The M.A.K Halliday Library Functional Linguistics Series Qingshun He A Corpus-Based Approach to Clause Combining in English from the Systemic Functional Perspective The M.A.K. Halliday Library Functional Linguistics Series Series editors Chenguang Chang Guowen Huang About the Series This series focuses on studies concerning the theory and application of Systemic Functional Linguistics It bears the name of Professor M.A.K. Halliday, as he is generally regarded as the founder of this school of linguistic thought The series covers studies on language and context, functional grammar, semantic variation, discourse analysis, multimodality, register and genre analysis, educational linguistics and other areas Systemic Functional Linguistics is a functional model of language inspired by the work of linguists such as Saussure, Hjelmslev, Whorf, and Firth The theory was initially developed by Professor M.A.K. Halliday and his colleagues in London during the 1960s, and since 1974 it has held an international congress every year at various continents around the world It is well-known for its application in a variety of fields, including education, translation, computational linguistics, multimodal studies, and healthcare, and scholars are always exploring new areas of application More information about this series at http://www.springer.com/series/13311 Qingshun He A Corpus-Based Approach to Clause Combining in English from the Systemic Functional Perspective Qingshun He School of Foreign Languages Sun Yat-Sen University Guangzhou, Guangdong, China ISSN 2198-9869 ISSN 2198-9877 (electronic) The M.A.K. Halliday Library Functional Linguistics Series ISBN 978-981-13-7390-9 ISBN 978-981-13-7391-6 (eBook) https://doi.org/10.1007/978-981-13-7391-6 © Springer Nature Singapore Pte Ltd 2019 This work is subject to copyright All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed The use of general descriptive names, registered names, trademarks, service marks, etc in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations This Springer imprint is published by the registered company Springer Nature Singapore Pte Ltd The registered company address is: 152 Beach Road, #21-01/04 Gateway East, Singapore 189721, Singapore Notational Conventions the initiative clause the continuing clause α the dominant clause β the dependent clause = elaborating + extending × enhancing “ locution ‘ idea ||| clause complex || clause | group/phrase [[[ ]]] rank-shifted or embedded clause complex [[ ]] rank-shifted or embedded clause [ ] rank-shifted or embedded group/phrase > included clause v Acknowledgments This research could not have been completed without the help of many colleagues and friends, among whom, I am particularly grateful to Profs Guowen Huang at South China Agricultural University and Chenguang Chang at Sun Yat-sen University Profs Binli Wen (Guangdong University of Foreign Studies), Bingjun Yang (Shanghai Jiao Tong University), Xiaopeng Liang (Qingdao University of Science and Technology), and Lise Fontaine (Cardiff University) have generously supported me in many ways during the writing and revising of the manuscript I would give my deepest thanks to Emeritus Profs Dennis Hawkes and Freda Hawkes at the University of South Wales for their kind encouragement and help during my visit in Cardiff Many thanks also to Rebecca Zhu, Carolyn Zhang, and Vaishnavi Venkatesh from Springer for their help The research is supported by the National Social Science Foundation of China (17BYY185) Qingshun He vii Contents 1 Introduction������������������������������������������������������������������������������������������������ 1 1.1 Research Background�������������������������������������������������������������������������� 1 1.2 Purpose of the Study���������������������������������������������������������������������������� 4 1.3 Organization of the Book �������������������������������������������������������������������� 6 References���������������������������������������������������������������������������������������������������� 7 2 A Systemic Functional Approach to Clause Combining in English������ 11 2.1 Introduction ���������������������������������������������������������������������������������������� 11 2.2 Overview of Clause Combining���������������������������������������������������������� 11 2.2.1 Parataxis���������������������������������������������������������������������������������� 14 2.2.2 Hypotaxis�������������������������������������������������������������������������������� 16 2.2.3 