Compounds and Word Trees
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Contact Morphology in Modern Greek Dialects
Contact Morphology in Modern Greek Dialects Contact Morphology in Modern Greek Dialects Edited by Angela Ralli Contact Morphology in Modern Greek Dialects Edited by Angela Ralli This book first published 2016 Cambridge Scholars Publishing Lady Stephenson Library, Newcastle upon Tyne, NE6 2PA, UK British Library Cataloguing in Publication Data A catalogue record for this book is available from the British Library Copyright © 2016 by Angela Ralli and contributors All rights for this book reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording or otherwise, without the prior permission of the copyright owner. ISBN (10): 1-4438-8691-2 ISBN (13): 978-1-4438-8691-8 CONTENTS Foreword ................................................................................................... vii Angela Ralli Headedness and/in Variation: Evidence from Italiot-Greek and Modern Greek Dialects ............................................................................................. 1 Marios Andreou The Morphological Marking of In-Definiteness: Evidence from Cappadocian and Pontic .................................................................... 21 Marianna Gkiouleka Internally- and Externally-Motivated Inter-Paradigm Levelling in Griko Verbal System ........................................................................................... 49 Nikos Koutsoukos Strategies and Patterns of Loan Verb Integration in Modern Greek Varieties .................................................................................................... -
Compound Word Formation.Pdf
Snyder, William (in press) Compound word formation. In Jeffrey Lidz, William Snyder, and Joseph Pater (eds.) The Oxford Handbook of Developmental Linguistics . Oxford: Oxford University Press. CHAPTER 6 Compound Word Formation William Snyder Languages differ in the mechanisms they provide for combining existing words into new, “compound” words. This chapter will focus on two major types of compound: synthetic -ER compounds, like English dishwasher (for either a human or a machine that washes dishes), where “-ER” stands for the crosslinguistic counterparts to agentive and instrumental -er in English; and endocentric bare-stem compounds, like English flower book , which could refer to a book about flowers, a book used to store pressed flowers, or many other types of book, as long there is a salient connection to flowers. With both types of compounding we find systematic cross- linguistic variation, and a literature that addresses some of the resulting questions for child language acquisition. In addition to these two varieties of compounding, a few others will be mentioned that look like promising areas for coordinated research on cross-linguistic variation and language acquisition. 6.1 Compounding—A Selective Review 6.1.1 Terminology The first step will be defining some key terms. An unfortunate aspect of the linguistic literature on morphology is a remarkable lack of consistency in what the “basic” terms are taken to mean. Strictly speaking one should begin with the very term “word,” but as Spencer (1991: 453) puts it, “One of the key unresolved questions in morphology is, ‘What is a word?’.” Setting this grander question to one side, a word will be called a “compound” if it is composed of two or more other words, and has approximately the same privileges of occurrence within a sentence as do other word-level members of its syntactic category (N, V, A, or P). -
Hunspell – the Free Spelling Checker
Hunspell – The free spelling checker About Hunspell Hunspell is a spell checker and morphological analyzer library and program designed for languages with rich morphology and complex word compounding or character encoding. Hunspell interfaces: Ispell-like terminal interface using Curses library, Ispell pipe interface, OpenOffice.org UNO module. Main features of Hunspell spell checker and morphological analyzer: - Unicode support (affix rules work only with the first 65535 Unicode characters) - Morphological analysis (in custom item and arrangement style) and stemming - Max. 65535 affix classes and twofold affix stripping (for agglutinative languages, like Azeri, Basque, Estonian, Finnish, Hungarian, Turkish, etc.) - Support complex compoundings (for example, Hungarian and German) - Support language specific features (for example, special casing of Azeri and Turkish dotted i, or German sharp s) - Handle conditional affixes, circumfixes, fogemorphemes, forbidden words, pseudoroots and homonyms. - Free software (LGPL, GPL, MPL tri-license) Usage The src/tools dictionary contains ten executables after compiling (or some of them are in the src/win_api): affixcompress: dictionary generation from large (millions of words) vocabularies analyze: example of spell checking, stemming and morphological analysis chmorph: example of automatic morphological generation and conversion example: example of spell checking and suggestion hunspell: main program for spell checking and others (see manual) hunzip: decompressor of hzip format hzip: compressor of -
Antisymmetry and the Lefthand in Morphology*
