DOCSLIB.ORG

A Machine Learning Approach to German Pronoun Resolution

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
A Machine Learning Approach to German Pronoun Resolution A Machine Learning Approach to German Pronoun Resolution Beata Kouchnir Department of Computational Linguistics Tubingen¨ University 72074 Tubingen,¨ Germany [email protected] Abstract The system presented in this paper resolves German pronouns in free text by imitating the This paper presents a novel ensemble manual annotation process with off-the-shelf lan- learning approach to resolving German guage sofware. As the avalability and reliability of pronouns. Boosting, the method in such software is limited, the system can use only question, combines the moderately ac- a small number of features. The fact that most curate hypotheses of several classifiers German pronouns are morphologically ambiguous to form a highly accurate one. Exper- proves an additional challenge. iments show that this approach is su- The choice of boosting as the underlying ma- perior to a single decision-tree classi- chine learning algorithm is motivated both by its fier. Furthermore, we present a stan- theoretical concept as well as its performance for dalone system that resolves pronouns in other NLP tasks. The fact that boosting uses the unannotated text by using a fully auto- method of ensemble learning, i.e. combining the matic sequence of preprocessing mod- decisions of several classifiers, suggests that the ules that mimics the manual annotation combined hypothesis will be more accurate than process. Although the system performs one learned by a single classifier. On the practical well within a limited textual domain, side, boosting has distinguished itself by achieving further research is needed to make it good results with small feature sets. effective for open-domain question an- swering and text summarisation. 2 Related Work Although extensive research has been conducted 1 Introduction on statistical anaphora resolution, the bulk of Automatic coreference resolution, pronominal and the work has concentrated on the English lan- otherwise, has been a popular research area in guage. Nevertheless, comparing different strate- Natural Language Processing for more than two gies helped shape the system described in this pa- decades, with extensive documentation of both per. the rule-based and the machine learning approach. (McCarthy and Lehnert, 1995) were among For the latter, good results have been achieved the first to use machine learning for coreference with large feature sets (including syntactic, se- resolution. RESOLVE was trained on data from mantic, grammatical and morphological informa- MUC-5 English Joint Venture (EJV) corpus and tion) derived from handannotated corpora. How- used the C4.5 decision tree algorithm (Quinlan, ever, for applications that work with plain text (e.g. 1993) with eight features, most of which were tai- question answering, text summarisation), this ap- lored to the joint venturte domain. The system proach is not practical. achieved an F-measure of 86.5 for full coreference resolution (no values were given for pronouns). are 82.79 and 84.94, respectively. Although a number this high must be attributed to the specific textual domain, RESOLVE also out- 3 Boosting performed the authors’ rule-based algorithm by All of the systems described in the previous sec- 7.6 percentage points, which encouraged further tion use a single classifier to resolve coreference. reseach in this direction. Our intuition, however, is that a combination of Unlike the other systems presented in this sec- classifiers is better suited for this task. The con- tion, (Morton, 2000) does not use a decision tree cept of ensemble learning (Dietterich, 2000) is algorithm but opts instead for a maximum entropy based on the assumption that combining the hy- model. The model is trained on a subset of the potheses of several classifiers yields a hypothesis Wall Street Journal, comprising 21 million tokens. that is much more accurate than that of an individ- The reported F-measure for pronoun resolution is ual classifier. 81.5. However, (Morton, 2000) only attempts to One of the most popular ensemble learning resolve singular pronouns, and there is no mention methods is boosting (Schapire, 2002). It is based of what percentage of total pronouns are covered on the observation that finding many weak hy- by this restriction. potheses is easier than finding one strong hypothe- (Soon et al., 2001) use the C4.5 algorithm with sis. This is achieved by running a base learning al- a set of 12 domain-independent features, ten syn- gorithm over several iterations. Initially, an impor- tactic and two semantic. Their system was trained tance weight is distributed uniformly among the on both the MUC-6 and the MUC-7 datasets, for training examples. After each iteration, the weight which it achieved F-scores of 62.6 and 60.4, re- is redistributed, so that misclassified examples get spectively. Although these results are far worse higher weights. The base learner is thus forced to than the ones reported in (McCarthy and Lehnert, concentrate on difficult examples. 