Embedding������������������������������������������������������������������������������ 20 2.3 Cline���������������������������������������������������������������������������������������������������� 26 2.4 Cline in Clause Combining ���������������������������������������������������������������� 30 2.5 A Sketch of Grammatical Metaphor���������������������������������������������������� 36 2.5.1 Ideational Metaphor and Interpersonal Metaphor������������������ 37 2.5.2 Textual Metaphor�������������������������������������������������������������������� 38 2.6 Summary���������������������������������������������������������������������������������������������� 39 References���������������������������������������������������������������������������������������������������� 40 3 Research Design ���������������������������������������������������������������������������������������� 43 3.1 Research Questions ���������������������������������������������������������������������������� 43 3.2 Research Methods ������������������������������������������������������������������������������ 44 3.3 Data Collection������������������������������������������������������������������������������������ 45 3.4 Data Processing ���������������������������������������������������������������������������������� 47 References���������������������������������������������������������������������������������������������������� 48 4 Genre Distributions of Clause Combining���������������������������������������������� 51 4.1 Introduction ���������������������������������������������������������������������������������������� 51 4.2 Crown Corpus-Based Research on Clause Combining ���������������������� 51 4.2.1 Overall Frequency Distribution���������������������������������������������� 51 4.2.2 Genre Distribution of Overall Frequency ������������������������������ 55 ix x Contents 4.2.3 Genre Distribution of Logico-semantic Relations������������������ 56 4.2.4 Genre Distribution of Embedding������������������������������������������ 63 4.2.5 Existing Questions������������������������������������������������������������������ 64 4.3 Research Based on the BNC and the COCA�������������������������������������� 64 4.3.1 Genre Distribution of Expansion�������������������������������������������� 64 4.3.2 Genre Distribution of Projection�������������������������������������������� 78 4.3.3 Genre Distribution of Embedding������������������������������������������ 88 4.4 Summary���������������������������������������������������������������������������������������������� 93 References���������������������������������������������������������������������������������������������������� 94 Diachronic Distribution of Clause Combining���������������������������������������� 95 5.1 Diachronic Distribution of Overall Frequency������������������������������������ 95 5.2 Diachronic Distribution of Expansion������������������������������������������������ 99 5.3 Diachronic Distribution of Projection ������������������������������������������������ 102 5.4 Diachronic Distribution of Embedding ���������������������������������������������� 105 5.5 Diachronic Distribution of Non-finite Clauses������������������������������������ 108 5.5.1 Diachronic Distribution of Non-finite Clauses of Expansion �������������������������������������������������������������������������� 111 5.5.2 Diachronic Distribution of Non-finite Embedded Clauses������������������������������������������������������������������������������������ 119 5.5.3 Diachronic Distribution of Personal Pronoun Subjects of Absolute Clauses�������������������������������������������������� 121 5.6 Summary���������������������������������������������������������������������������������������������� 124 References���������������������������������������������������������������������������������������������������� 125 6 Grammatical Metaphor in Clause Combining���������������������������������������� 127 6.1 Introduction ���������������������������������������������������������������������������������������� 127 6.2 The Creation of Grammatical Metaphor �������������������������������������������� 127 6.3 Types of Grammatical Metaphor in Clause Combining���������������������� 129 6.3.1 Ideational Metaphor���������������������������������������������������������������� 130 6.3.2 Textual Metaphor�������������������������������������������������������������������� 131 6.4 Diachronic Distribution of Grammatical Metaphor in Clause Combining �������������������������������������������������������������������������� 