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The Empirical Base of Linguistics: Grammaticality Judgments and Linguistic Methodology
UCLA UCLA Previously Published Works Title The empirical base of linguistics: Grammaticality judgments and linguistic methodology Permalink https://escholarship.org/uc/item/05b2s4wg ISBN 978-3946234043 Author Schütze, Carson T Publication Date 2016-02-01 DOI 10.17169/langsci.b89.101 Data Availability The data associated with this publication are managed by: Language Science Press, Berlin Peer reviewed eScholarship.org Powered by the California Digital Library University of California The empirical base of linguistics Grammaticality judgments and linguistic methodology Carson T. Schütze language Classics in Linguistics 2 science press Classics in Linguistics Chief Editors: Martin Haspelmath, Stefan Müller In this series: 1. Lehmann, Christian. Thoughts on grammaticalization 2. Schütze, Carson T. The empirical base of linguistics: Grammaticality judgments and linguistic methodology 3. Bickerton, Derek. Roots of language ISSN: 2366-374X The empirical base of linguistics Grammaticality judgments and linguistic methodology Carson T. Schütze language science press Carson T. Schütze. 2019. The empirical base of linguistics: Grammaticality judgments and linguistic methodology (Classics in Linguistics 2). Berlin: Language Science Press. This title can be downloaded at: http://langsci-press.org/catalog/book/89 © 2019, Carson T. Schütze Published under the Creative Commons Attribution 4.0 Licence (CC BY 4.0): http://creativecommons.org/licenses/by/4.0/ ISBN: 978-3-946234-02-9 (Digital) 978-3-946234-03-6 (Hardcover) 978-3-946234-04-3 (Softcover) 978-1-523743-32-2 -
CAS LX 522 Syntax I
It is likely… CAS LX 522 IP This satisfies the EPP in Syntax I both clauses. The main DPj I′ clause has Mary in SpecIP. Mary The embedded clause has Vi+I VP is the trace in SpecIP. V AP Week 14b. PRO and control ti This specific instance of A- A IP movement, where we move a likely subject from an embedded DP I′ clause to a higher clause is tj generally called subject raising. I VP to leave Reluctance to leave Reluctance to leave Now, consider: Reluctant has two θ-roles to assign. Mary is reluctant to leave. One to the one feeling the reluctance (Experiencer) One to the proposition about which the reluctance holds (Proposition) This looks very similar to Mary is likely to leave. Can we draw the same kind of tree for it? Leave has one θ-role to assign. To the one doing the leaving (Agent). How many θ-roles does reluctant assign? In Mary is reluctant to leave, what θ-role does Mary get? IP Reluctance to leave Reluctance… DPi I′ Mary Vj+I VP In Mary is reluctant to leave, is V AP Mary is doing the leaving, gets Agent t Mary is reluctant to leave. j t from leave. i A′ Reluctant assigns its θ- Mary is showing the reluctance, gets θ roles within AP as A θ IP Experiencer from reluctant. required, Mary moves reluctant up to SpecIP in the main I′ clause by Spellout. ? And we have a problem: I vP But what gets the θ-role to Mary appears to be getting two θ-roles, from leave, and what v′ in violation of the θ-criterion. -
Scaffolding Learning of Language Structures with Visual‐Syntactic Text
UC Irvine UC Irvine Previously Published Works Title Scaffolding learning of language structures with visual-syntactic text formatting Permalink https://escholarship.org/uc/item/6235t25b Journal British Journal of Educational Technology, 50(4) ISSN 0007-1013 Authors Park, Y Xu, Y Collins, P et al. Publication Date 2018 DOI 10.1111/bjet.12689 Peer reviewed eScholarship.org Powered by the California Digital Library University of California British Journal of Educational Technology Vol 0 No 0 2018 1–17 doi:10.1111/bjet.12689 Scaffolding learning of language structures with visual-syntactic text formatting Youngmin Park, Ying Xu , Penelope Collins, George Farkas and Mark Warschauer Youngmin Park is a Lecturer at Pusan National University, Korea. She received her Ph.D. degree from the University of California, Irvine, specializing in Language, Literacy and Technology. Ying Xu is a Ph.D. student at the University of California, Irvine, with a specialization in specializing in Language, Literacy and Technology. Penelope Collins is an associate professor at the University of California, Irvine. Her research examines the development of language and literacy skills for children from linguistically diverse backgrounds. George Farkas is a professor at the University of California, Irvine. He has employed a range of statistical approaches and databases to examine the causes and consequences of reading achievement gap across varying age groups and educational settings. Mark Warschauer is a professor at the University of California, Irvine. He works on a range of research projects related to digital media in education. Address for correspondence: Ying Xu, University of California Irvine, 3200 Education Bldg, Irvine, CA 92697, USA. -
Greek and Latin Roots, Prefixes, and Suffixes
