Lecture 2: Markup and Annotation
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Talk Bank: a Multimodal Database of Communicative Interaction
Talk Bank: A Multimodal Database of Communicative Interaction 1. Overview The ongoing growth in computer power and connectivity has led to dramatic changes in the methodology of science and engineering. By stimulating fundamental theoretical discoveries in the analysis of semistructured data, we can to extend these methodological advances to the social and behavioral sciences. Specifically, we propose the construction of a major new tool for the social sciences, called TalkBank. The goal of TalkBank is the creation of a distributed, web- based data archiving system for transcribed video and audio data on communicative interactions. We will develop an XML-based annotation framework called Codon to serve as the formal specification for data in TalkBank. Tools will be created for the entry of new and existing data into the Codon format; transcriptions will be linked to speech and video; and there will be extensive support for collaborative commentary from competing perspectives. The TalkBank project will establish a framework that will facilitate the development of a distributed system of allied databases based on a common set of computational tools. Instead of attempting to impose a single uniform standard for coding and annotation, we will promote annotational pluralism within the framework of the abstraction layer provided by Codon. This representation will use labeled acyclic digraphs to support translation between the various annotation systems required for specific sub-disciplines. There will be no attempt to promote any single annotation scheme over others. Instead, by promoting comparison and translation between schemes, we will allow individual users to select the custom annotation scheme most appropriate for their purposes. -
Usage of IT Terminology in Corpus Linguistics Mavlonova Mavluda Davurovna
International Journal of Innovative Technology and Exploring Engineering (IJITEE) ISSN: 2278-3075, Volume-8, Issue-7S, May 2019 Usage of IT Terminology in Corpus Linguistics Mavlonova Mavluda Davurovna At this period corpora were used in semantics and related Abstract: Corpus linguistic will be the one of latest and fast field. At this period corpus linguistics was not commonly method for teaching and learning of different languages. used, no computers were used. Corpus linguistic history Proposed article can provide the corpus linguistic introduction were opposed by Noam Chomsky. Now a day’s modern and give the general overview about the linguistic team of corpus. corpus linguistic was formed from English work context and Article described about the corpus, novelties and corpus are associated in the following field. Proposed paper can focus on the now it is used in many other languages. Alongside was using the corpus linguistic in IT field. As from research it is corpus linguistic history and this is considered as obvious that corpora will be used as internet and primary data in methodology [Abdumanapovna, 2018]. A landmark is the field of IT. The method of text corpus is the digestive modern corpus linguistic which was publish by Henry approach which can drive the different set of rules to govern the Kucera. natural language from the text in the particular language, it can Corpus linguistic introduce new methods and techniques explore about languages that how it can inter-related with other. for more complete description of modern languages and Hence the corpus linguistic will be automatically drive from the these also provide opportunities to obtain new result with text sources. -
Collection of Usage Information for Language Resources from Academic Articles
Collection of Usage Information for Language Resources from Academic Articles Shunsuke Kozaway, Hitomi Tohyamayy, Kiyotaka Uchimotoyyy, Shigeki Matsubaray yGraduate School of Information Science, Nagoya University yyInformation Technology Center, Nagoya University Furo-cho, Chikusa-ku, Nagoya, 464-8601, Japan yyyNational Institute of Information and Communications Technology 4-2-1 Nukui-Kitamachi, Koganei, Tokyo, 184-8795, Japan fkozawa,[email protected], [email protected], [email protected] Abstract Recently, language resources (LRs) are becoming indispensable for linguistic researches. However, existing LRs are often not fully utilized because their variety of usage is not well known, indicating that their intrinsic value is not recognized very well either. Regarding this issue, lists of usage information might improve LR searches and lead to their efficient use. In this research, therefore, we collect a list of usage information for each LR from academic articles to promote the efficient utilization of LRs. This paper proposes to construct a text corpus annotated with usage information (UI corpus). In particular, we automatically extract sentences containing LR names from academic articles. Then, the extracted sentences are annotated with usage information by two annotators in a cascaded manner. We show that the UI corpus contributes to efficient LR searches by combining the UI corpus with a metadata database of LRs and comparing the number of LRs retrieved with and without the UI corpus. 1. Introduction Thesaurus1. In recent years, such language resources (LRs) as corpora • He also employed Roget’s Thesaurus in 100 words of and dictionaries are being widely used for research in the window to implement WSD. -
Studying Social Tagging and Folksonomy: a Review and Framework
Studying Social Tagging and Folksonomy: A Review and Framework Item Type Journal Article (On-line/Unpaginated) Authors Trant, Jennifer Citation Studying Social Tagging and Folksonomy: A Review and Framework 2009-01, 10(1) Journal of Digital Information Journal Journal of Digital Information Download date 02/10/2021 03:25:18 Link to Item http://hdl.handle.net/10150/105375 Trant, Jennifer (2009) Studying Social Tagging and Folksonomy: A Review and Framework. Journal of Digital Information 10(1). Studying Social Tagging and Folksonomy: A Review and Framework J. Trant, University of Toronto / Archives & Museum Informatics 158 Lee Ave, Toronto, ON Canada M4E 2P3 jtrant [at] archimuse.com Abstract This paper reviews research into social tagging and folksonomy (as reflected in about 180 sources published through December 2007). Methods of researching the contribution of social tagging and folksonomy are described, and outstanding research questions are presented. This is a new area of research, where theoretical perspectives and relevant research methods are only now being defined. This paper provides a framework for the study of folksonomy, tagging and social tagging systems. Three broad approaches are identified, focusing first, on the folksonomy itself (and the role of tags in indexing and retrieval); secondly, on tagging (and the behaviour of users); and thirdly, on the nature of social tagging systems (as socio-technical frameworks). Keywords: Social tagging, folksonomy, tagging, literature review, research review 1. Introduction User-generated keywords – tags – have been suggested as a lightweight way of enhancing descriptions of on-line information resources, and improving their access through broader indexing. “Social Tagging” refers to the practice of publicly labeling or categorizing resources in a shared, on-line environment. -