CatWPL 7 071-087 13/6/00 12:26 Página 71 CatWPL 7, 1999 71-87 Antisymmetry And The Lefthand In Morphology* Frank Drijkoningen Utrecht Institute of Linguistics-OTS. Department of Foreign Languages Kromme Nieuwegracht 29. 3512 HD Utrecht. The Netherlands [email protected] Received: December 13th 1998 Accepted: March 17th 1999 Abstract As Kayne (1994) has shown, the theory of antisymmetry of syntax also provides an explanation of a structural property of morphological complexes, the Righthand Head Rule. In this paper we show that an antisymmetry approach to the Righthand Head Rule eventually is to be preferred on empirical grounds, because it describes and explains the properties of a set of hitherto puzz- ling morphological processes —known as discontinuous affixation, circumfixation or parasyn- thesis. In considering these and a number of more standard morphological structures, we argue that one difference bearing on the proper balance between morphology and syntax should be re-ins- talled (re- with respect to Kayne), a difference between the antisymmetry of the syntax of mor- phology and the antisymmetry of the syntax of syntax proper. Key words: antisymmetry, Righthand Head Rule, circumfixation, parasynthesis, prefixation, category-changing prefixation, discontinuities in morphology. Resum. L’antisimetria i el costat esquerre en morfologia Com Kayne (1994) mostra, la teoria de l’antisimetria en la sintaxi també ens dóna una explicació d’una propietat estructural de complexos morfològics, la Regla del Nucli a la Dreta. En aquest article mostrem que un tractament antisimètric de la Regla del Nucli a la Dreta es prefereix even- tualment en dominis empírics, perquè descriu i explica les propietats d’una sèrie de processos fins ara morfològics —coneguts com afixació discontínua, circumfixació o parasíntesi. -
Building a Treebank for French
Building a treebank for French £ £¥ Anne Abeillé£ , Lionel Clément , Alexandra Kinyon ¥ £ TALaNa, Université Paris 7 University of Pennsylvania 75251 Paris cedex 05 Philadelphia FRANCE USA abeille, clement, [email protected] Abstract Very few gold standard annotated corpora are currently available for French. We present an ongoing project to build a reference treebank for French starting with a tagged newspaper corpus of 1 Million words (Abeillé et al., 1998), (Abeillé and Clément, 1999). Similarly to the Penn TreeBank (Marcus et al., 1993), we distinguish an automatic parsing phase followed by a second phase of systematic manual validation and correction. Similarly to the Prague treebank (Hajicova et al., 1998), we rely on several types of morphosyntactic and syntactic annotations for which we define extensive guidelines. Our goal is to provide a theory neutral, surface oriented, error free treebank for French. Similarly to the Negra project (Brants et al., 1999), we annotate both constituents and functional relations. 1. The tagged corpus pronoun (= him ) or a weak clitic pronoun (= to him or to As reported in (Abeillé and Clément, 1999), we present her), plus can either be a negative adverb (= not any more) the general methodology, the automatic tagging phase, the or a simple adverb (= more). Inflectional morphology also human validation phase and the final state of the tagged has to be annotated since morphological endings are impor- corpus. tant for gathering constituants (based on agreement marks) and also because lots of forms in French are ambiguous 1.1. Methodology with respect to mode, person, number or gender. For exam- 1.1.1. -
The Linking Element and Swedish Complex Nominal Compounds
THE LINKING ELEMENT AND SWEDISH COMPLEX NOMINAL COMPOUNDS Jeffrey Kline Gilbert A thesis submitted to the faculty of the University of North Carolina at Chapel Hill in partial fulfillment of the requirements for the degree of Master of Arts in the Department of Linguistics. Chapel Hill 2012 Approved by: Randall Hendrick Katya Pertsova J. Michael Terry © 2012 Jeffrey Kline Gilbert ALL RIGHTS RESERVED ii ABSTRACT JEFFREY KLINE GILBERT: The Linking Element and Swedish Complex Nominal Compounds (Under the direction of Randall Hendrick and Katya Pertsova) This thesis investigates the linking element that sometimes appears in Swedish compounds made up of three noun stems, also called complex nominal compounds. I present a comprehensive analysis of Swedish compounding and the nature of the linking element, and then argue that the appearance of the linking element, typically –s–, in complex nominal compounds is predictable. This thesis proposes that the linking element is a marker of a particular syntactic structure, and thereby a particular linear ordering of the nouns inside a complex compound. Two previous syntactic proposals (Josefsson, 1998; Mukai, 2008) for the linking element and Swedish complex compounds are discussed, and I argue that these proposals are partly problematic due to their application of Kayne’s (1994) antisymmetry theory of syntax. I discuss Kayne’s antisymmetry theory, with its restrictions to asymmetric c-command, and offer a solution to the problem found in the previous proposals. I contend that antisymmetry theory can account for both the subword structure and linearization of Swedish complex nominal compounds with and without the linking element. iii To my parents for their unconditional support of all my interests, which helped develop my love of language. -
The Stress and Structure of Modified Noun Phrases in English MARK LIBERMAN and RICHARD SPROAT