GREEK AND LATIN ROOTS, PREFIXES, AND SUFFIXES This is a resource pack that I put together for myself to teach roots, prefixes, and suffixes as part of a separate vocabulary class (short weekly sessions). It is a combination of helpful resources that I have found on the web as well as some tips of my own (such as the simple lesson plan). Lesson Plan Ideas ........................................................................................................... 3 Simple Lesson Plan for Word Study: ........................................................................... 3 Lesson Plan Idea 2 ...................................................................................................... 3 Background Information .................................................................................................. 5 Why Study Word Roots, Prefixes, and Suffixes? ......................................................... 6 Latin and Greek Word Elements .............................................................................. 6 Latin Roots, Prefixes, and Suffixes .......................................................................... 6 Root, Prefix, and Suffix Lists ........................................................................................... 8 List 1: MEGA root list ................................................................................................... 9 List 2: Roots, Prefixes, and Suffixes .......................................................................... 32 List 3: Prefix List ...................................................................................................... -
Language Structure: Phrases “Productivity” a Property of Language • Definition – Language Is an Open System
Language Structure: Phrases “Productivity” a property of Language • Definition – Language is an open system. We can produce potentially an infinite number of different messages by combining elements differently. • Example – Words into phrases. An Example of Productivity • Human language is a communication system that bears some similarities to other animal communication systems, but is also characterized by certain unique features. (24 words) • I think that human language is a communication system that bears some similarities to other animal communication systems, but is also characterized by certain unique features, which are fascinating in and of themselves. (33 words) • I have always thought, and I have spent many years verifying, that human language is a communication system that bears some similarities to other animal communication systems, but is also characterized by certain unique features, which are fascinating in and of themselves. (42 words) • Although mainstream some people might not agree with me, I have always thought… Creating Infinite Messages • Discrete elements – Words, Phrases • Selection – Ease, Meaning, Identity • Combination – Rules of organization Models of Word reCombination 1. Word chains (Markov model) Phrase-level meaning is derived from understanding each word as it is presented in the context of immediately adjacent words. 2. Hierarchical model There are long-distant dependencies between words in a phrase, and these inform the meaning of the entire phrase. Markov Model Rule: Select and concatenate (according to meaning and what types of words should occur next to each other). bites bites bites Man over over over jumps jumps jumps house house house Markov Model • Assumption −Only adjacent words are meaningfully (and lawfully) related. -
Chapter 30 HPSG and Lexical Functional Grammar Stephen Wechsler the University of Texas Ash Asudeh University of Rochester & Carleton University
Chapter 30 HPSG and Lexical Functional Grammar Stephen Wechsler The University of Texas Ash Asudeh University of Rochester & Carleton University This chapter compares two closely related grammatical frameworks, Head-Driven Phrase Structure Grammar (HPSG) and Lexical Functional Grammar (LFG). Among the similarities: both frameworks draw a lexicalist distinction between morphology and syntax, both associate certain words with lexical argument structures, both employ semantic theories based on underspecification, and both are fully explicit and computationally implemented. The two frameworks make available many of the same representational resources. Typical differences between the analyses proffered under the two frameworks can often be traced to concomitant differ- ences of emphasis in the design orientations of their founding formulations: while HPSG’s origins emphasized the formal representation of syntactic locality condi- tions, those of LFG emphasized the formal representation of functional equivalence classes across grammatical structures. Our comparison of the two theories includes a point by point syntactic comparison, after which we turn to an exposition ofGlue Semantics, a theory of semantic composition closely associated with LFG. 1 Introduction Head-Driven Phrase Structure Grammar is similar in many respects to its sister framework, Lexical Functional Grammar or LFG (Bresnan et al. 2016; Dalrymple et al. 2019). Both HPSG and LFG are lexicalist frameworks in the sense that they distinguish between the morphological system that creates words and the syn- tax proper that combines those fully inflected words into phrases and sentences. Stephen Wechsler & Ash Asudeh. 2021. HPSG and Lexical Functional Gram- mar. In Stefan Müller, Anne Abeillé, Robert D. Borsley & Jean- Pierre Koenig (eds.), Head-Driven Phrase Structure Grammar: The handbook. -
Chapter 7 Linguistics As a Science of Structure Ryan M
