DOCSLIB.ORG

On the Idiosyncrasies of the Mandarin Chinese Classifier System

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
On the Idiosyncrasies of the Mandarin Chinese Classifier System On the Idiosyncrasies of the Mandarin Chinese Classifier System Shijia Liu@ and Hongyuan Mei@ and Adina WilliamsP and Ryan Cotterell@, H @Department of Computer Science, Johns Hopkins University PFacebook Artificial Intelligence Research HDepartment of Computer Science and Technology, University of Cambridge fsliu126,[email protected], [email protected], [email protected] Abstract Classifier P¯ıny¯ın Semantic Class While idiosyncrasies of the Chinese classi- * ge` objects, general-purpose fier system have been a richly studied topic 件 jian` matters among linguists (Adams and Conklin, 1973; 4 tou´ domesticated animals Erbaugh, 1986; Lakoff, 1986), not much work ê zh¯ı general animals has been done to quantify them with statisti- zhang¯ cal methods. In this paper, we introduce an flat objects information-theoretic approach to measuring a tiao´ long, narrow objects idiosyncrasy; we examine how much the un- y xiang` items, projects certainty in Mandarin Chinese classifiers can S dao` orders, roads, projections be reduced by knowing semantic information 9 pˇı horses, cloth about the nouns that the classifiers modify. 顿 dun` meals Using the empirical distribution of classifiers from the parsed Chinese Gigaword corpus Table 1: Examples of Mandarin classifiers. Classi- (Graff et al., 2005), we compute the mutual fiers’ simplified Mandarin Chinese characters (1st col- information (in bits) between the distribution umn), p¯ıny¯ın pronunciations (2nd column), and com- over classifiers and distributions over other lin- monly modified noun types (3rd column) are listed. guistic quantities. We investigate whether se- mantic classes of nouns and adjectives differ in how much they reduce uncertainty in classi- fier choice, and find that it is not fully idiosyn- 2015, Table1 gives some canonical examples), and cratic; while there are no obvious trends for the classifier choices are often argued to be based on majority of semantic classes, shape nouns re- inherent, possibly universal, semantic properties duce uncertainty in classifier choice the most. associated with the noun, such as shape (Kuo and Sera, 2009; Zhang and Jiang, 2016). Indeed, in 1 Introduction a summary article, Tai(1994) writes: “Chinese Many of the world’s languages make use of nu- classifier systems are cognitively based, rather than meral classifiers (Aikhenvald, 2000). While theo- arbitrary systems of classification.” If classifier retical debate still rages on the function of numeral choice were solely based on conceptual features of classifiers (Krifka, 1995; Ahrens and Huang, 1996; a given noun, then we might expect it to be nearly Cheng et al., 1998; Chierchia, 1998; Li, 2000; Nis- determinate—like gender-marking on nouns in bett, 2004; Bale and Coon, 2014), it is generally ac- German, Slavic, or Romance languages (Erbaugh, cepted that they need to be present for nouns to be 1986, 400)—and perhaps even fixed for all of a modified by numerals, quantifiers, demonstratives, given noun’s synonyms. or other qualifiers (Li and Thompson, 1981, 104). However, selecting which classifers go with In Mandarin Chinese, for instance, the phrase one nouns in practice is an idiosyncratic process, often person translates as 一个人 (y¯ı ge` ren´ ); the classi- with several grammatical options (see Table2 fier * (ge`) has no clear translation in English, yet, for two examples). Moreover, knowing what a nevertheless, it is necessary to place it between the noun means doesn’t always mean you can guess numeral 一 (y¯ı) and the word for person º (ren´ ). the classifier. For example, most nouns referring There are hundreds of numeral classifiers in to animals, such as t (lu¨´, donkey) or 羊 (yang´ , the Mandarin lexicon (Po-Ching and Rimmington, goat), use the classifier ê (zh¯ı). However, horses Classifier p(C j N = ºººëëë) p(C j N = 工工工程程程) Why investigate the idiosyncrasy of the Man- M (wei` ) 0.4838 0.0058 darin Chinese classifier system? How idiosyncratic 名 (m´ıng) 0.3586 0.0088 or predictable natural language is has captivated * (ge`) 0.0205 0.0486 researchers since Shannon(1951) originally pro- y (p¯ı) 0.0128 0.0060 posed the question in the context of printed En- y (xiang` ) 0.0063 0.4077 glish text. Indeed, looking at predictability directly 期 (q¯ı) 0.0002 0.2570 Everything else 0.1178 0.2661 relates to the complexity of language—a funda- mental question in linguistics (Newmeyer and Pre- Table 2: Empirical distribution of selected classifiers ston, 2014; Dingemanse et al., 2015)—which has over two nouns: ºë (ren´ sh`ı, people) and 工程 (gong¯ also been claimed to have consequences learnabil- cheng,´ project). Most of the probability mass is allo- ity and processing. For example, how hard it is cated to only a few classifiers for both nouns (bolded). for a learner to master irregularity, say, in the En- glish past tense (Rumelhart and McClelland, 1987; Pinker and Prince, 1994; Pinker and Ullman, 2002; ê cannot use (zh¯ı), despite