6 The Stress and Structure of Modified Noun Phrases in English MARK LIBERMAN AND RICHARD SPROAT 1 Introduction Our topic is the stress pattern of English noun phrases in which the head noun is preceded by a sequence of modifiers. 1 We assume a context of use that is rhetorically stress-neutral; the phenomena of FOCUS, CONTRAST and ANAPHORA-henceforth FCA-are taken to be perturbations of the patterns that we discuss. We attempt to establish the basic regularities that shape the complex data in this area, against the background of a broad (and thus complex) description. Our purpose is to establish an adequate set of descriptive categories, able to support a formal model of the syntax, semantics and prosody of complex nominals. We would like such a model to be adequate for parsing and assigning stress to modified noun phrases in unconstrained English text. We start with a careful description of the phenomena, followed by a more formal account of the proposed syntactic analysis, and a sketch of the implications for parsing and stress-assignment algorithms. Many syntacticians (e.g., Jackendoff 1977) have noted the existence of at least four distinct prenominal positions, arranged in a right-branching structure: (1) 4 3 2 1 0 the three exotic chess boards John's many large book bags those few Chinese store owners Position 4 is stereotypically occupied by articles, demonstratives, and pos sessive phrases; position 3 by certain quantifiers and numerals; position 1The authors would like to thank an anonymous reviewer for useful comments, and Julia Hirschberg and Mats Rooth for some discussion. -
A Poor Man's Approach to CLEF
A poor man's approach to CLEF Arjen P. de Vries1;2 1 CWI, Amsterdam, The Netherlands 2 University of Twente, Enschede, The Netherlands [email protected] October 16, 2000 1 Goals The Mirror DBMS [dV99] aims specifically at supporting both data management and content man- agement in a single system. Its design separates the retrieval model from the specific techniques used for implementation, thus allowing more flexibility to experiment with a variety of retrieval models. Its design based on database techniques intends to support this flexibility without caus- ing a major penalty on the efficiency and scalability of the system. The support for information retrieval in our system is presented in detail in [dVH99], [dV98], and [dVW99]. The primary goal of our participation in CLEF is to acquire experience with supporting Dutch users. Also, we want to investigate whether we can obtain a reasonable performance without requiring expensive (but high quality) resources. We do not expect to obtain impressive results with our system, but hope to obtain a baseline from which we can develop our system further. We decided to submit runs for all four target languages, but our main interest is in the bilingual Dutch to English runs. 2 Pre-processing We have used only ‘off-the-shelf' tools for stopping, stemming, compound-splitting (only for Dutch) and translation. All our tools are available for free, without usage restrictions for research purposes. Stopping and stemming Moderately sized stoplists, of comparable coverage, were made available by University of Twente (see also Table 1). We used the stemmers provided by Muscat1, an open source search engine. -
Robust Prediction of Punctuation and Truecasing for Medical ASR
Robust Prediction of Punctuation and Truecasing for Medical ASR Monica Sunkara Srikanth Ronanki Kalpit Dixit Sravan Bodapati Katrin Kirchhoff Amazon AWS AI, USA fsunkaral, [email protected] Abstract the accuracy of subsequent natural language under- standing algorithms (Peitz et al., 2011a; Makhoul Automatic speech recognition (ASR) systems et al., 2005) to identify information such as pa- in the medical domain that focus on transcrib- tient diagnosis, treatments, dosages, symptoms and ing clinical dictations and doctor-patient con- signs. Typically, clinicians explicitly dictate the versations often pose many challenges due to the complexity of the domain. ASR output punctuation commands like “period”, “add comma” typically undergoes automatic punctuation to etc., and a postprocessing component takes care enable users to speak naturally, without hav- of punctuation restoration. This process is usu- ing to vocalise awkward and explicit punc- ally error-prone as the clinicians may struggle with tuation commands, such as “period”, “add appropriate punctuation insertion during dictation. comma” or “exclamation point”, while true- Moreover, doctor-patient conversations lack ex- casing enhances user readability and improves plicit vocalization of punctuation marks motivating the performance of downstream NLP tasks. This paper proposes a conditional joint mod- the need for automatic prediction of punctuation eling framework for prediction of punctuation and truecasing. In this work, we aim to solve the and truecasing using pretrained masked lan- problem of automatic punctuation and truecasing guage models such as BERT, BioBERT and restoration to medical ASR system text outputs. RoBERTa. We also present techniques for Most recent approaches to punctuation and true- domain and task specific adaptation by fine- casing restoration problem rely on deep learning tuning masked language models with medical (Nguyen et al., 2019a; Salloum et al., 2017). -
Lexical Analysis