Chapter 7 Linguistics as a science of structure Ryan M. Nefdt University of the Western Cape Generative linguistics has rapidly changed during the course of a relatively short period. This has caused many to question its scientific status as a realist scientific theory (Stokhof & van Lambalgen 2011; Lappin et al. 2000). In this chapter, I argue against this conclusion. Specifically, I claim that the mathematical foundations of the science present a different story below the surface. I agree with critics that due to the major shifts in theory over the past 80 years, linguistics is indeed opened up to the problem of pessimistic meta-induction or radical theory change. However, I further argue that a structural realist approach (Ladyman 1998; French 2006) can save the field from this problem and at the same time capture its structural nature. I discuss particular historical instances of theory change in generative grammar as evidence for this interpretation and finally attempt to extend it beyond the gener- ative tradition to encompass previous frameworks in linguistics. 1 Introduction The generativist revolution in linguistics started in the mid-1950s, inspired in large part by insights from mathematical logic and in particular proof theory. Since then, generative linguistics has become a dominant paradigm, with many connections to both the formal and natural sciences. At the centre of the newly established discipline was the syntactic or formal engine, the structures of which were revealed through modelling grammatical form. The generativist paradigm in linguistics initially relied heavily upon the proof-theoretic techniques intro- duced by Emil Post and other formal logicians to model the form language takes (Tomalin 2006; Pullum 2011; 2013).1 Yet despite these aforementioned formal be- ginnings, the generative theory of linguistics has changed its commitments quite 1Here my focus will largely be on the formal history of generative syntax but I will make some comments on other aspects of linguistics along the way. -
Lexical-Functional Grammar and Order-Free Semantic Composition
COLING 82, J. Horeck~(eel) North-HoOandPubllshi~ Company O A~deml~ 1982 Lexical-Functional Grammar and Order-Free Semantic Composition Per-Kristian Halvorsen Norwegian Research Council's Computing Center for the Humanities and Center for Cognitive Science, MIT This paper summarizes the extension of the theory of lexical-functional grammar to include a formal, model-theoretic, semantics. The algorithmic specification of the semantic interpretation procedures is order-free which distinguishes the system from other theories providing model-theoretic interpretation for natural language. Attention is focused on the computational advantages of a semantic interpretation system that takes as its input functional structures as opposed to syntactic surface-structures. A pressing problem for computational linguistics is the development of linguistic theories which are supported by strong independent linguistic argumentation, and which can, simultaneously, serve as a basis for efficient implementations in language processing systems. Linguistic theories with these properties make it possible for computational implementations to build directly on the work of linguists both in the area of grammar-writing, and in the area of theory development (cf. universal conditions on anaphoric binding, filler-gap dependencies etc.). Lexical-functional grammar (LFG) is a linguistic theory which has been developed with equal attention being paid to theoretical linguistic and computational processing considerations (Kaplan & Bresnan 1981). The linguistic theory has ample and broad motivation (vide the papers in Bresnan 1982), and it is transparently implementable as a syntactic parsing system (Kaplan & Halvorsen forthcoming). LFG takes grammatical relations to be of primary importance (as opposed to the transformational theory where grammatical functions play a subsidiary role). -
Introduction to Transformational Grammar
Introduction to Transformational Grammar Kyle Johnson University of Massachusetts at Amherst Fall 2004 Contents Preface iii 1 The Subject Matter 1 1.1 Linguisticsaslearningtheory . 1 1.2 The evidential basis of syntactic theory . 7 2 Phrase Structure 15 2.1 SubstitutionClasses............................. 16 2.2 Phrases .................................... 20 2.3 Xphrases................................... 29 2.4 ArgumentsandModifiers ......................... 41 3 Positioning Arguments 57 3.1 Expletives and the Extended Projection Principle . ..... 58 3.2 Case Theory and ordering complements . 61 3.3 Small Clauses and the Derived Subjects Hypothesis . ... 68 3.4 PROandControlInfinitives . .. .. .. .. .. .. 79 3.5 Evidence for Argument Movement from Quantifier Float . 83 3.6 Towards a typology of infinitive types . 92 3.7 Constraints on Argument Movement and the typology of verbs . 97 4 Verb Movement 105 4.1 The “Classic” Verb Movement account . 106 4.2 Head Movement’s role in “Verb Second” word order . 115 4.3 The Pollockian revolution: exploded IPs . 123 4.4 Features and covert movement . 136 5 Determiner Phrases and Noun Movement 149 5.1 TheDPHypothesis ............................. 151 5.2 NounMovement............................... 155 Contents 6 Complement Structure 179 6.1 Nouns and the θ-rolestheyassign .................... 180 6.2 Double Object constructions and Larsonian shells . 195 6.3 Complement structure and Object Shift . 207 7 Subjects and Complex Predicates 229 7.1 Gettingintotherightposition . 229 7.2 SubjectArguments ............................. 233 7.2.1 ArgumentStructure ........................ 235 7.2.2 The syntactic benefits of ν .................... 245 7.3 The relative positions of µP and νP: Evidence from ‘again’ . 246 7.4 The Minimal Link Condition and Romance causatives . 254 7.5 RemainingProblems ............................ 271 7.5.1 The main verb in English is too high . -