132 6.4.1 Diachronic Distribution of Experiential Metaphor ���������������� 133 6.4.2 Diachronic Distribution of Logical Metaphor������������������������ 148 6.4.3 Diachronic Distribution of Cohesive Metaphor���������������������� 150 6.5 Genre Distribution of Grammatical Metaphor in Clause Combining ������������������������������������������������������������������������������������������ 163 6.5.1 Genre Distribution of Experiential Metaphor ������������������������ 163 6.5.2 Genre Distribution of Logical Metaphor�������������������������������� 167 6.5.3 Genre Distribution of Cohesive Metaphor������������������������������ 168 6.6 Summary���������������������������������������������������������������������������������������������� 172 References���������������������������������������������������������������������������������������������������� 174 Contents xi 7 Conclusion�������������������������������������������������������������������������������������������������� 177 7.1 Research Findings ������������������������������������������������������������������������������ 177 7.2 Limitations and Suggestions���������������������������������������������������������������� 180 7.2.1 Limitations������������������������������������������������������������������������������ 181 7.2.2 Further Research �������������������������������������������������������������������� 182 References���������������������������������������������������������������������������������������������������� 183 Appendices�������������������������������������������������������������������������������������������������������� 185 7.2 Limitations and Suggestions 181 logical metaphor from the perspective of verbalization of conjunction groups, and cohesive metaphor from the perspective of transcategorization of conjunctive expressions, which precludes the opinion that ideational metaphors in the environment of text are interpreted as textual metaphor and proposes that ideational metaphor not only has textual effects but also can induce textual metaphor Theoretically, textual function is itself the second-order language use, and grammatical metaphor is also the second-order language use (Halliday and Matthiessen 1999) Both interpersonal metaphor and ideational metaphor can induce textual metaphor, but textual metaphor cannot induce ideational metaphor or interpersonal metaphor This is also a reflection of the unidirectionality of transfer in grammatical metaphor proposed by He and Yang (2014) 7.2.1 Limitations We combined the method of qualitative research and quantitative research not only to construct the theory of clause combining but also to explore the synchronic and diachronic distributions of the different relations using the actually used language However, the corpus-based systemic functional research of the distributions of and the transfers in clause combining is confronted with the following problems: First, the limited data manually retrieved are not sufficient enough for the comprehensive exploration of the genre and diachronic distributions of clause combining Manually retrieved data are accurate, but the small number of retrieved occurrences is not enough to reflect exactly the genre distribution trend of different types of clause combining We only analyzed about 1200 sentences collected from the Crown corpus, 300 in each genre Such a small number of sentences cannot represent the whole picture of the corpus or the genre distribution trend Even in the same genre, different texts will have different language priorities One text or several hundred sentences in a text cannot represent the language characteristics of the genre In addition, the analysis of clause combining is inevitably subjective because some clause complexes not have explicit conjunctive expressions realizing relator The relation types without explicit conjunctive expressions are open-ended, and they need the reader’s subjective reasoning, but the manual analysis is largely a reflection of the analyst’s personal preference It is because of this, the proportion of paratactic elaborations we retrieved is different from that by Halliday and Matthiessen (2014) Second, relationships without explicit conjunctive expressions are difficult to be retrieved automatically, and it is impossible to conduct hierarchical analysis of the retrieved data Computer has the advantage of being able to process more data quickly, revealing some hidden features of the language, but there is still a considerable way to go for the depth, accuracy, flexibility, and richness of