Lexical Analysis Lecture 3 Instructor: Fredrik Kjolstad Slide design by Prof. Alex Aiken, with modifications 1 Outline • Informal sketch of lexical analysis – Identifies tokens in input string • Issues in lexical analysis – Lookahead – Ambiguities • Specifying lexers (aka. scanners) – By regular expressions (aka. regex) – Examples of regular expressions 2 Lexical Analysis • What do we want to do? Example: if (i == j) Z = 0; else Z = 1; • The input is just a string of characters: \tif (i == j)\n\t\tz = 0;\n\telse\n\t\tz = 1; • Goal: Partition input string into substrings – Where the substrings are called tokens 3 What’s a Token? • A syntactic category – In English: noun, verb, adjective, … – In a programming language: Identifier, Integer, Keyword, Whitespace, … 4 Tokens • A token class corresponds to a set of strings Infinite set • Examples i var1 ports – Identifier: strings of letters or foo Person digits, starting with a letter … – Integer: a non-empty string of digits – Keyword: “else” or “if” or “begin” or … – Whitespace: a non-empty sequence of blanks, newlines, and tabs 5 What are Tokens For? • Classify program substrings according to role • Lexical analysis produces a stream of tokens • … which is input to the parser • Parser relies on token distinctions – An identifier is treated differently than a keyword 6 Designing a Lexical Analyzer: Step 1 • Define a finite set of tokens – Tokens describe all items of interest • Identifiers, integers, keywords – Choice of tokens depends on • language • design of parser 7 Example • Recall \tif -
The Place of Morphology in Grammar: Historical Overview
Universität Leipzig, Institut für Linguistik SS 13 The place of morphology in grammar: Historical overview 1 The Standard Theory • The structure of the aspects model, cf. Chomsky (1965) Phrase structure rules Lexicon Deep Structure Semantic interpretation Transformational rules Surface structure Phonology • Lexical insertion is part of the transformational rules (in fact the first one): items from the lexicon are inserted into appropriate terminal nodes (if they match the categorial specifi- cation of the node; further restrictions are encoded in the lexical entries of the words, e.g. subcateogrization) • processes like agreement and concord are also transformational rules: features are copied from the controller (e.g. DP) to the target (e.g. verb) • agreement morphemes realize the syntactic features in phonology (= late insertion) • the lexicon contains only simple words, but no compounds or derived words. All word for- mation is therefore handled in syntax: e.g. nominalizations are derived from underlying finite verbal sentences, the nominalizing morphology is thus a by-product of a transforma- tion (1) a. TomgavearosetoHarriet. → b. Tom’s gift (of a rose) (to Harriet) c. Tom’sgivingof a rose (to Harriet) • evennominalcompoundslike manservant were derived from full sentences (cf. Lees (1960)): (2) a. Archieneeds[aservant[theservantisaman]] → b. Archie needs [a servant [who is a man]] → c. Archie needs [a servant [a man]] → d. Archie needs [a servant man] → e. Archie needs a manservant. Morphology was divided up between phonology (inflectional morphology) and syntax (deriva- → tional morphology) 1 Salzmann: Seminar Morphologie I: Wo ist die Morphologie? 2 Remarks on nominalizations: the weak lexicalist hypothesis • Chomsky (1970): the need for a separate theory of derivational morphology • transformations should capture regular correspondences between linguistic form, idiosyn- cratic information belongs in the lexicon • a transformation should capture productive and regular relationships between sentences, e.g. -
Name Description
hunspell(4) hunspell(4) NAME hunspell − format of Hunspell dictionaries and affix files DESCRIPTION Hunspell(1) requires twofiles to define the language that it is spell checking. The first file is a dictionary containing words for the language, and the second is an "affix" file that defines the meaning of special flags in the dictionary. Adictionary file (*.dic) contains a list of words, one per line. The first line of the dictionaries (except per- sonal dictionaries) contains the approximate word count (for optimal hash memory size). Each word may optionally be followed by a slash ("/") and one or more flags, which represents affixes or special attributes. Dictionary words can contain also slashes with the "" syntax. Default flag format is a single (usually alpha- betic) character.After the dictionary words there are also optional fields separated by tabulators or spaces (spaces only work as morphological field separators, if theyare followed by morphological field ids, see also Optional data fields). Personal dictionaries are simple word lists. Asterisk at the first character position signs prohibition. Asec- ond word separated by a slash sets the affixation. foo Foo/Simpson *bar In this example, "foo" and "Foo" are personal words, plus Foo will be recognized with affixes of Simpson (Foo’setc.) and bar is a forbidden word. An affix file (*.aff) may contain a lot of optional attributes. For example, SET is used for setting the char- acter encodings of affixes and dictionary files. TRY sets the change characters for suggestions. REP sets a replacement table for multiple character corrections in suggestion mode. PFX and SFX defines prefix and suffix classes named with affix flags.