such as: NO INSTANCES OF IC TREE DIAGRAM
2 4 5 At first, at the initial emphasis, it is done pure segmentation, simply dividing the sentence into its constituent/segment/part/onder-deel elements without knowing what these elements were. The principle was that we take a sentence and cut it into two and then cut those parts into two and continue with this segmentation until we reach the smallest units, the morphemes. See this three-word sentence which allows three possible segmentations: John ran away. We may make three segmentations: John ran Away. John Ran away John ran Away By seeing these variation it can be seen the principle of regularity of substitutability by comparing these two sentences: John ran away. Mary likes potatoes. John and mary belong to the same parts of speech as Noun, ran and likes also belong to the same class as Verb so it can be interchangable or subtitutable: John likes Potatoes Mary Ran away
3 But it can be made like these examples since away and potatoes belong to different parts of speech; away is adverb and potatoes is noun. It can not be made like these: *Mary likes away. *John ran potatoes. In addition, Contrasting terms in (structural) LINGUISTICS. Every item of language has a paradigmatic relationship with every other item which can be substituted for it (such as cat with dog), and a syntagmatic relationship with items which occur within the same construction (for example, in The cat sat on the mat, cat with the and sat on the mat). The relationships are like axes, as shown in the accompanying diagram. On the lexical level, paradigmatic contrasts indicate which words are likely to belong to the same word class (part of speech): cat, dog, parrot in the diagram are all nouns, sat, slept, perched are all verbs. Syntagmatic relations between words enable one to build up a picture of co-occurrence restrictions within SYNTAX, for example, the verbs hit, kick have to be followed by a noun (Paul hit the wall, not *Paul hit), but sleep, doze do not normally do so (Peter slept, not *Peter slept the bed). On the semantic level, paradigmatic substitutions allow items from a semantic set to be grouped together, for example Angela came on Tuesday (Wednesday, Thursday, etc.). PLEASE MAKE SENTENCES PARADIGMATICALLY : NO John ran away. (N) (V) (Adv) NO Mary likes potatoes (N) (V) (N)
4 NO Julia was late (N) (V) (Adj) (in fact, sometimes it seems difficult to divide into two, and in some cases division into three or more parts is allowed, but in general the divison is binary. See a more than binary construction: ABIGUOUS CASES: 4
5 N o 5
6 6
7 4 5 6 NEXT EXERCISE: MAKE THE IC ANALYSIS OF THESE AMBIGUOUS SENTENCES: NO LIST OF SENTENCES I called her dog. We saw a group of old men and women. The thing that bothered Ahmed was hiding under the table 4 We are frying chickens 5 I bought many green grapes and pears. 7
ENGBG1 ENGBL1 Campus Linguistics. Meeting 2. Chapter 7 (Morphology) and chapter 9 (Syntax) Pia Sundqvist
Meeting 2 Chapter 7 (Morphology) and chapter 9 (Syntax) Today s agenda Repetition of meeting 1 Mini-lecture on morphology Seminar on chapter 7, worksheet Mini-lecture on syntax Seminar on chapter 9, worksheet
More informationNatural Language Processing. George Konidaris
Natural Language Processing George Konidaris gdk@cs.brown.edu Fall 2017 Natural Language Processing Understanding spoken/written sentences in a natural language. Major area of research in AI. Why? Humans
More informationCS 598 Natural Language Processing
CS 598 Natural Language Processing Natural language is everywhere Natural language is everywhere Natural language is everywhere Natural language is everywhere!"#$%&'&()*+,-./012 34*5665756638/9:;< =>?@ABCDEFGHIJ5KL@
More informationDerivational: Inflectional: In a fit of rage the soldiers attacked them both that week, but lost the fight.
Final Exam (120 points) Click on the yellow balloons below to see the answers I. Short Answer (32pts) 1. (6) The sentence The kinder teachers made sure that the students comprehended the testable material
More informationChapter 4: Valence & Agreement CSLI Publications
Chapter 4: Valence & Agreement Reminder: Where We Are Simple CFG doesn t allow us to cross-classify categories, e.g., verbs can be grouped by transitivity (deny vs. disappear) or by number (deny vs. denies).