manual processing The higher the grammar level, the more difficult it is for automatic analyzing For example, 182 7 Conclusion automatic analysis can deal with any lexical patterns and can operate the low-level mode analysis within the lexico-grammatical stratum, but it is not possible to carry out a complete systemic functional analysis of clauses or semantic analysis because meaning is fuzzy and inexplicable in nature Therefore, it is difficult to retrieve the relationships between clauses The relation types of clause complexes in SFL are at the semantic stratum rather than at the lexico-grammatical stratum We can retrieve language forms from corpus, but we cannot retrieve meaning This results in the fact that a considerable number of the concordance lines we retrieved from the corpus using relevant regular expressions not meet the search requirement In addition, different levels of relationships can be retrieved through manual retrieval For example, of the manually retrieved relations, many are more than two levels of embedding, some even up to seven levels Automatic retrieval cannot distinguish levels Because of the restrictions of the search queries, we can only retrieve the first level embedding, which to some extent affected the validity of the data analysis According to SFL, there is not a clear boundary between two categories; rather they form a cline In fact, in many cases, a grammatical form may realize different types of relations, but the potential relations are fixed by the relevant regular expressions we wrote in terms of language form 7.2.2 Further Research Clausal relations are realized by explicit or implicit grammatical markers The explicit markers can be automatically retrieved, but the implicit markers are more suitable for manual processing This requires that in future research we should follow the requirement of the research itself to implement the complementarity of methods, emphasizing the combination of quantitative and qualitative research and the integration of manual and automatic operations With the development of the theory of SFL and the continuous improvement of computer technology, automatic operation will increase gradually from the lower-level analyses to the higher-level analyses It will develop from explicit marker retrieving to implicit marker retrieving to automate the retrieval of different types of clausal relations to a higher and higher degree Therefore, it is possible to extract all the occurrences of all the types of clausal relations and to disclose the synchronic and diachronic distributions of these relations With enough data, we can make the results more convincible Grammatical metaphor is an important content of functional syntax We explored the genre and diachronic distributions of experiential metaphor and logical metaphor from the perspective of rank-shift and the two types of cohesive metaphor from the perspective of transcategorization However, grammatical metaphor arises from the rearrangement of meaning at the lexico-grammatical stratum (Halliday 1978), and there may be grammatical metaphors in all the three metafunctions of language Grammatical metaphor proposed by Halliday (1985, 1994) and Halliday and Matthiessen (2004, 2014) includes ideational metaphor and interpersonal metaphor The former is further divided into experiential metaphor and logical metaphor References 183 Interpersonal metaphor includes metaphor of modality and metaphor of mood However, this research only analyzed ideational metaphor and two types of cohesive metaphor, but not interpersonal metaphor Therefore, the future corpus-based study of grammatical metaphor should not only explore the generation of the two types of interpersonal metaphor and their synchronic and diachronic distributions but also further explore the synchronic and diachronic distributions of other types of textual metaphor arising from the rearrangement of the thematic and information structures based on the identifying criterion of double functionality Different languages have different organization patterns In this research, we only discussed the genre and diachronic distribution trends of different clausal relations in English Then, what clausal relation types are there in other languages and what are their genre and diachronic distribution trends? In Chinese, for example, there are much fewer morphological markers than in English, and the relationships between clauses are always implicit And in Chinese clause complexes, the primary clauses always occur preceding the secondary clauses The