being semantically Kirov and Cotterell, 2018) might be affected by pre- similar to goats and donkeys, and instead must dictability, and highly predictable noun-adjacent 9 appear with (pˇı). Conversely, knowing which words, such as gender affixes in German and pre- particular subset of noun meaning is reflected in nominal adjectives in English, are also shown to the classifer also doesn’t mean that you can use confer online processing advantages (Dye et al., that classifier with any noun that seems to have 2016, 2017, 2018). Within the Chinese classifier a the right semantics. For example, classifier system itself, the very common, general-purpose (tiao´ ) can be used with nouns referring to long and classifier * (ge`) is acquired by children earlier than narrow objects, like rivers, snakes, fish, pants, and rarer, more semantically rich ones (Hu, 1993). Gen- certain breeds of dogs—but never cats, regardless eral classifiers are also found to occur more often of how long and narrow they might be! In general, in corpora with nouns that are less predictable in classifiers carve up the semantic space in a very context (i.e., nouns with high surprisal; Hale 2001) idiosyncratic manner that is neither fully arbitrary, (Zhan and Levy, 2018), providing initial evidence nor fully predictable from semantic features. that predictability likely plays a role in classifier- Given this, we can ask: precisely how idiosyn- noun pairing more generally. Furthermore, pro- cratic is the Mandarin Chinese classifier system? viding classifiers improves participants’ recall For a given noun, how predictable is the set of of nouns in laboratory experiments (Zhang and classifiers that can be grammatically employed? Schmitt, 1998; Gao and Malt, 2009) (but see Huang For instance, had we not known that the Mandarin and Chen 2014)—but, it isn’t known whether clas- word for horse l (maˇ) predominantly takes the sifiers do so by modulating noun predictability. classifier 9 (pˇı), how likely would we have been to guess it over the much more common animal 2 Quantifying Classifier Idiosyncrasy classifier ê (zh¯ı)? Is it more important to know We take an information-theoretic approach to that a noun is l (maˇ) or simply that the noun is statistically quantify the idiosyncrasy of the Man- an animal noun? We address these questions by darin Chinese classifier system, and measure the computing how much the uncertainty in the distri- uncertainty (entropy) reduction—or mutual infor- bution over classifiers can be reduced by knowing mation (MI) (Cover and Thomas, 2012)—between information about nouns and noun semantics. We classifiers and other linguistic quantities, like quantify this notion of classifier idiosyncrasy by nouns or adjectives. Intuitively, MI lets us directly calculating the mutual information between clas- measure classifier “idiosyncrasy”, because it tells sifiers and nouns, and also between classifiers and us how much information (in bits) about a classifier several sets that are relevant to noun meaning (i.e., we can get by observing another linguistic quantity. categories of noun senses, sets of noun synonyms, If classifiers were completely independent from adjectives, and categories of adjective senses). Our other quantities, knowing them would give us no results yield concrete, quantitative measures of information about classifier choice. idiosyncrasy in bits, that can supplement existing hand-annotated, intuition-based approaches that Notation. Let C be a classifier-valued random organize Mandarin classifiers into an ontology. variable with range C, the set of Mandarin Chinese classifiers. Let X be a second random variable, into 26 SemCor supersense categories (Tsvetkov which models a second linguistic quantity, with et al., 2015), and then compute I(C; Ni) (i 2 range X . Mutual information (MI) is defined as f1; 2; :::; 26g) for each supersense category. The supersense categories (e.g., animal, plant, person, I(C; X) ≡ H(C) − H(C j X) (1a) artifact, etc.) provide a semantic classification sys- X p(c; x) tem for English nouns. Since there are no known = p(c; x) log (1b) p(c)p(x) supersense categories for Mandarin, we need to c2C;x2X translate Chinese nouns into English to perform our Let N and A denote the sets of nouns and adjec- analysis. We use SemCor supersense categories tives, respectively, with N and A be noun- and instead of WordNet hypernyms because different adjective-valued random variables, respectively. “basic levels” for each noun make it difficult to Let Ni and Ai denote the sets of nouns and adjec- determine the “correct” category for each noun. tives in ith SemCor supersense category for nouns (Tsvetkov et al., 2015) and adjectives (Tsvetkov 2.4 MI between Classifiers and Adjective et al., 2014), respectively, with their random vari- Supersenses ables being N and A , respectively. Let S be the i i We translated and divided the adjectives into 12 set of all English WordNet (Miller, 1998) senses supersense categories (Tsvetkov et al., 2014), of nouns, with S be the WordNet sense-valued ran- and compute mutual information I(C; Ai) (i 2 dom variable.