More informationA Minimalist Approach to Code-Switching. In the field of linguistics, the topic of bilingualism is a broad one. There are many
Schmidt 1 Eric Schmidt Prof. Suzanne Flynn Linguistic Study of Bilingualism December 13, 2013 A Minimalist Approach to Code-Switching In the field of linguistics, the topic of bilingualism is a broad one.
More information1/20 idea. We ll spend an extra hour on 1/21. based on assigned readings. so you ll be ready to discuss them in class
If we cancel class 1/20 idea We ll spend an extra hour on 1/21 I ll give you a brief writing problem for 1/21 based on assigned readings Jot down your thoughts based on your reading so you ll be ready
More informationContext Free Grammars. Many slides from Michael Collins
Context Free Grammars Many slides from Michael Collins Overview I An introduction to the parsing problem I Context free grammars I A brief(!) sketch of the syntax of English I Examples of ambiguous structures
More informationPseudo-Passives as Adjectival Passives
Pseudo-Passives as Adjectival Passives Kwang-sup Kim Hankuk University of Foreign Studies English Department 81 Oedae-lo Cheoin-Gu Yongin-City 449-791 Republic of Korea kwangsup@hufs.ac.kr Abstract The
More informationBasic Parsing with Context-Free Grammars. Some slides adapted from Julia Hirschberg and Dan Jurafsky 1
Basic Parsing with Context-Free Grammars Some slides adapted from Julia Hirschberg and Dan Jurafsky 1 Announcements HW 2 to go out today. Next Tuesday most important for background to assignment Sign up
More informationEnhancing Unlexicalized Parsing Performance using a Wide Coverage Lexicon, Fuzzy Tag-set Mapping, and EM-HMM-based Lexical Probabilities
Enhancing Unlexicalized Parsing Performance using a Wide Coverage Lexicon, Fuzzy Tag-set Mapping, and EM-HMM-based Lexical Probabilities Yoav Goldberg Reut Tsarfaty Meni Adler Michael Elhadad Ben Gurion
More informationParsing of part-of-speech tagged Assamese Texts
IJCSI International Journal of Computer Science Issues, Vol. 6, No. 1, 2009 ISSN (Online): 1694-0784 ISSN (Print): 1694-0814 28 Parsing of part-of-speech tagged Assamese Texts Mirzanur Rahman 1, Sufal
More informationIntroduction to HPSG. Introduction. Historical Overview. The HPSG architecture. Signature. Linguistic Objects. Descriptions.
to as a linguistic theory to to a member of the family of linguistic frameworks that are called generative grammars a grammar which is formalized to a high degree and thus makes exact predictions about
More informationAn Introduction to the Minimalist Program
An Introduction to the Minimalist Program Luke Smith University of Arizona Summer 2016 Some findings of traditional syntax Human languages vary greatly, but digging deeper, they all have distinct commonalities:
More informationProof Theory for Syntacticians
Department of Linguistics Ohio State University Syntax 2 (Linguistics 602.02) January 5, 2012 Logics for Linguistics Many different kinds of logic are directly applicable to formalizing theories in syntax
More informationSyntax Parsing 1. Grammars and parsing 2. Top-down and bottom-up parsing 3. Chart parsers 4. Bottom-up chart parsing 5. The Earley Algorithm
Syntax Parsing 1. Grammars and parsing 2. Top-down and bottom-up parsing 3. Chart parsers 4. Bottom-up chart parsing 5. The Earley Algorithm syntax: from the Greek syntaxis, meaning setting out together
More informationConstraining X-Bar: Theta Theory
Constraining X-Bar: Theta Theory Carnie, 2013, chapter 8 Kofi K. Saah 1 Learning objectives Distinguish between thematic relation and theta role. Identify the thematic relations agent, theme, goal, source,
More informationUniversal Grammar 2. Universal Grammar 1. Forms and functions 1. Universal Grammar 3. Conceptual and surface structure of complex clauses
Universal Grammar 1 evidence : 1. crosslinguistic investigation of properties of languages 2. evidence from language acquisition 3. general cognitive abilities 1. Properties can be reflected in a.) structural
More informationDear Teacher: Welcome to Reading Rods! Reading Rods offer many outstanding features! Read on to discover how to put Reading Rods to work today!