position of the English clauses in clause complexes is relatively flexible The finite dependent clauses all require conjunctive expressions to realize relator, but the finite continuing clauses not, and they will always follow the initiating clauses Since there are fewer explicit conjunctive markers, then are there more paratactic relations but fewer hypotactic relations in Chinese than in English? English non-finite clauses not necessarily require explicit conjunctive expressions to realize relator because non-finite clauses always realize hypotaxis Chinese verbs not have non-finite morphological markers, then how can we identify Chinese non-finite clauses or how can we distinguish Chinese parataxis from hypotaxis? In this sense, different languages can realize the same relation, but the organizations of language are different in different languages The corpus-based cross-language research can reveal the distribution trends of different types of clausal relations in different languages, including the synchronic and diachronic distributions This kind of research can be used to evaluate the translations from one aspect Further research of these questions will help not only understand the different clause linking patterns but also explore their cross-language uses and further enrich the theory of functional syntax References Halliday, M. A K (1978) Language as social semiotic: The social interpretation of language and meaning London: Edward Arnold Halliday, M. A K (1985) An introduction to functional grammar London: Edward Arnold Halliday, M. A K (1994) An introduction to functional grammar (2nd ed.) London: Edward Arnold Halliday, M. A K., & Matthiessen, C. M I. M (1999) Construing experience through meaning: A language-based approach to cognition London/New York: Cassell 184 7 Conclusion Halliday, M. A K., & Matthiessen, C. M I. M (2004) An introduction to functional grammar (3rd ed.) London: Edward Arnold Halliday, M. A K., & Matthiessen, C. M I. M (2014) An introduction to functional grammar (4th ed.) London/New York: Routledge He, Q., & Yang, B (2014) A study of transfer directions in grammatical metaphor Australian Journal of Linguistics, 3, 345–360 Appendices Appendix 1: CLAWS Tagset APPGE Possessive pronoun, pre-nominal (e.g., my, your, our) AT Article (e.g., the, no) AT1 Singular article (e.g., a, an, every) BCL Before-clause marker (e.g., in order (that), in order (to)) CC Coordinating conjunction (e.g., and, or) CCB Adversative coordinating conjunction (but) CS Subordinating conjunction (e.g., if, because, unless, so, for) CSA As (as conjunction) CSN Than (as conjunction) CST That (as conjunction) CSW Whether (as conjunction) DA After-determiner or post-determiner capable of pronominal function (e.g., such, former, same) DA1 Singular after-determiner (e.g., little, much) DA2 Plural after-determiner (e.g., few, several, many) DAR Comparative after-determiner (e.g., more, less, fewer) DAT Superlative after-determiner (e.g., most, least, fewest) DB Before determiner or pre-determiner capable of pronominal function (all, half) DB2 Plural before-determiner (both) DD Determiner (capable of pronominal function) (e.g., any, some) DD1 Singular determiner (e.g., this, that, another) DD2 Plural determiner (these, those) DDQ Wh-determiner (which, what) DDQGE Wh-determiner, genitive (whose) DDQV Wh-ever determiner (whichever, whatever) © Springer Nature Singapore Pte Ltd 2019 Q He, A Corpus-Based Approach to Clause Combining in English from the Systemic Functional Perspective, The M.A.K Halliday Library Functional Linguistics Series, https://doi.org/10.1007/978-981-13-7391-6 185 186 EX FO FU FW GE IF II IO IW JJ JJR JJT JK MC MC1 MC2 MCGE MCMC MD MF ND1 NN NN1 NN2 NNA NNB NNL1 NNL2 NNO NNO2 NNT1 NNT2 NNU NNU1 NNU2 NP NP1 NP2 NPD1 NPD2 NPM1 NPM2 PN PN1 PNQO Appendices Existential there Formula Unclassified word Foreign word Germanic genitive marker—(’ or ’s) For (as preposition) General preposition Of (as preposition) With, without (as prepositions) General adjective General comparative adjective (e.g., older, better, stronger) General superlative adjective (e.g., oldest, best, strongest) Catenative adjective (able in be able to, willing in be willing to) Cardinal number, neutral for number (two, three…) Singular cardinal number (one) Plural cardinal number (e.g., sixes, sevens) Genitive cardinal number, neutral for number (two’s, 100s) Hyphenated number (40–50, 1770–1827) Ordinal number (e.g., first, second, next, last) Fraction, neutral for number (e.g., quarters, two-thirds) Singular noun of