Load more

Recommended publications
  • Quantifying Constructions in English and Chinese a Corpus-Based Contrastive Study
    Quantifying Constructions in English and Chinese A Corpus-Based Contrastive Study Tony McEnery1 and Richard Xiao1 Abstract Quantifiers are a linguistic concept that mirrors quantity in reality. They indicate ‘how many’ or ‘how much’, for example, the number of entities denoted by a noun, the count of actions or events, the length of time, and the distance in space. All human languages have linguistic devices that express such ideas, though the encoding of natural language semantics can vary from language to language. This paper compares quantifying constructions in English and Chinese on the basis of comparable corpora of spoken and written data in the two languages. We will focus on classifiers in Chinese and their counterparts in English, as well as the interaction between quantifying constructions and progressives, which is normally ruled out by aspect theory, with the aim of addressing the following research questions: • What linguistic devices are used in Chinese and English for quantification? • How different (or similar) are classifiers in Chinese as a classifier language and in English as a non-classifier language? • Can quantifiers interact with progressives in English and Chinese if such interactions are theoretically ruled out by aspect theory? Before these research questions are explored in detail, it is appropriate to first present the principal data used in this study, which includes two written corpora and two spoken corpora. The Freiburg-LOB (FLOB) corpus is a recent update of LOB, which is composed of approximately one million tokens of written British English sampled proportionally from fifteen text categories published in the early 1990s (Hundt et al.
    [Show full text]
  • A Context-Based Classifier Prediction System for Chinese Language Learners
    ClassifierGuesser: A Context-based Classifier Prediction System for Chinese Language Learners Nicole Peinelt1,2 and Maria Liakata1,2 and Shu-Kai Hsieh3 1The Alan Turing Institute, London, UK 2Department of Computer Science, University of Warwick, Coventry, UK 3Graduate Institute of Linguistics, National Taiwan University, Taipei, Taiwan {n.peinelt, m.liakata}@warwick.ac.uk, [email protected] Abstract 2011), as well as an SVM with syntactic and ontological features (Guo and Zhong, 2005). Classifiers are function words that are However, without any context classifier assign- used to express quantities in Chinese ment can be ambiguous. For instance, the and are especially difficult for language noun 球 ‘ball’ can be modified by ke - a clas- learners. In contrast to previous stud- sifier for round objects - when referring tothe ies, we argue that the choice of clas- object itself as in (1), but requires the event sifiers is highly contextual and train classifier chang in the context of a ball match context-aware machine learning mod- as in (2). We argue that context is an impor- els based on a novel publicly available tant factor for classifier selection, since a head dataset, outperforming previous base- word may have multiple associated classifiers, lines. We further present use cases for but the final classifier selection is restricted by our database and models in an interac- the context. tive demo system. (1) 一 颗 红色 的 球 1 Introduction one ke red DE ball Languages such as Chinese are characterized ‘a red ball’ by the existence of a class of words commonly (2) 一 场 精彩 的 球 referred to as ‘classifiers’ or ‘measure words’.