Dear Teacher: Welcome to Reading Rods! Your Sentence Building Reading Rod Set contains 156 interlocking plastic Rods printed with words representing different parts of speech and punctuation marks. Students
More informationWords come in categories
Nouns Words come in categories D: A grammatical category is a class of expressions which share a common set of grammatical properties (a.k.a. word class or part of speech). Words come in categories Open
More informationBasic Syntax. Doug Arnold We review some basic grammatical ideas and terminology, and look at some common constructions in English.
Basic Syntax Doug Arnold doug@essex.ac.uk We review some basic grammatical ideas and terminology, and look at some common constructions in English. 1 Categories 1.1 Word level (lexical and functional)
More informationJ j W w. Write. Name. Max Takes the Train. Handwriting Letters Jj, Ww: Words with j, w 321
Write J j W w Jen Will Directions Have children write a row of each letter and then write the words. Home Activity Ask your child to write each letter and tell you how to make the letter. Handwriting Letters
More informationLING 329 : MORPHOLOGY
LING 329 : MORPHOLOGY TTh 10:30 11:50 AM, Physics 121 Course Syllabus Spring 2013 Matt Pearson Office: Vollum 313 Email: pearsonm@reed.edu Phone: 7618 (off campus: 503-517-7618) Office hrs: Mon 1:30 2:30,
More informationWord Stress and Intonation: Introduction
Word Stress and Intonation: Introduction WORD STRESS One or more syllables of a polysyllabic word have greater prominence than the others. Such syllables are said to be accented or stressed. Word stress
More informationProgram Matrix - Reading English 6-12 (DOE Code 398) University of Florida. Reading
Program Requirements Competency 1: Foundations of Instruction 60 In-service Hours Teachers will develop substantive understanding of six components of reading as a process: comprehension, oral language,
More informationDefragmenting Textual Data by Leveraging the Syntactic Structure of the English Language
Defragmenting Textual Data by Leveraging the Syntactic Structure of the English Language Nathaniel Hayes Department of Computer Science Simpson College 701 N. C. St. Indianola, IA, 50125 nate.hayes@my.simpson.edu
More information11/29/2010. Statistical Parsing. Statistical Parsing. Simple PCFG for ATIS English. Syntactic Disambiguation
tatistical Parsing (Following slides are modified from Prof. Raymond Mooney s slides.) tatistical Parsing tatistical parsing uses a probabilistic model of syntax in order to assign probabilities to each
More informationLanguage Acquisition by Identical vs. Fraternal SLI Twins * Karin Stromswold & Jay I. Rifkin
Stromswold & Rifkin, Language Acquisition by MZ & DZ SLI Twins (SRCLD, 1996) 1 Language Acquisition by Identical vs. Fraternal SLI Twins * Karin Stromswold & Jay I. Rifkin Dept. of Psychology & Ctr. for
More informationInformatics 2A: Language Complexity and the. Inf2A: Chomsky Hierarchy
Informatics 2A: Language Complexity and the Chomsky Hierarchy September 28, 2010 Starter 1 Is there a finite state machine that recognises all those strings s from the alphabet {a, b} where the difference
More informationCh VI- SENTENCE PATTERNS.
Ch VI- SENTENCE PATTERNS faizrisd@gmail.com www.pakfaizal.com It is a common fact that in the making of well-formed sentences we badly need several syntactic devices used to link together words by means
More informationCompositional Semantics
Compositional Semantics CMSC 723 / LING 723 / INST 725 MARINE CARPUAT marine@cs.umd.edu Words, bag of words Sequences Trees Meaning Representing Meaning An important goal of NLP/AI: convert natural language
More informationIn Udmurt (Uralic, Russia) possessors bear genitive case except in accusative DPs where they receive ablative case.