direction (e.g., north, southeast) Common noun, neutral for number (e.g., sheep, cod, headquarters) Singular common noun (e.g., book, girl) Plural common noun (e.g., books, girls) Following noun of title (e.g., M.A.) Preceding noun of title (e.g., Mr., Prof.) Singular locative noun (e.g., Island, Street) Plural locative noun (e.g., Islands, Streets) Numeral noun, neutral for number (e.g., dozen, hundred) Numeral noun, plural (e.g., hundreds, thousands) Temporal noun, singular (e.g., day, week, year) Temporal noun, plural (e.g., days, weeks, years) Unit of measurement, neutral for number (e.g., in, cc) Singular unit of measurement (e.g., inch, centimeter) Plural unit of measurement (e.g., inches, centimeters) Proper noun, neutral for number (e.g., IBM, Andes) Singular proper noun (e.g., London, Jane, Frederick) Plural proper noun (e.g., Browns, Reagans, Koreas) Singular weekday noun (e.g., Sunday) Plural weekday noun (e.g., Sundays) Singular month noun (e.g., October) Plural month noun (e.g., Octobers) Indefinite pronoun, neutral for number (none) Indefinite pronoun, singular (e.g., anyone, everything, nobody, one) Objective wh-pronoun (whom) Appendices PNQS PNQV PNX1 PPGE PPH1 PPHO1 PPHO2 PPHS1 PPHS2 PPIO1 PPIO2 PPIS1 PPIS2 PPX1 PPX2 PPY RA REX RG RGQ RGQV RGR RGT RL RP RPK RR RRQ RRQV RRR RRT RT TO UH VB0 VBDR VBDZ VBG VBI VBM VBN VBR VBZ VD0 VDD 187 Subjective wh-pronoun (who) Wh-ever pronoun (whoever, whomever, whomsoever, whosoever) Reflexive indefinite pronoun (oneself) Nominal possessive personal pronoun (e.g., mine, yours) Third person singular neuter personal pronoun (it) Third person singular objective personal pronoun (him, her) Third person plural objective personal pronoun (them) Third person singular subjective personal pronoun (he, she) Third person plural subjective personal pronoun (they) First person singular objective personal pronoun (me) First person plural objective personal pronoun (us) First person singular subjective personal pronoun (I) First person plural subjective personal pronoun (we) Singular reflexive personal pronoun (e.g., yourself, itself) Plural reflexive personal pronoun (e.g., yourselves, themselves) Second person personal pronoun (you) Adverb, after nominal head (e.g., else, galore) Adverb introducing appositional constructions (e.g., namely, viz., e.g.) Degree adverb (very, so, too) Wh-degree adverb (how) Wh-ever degree adverb (however) Comparative degree adverb (more, less) Superlative degree adverb (most, least) Locative adverb (e.g., alongside, forward) Prep adverb, particle (e.g., about, in) Prep adv., catenative (about in be about to) General adverb Wh-general adverb (where, when, why, how) Wh-ever general adverb (wherever, whenever) Comparative general adverb (e.g., better, longer) Superlative general adverb (e.g., best, longest) Quasi-nominal adverb of time (e.g., now, tomorrow) Infinitive marker (to) Interjection (e.g., oh, yes, um) Be, base form (finite, i.e., imperative, subjunctive) Were Was Being Be, infinitive (To be or not… It will be …) Am Been Are Is Do, base form (finite) Did 188 VDG VDI VDN VDZ VH0 VHD VHG VHI VHN VHZ VM VMK VV0 VVD VVG VVGK VVI VVN VVNK VVZ XX ZZ1 ZZ2 Appendices Doing Do, infinitive (I may do… To do…) Done Does Have, base form (finite) Had (past tense) Having Have, infinitive Had (past participle) Has Modal auxiliary (can, will, would, etc.) Modal catenative (ought, used) Base form of lexical verb (e.g., give, work) Past tense of lexical verb (e.g., gave, worked) -ing participle of lexical verb (e.g., giving, working) -ing participle catenative (going in be going to) Infinitive (e.g., to give… It will work…) Past participle of lexical verb (e.g., given, worked) Past participle catenative (e.g., bound in be bound to) -s form of lexical verb (e.g., gives, works) Not, n’t Singular letter of the alphabet (e.g., a, b) Plural letter of the alphabet (e.g., a’s, b’s) Appendices 189 Appendix 2: POS List [nn*] [v*] [j*] [r*] [xx*] [at*] [d*] [p*] [app*] [i*] [c*] [n*] [*nn1*] [*nn2*] [*nn0*] [np*] [nn*] [vv0*] [v?i*] [vvi*] [vm*] [v?z*] noun.all verb.all adj.all adv.all neg.all art.all det.all pron.all poss.all prep.all conj.all noun.all+ noun.SG noun.PL noun.CMN noun.+PROP noun.-PROP verb.BASE verb.INF verb.INF/LEX verb.MODAL verb.3SG [v?d*] [v?n*] [v?g*] [vv*] [vb*] [vd*] [vh*] [jjr*] [jjt*] [rp*] [rrq*] [pn1*] [pp*] [pnq*] [ppx*] [mc*] [md*] [cc*] [cs*] [uh*] [y*] verb.ED verb.EN verb.ING verb.[LEX] verb.[BE] verb.[DO] verb.