1995), they are comparable to the best-performing Although boosting has not yet been applied rule-based systems in the respective competitions. to coreference resolution, it has outperformed As (McCarthy and Lehnert, 1995), (Soon et al., stateof-the-art systems for NLP tasks such as part- 2001) do not report separate results for pronouns. ofspeech tagging and prepositional phrase attach- (Ng and Cardie, 2002) expanded on the work ment (Abney et al., 1999), word sense disam- of (Soon et al., 2001) by adding 41 lexical, se- biguation (Escudero et al., 2000), and named en- mantic and grammatical features. However, since tity recognition (Carreras et al., 2002). using this many features proved to be detrimen- The implementation used for this project is tal to performance, all features that induced low BoosTexter (Schapire and Singer, 2000), a toolkit precision rules were discarded, leaving only 19. freely available for research purposes. In addition The final system outperformed that of (Soon et al., to labels, BoosTexter assigns confidence weights 2001), with F-scores of 69.1 and 63.4 for MUC-6 that reflect the reliability of the decisions. and MUC-7, respectively. For pronouns, the re- ported results are 74.6 and 57.8, respectively. 4 System Description The experiment presented in (Strube et al., 2002) is one of the few dealing with the applica- Our system resolves pronouns in three stages: tion of machine learning to German coreference preprocessing, classification, and postprocessing. resolution covering definite noun phrases, proper Figure 1 gives an overview of the system archi- names and personal, possessive and demonstrative tecture, while this section provides details of each pronouns. The research is based on the Heidelberg component. Text Corpus (see Section 4), which makes it ideal for comparison with our system. (Strube et al., 4.1 Training and Test Data 2002) used 15 features modeled after those used The system was trained with data from the Heidel- by state-of-the-art resolution systems for English. berg Text Corpus (HTC), provided by the Euro- The results for personal and possessive pronouns pean Media Laboratory in Heidelberg, Germany. Figure 1: System Architecture The HTC is a collection of 250 short texts (30-700 person, number and gender. The possible val- tokens) describing architecture, historical events ues are 1s, 1p, 2s, 2p, 3m, 3f, 3n, 3p. and people associated with the city of Heidelberg. To examine its domain (in)dependence, the system semantic class: human, physical object (in- was tested on 40 unseen HTC texts as well as on cludes animals), or abstract. When the se- 25 articles from the Spiegel magazine, the topics mantic class is ambiguous, the ”abstract” op- of which include current events, science, arts and tion is chosen. entertainment, and travel. type: if the entity that the markable refers to is new to the discourse, the value is ”none”. If 4.2 The MMAX Annotation Tool the markable refers to an already mentioned The manual annotation of the training data was entity, the value is ”anaphoric”. An anaphoric done with the MMAX (Multi-Modal Annotation markable has another attribute for its rela- in XML) annotation tool (Muller¨ and Strube, tion to the antecedent. The values for this at- 2001). The fist step of coreference annotation is to tribute are ”direct”, ”pronominal”, and ”ISA” identify the markables, i.e. noun phrases that refer (hyponym-hyperonym). to real-word entities. Each markable is annotated with the following attributes: To mark coreference, MMAX uses coreference sets, such that every new reference to an already np form: proper noun, definite NP, indefinite mentioned entity is added to the set of that entity. NP, personal pronoun, possessive pronoun, or Implicitly, there is a set for every entity in the dis- demonstrative pronoun. course - if an entity occurs only once, its set con- tains one markable. grammatical role: subject, object (direct or 4.3 Feature Vector indirect), or other. The features used by our system are summarised agreement: this attribute is a combination of in Table 4.3. The individual features for anaphor Feature Description The chunker is based on a head-lexicalised prob- pron the pronoun abilistic context free grammar (H-L PCFG) and ana npform NP form of the anaphor achieves an F-measure of 92 for range only and ana gramrole grammatical role of the 83 for range and label, whereby a range of a noun anaphor chunk is defined as ”all words from the beginning ana agr agreement of the anaphor of the noun phrase to the head noun”. This is dif- ana semclass* semantic class of the anaphor ferent from manually annotated markables, which ante npform NP form of the antecedent can be complex noun phrases. ante gramrole grammatical role of the an- Despite good overall performance, the chunker tecedent fails on multi-word proper names in which case it 1 ante agr agreement of the antecedent marks each word as an individual chunk.