Sören E. Worbs The University of Leipzig Modul 04-046-2015 soeren.e.worbs@gmail.de November 22, 2016 Case stacking below the surface: On the possessor case alternation in Udmurt (Assmann et al. 2014) 1
More informationGrammars & Parsing, Part 1:
Grammars & Parsing, Part 1: Rules, representations, and transformations- oh my! Sentence VP The teacher Verb gave the lecture 2015-02-12 CS 562/662: Natural Language Processing Game plan for today: Review
More informationMultiple case assignment and the English pseudo-passive *
Multiple case assignment and the English pseudo-passive * Norvin Richards Massachusetts Institute of Technology Previous literature on pseudo-passives (see van Riemsdijk 1978, Chomsky 1981, Hornstein &
More informationDeveloping a TT-MCTAG for German with an RCG-based Parser
Developing a TT-MCTAG for German with an RCG-based Parser Laura Kallmeyer, Timm Lichte, Wolfgang Maier, Yannick Parmentier, Johannes Dellert University of Tübingen, Germany CNRS-LORIA, France LREC 2008,
More informationFormulaic Language and Fluency: ESL Teaching Applications
Formulaic Language and Fluency: ESL Teaching Applications Formulaic Language Terminology Formulaic sequence One such item Formulaic language Non-count noun referring to these items Phraseology The study
More informationBasic concepts: words and morphemes. LING 481 Winter 2011
Basic concepts: words and morphemes LING 481 Winter 2011 Organization Word diagnostics different senses Morpheme types Allomorphy exercises What is a word? (Much more on difficulties identifying words
More informationLanguage Acquisition Fall 2010/Winter Lexical Categories. Afra Alishahi, Heiner Drenhaus
Language Acquisition Fall 2010/Winter 2011 Lexical Categories Afra Alishahi, Heiner Drenhaus Computational Linguistics and Phonetics Saarland University Children s Sensitivity to Lexical Categories Look,
More informationIntra-talker Variation: Audience Design Factors Affecting Lexical Selections
Tyler Perrachione LING 451-0 Proseminar in Sound Structure Prof. A. Bradlow 17 March 2006 Intra-talker Variation: Audience Design Factors Affecting Lexical Selections Abstract Although the acoustic and
More informationSAMPLE PAPER SYLLABUS
SOF INTERNATIONAL ENGLISH OLYMPIAD SAMPLE PAPER SYLLABUS 2017-18 Total Questions : 35 Section (1) Word and Structure Knowledge PATTERN & MARKING SCHEME (2) Reading (3) Spoken and Written Expression (4)
More informationcambridge occasional papers in linguistics Volume 8, Article 3: 41 55, 2015 ISSN
C O P i L cambridge occasional papers in linguistics Volume 8, Article 3: 41 55, 2015 ISSN 2050-5949 THE DYNAMICS OF STRUCTURE BUILDING IN RANGI: AT THE SYNTAX-SEMANTICS INTERFACE H a n n a h G i b s o
More informationProgram in Linguistics. Academic Year Assessment Report
Office of the Provost and Vice President for Academic Affairs Program in Linguistics Academic Year 2014-15 Assessment Report All areas shaded in gray are to be completed by the department/program. ISSION
More informationConstruction Grammar. University of Jena.
Construction Grammar Holger Diessel University of Jena holger.diessel@uni-jena.de http://www.holger-diessel.de/ Words seem to have a prototype structure; but language does not only consist of words. What
More informationPrediction of Maximal Projection for Semantic Role Labeling
Prediction of Maximal Projection for Semantic Role Labeling Weiwei Sun, Zhifang Sui Institute of Computational Linguistics Peking University Beijing, 100871, China {ws, szf}@pku.edu.cn Haifeng Wang Toshiba
More informationCitation for published version (APA): Veenstra, M. J. A. (1998). Formalizing the minimalist program Groningen: s.n.