    [Show full text]
  • Classifier Effect in Early and Late Bilinguals
    This document is downloaded from DR‑NTU (https://dr.ntu.edu.sg) Nanyang Technological University, Singapore. Language and thought : classifier effect in early and late bilinguals Tang, Huimin. 2011 Tang, H. (2011). Language and Thought : Classifier Effect in Early and Late Bilinguals. Final year project report, Nanyang Technological University. https://hdl.handle.net/10356/94061 Downloaded on 02 Oct 2021 00:47:01 SGT ATTENTION: The Singapore Copyright Act applies to the use of this document. Nanyang Technological University Library NANYANG TECHNOLOGICAL UNIVERSITY SCHOOL OF HUMANITIES AND SOCIAL SCIENCES Language and Thought: Classifier Effect in Early and Late Bilinguals Name: Tang Huimin (088169D12) Supervisor: Prof. Nayoung Kwon A Final Year Project submitted to the School of Humanities and Social Sciences, Nanyang Technological University in partial fulfillment of the requirements for the Degree of Bachelor of Arts in Linguistics & Multilingual Studies 2011 ATTENTION: The Singapore Copyright Act applies to the use of this document. Nanyang Technological University Library ACKNOWLEDGEMENTS It has been an amazing learning journey working on this project. The final work would not have been possible if not for the following people who have offered invaluable help to me during the course of this project. First of all, I would like to extend my sincere thanks to my supervisor, Professor Nayoung Kwon for her enthusiastic and patient guidance. Her thoughtful comments, expertise in experimental design and statistical analyses have been extremely helpful towards the completion of this study. Also, her constant encouragement has a great emotional support to me. I would like to thank all my friends and course mates from the Faculty of Linguistics and Multilingual Studies in Nanyang Technological University, who helped me in recruiting subjects for the experiments.
    [Show full text]
  • The Study of Chinese Noun-Classifier Compounds
    2019 2nd International Conference on Arts, Linguistics, Literature and Humanities (ICALLH 2019) The Study of Chinese Noun-Classifier Compounds Yanji Cui School of Foreign Languages, Yanbian University, Yanji, 133002, China [email protected] Keywords: formative morpheme; noun-classifier compounds; word structure. Abstract: Chinese noun-classifier compounds have the special structure in the Chinese vocabulary system. They have their own features both in the syntactic structure and the word meaning. The particularity of noun-classifiers lies in the complexity of their internal structure. The degree of grammaticalization of classifiers gives the explanation to the differences. They can be divided into three categories, they are real noun-classifier compounds, pseudo noun-classifier compounds and the noun compounds. This paper wants to study on the inner structure of the noun-classifier compounds, and the nature of the classifier in the noun-classifier compounds 1. Introduction In modern Chinese, there are a group of compounds which usually contain two elements, one of which is the noun, and the other is classifier. this kind of noun structure is usually called the noun- classifier compound, such as: cheliang (cars) chuanzhi (ships) mapi (horses) huaduo (flowers) tianmu(field) zhizhang (paper) renkou (population) qiangzhi (guns) huaping(vase) shubao(school bag) xinfeng(envelope) yinliang (money) (1) These kind of compounds have a long history, they appeared before the southern and northern dynasties, and became richer since then. [1] It can be seen from the above examples that among the two elements in these words: the first one is the nominal morpheme and the second one is the classifier morpheme.
    [Show full text]
  • Chinese Loanwords in Vietnamese Pronouns and Terms of Address and Reference
    Proceedings of the 29th North American Conference on Chinese Linguistics (NACCL-29). 2017. Volume 1. Edited by Lan Zhang. University of Memphis, Memphis, TN. Pages 286-303. Chinese Loanwords in Vietnamese Pronouns and Terms of Address and Reference Mark J. Alves Montgomery College Chinese loanwords have played a significant role in the Vietnamese system of pronouns and terms of address and reference. Semantic and pragmatic features of Chinese kinship terms and names have been transferred into the overall Vietnamese referential system. However, many of the Chinese loanwords in this semantic domain have undergone grammaticalization quite distinct from those in any variety of Chinese, thereby mitigating the notion of Chinese as being a primary source of the structure of in that system. This paper also considers how kinship terms, titles, and names came to have 1st and 2nd person reference potentially via language contact with Chinese, areal linguistic influence in Southeast Asia, or both. Many related questions will require future studies. 1. Background and Overview Identifying the linguistic influence of Chinese on Vietnamese generally begins with Chinese loanwords, permeate various levels of the Vietnamese lexicon (cf. Lê 2002, Alves 2009). What has become increasingly clear is that a great deal of the lexical and phonological features of Vietnamese must be attributed to a period of substantive Sino- Vietnamese—or more properly Sinitic-Vietic—bilingualism and language contact. Phan (2013) has hypothesized the former existence of ‘Annamese Chinese,’ an earlier but now non-existent variety of Chinese that, he claims, emerged in northern Vietnam from the early to mid-first millennium CE and lasted presumably through the end of the Tang Dynasty, but ultimately merged via language shift with Viet-Muong at some point.