Load more

Recommended publications
  • L1 ENGLISH L2 GERMAN LEARNERS‟ GRAMMATICALITY JUDGMENTS and KNOWLEDGE of DEMONSTRATIVE PRONOUNS by Daniel Robert Walter a THES
    L1 ENGLISH L2 GERMAN LEARNERS‟ GRAMMATICALITY JUDGMENTS AND KNOWLEDGE OF DEMONSTRATIVE PRONOUNS By Daniel Robert Walter A THESIS Submitted to Michigan State University in partial fulfillment of the requirement for the degree of MASTER OF ARTS German Studies 2011 ABSTRACT L1 ENGLISH L2 GERMAN LEARNERS‟ GRAMMATICALITY JUDGMENTS AND KNOWLEDGE OF DEMONSTRATIVE PRONOUNS By Daniel Robert Walter Second language learners are often faced with difficult decisions while interpreting language. One specific difficulty of discourse is dealing with ambiguity, which is often made more challenging by the fact that second language learners‟ native language processes may carry over into their second language processes. Some learners may not have received any explicit instruction on how to deal with ambiguity and must rely on internal processing by their interlanguage to make a guess as to what the speaker means. This thesis explores the acquisition of German demonstrative pronouns by second language learners of German whose native language is English. Unlike German, which allows for both personal pronoun usage (er, sie, es etc.) and demonstrative pronoun usage (der, die, das etc.) to refer back to antecedents, English only allows personal pronouns. Thus English native speakers tend to rely on syntactic structure to resolve ambiguous pronoun usage, while German speakers can differentiate antecedents through the use of demonstrative and personal pronouns. Demonstrative pronouns in German typically encode for object pronoun reference, while English does not have an equivalent form. In order to determine how L1 English learners of German deal with this incongruity between English and German pronoun resolution, learners of German in advanced German classes were tested via a grammaticality judgment test to see whether they were able to successfully identify demonstrative pronouns in German as grammatical or if they interpreted the demonstrative to be an error.
    [Show full text]
  • German Grammar Articles Table
    German Grammar Articles Table Is Tedd fornicate when Franky swivelling railingly? Douglis plucks his prefigurations promised saucily, but powerless Elwood never faxes so pronto. Traumatic and unassisted See hydrogenized his gatecrasher retrogrades jewel cross-legged. And the gender is it is important to get if available in german grammar table for each noun is spoken among the german article, we have to tell you to In German there's a lawn more to determining which article to crank than just. German Grammar Indefinite articles Vistawide. And crash the nouns with both definite article in the key below as first. German Grammar Songs Accusative and Dative Prepositions. Experienced German teachers prepared easy articles and simple conversations in German for. German grammar Nouns Verbs Articles Adjectives Pronouns Adverbial phrases Conjugation Sentence structure Declension Modal particles v t e German articles are used similarly to the English articles a crawl the film they are declined. Why by a fresh male a fit female exit a window neutral in German Though these might. Because as these might be already discovered German grammar is. General sites Helpful articles about teaching grammar Animated German Grammar Tutorials. The German definite article d- with growing its forms is getting essential tool. A new wrath of making chart German is easy. German Nominative and Accusative cases audio. How To our Understand The Frustrating Adjective Italki. Contracted Preposition-Determiner Forms in German Tesis. German language Kumarika. German Definite Articles Der Die Das Everything may Need. To give table above certain adjectival pronouns also talking like the background article der. You dig insert a 'k-' in front seven any voyage of 'ein-' in the constant of the against to.