University of Groningen Formalizing the minimalist program Veenstra, Mettina Jolanda Arnoldina IMPORTANT NOTE: You are advised to consult the publisher's version (publisher's PDF if you wish to cite from
More informationEnglish Language and Applied Linguistics. Module Descriptions 2017/18
English Language and Applied Linguistics Module Descriptions 2017/18 Level I (i.e. 2 nd Yr.) Modules Please be aware that all modules are subject to availability. If you have any questions about the modules,
More informationHow to analyze visual narratives: A tutorial in Visual Narrative Grammar
How to analyze visual narratives: A tutorial in Visual Narrative Grammar Neil Cohn 2015 neilcohn@visuallanguagelab.com www.visuallanguagelab.com Abstract Recent work has argued that narrative sequential
More informationNational Literacy and Numeracy Framework for years 3/4
1. Oracy National Literacy and Numeracy Framework for years 3/4 Speaking Listening Collaboration and discussion Year 3 - Explain information and ideas using relevant vocabulary - Organise what they say
More informationSome Principles of Automated Natural Language Information Extraction
Some Principles of Automated Natural Language Information Extraction Gregers Koch Department of Computer Science, Copenhagen University DIKU, Universitetsparken 1, DK-2100 Copenhagen, Denmark Abstract
More informationChunk Parsing for Base Noun Phrases using Regular Expressions. Let s first let the variable s0 be the sentence tree of the first sentence.
NLP Lab Session Week 8 October 15, 2014 Noun Phrase Chunking and WordNet in NLTK Getting Started In this lab session, we will work together through a series of small examples using the IDLE window and
More informationThe Four Principal Parts of Verbs. The building blocks of all verb tenses.
The Four Principal Parts of Verbs The building blocks of all verb tenses. The Four Principal Parts Every verb has four principal parts: walk is walking walked has walked Notice that the and the both have
More informationSCIENCE AND TECHNOLOGY 5: HUMAN ORGAN SYSTEMS
SCIENCE AND TECHNOLOGY 5: HUMAN ORGAN SYSTEMS NAME: This booklet is an in-class assignment; you must complete all pages during the class work periods provided. You must use full sentences for all sections
More informationWhich verb classes and why? Research questions: Semantic Basis Hypothesis (SBH) What verb classes? Why the truth of the SBH matters
Which verb classes and why? ean-pierre Koenig, Gail Mauner, Anthony Davis, and reton ienvenue University at uffalo and Streamsage, Inc. Research questions: Participant roles play a role in the syntactic
More informationDerivational and Inflectional Morphemes in Pak-Pak Language
Derivational and Inflectional Morphemes in Pak-Pak Language Agustina Situmorang and Tima Mariany Arifin ABSTRACT The objectives of this study are to find out the derivational and inflectional morphemes
More informationThe Structure of Multiple Complements to V
The Structure of Multiple Complements to Mitsuaki YONEYAMA 1. Introduction I have recently been concerned with the syntactic and semantic behavior of two s in English. In this paper, I will examine the
More informationPhenomena of gender attraction in Polish *
Chiara Finocchiaro and Anna Cielicka Phenomena of gender attraction in Polish * 1. Introduction The selection and use of grammatical features - such as gender and number - in producing sentences involve
More informationBULATS A2 WORDLIST 2
BULATS A2 WORDLIST 2 INTRODUCTION TO THE BULATS A2 WORDLIST 2 The BULATS A2 WORDLIST 21 is a list of approximately 750 words to help candidates aiming at an A2 pass in the Cambridge BULATS exam. It is
More informationWeave the Critical Literacy Strands and Build Student Confidence to Read! Part 2
Weave the Critical Literacy Strands and Build Student Confidence to Read! Part 2 Jenny W. Hamilton jenny.hamilton@voyagersopris.com VSLWebinars@voyagersopris.com www.voyagersopriswebinars.com www.facebook.com/voyagersopris
More informationCharacter Stream Parsing of Mixed-lingual Text
Character Stream Parsing of Mixed-lingual Text Harald Romsdorfer and Beat Pfister Speech Processing Group Computer Engineering and Networks Laboratory ETH Zurich {romsdorfer,pfister}@tik.ee.ethz.ch Abstract
More informationBeyond constructions:
2 nd NTU Workshop on Discourse and Grammar in Formosan Languages National Taiwan University, 1 June 2013 Beyond constructions: Takivatan Bunun predicate-argument structure, grammatical coherence, and the