    [Show full text]
  • Title Comparing Classifier Use in 1995 and 2010 Early Child Cantonese to Explore Social Change in Hong Kong Author(S)
    View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by HKU Scholars Hub Comparing classifier use in 1995 and 2010 early child Cantonese Title to explore social change in Hong Kong Author(s) Li, H; Wong, ECM Citation Chinese Language and Discourse, 2014, v. 5 n. 1, p. 79-97 Issued Date 2014 URL http://hdl.handle.net/10722/211461 Chinese Language and Discourse. Copyright © John Benjamins Rights Publishing Co. Compare Classifier Usage in Early Child Cantonese 1 Running Head: COMPARING CLASSIFIER USAGE IN EARLY CHILD CANTONESE Comparing Classifier Use in 1995 and 2010 Early Child Cantonese to Explore Social Change in Hong Kong Hui Li Eileen Chin Mei Wong The University of Hong Kong Acknowledgements This work was partially supported by the GRF Fund (RGC Ref No. 747109), HKSAR. We are very grateful to Prof. K.K. Luke and Prof. C.F. Sun for their comments and suggestions. Compare Classifier Usage in Early Child Cantonese 2 Abstract This study compared and analysed the classifier usage in two cohorts: the 492 Cantonese-speaking young children tested in 1995 (Tse & Li, 2011), and the 143 children tested in 2010 (Li &Tse, 2011). The results indicated that: (1) the 1995 and 2010 cohorts shared the same 8 most commonly used classifiers, 個 go3,隻 zek3, 架 gaa3,杯 bui1, 把 baa2, 嚿 gau6, 張 zoeng1,間 gaan1; (2) Two top 10 classifiers were found in the 2010 cohort: 支 zi1, and 部 bou6; (3) both cohorts overused the general classifier 個 go3; and (4) both cohorts overused 隻 zek3 and 嚿 gau6 to replace sortal classifiers and even to replace the general classifier 個 go3.
    [Show full text]
  • The Classifier System in Mandarin Chinese
    To appear in LINGUA in 2013 DISTINGUISHING CLASSIFIERS AND MEASURE WORDS: ∗ A MATHEMATICAL PERSPECTIVE AND IMPLICATIONS One-Soon Her Graduate Institute of Linguistics & Research Center of Mind, Brain, and Learning, National Chengchi University, Taipei 11605, Taiwan, ROC Abstract Based on the insight that a measure word (M) in [Num (Adj)-C/M N] is semantically substantive, while a classifier (C) is redundant and does not block modification or quantification to N (Her & Hsieh 2010), this paper proposes a distinction of C/M from a mathematical perspective. Synthesizing the concepts of parceler (Landman 2004), divider (Borer 2005), and multiplicand (Au Yeung 2005, 2007), I follow Her (2010) and contend that while C/M both function as a multiplicand mathematically, C’s value is necessarily 1 and M’s is not, thus ¬1. This offers a natural explanation to the semantic tests developed in Her and Hsieh (2010). Implications are discussed for these areas: typology of classifiers and classifier languages, correlations between numeral systems and the employment of C/M, the universal count/mass distinction at the lexical level, and first language acquisition of classifiers and numbers. Keywords: classifier, measure word, multiplication, multiplicand, 1, ¬1 1. Introduction Most, if not all, linguists would agree that there is a semantic distinction between the classifier (C) ben for books in (1) and the measure word (M) xiang ‘box’ in (2). * Fax: +996 2 29387466; Mobile: +886 2 926142388. E-mail address: [email protected]. (1) 三 本 書1 san ben shu 3 C book ‘3 books’ (2) 三 箱 書 san xiang shu 3 M-box book ‘3 boxes of books’ The element between Num and N has been classified into several types2; Chao (1968), for example, lists individual measure (what we call classifier); group measure (e.g., 組zu ‘group’); partitive measure (e.g., 份fen ‘portion, share’); container measure (e.g., 碗wan ‘bowl’); and standard measure (e.g., 碼ma ‘yard’).