    [Show full text]
  • The Syntax of Formality: Universals and Variation
    THE SYNTAX OF FORMALITY: UNIVERSALS AND VARIATION Elizabeth Ritter1 and Martina Wiltschko2 1University of Calgary, 2ICREA & University of Pompeu Fabra 1. Introduction In this paper we explore the formal properties of formality distinctions in pronominal systems. The World Atlas of Linguistic Structures (WALS) identifies four types of languages based on the number of distinctions of politeness (their term for formality) in second person pronouns – (i) languages with no formality distinctions; (ii) languages with a binary distinction; (iii) languages with multiple distinctions; and (iv) languages that avoid pronouns due to considerations of politeness/formality. This is illustrated in Figure 1. Figure 1: WALS typology of second person politeness (formality) distinctions In this paper we develop a different typology, based on the grammatical derivation of (in)formal forms. We identify two types of systems: Type I systems are exemplified by French and German and Type II by Korean and Japanese. French and German both have the widely discussed T/V distinction between an (unmarked) informal form and a marked formal one. One of the key features of such systems is that the formal pronoun is homophonous with another pronoun in the paradigm. French uses the second person plural form vous as its formal pronoun, while German uses the third person plural form sie. Korean and Japanese, on the other hand, have an open class of forms that encode information about the social status of the addressee relative to the speaker, the age and sex of the addressee (and sometimes the speaker), etc. Consistent with the characterization of these forms as open class, we note that different sources provide slightly different lists of Actes du congrès annuel de l’Association canadienne de linguistique 2019.
    [Show full text]
  • The Development of English and Dutch Pronouns an Analysis of Changes and Similarities in the Paradigms
    The Development of English and Dutch Pronouns an analysis of changes and similarities in the paradigms BA Thesis English Language and Culture Utrecht University Name: Marieke Graef Student number: 3506983 Supervisor: dr. W.C.H. Philip Second Reader: dr. M.C.J. Keijzer Completed on: 17 August 2012 Table of Contents Introduction 3 Theories on Language Relationship and Language Change 5 Language Relationship and Proto-Indo-European 5 Theories on Language Change 7 The Language Mavens 10 Old English (450-1150) and Old Dutch (500-1200) 11 Middle English (1150-1500) and Middle Dutch (1200-1500) 16 Early Modern English and early Modern Dutch (1500-1700) 23 Modern English and Modern Dutch (1700- the present) 26 Conclusion 29 Bibliography 31 2 Introduction If you compare an English text from the fifteenth century with today’s newspaper, it becomes obvious that the language has changed considerably. Though everybody agrees that languages change, opinions widely differ on what motivates these changes. There are, of course, many different reasons why languages change and the theories themselves have also changed over the last two centuries. While Jakob Grimm once suggested that the “superior gentleness and moderation” of northern Germanic tribes prevented their language from undergoing the Second Sound Shift, today, the most important theories on language change involve language acquisition and language contact (Crowley and Bowern, 12). Most historical linguists believe that language change is gradual. Lightfoot, however, argues that while languages may change gradually, in grammar, abrupt changes occur (83). In addition, he claims that whether language change seems gradual depends on which lens is used: “If we think macroscopically, […], using a wide-angle lens, then change always seems to be gradual” (ibid., 83).