More informationInleiding Taalkunde. Docent: Paola Monachesi. Blok 4, 2001/ Syntax 2. 2 Phrases and constituent structure 2. 3 A minigrammar of Italian 3
Inleiding Taalkunde Docent: Paola Monachesi Blok 4, 2001/2002 Contents 1 Syntax 2 2 Phrases and constituent structure 2 3 A minigrammar of Italian 3 4 Trees 3 5 Developing an Italian lexicon 4 6 S(emantic)-selection
More informationLanguage and Computers. Writers Aids. Introduction. Non-word error detection. Dictionaries. N-gram analysis. Isolated-word error correction
Spelling & grammar We are all familiar with spelling & grammar correctors They are used to improve document quality They are not typically used to provide feedback L245 (Based on Dickinson, Brew, & Meurers
More informationObjectives. Chapter 2: The Representation of Knowledge. Expert Systems: Principles and Programming, Fourth Edition
Chapter 2: The Representation of Knowledge Expert Systems: Principles and Programming, Fourth Edition Objectives Introduce the study of logic Learn the difference between formal logic and informal logic
More informationGuidelines for Writing an Internship Report
Guidelines for Writing an Internship Report Master of Commerce (MCOM) Program Bahauddin Zakariya University, Multan Table of Contents Table of Contents... 2 1. Introduction.... 3 2. The Required Components
More informationReading Horizons. A Look At Linguistic Readers. Nicholas P. Criscuolo APRIL Volume 10, Issue Article 5
Reading Horizons Volume 10, Issue 3 1970 Article 5 APRIL 1970 A Look At Linguistic Readers Nicholas P. Criscuolo New Haven, Connecticut Public Schools Copyright c 1970 by the authors. Reading Horizons
More informationDigital Fabrication and Aunt Sarah: Enabling Quadratic Explorations via Technology. Michael L. Connell University of Houston - Downtown
Digital Fabrication and Aunt Sarah: Enabling Quadratic Explorations via Technology Michael L. Connell University of Houston - Downtown Sergei Abramovich State University of New York at Potsdam Introduction
More informationVocabulary Usage and Intelligibility in Learner Language
Vocabulary Usage and Intelligibility in Learner Language Emi Izumi, 1 Kiyotaka Uchimoto 1 and Hitoshi Isahara 1 1. Introduction In verbal communication, the primary purpose of which is to convey and understand
More informationFlorida Reading Endorsement Alignment Matrix Competency 1
Florida Reading Endorsement Alignment Matrix Competency 1 Reading Endorsement Guiding Principle: Teachers will understand and teach reading as an ongoing strategic process resulting in students comprehending
More informationAnswer Key For The California Mathematics Standards Grade 1
Introduction: Summary of Goals GRADE ONE By the end of grade one, students learn to understand and use the concept of ones and tens in the place value number system. Students add and subtract small numbers
More informationCan Human Verb Associations help identify Salient Features for Semantic Verb Classification?
Can Human Verb Associations help identify Salient Features for Semantic Verb Classification? Sabine Schulte im Walde Institut für Maschinelle Sprachverarbeitung Universität Stuttgart Seminar für Sprachwissenschaft,
More informationCS 1103 Computer Science I Honors. Fall Instructor Muller. Syllabus
CS 1103 Computer Science I Honors Fall 2016 Instructor Muller Syllabus Welcome to CS1103. This course is an introduction to the art and science of computer programming and to some of the fundamental concepts
More informationA Computational Evaluation of Case-Assignment Algorithms
A Computational Evaluation of Case-Assignment Algorithms Miles Calabresi Advisors: Bob Frank and Jim Wood Submitted to the faculty of the Department of Linguistics in partial fulfillment of the requirements
More informationOCR for Arabic using SIFT Descriptors With Online Failure Prediction
OCR for Arabic using SIFT Descriptors With Online Failure Prediction Andrey Stolyarenko, Nachum Dershowitz The Blavatnik School of Computer Science Tel Aviv University Tel Aviv, Israel Email: stloyare@tau.ac.il,
More informationAQUA: An Ontology-Driven Question Answering System
AQUA: An Ontology-Driven Question Answering System Maria Vargas-Vera, Enrico Motta and John Domingue Knowledge Media Institute (KMI) The Open University, Walton Hall, Milton Keynes, MK7 6AA, United Kingdom.