    [Show full text]
  • Processing Tone and Vowel Information in Mandarin: an Eye-Tracking Study of Contextual Effects on Speech Processing
    Processing Tone and Vowel Information in Mandarin: An Eye-tracking Study of Contextual Effects on Speech Processing by Xizi Deng M.A. (Linguistics), The Chinese University of Hong Kong, 2016 B.A. (Chinese Language and Literature), Sichuan Normal University, 2015 Thesis Submitted in Partial Fulfillment of the Requirements for the Degree of Master of Arts in the Department of Linguistics Faculty of Arts and Social Sciences © Xizi Deng 2020 SIMON FRASER UNIVERSITY Spring 2020 Copyright in this work rests with the author. Please ensure that any reproduction or re-use is done in accordance with the relevant national copyright legislation. Approval Name: Xizi Deng Degree: Master of Arts Title: Processing Tone and Vowel Information in Mandarin: An Eye-tracking Study of Contextual Effects on Speech Processing Examining Committee: Chair: Suzanne Hilgendorf Associate Professor Henny Yeung Senior Supervisor Assistant Professor John Alderete Supervisor Professor Ashley Farris-Trimble Supervisor Assistant Professor Philip Monahan External Examiner Assistant Professor Department of Linguistics University of Toronto Date Defended/Approved: April 6th, 2020 ii Ethics Statement iii Abstract Prior work has suggested that rime (vowel) information is given priority over tone information in the perception of isolated words but there are flipped roles of tone and rime in a semantically constraining context. Here, I examined the eye gaze of native listeners of Mandarin Chinese, asking when and how top-down contextual effects from hearing a noun classifier constrains real-time processing of a target noun, and whether this classifier context has differential impacts on activating tone and rime information. The results show that, when hearing the classifier, average looking time to the target noun and noun competitors with the same tone or rime was significantly greater than to phonologically unrelated nouns.
    [Show full text]
  • Marjorie Chan's C7385. Chinese Dialects
    Chinese 7385: Chinese Dialects SPRING SEMESTER 2020 Chinese 7385 C H I N E S E DIALECTS Professor Marjorie K.M. Chan Dept. of East Asian Langs. & Lits. The Ohio State University Columbus, OH 43210 U.S.A. _____________________________________________________________________________________________________________________________________________________________________ COURSE: Chinese 7385. Chinese Dialects Class No. & Credit Hours: 32185 (3 credits, G) Prerequisites: Chinese 5380, or permission of instructor DAY & TIME T R 3:55 - 5:15 PM PLACE: Derby Hall, Room 060 (154 N. Oval Mall) OFFICE HOURS: R 1:30 - 3:30 p.m., or by appointment Office: 362 Hagerty Hall Tel: 292.3619 (Dept.: 292.5816) E-mail: chan.9 osu.edu HOME PAGE: http://u.osu.edu/chan.9/ COURSE PAGE: http://u.osu.edu/chan.9/c7385/ _____________________________________________________________________________________________________________________________________________________________________ TEXTBOOKS There are no textbooks assigned to this course. Readings are primarily e-journal articles that can be retrieved from OSU Libraries’ online catalog. First, go to Ohio State University Libraries <library.osu.edu>, and under "Links" on the right-hand menu, select “Online Journals List” and find the relevant e-journal titles. Additional readings will be made available during the semester. Thompson (Main) Library Reserve and Electronic Reserves: Some reference books will be placed in Closed Reserve at Thompson (Main) Library (loan periods may vary) during the semester. (Note: Reserved
    [Show full text]
  • Rules Vs. Analogy in Mandarin Classifier Selection*
    LANGUAGE AND LINGUISTICS 1.2:187-209, 2000 Rules vs. Analogy in Mandarin Classifier Selection* James Myers National Chung Cheng University A long-running debate concerns whether human language is processed solely by analogy to memorized exemplars, as connectionists have claimed, or instead may be processed by symbol-manipulating rules (e.g. Pinker 1999). In this paper we bring this debate to the Mandarin noun classifier system, arguing that the so-called general classifier 個 ge is selected by a default rule. Reviewing evidence from a variety of sources, including new corpus analyses, we first argue that the selection of most classifiers is lexically mediated, and then show that ge has no lexical semantics. Finally, we show that ge is used in a variety of situations that have nothing in common except for the inability to form analogies with examples in memory: when nouns are too dissimilar from lexical exemplars, are derived from other syntactic categories, or cooccur with classifiers too infrequently, and when speakers have memory access problems. Key words: analogy, rule, classifier, default rule 1. Introduction Work done over the last decade on the Mandarin noun classifier system has taught us much about the nature of nominal semantics and human categorization. In this paper, however, we are not particularly interested in nominal semantics or human categorization. Instead, we aim to use the Mandarin noun classifier system as a source of data for a different issue, something that might be called the rule/analogy debate. This is the debate between researchers who maintain the classical generativist line that human language is processed by symbol-manipulating rules (e.g.