[HAVE] adj.CMP adj.SPRL adv.PRTCL adv.WH pron.INDF pron.PERS pron.WH pron.REFL num.CARD num.ORD conj.CRD conj.SUB interj PUNC Appendix 3: Query Syntax Simple slot Syntax Word [pos] [pos*] [lemma] [=word] [user:list] Meaning One exact word Part of speech (exact) Part of speech (wildcard) Lemmas (all forms of a word) Synonyms [[=strong] Customized lists Examples Mysterious [v?g*] Sample matches Mysterious Going, using [v*] Find, does, keeping, started [sing] Sing, singing, sang [tall] Tall, taller, tallest Formidable, muscular, fervent [mark_davies@byu edu:clothes] Tie, shirt, blouse Appendices 190 Simple slot Syntax Word|word *xx X?xx X?xx* -word word.[pos] word*.[pos] [lemma] [pos] [=word] [pos] Meaning Any of these words Wildcard: * = any # letters Wildcard: ? = one letter Examples stunning|gorgeous|charming un*ly s?ng s?ng* NOT (followed by -[nn*] PoS, lemma, word, etc.) Exact word and strike.[v*] part of speech Substring and part dis*.[vvd] of speech Lemma and part of [strike].[v*] speech Synonym and part [=beat].[v*] of speech Sample matches Stunning, charming, gorgeous Unlikely, unusually Sing, sang, song Song, singer, songbirds The, in, is Strike (only as a verb) Discovered, disappeared, discussed Strike, struck, striking [[=word]] Synonym and lemma [[=publish]] [[user:list]] Customized list and lemma [[mark_davies@byu edu:clothes]] [[=word]] [pos] Synonym and lemma and part of speech Customized list and lemma and part of speech [[=clean]].[v*] Hit, strike, defeat (but not nouns, like rhythm or drumming) Announced, circulating, publishes, issue (no part of speech specified, so some noun uses) Tie, tying, socks, socked, shirt, blouses (no part of speech specified, hence tying) Mop, scrubs, polishing [[mark_davies@byu edu:clothes]].[n*] Tie, ties, sock, socks (i.e., just nouns) [[user:list]] [pos] Multiple slots Syntax fast|quick|rapid [nn*] Pretty -[nn*] [get] her to [v*] |,|; nevertheless [p*] [v*] [break] the [nn*] [[beat]].[v*] * [nn*] [=gorgeous] [nn*] [put] on [ap*] [mark_davies@byu edu:clothes].[n*] Examples Fast food, rapid transit Pretty smart’ pretty as (but not pretty girl, pretty picture, etc.) Get her to stay, got her to sleep Nevertheless it is ; nevertheless he said Break the law, broke the story Beat the Yankees, beaten to death Beautiful woman, attractive wife Put on her hat, putting on my pants 191 Appendices Appendix 4: Systems for Statistics (Figs A1 and A2) hypotaxis α β taxis DEPENDENCY parataxis 12 defining embedding head fact appositive LEVEL idea ’ in subject in complement locution ” MODE projection quote *=> report †=> FUNCTION minor =>* major proposition proposal exposition clausal relation exemplification LOGICOSEMANTIC elaborating = clarification description positive addition expansion extending + alternation negative adversative replacive variation subtractive means RECURSION manner stop comparison place go on enhancing × cause reason purpose result time condition positive negative concessive Fig A1 System network of clausal relations in English Appendices 192 fiction GENRE press prose learned simple-clause TAXIS- parataxis TYPE hypotaxis taxis a-initial POSITION b-initial a-middle CAGEGORY b-middle head embedding DEPTH postmodifier FUNCTION- nominal-group IN adverbial-group appositive FINITENESS finite nonfinite clause PROJECTION- locution LEVEL idea projection PROJECTION- reporting MODE quoting PROJECTIONFUNCTION major MAJOR- proposition TYPE proposal minor exposition exemplicifation ELABORATIONelaboration clarification TYPE DESCRIPTION- whole TYPE part description addition TYPE clause-clause LOGICOSEMANTIC expansion MODE extension positive ADDITIONnegative TYPE adversative EXTENSION- alternation TYPE VARIATION- replacive variation TYPE subtractive possession temporal TEMPORALTYPE same-time different-time DIFFERENCE- later TYPE earlier spatial enhancement ENHANCEMENTTYPE manner causal MANNER- means TYPE comparison reason CAUSALpurpose TYPE result conditional participant PARTICIPANTTYPE positive-condition CONDITIONALnegative-condition TYPE concessive subject complement COMPLEMENT- of-verbal-group TYPE of-prepositional-group level-1 level-2 NESTING level-3 level-4 level-5 level-6 level-7 minor-clause Fig A2 System network of clause combining working in the UAM Corpus Tool Appendices 193 Appendix 5: Table of Corpus Data Statistics (Table A1) Table A1 Genre distributions of clause combining in the Brown Corpus Feature Total units Simple-clause Clause-clause Minor-clause Category Taxis Embedding Taxis Parataxis Hypotaxis Position a-initial b-initial a-middle b-middle Depth Head Post-modifier Appositive Function-in Nominal-group Adverbial-group Finiteness Finite