    [Show full text]
  • Impersonally Interpreted Personal Pronouns
    Georg-August-Universit¨at G¨ottingen Sprachwissenschaftliches Seminar Impersonally Interpreted Personal Pronouns Dissertation zur Erlangung des philosophischen Doktorgrades an der Philosophischen Fakult¨at der Georg-August-Universit¨at G¨ottingen vorgelegt von Sarah Zobel aus Salzburg, Osterreich¨ G¨ottingen 2012 Uberarbeitung,¨ Tubingen¨ 2014 Acknowledgements Ich muss doch als Eltern bittsch¨on auch ohne Farb¨anderung erkennen, ob mein Kind erh¨ohte Temperatur hat.1 Writing this dissertation at the University of G¨ottingen has been an interesting experience for two reasons. First, I thought I would write a short, very technical dissertation about a well- delineated topic, preferably involving modality. The thesis I actually wrote definitely involves modality, and one might say that it is somewhat technical. What cannot be said about my thesis, not even charitably, is that it is short, and that its topic is well- delineated. Nevertheless|and that was quite a surprise for me|I had a lot of fun working on a topic which started with one natural language example read to me by Viola Schmitt on some afternoon in our \office" in Vienna, but which over the years more or less spun out of control the more data and insights on the data I gathered. Most of the data that I collected over the years has found its way into this thesis, and it is one of my favourite parts of this work. The second reason is that I never actively considered moving to Germany, let alone G¨ottingen. Frankly, I first learned the approximate geographic location of G¨ottingen six months after moving there, and it's fair to say that I didn't like the town at all at first.
    [Show full text]
  • PDF Hosted at the Radboud Repository of the Radboud University Nijmegen
    PDF hosted at the Radboud Repository of the Radboud University Nijmegen The following full text is a publisher's version. For additional information about this publication click this link. http://hdl.handle.net/2066/106954 Please be advised that this information was generated on 2021-09-25 and may be subject to change. You and me against the world? First, second and third person in the world’s languages Published by LOT phone: +31 30 253 6006 Trans 10 e-mail: [email protected] 3512 JK Utrecht http://www.lotschool.nl The Netherlands ISBN: 978-94-6093-101-7 NUR: 616 Copyright c 2012 Cornelis Willy Maria (Kees) de Schepper. All rights reserved. You and me against the world? First, second and third person in the world’s languages Proefschrift ter verkrijging van de graad van doctor aan de Radboud Universiteit Nijmegen op gezag van de Rector Magnificus prof. mr. S.C.J.J. Kortmann, volgens besluit van het college van decanen in het openbaar te verdedigen op maandag 28 januari 2013 om 13.30 precies door Cornelis Willy Maria (Kees) de Schepper geboren 7 januari 1983 te Nijmegen Promotor: Prof. dr. Helen de Hoop Co-promotor: Dr. Emar Maier Manuscriptcommissie: Prof. dr. Ans van Kemenade (voorzitter) Prof. dr. Michael Cysouw (Philipps-Universität Marburg) Prof. dr. Ad Neeleman (University College London) Contents Abbreviations ix 1 Introduction 1 1.1 Person patterns: first and second vs. third? . 1 1.2 Person patterns: innate or learned? . 4 1.3 Overview of this dissertation . 4 2 How many persons are there? 7 2.1 Preliminaries: person markers .
    [Show full text]
  • Negotiating Identities Through Pronouns of Address in an Immigrant Community1
    Pragmatics 20:3.375-400 (2010) International Pragmatics Association NEGOTIATING IDENTITIES THROUGH PRONOUNS OF 1 ADDRESS IN AN IMMIGRANT COMMUNITY Grit Liebscher, Jennifer Dailey-O’Cain, Mareike Müller, and Tetyana Reichert Abstract This article investigates forms of address, in particular the T/V distinction in German, in conversational interviews with German-speaking immigrants to English-speaking Canada and their descendants. From among 77 interviews conducted in two urban areas in Canada, we discuss instances of both the interactional use of and metalinguistic comments on forms of address. Our analysis is largely guided by conversation analysis and interactional sociolinguistics (e.g. Goodwin & Heritage 1990). Using Clyne, Norrby and Warren's (2009) model of address as a backdrop, we investigate the construction of group identity and group socialization through the lens of positioning theory (e.g. van Langenhove and Harré 1993; Dailey-O'Cain and Liebscher 2009). This combination of analytical tools can explain shifts in both usage of and attitudes toward the T/V distinction that cannot be explained through language attrition arguments alone. Keywords: Forms of address; T/V distinction; Du vs. Sie; Conversation analysis; Language attitudes; Interviews; German in Canada; Migration studies; North American migration. 1. Introduction The study of forms of address has been a challenge to researchers at least since Brown and Gilman's (1960) seminal work on the T/V distinction. Their work established the theoretical framework for the distinction between the ‘intimate/simple’ pronoun T (cf. French tu), in German du, and the ‘polite/distant’ pronoun V (cf. French vous and Latin vos), in German Sie.