Syntactic Structures and Their Symbiotic Guests. Notes on Analepsis from the Perspective of On- Line Syntax*
Pragmatics 24:3.533-560 (2014) International Pragmatics Association DOI: 10.1075/prag.24.3.05aue SYNTACTIC STRUCTURES AND THEIR SYMBIOTIC GUESTS. NOTES ON ANALEPSIS FROM THE PERSPECTIVE OF ON- LINE SYNTAX* Peter Auer Abstract The empirical focus of this paper is on utterances that re-use syntactic structures from a preceding syntactic unit. Next utterances of this type are usually treated as (coordination) ellipsis. It is argued that from an on-line perspective on spoken syntax, they are better described as structural latency: A grammatical structure already established remains available and can therefore be made use of with one or more of its slots being filled by new material. A variety of cases of this particular kind of conversational symbiosis are discussed. It is argued that they should receive a common treatment. A number of features of the general host/guest relationship are discussed. Keywords: Analepsis; On-line syntax; Structural latency. "Ein Blick in die erste beste Erzählung und eine einfache Ueberlegung muss beweisen, dass jede frühere Aeusserung des Erzählenden die Exposition aller nachfolgenden Prädikate bildet." (Wegener 1885: 46)1 1. Introduction The notion of 'ellipsis' is often regarded with some skepticism by Interactional Linguists - the orientation to 'full' sentences is all too obvious (cf. Selting 1997), and the idea that speakers produce complete sentences just in order to delete some parts of them afterwards surely fails to account for the processual dynamics of sentence production and understanding (cf. Kindt 1985) in time. On the other hand, there can be little doubt that speakers often produce utterance units that could not be understood * I wish to thank Elizabeth Couper-Kuhlen and Susanne Günthner for their helpful comments on a previous version of this paper. -
LING83600: Context-Free Grammars
LING83600: Context-free grammars Kyle Gorman 1 Introduction Context-free grammars (or CFGs) are a formalization of what linguists call “phrase structure gram- mars”. The formalism is originally due to Chomsky (1956) though it has been independently discovered several times. The insight underlying CFGs is the notion of constituency. Most linguists believe that human languages cannot be even weakly described by CFGs (e.g., Schieber 1985). And in formal work, context-free grammars have long been superseded by “trans- formational” approaches which introduce movement operations (in some camps), or by “general- ized phrase structure” approaches which add more complex phrase-building operations (in other camps). However, unlike more expressive formalisms, there exist relatively-efficient cubic-time parsing algorithms for CFGs. Nearly all programming languages are described by—and parsed using—a CFG,1 and CFG grammars of human languages are widely used as a model of syntactic structure in natural language processing and understanding tasks. Bibliographic note This handout covers the formal definition of context-free grammars; the Cocke-Younger-Kasami (CYK) parsing algorithm will be covered in a separate assignment. The definitions here are loosely based on chapter 11 of Jurafsky & Martin, who in turn draw from Hopcroft and Ullman 1979. 2 Definitions 2.1 Context-free grammars A context-free grammar G is a four-tuple N; Σ; R; S such that: • N is a set of non-terminal symbols, corresponding to phrase markers in a syntactic tree. • Σ is a set of terminal symbols, corresponding to words (i.e., X0s) in a syntactic tree. • R is a set of production rules. -
Generative Linguistics and Neural Networks at 60: Foundation, Friction, and Fusion*
Generative linguistics and neural networks at 60: foundation, friction, and fusion* Joe Pater, University of Massachusetts Amherst October 3, 2018. Abstract. The birthdate of both generative linguistics and neural networks can be taken as 1957, the year of the publication of foundational work by both Noam Chomsky and Frank Rosenblatt. This paper traces the development of these two approaches to cognitive science, from their largely autonomous early development in their first thirty years, through their collision in the 1980s around the past tense debate (Rumelhart and McClelland 1986, Pinker and Prince 1988), and their integration in much subsequent work up to the present. Although this integration has produced a considerable body of results, the continued general gulf between these two lines of research is likely impeding progress in both: on learning in generative linguistics, and on the representation of language in neural modeling. The paper concludes with a brief argument that generative linguistics is unlikely to fulfill its promise of accounting for language learning if it continues to maintain its distance from neural and statistical approaches to learning. 1. Introduction At the beginning of 1957, two men nearing their 29th birthdays published work that laid the foundation for two radically different approaches to cognitive science. One of these men, Noam Chomsky, continues to contribute sixty years later to the field that he founded, generative linguistics. The book he published in 1957, Syntactic Structures, has been ranked as the most influential work in cognitive science from the 20th century.1 The other one, Frank Rosenblatt, had by the late 1960s largely moved on from his research on perceptrons – now called neural networks – and died tragically young in 1971.