Nonfinite Logico-semantic Projection Expansion Participant Projection-level Locution Idea Projection-mode Reporting Quoting Projection-function Major Minor Fiction Percent N = 548 23.0 76.5 0.5 N = 419 80.4 19.6 N = 337 51.0 49.0 N = 337 77.4 19.0 1.8 1.8 N = 82 37.8 62.2 0.0 N = 51 84.3 15.7 N = 419 70.6 29.4 N = 419 20.5 72.1 7.4 N = 86 53.5 46.5 N = 86 55.8 44.2 N = 86 96.5 3.5 N 126 419 337 82 172 165 261 64 6 31 51 43 296 123 86 302 31 46 40 48 38 83 Press Percent N = 644 17.1 82.9 0.0 N = 534 67.6 32.4 N = 361 27.4 72.6 N = 361 81.4 16.1 0.6 1.9 N = 173 37.0 57.8 5.2 N = 100 94.0 6.0 N = 534 67.4 32.6 N = 534 25.8 62.2 12.0 N = 138 81.2 18.8 N = 138 81.2 18.8 N = 138 99.3 0.7 N 110 534 361 173 99 262 294 58 64 100 94 360 174 138 332 64 112 26 112 26 137 Prose Percent N = 637 20.3 79.7 0.0 N = 508 70.1 29.9 N = 356 36.8 63.2 N = 356 92.4 7.3 0.0 0.3 N = 152 17.8 82.2 0.0 N = 125 99.2 0.8 N = 508 44.3 55.7 N = 508 5.9 88.8 5.3 N = 30 93.3 6.7 N = 30 100.0 0.0 N = 30 100.0 0.0 N 129 508 356 152 131 225 329 26 27 125 124 225 283 30 451 27 28 30 30 Learned Percent N = 595 17.1 82.9 0.0 N = 493 67.7 32.3 N = 334 31.4 68.6 N = 334 81.4 18.0 0.6 0.0 N = 159 18.2 74.2 7.5 N = 118 99.2 0.8 N = 493 60.9 39.1 N = 493 14.0 80.1 5.9 N = 69 52.2 47.8 N = 69 79.7 20.3 N = 69 100.0 0.0 N 102 493 334 159 105 229 272 60 29 118 12 117 300 193 69 395 29 36 33 55 14 69 (continued) Appendices 194 Table A1 (continued) Feature Major Proposition Proposal Mode Elaboration Extension Enhancement Elaboration Exposition Exemplification Clarification Description Description Whole Part Extension Addition Alternation Variation Possession Addition Positive Negative Adversative Variation Replacive Subtractive Enhancement Temporal Spatial Manner Causal Conditional Temporal Same-time Different-time Difference Later Earlier Fiction Percent N = 83 88.0 12.0 N = 302 20.9 37.7 41.4 N = 63 11.1 3.2 3.2 82.5 N = 52 5.8 94.2 N = 114 96.5 0.9 1.8 0.9 N = 110 86.4 0.0 13.6 N = 2 100.0 0.0 N = 125 48.8 4.0 11.2 28.8 7.2 N = 61 45.9 54.1 N = 33 90.9 9.1 N 73 10 63 114 125 2 52 49 110 95 15 61 14 36 28 33 30 Press Percent N = 137 99.3 0.7 N = 332 37.7 27.4 34.9 N = 125 1.6 0.0 0.8 97.6 N = 122 2.5 97.5 N = 91 91.2 4.4 2.2 2.2 N = 83 81.9 1.2 16.9 N = 2 100.0 0.0 N = 116 24.1 9.5 7.8 45.7 12.9 N = 28 71.4 28.6 N = 8 25.0 75.0 N 136 125 91 116 122 119 83 2 68 14 28 11 53 15 20 Prose Percent N = 30 100.0 0.0 N = 451 37.5 29.9 32.6 N = 169 1.8 0.6 0.0 97.6 N = 165 4.8 95.2 N = 135 90.4 6.7 1.5 1.5 N = 122 98.4 0.0 1.6 N = 2 100.0 0.0 N = 147 18.4 6.1 4.8 57.1 13.6 N = 27 40.7 59.3 N = 16 6.2 93.8 N 30 169 135 147 165 157 122 2 120 2 27 84 20 11 16 15 Learned Percent N = 69 98.6 1.4 N = 395 37.5 28.1 34.4 N = 148 2.0 0.0 0.0 98.0 N = 145 4.8 95.2 N = 111 92.8 2.7 2.7 1.8 N = 103 92.2 1.0 6.8 N = 3 100.0 0.0 N = 136 23.5 5.1 18.4 36.0 16.9 N = 32 78.1 21.9 N = 7 42.9 57.1 N 68 148 111 136 0 145 138 103 3 95 32 25 49 23 25 (continued) Appendices 195 Table A1 (continued) Feature Manner Means Comparison Causal Reason Purpose Result Conditional Positive-condition Negative-condition Concessive Participant Subject Complement Complement Of-verbal-group Of-prepositional-group Nesting Level-1 Level-2 Level-3 Level-4 Level-5 Level-6 Level-7 Fiction Percent N = 14 0.0 100.0 N = 36 11.1 41.7 47.2 N = 9 33.3 0.0 66.7 N = 31 25.8 74.2 N = 23 87.0 13.0 N = 419 41.8 37.9 13.4 4.5 1.7 0.5 0.2 N 14 15 17 23 20 175 159 56 19 Press Percent N = 9 44.4 55.6 N = 53 24.5 66.0 9.4 N = 15 60.0 6.7 33.3 N = 64 28.1 71.9 N = 46 26.1 73.9 N = 534 36.1 40.4 15.2 6.0 1.9 0.4 0.0 N 13 35 18 46 12 34 193 216 81 32 10 Prose Percent N = 7 71.4 28.6 N = 84 9.5 89.3 1.2 N = 20 45.0 5.0 50.0 N = 27 3.7 96.3 N = 26 11.5 88.5 N = 508 34.1 42.3 16.9 5.3 1.0 0.2 0.2 N 75 10 26 23 173 215 86 27 1 Learned Percent N = 25 84.0 16.0 N = 49 36.7 42.9 20.4 N = 23 47.8 0.0 52.2 N = 29 27.6 72.4 N = 21 14.3 85.7 N = 493 41.0 42.2 12.4 3.9 0.4 0.2 0.0 N 21 18 21 10 11 12 21 18 202 208 61 19 ... parataxis are equal in status, the first clause being the initiating clause and the second clause, the continuing clause The two clauses in a clause complex of hypotaxis are unequal: the one that can... (BNC_NEWS) The prepositional phrase with all your heart in 2- 3a augments the clause circumstantially within the domain of the clause In contrast, the non-finite clause using a bowser expands the clause, ... function as adjuncts of the matrix clauses In other words, without these two subordinate clauses, the matrix clauses can still stand alone The subordinate clauses in 1-3 c and 1-3 d are embedded in the