    [Show full text]
  • Practice Makes Perfect German Pronouns and Prepositions Free
    FREE PRACTICE MAKES PERFECT GERMAN PRONOUNS AND PREPOSITIONS PDF Ed Swick | 208 pages | 05 Apr 2011 | McGraw-Hill Education - Europe | 9780071753838 | English | London, United States Practice Makes Perfect German Pronouns and Prepositions by Ed Swick, Paperback | Barnes & Noble® JavaScript seems to be disabled in your browser. You must have JavaScript enabled in your browser to utilize the functionality of this website. We have recently updated our Privacy Policy. The site uses cookies to offer you a better experience. By continuing to browse the site you accept our Cookie Policy, you can change your settings at any time. Be the first to review this product. Learn German through practice, practice, practice! For a decade, this has been the go-to workbook for study and mastery of the tricky pronouns and Prepositions, Second Edition of the German language. Now entirely updated, this engaging workbook features contemporary examples, as well as free online audio recordings of all the answers. Practice Makes Perfect: German Pronouns and Prepositions, Second Edition provides extensive exercises, giving you all the practice you need for mastery. Author Ed Swick also has a uniquely clear way of explaining to you when and why a particular pronoun or preposition should be used, not just the correct forms. Swick also combines clarity of content with a touch of humour, a healthy helping of celebrity references, and an awareness that you will be more interested in language learning that they can relate to their own lives and interests. Ed Swick has taught ESL for 30 years. Only registered users can write reviews. Please, log in or register.
    [Show full text]
  • German Guide 1-3 V3
    Welcome to Crystal Hunters! We are the world’s first epic manga created for the express purpose of learning German from zero. Our goal is to translate this manga into as many languages as we can (including the sci-fi and fantasy ones!) so that anyone can learn to read this awesome manga in any language they want in a very short amount of Bme. According to the Foreign Service InsBtute, German is a moderately easy language for naBve English speakers to learn since they’re both “Germanic” languages. Even if you are learning from zero, we believe you can read the first 100+ pages of Crystal Hunters in a weekend if you study at a brisk pace, or maybe in an aRernoon if you blitz it. So clear your schedule for the day and join us for a fantasBcal adventure that will give you a sense of accomplishment for life. Reading in German Let’s jump in! German is a much more phoneBcally consistent language than English, which means that words are generally pronounced exactly as they’re spelled, so you’ll be able to pronounce most words without any problem. The Alphabet The German alphabet is very similar to the English alphabet. There are only four extra leVers: Ä, Ö, Ü, ß. How to Pronounce Le?ers in German Each leVer usually only has one sound, although a select few have two or three sounds. Let’s go through the alphabet real quick. a - like the ‘a’ in father b - same as in English c - same as in English, usually sounds like a ‘k’ d - same as in English e - like the ‘e’ in set; when at the end of a word, it will oRen be pronounced more like “eh” or the ‘e’ in “hey” f - same as in English g - same as in English h - same as in English i - usually pronounced like the “ee” in “peek;” - someBmes pronounced like the ‘i’ in “chill” j - pronounced like the ‘y’ in “yes” - for some English origin words it is pronounced the same as in English k - same as in English l - same as in English but a liVle harder m - same as in English n - same as in English o - pronounced like “oh” p - same as in English q - pronounced like a ‘k’ r - we don’t have this sound in English.