    [Show full text]
  • Semantic Change in the Grammaticalization of Classifiers in Mandarin Chinese Janet Zhiqun Xing Section 1 Introduction 1. Chinese
    Semantic change in the grammaticalization of classifiers in Mandarin 3.Source meaning and classifier meaning Chinese (1) source meaning: the etymological meaning of the lexical item from which Janet Zhiqun Xing the classifier meaning has developed (2) Source meanings are countable, concrete, visible, related to objects, actions or events commonly seen in the ancient world Section 1 Introduction (3) source meaning v.s. classifier meaning: classifies with the same or a 1. Chinese numeral classifier: an individualizer which performs the same similar source meaning may not share common characteristics among their function as a singulative derivational affix in language with the classifier meanings collective/singulative distinction e.g. 條 tree branchlong objects 一條繩子 2. Function: it provides a way to individualize and classify its referent 支 tree branchbranchable concepts 一支部隊 3. Numeral classifiers were derived from “noun1+numeral+noun1” 4. development of classifier meanings: construction. (1) the lexical meaning before a lexeme enters into the grammatical form, 4. semantic change & grammaticalization: “NUM+NP/CL” Grammaticalization: lexical grammatical (2) the classifier meaning in the grammatical form “NUM+CL+NP” concrete/specificabstract/general categorical change: verbal/nominalclassifier meaning Semantic change is one of the major components in the process of grammaticalization. Section 3 Semantic change in grammaticalizaiton 5. (1) What factors trigger the emergence and disappearance of numeral classifiers? 1. Metaphoricalization: an analogical principle involves conceptualizing one (2) What factors lead to semantic change in the grammaticalization of element of a conceptual structure Ca in terms of an element of another conceptual structure Cb. (e.g.本、枝、條) numeral classifiers? 2.
    [Show full text]
  • ON the SYNTAX of CHINESE NOMINALS by HUIMIN JI
    ONTHE SYNTAX OF CHINESE NOMINALS by HUIMINJI (Under the Direction of Marlyse Baptista) ABSTRACT This dissertation investigates the use of classifiers in Chinese and more specifically compares Mandarin and the Wu dialect in terms of classifier usage. Different syntactic structures are proposed for the surface form [Cl + N] to derive its definite and indefinite interpretations. Classifiers are argued to encode only the feature of countability. The classifier in Wu moves to D when the [Cl + N] form has a definite interpretation. Xie ‘some’, usually considered to be a plural marker or a plural classifier in the linguistic literature, is argued to be a quantifier which can be used with both count and mass nouns. This dissertation also analyzes the so-called complex definites. Pronouns are assumed to be determiners in Mandarin. Possessives function like adjectives and they do not encode the definiteness feature in Mandarin. Multiple possessives realizing different theta roles can occur prenominally and their order is fixed. It is assumed that different possessives occupy the specifier positions of different functional projections. Proper names in Mandarin are argued to be in various syntactic positions. Demonstrative determiners are assumed to project their own phrasal category in this dissertation. INDEX WORDS: determiner phrase, classifier phrase, definiteness, specificity, complex definites ONTHE SYNTAX OF CHINESE NOMINALS by HUIMINJI B.A. Zhejiang Normal University, China, 1986 M.A. Shanghai International Studies University, China, 1995 A Dissertation Submitted to the Graduate Faculty of The University of Georgia in Partial Fulfillment of the Requirements for the Degree DOCTOR OF PHILOSOPHY ATHENS, GEORGIA 2007 © 2007 Huimin Ji All Rights Reserved ONTHE SYNTAX OF CHINESE NOMINALS by HUIMINJI Major Professor: Marlyse Baptista Committee: Keith Langston Michael A.
    [Show full text]