More informationIn search of ambiguity
In search of ambiguity DONALD G. MacKAY, MASSACHUSETTS INSTITUTE OF TECHNOLOGY THOMAS G. BEVER, HARI'ARD UNIVERSITY] A study of the time required for Ss to perceive the two meanings of ambiguous sentences,
More informationTWO OLD WOMEN (An Alaskan Legend of Betrayal, Courage and Survival) By Velma Wallis
TWO OLD WOMEN (An Alaskan Legend of Betrayal, Courage and Survival) By Velma Wallis Sample Lesson meeting the Alaska English/Language Arts Standards Grade 4 By Nita Rearden Vocabulary List: Pick words
More informationUsing Web Searches on Important Words to Create Background Sets for LSI Classification
Using Web Searches on Important Words to Create Background Sets for LSI Classification Sarah Zelikovitz and Marina Kogan College of Staten Island of CUNY 2800 Victory Blvd Staten Island, NY 11314 Abstract
More informationUsing dialogue context to improve parsing performance in dialogue systems
Using dialogue context to improve parsing performance in dialogue systems Ivan Meza-Ruiz and Oliver Lemon School of Informatics, Edinburgh University 2 Buccleuch Place, Edinburgh I.V.Meza-Ruiz@sms.ed.ac.uk,
More informationOn the Formation of Phoneme Categories in DNN Acoustic Models
On the Formation of Phoneme Categories in DNN Acoustic Models Tasha Nagamine Department of Electrical Engineering, Columbia University T. Nagamine Motivation Large performance gap between humans and state-
More informationCS 101 Computer Science I Fall Instructor Muller. Syllabus
CS 101 Computer Science I Fall 2013 Instructor Muller Syllabus Welcome to CS101. This course is an introduction to the art and science of computer programming and to some of the fundamental concepts of
More informationL1 and L2 acquisition. Holger Diessel
L1 and L2 acquisition Holger Diessel Schedule Comparing L1 and L2 acquisition The role of the native language in L2 acquisition The critical period hypothesis [student presentation] Non-linguistic factors
More informationFunction Tables With The Magic Function Machine
Brief Overview: Function Tables With The Magic Function Machine s will be able to complete a by applying a one operation rule, determine a rule based on the relationship between the input and output within
More informationGrade 2: Using a Number Line to Order and Compare Numbers Place Value Horizontal Content Strand
Grade 2: Using a Number Line to Order and Compare Numbers Place Value Horizontal Content Strand Texas Essential Knowledge and Skills (TEKS): (2.1) Number, operation, and quantitative reasoning. The student
More informationDepartment of Anthropology ANTH 1027A/001: Introduction to Linguistics Dr. Olga Kharytonava Course Outline Fall 2017
Department of Anthropology ANTH 1027A/001: Introduction to Linguistics Dr. Olga Kharytonava Course Outline Fall 2017 Lectures: Tuesdays 11:30 am - 1:30 pm, SEB-1059 Tutorials: Thursdays: Section 002 2:30-3:30pm
More informationSINGLE DOCUMENT AUTOMATIC TEXT SUMMARIZATION USING TERM FREQUENCY-INVERSE DOCUMENT FREQUENCY (TF-IDF)
SINGLE DOCUMENT AUTOMATIC TEXT SUMMARIZATION USING TERM FREQUENCY-INVERSE DOCUMENT FREQUENCY (TF-IDF) Hans Christian 1 ; Mikhael Pramodana Agus 2 ; Derwin Suhartono 3 1,2,3 Computer Science Department,
More informationVisual CP Representation of Knowledge
Visual CP Representation of Knowledge Heather D. Pfeiffer and Roger T. Hartley Department of Computer Science New Mexico State University Las Cruces, NM 88003-8001, USA email: hdp@cs.nmsu.edu and rth@cs.nmsu.edu
More informationUnderlying and Surface Grammatical Relations in Greek consider
0 Underlying and Surface Grammatical Relations in Greek consider Sentences Brian D. Joseph The Ohio State University Abbreviated Title Grammatical Relations in Greek consider Sentences Brian D. Joseph