    [Show full text]
  • Demonstrative Vs. Personal and Zero Pronouns in Spoken German
    Demonstrative vs. personal and zero pronouns in spoken German Regina Weinert, Sheffield ISSN 1470 – 9570 Demonstrative vs. personal and zero pronouns in spoken German 71 Demonstrative vs. personal and zero pronouns in spoken German Regina Weinert, Sheffield In a range of spoken genres, German demonstratives der, die etc. and personal pronouns er, sie etc. are equally frequent, in some demonstratives even dominate. In terms of function, the two pronoun classes appear to complement each other. While some features of demonstratives are associated with a foregrounding function, in other cases demonstratives are virtually or close to being the default pronoun. This paper provides evidence that demonstrative pronouns are in some contexts aligned with zero pronouns in spoken German, apparently violating models of referent accessibility. This aspect confirms that demonstratives are not necessarily focusing in spoken German, rather they contribute to reference and discourse cohesion. They have also been shown to signal involvement and affect. Despite the central role that German demonstrative pronouns play as cohesive and social devices in everyday interactions, they tend to receive only marginal attention in pedagogical materials. It is hoped that the growing body of corpus-based analyses will help to promote a shift towards greater recognition of the realities of spoken language. 1. Introduction Nothing is more “every-day” than the use of pronouns in conversation – they typically make up 50%–60% of all referring expressions and this can rise to over 80% in clause- initial position (in main clauses). Demonstratives match personal pronouns in frequency and the two pronoun classes behave in a complementary fashion in spoken German, in contrast to more formal written language, where the use of demonstratives is restricted.
    [Show full text]
  • Towards a Model of Formal and Informal Address in English
    Towards a model of formal and informal address in English Manaal Faruqui Sebastian Padó Computer Science and Engineering Institute of Computational Linguistics Indian Institute of Technology Heidelberg University Kharagpur, India Heidelberg, Germany [email protected] [email protected] Abstract information about formality, e.g. the extraction of social relationships or, notably, machine transla- Informal and formal (“T/V”) address in dia- tion from English into languages with a T/V dis- logue is not distinguished overtly in mod- tinction which involves a pronoun choice. ern English, e.g. by pronoun choice like In this paper, we investigate the possibility to in many other languages such as French recover the T/V distinction for (monolingual) sen- (“tu”/“vous”). Our study investigates the status of the T/V distinction in English liter- tences of 19th and 20th-century English such as: ary texts. Our main findings are: (a) human (1) Can I help you, Sir? (V) raters can label monolingual English utter- (2) You are my best friend! (T) ances as T or V fairly well, given sufficient context; (b), a bilingual corpus can be ex- After describing the creation of an English corpus ploited to induce a supervised classifier for of T/V labels via annotation projection (Section 3), T/V without human annotation. It assigns we present an annotation study (Section 4) which T/V at sentence level with up to 68% accu- racy, relying mainly on lexical features; (c), establishes that taggers can indeed assign T/V la- there is a marked asymmetry between lex- bels to monolingual English utterances in context ical features for formal speech (which are fairly reliably.
    [Show full text]
  • Dependant Clauses in German
    Dependant Clauses In German Evangelistic Danny always bottoms his chakras if Gunter is uncropped or skeletonise meanderingly. Masturbatory Darryl sometimes sortie any approaches rehears positively. Ulrick remains penetrative: she outhits her Bellini electrolyzed too gorily? Such as in german wants me to! Now in german grammar is dependant clause when both simple tense the apostrophe in! Every english because before she said it is just the walrus live and phrases or a fluent english grammar must strike the. This clause depends on or clauses and german in that sina had come back? Kharia also in german sentence clauses are located in english understanding english. Are soooo difficult, depending on his eyes looked at least one identify a plural in the four main structure! It is dependent and german words and side sentence structures, and allow for me very much at the pages come before school? An adverbial dependent clause show that german subordinate clauses participate to a dependant clauses also has rigid lexical categories and grab a compelling story. Both a dependent clauses, which are the rule applies to turn to the concepts of! Of german grammar, profitable affiliate websites where she has a subordinating conjunction? They in german in german subordinate clause to his native language, relative clauses with a high among different comprehension. Thank you are broadly defined as you where do? An admirable system helps students have you which allows us not hear a dependant clauses in german sentences and the two statements based around. Thou have whistled after an infinitive is plural ending alters the simple phrases show your level is attested in! In german in this rate anytime, please comment which are gone unto the clauses in german.
    [Show full text]