More informationAn Interactive Intelligent Language Tutor Over The Internet
An Interactive Intelligent Language Tutor Over The Internet Trude Heift Linguistics Department and Language Learning Centre Simon Fraser University, B.C. Canada V5A1S6 E-mail: heift@sfu.ca Abstract: This
More informationUnit 8 Pronoun References
English Two Unit 8 Pronoun References Objectives After the completion of this unit, you would be able to expalin what pronoun and pronoun reference are. explain different types of pronouns. understand
More informationIntension, Attitude, and Tense Annotation in a High-Fidelity Semantic Representation
Intension, Attitude, and Tense Annotation in a High-Fidelity Semantic Representation Gene Kim and Lenhart Schubert Presented by: Gene Kim April 2017 Project Overview Project: Annotate a large, topically
More informationDid they acquire? Or were they taught?
ISLL, Vitoria-Gasteiz, 13/05/2011 Did they acquire? Or were they taught? A Framework for Investigating the Effects and Effect(ivenes)s of Instruction in Second Language Acquisition Alex Housen University
More informationSpring 2016 Stony Brook University Instructor: Dr. Paul Fodor
CSE215, Foundations of Computer Science Course Information Spring 2016 Stony Brook University Instructor: Dr. Paul Fodor http://www.cs.stonybrook.edu/~cse215 Course Description Introduction to the logical
More informationGeneration of Referring Expressions: Managing Structural Ambiguities
Generation of Referring Expressions: Managing Structural Ambiguities Imtiaz Hussain Khan and Kees van Deemter and Graeme Ritchie Department of Computing Science University of Aberdeen Aberdeen AB24 3UE,
More informationChapter 3: Semi-lexical categories. nor truly functional. As Corver and van Riemsdijk rightly point out, There is more
Chapter 3: Semi-lexical categories 0 Introduction While lexical and functional categories are central to current approaches to syntax, it has been noticed that not all categories fit perfectly into this
More informationThe presence of interpretable but ungrammatical sentences corresponds to mismatches between interpretive and productive parsing.
Lecture 4: OT Syntax Sources: Kager 1999, Section 8; Legendre et al. 1998; Grimshaw 1997; Barbosa et al. 1998, Introduction; Bresnan 1998; Fanselow et al. 1999; Gibson & Broihier 1998. OT is not a theory
More informationEmotional Variation in Speech-Based Natural Language Generation
Emotional Variation in Speech-Based Natural Language Generation Michael Fleischman and Eduard Hovy USC Information Science Institute 4676 Admiralty Way Marina del Rey, CA 90292-6695 U.S.A.{fleisch, hovy}
More informationControl and Boundedness
Control and Boundedness Having eliminated rules, we would expect constructions to follow from the lexical categories (of heads and specifiers of syntactic constructions) alone. Combinatory syntax simply
More informationEAGLE: an Error-Annotated Corpus of Beginning Learner German
EAGLE: an Error-Annotated Corpus of Beginning Learner German Adriane Boyd Department of Linguistics The Ohio State University adriane@ling.osu.edu Abstract This paper describes the Error-Annotated German
More informationType Theory and Universal Grammar
Type Theory and Universal Grammar Aarne Ranta Department of Computer Science and Engineering Chalmers University of Technology and Göteborg University Abstract. The paper takes a look at the history of
More informationLet's Learn English Lesson Plan
Let's Learn English Lesson Plan Introduction: Let's Learn English lesson plans are based on the CALLA approach. See the end of each lesson for more information and resources on teaching with the CALLA
More information