Instructions on the Annotation of Pdf Files
P-annotatePDF-v11b INSTRUCTIONS ON THE ANNOTATION OF PDF FILES To view, print and annotate your chapter you will need Adobe Reader version 9 (or higher). This program is freely available for a whole series of platforms that include PC, Mac, and UNIX and can be downloaded from http://get.adobe.com/reader/. The exact system requirements are given at the Adobe site: http://www.adobe.com/products/reader/tech-specs.html. Note: if you opt to annotate the file with software other than Adobe Reader then please also highlight the appropriate place in the PDF file. PDF ANNOTATIONS Adobe Reader version 9 Adobe Reader version X and XI When you open the PDF file using Adobe Reader, the To make annotations in the PDF file, open the PDF file using Commenting tool bar should be displayed automatically; if Adobe Reader XI, click on ‘Comment’. not, click on ‘Tools’, select ‘Comment & Markup’, then click If this option is not available in your Adobe Reader menus on ‘Show Comment & Markup tool bar’ (or ‘Show then it is possible that your Adobe Acrobat version is lower Commenting bar’ on the Mac). If these options are not than XI or the PDF has not been prepared properly. available in your Adobe Reader menus then it is possible that your Adobe Acrobat version is lower than 9 or the PDF has not been prepared properly. This opens a task pane and, below that, a list of all (Mac) Comments in the text. PDF ANNOTATIONS (Adobe Reader version 9) The default for the Commenting tool bar is set to ‘off’ in version 9. -
Linguistic Annotation of the Digital Papyrological Corpus: Sematia
Marja Vierros Linguistic Annotation of the Digital Papyrological Corpus: Sematia 1 Introduction: Why to annotate papyri linguistically? Linguists who study historical languages usually find the methods of corpus linguis- tics exceptionally helpful. When the intuitions of native speakers are lacking, as is the case for historical languages, the corpora provide researchers with materials that replaces the intuitions on which the researchers of modern languages can rely. Using large corpora and computers to count and retrieve information also provides empiri- cal back-up from actual language usage. In the case of ancient Greek, the corpus of literary texts (e.g. Thesaurus Linguae Graecae or the Greek and Roman Collection in the Perseus Digital Library) gives information on the Greek language as it was used in lyric poetry, epic, drama, and prose writing; all these literary genres had some artistic aims and therefore do not always describe language as it was used in normal commu- nication. Ancient written texts rarely reflect the everyday language use, let alone speech. However, the corpus of documentary papyri gets close. The writers of the pa- pyri vary between professionally trained scribes and some individuals who had only rudimentary writing skills. The text types also vary from official decrees and orders to small notes and receipts. What they have in common, though, is that they have been written for a specific, current need instead of trying to impress a specific audience. Documentary papyri represent everyday texts, utilitarian prose,1 and in that respect, they provide us a very valuable source of language actually used by common people in everyday circumstances. -
Type Annotations Specification
Type Annotations Specification (JSR 308) Michael D. Ernst [email protected] May 2, 2013 The JSR 308 webpage is http://types.cs.washington.edu/jsr308/. It contains the latest version of this document, along with other information such as a FAQ, the reference implementation, and sample annotation processors. Contents 1 Introduction 2 2 Java language syntax extensions 2 2.1 Source locations for annotations on types . 2 2.1.1 Implicit type uses are not annotatable . 5 2.1.2 Not all type names are annotatable . 5 2.2 Java language grammar changes . 6 2.2.1 Syntax of array annotations . 8 2.2.2 Syntax of annotations on qualified types . 9 2.3 Target meta-annotations for type annotations . 9 3 Class file format extensions 11 3.1 The type annotation structure . 12 3.2 The target type field: the type of annotated element . 13 3.3 The target info field: identifying a program element . 13 3.3.1 Type parameters . 13 3.3.2 Class supertypes: extends and implements clauses . 14 3.3.3 Type parameter bounds . 14 3.3.4 Method return type, receiver, and fields . 15 3.3.5 Method formal parameters . 15 3.3.6 throws clauses . 15 3.3.7 Local variables and resource variables . 15 3.3.8 Exception parameters (catch clauses) . 16 3.3.9 Type tests, object creation, and method/constructor references . 16 3.3.10 Casts and type arguments to constructor/method invocation/references . 16 3.4 The type path structure: Identifying part of a compound type . 17 A Examples of classfile structure 18 A.1 Examples of type parameter bounds . -
Folksannotation: a Semantic Metadata Tool for Annotating Learning Resources Using Folksonomies and Domain Ontologies
FolksAnnotation: A Semantic Metadata Tool for Annotating Learning Resources Using Folksonomies and Domain Ontologies Hend S. Al-Khalifa and Hugh C. Davis Learning Technology Research Group, ECS, The University of Southampton, Southampton, UK {hsak04r/hcd}@ecs.soton.ac.uk Abstract Furthermore, web resources stored in social bookmarking services have potential for educational There are many resources on the Web which are use. In order to realize this potential, we need to add suitable for educational purposes. Unfortunately the an extra layer of semantic metadata to the web task of identifying suitable resources for a particular resources stored in social bookmarking services; this educational purpose is difficult as they have not can be done via adding pedagogical values to the web typically been annotated with educational metadata. resources so that they can be used in an educational However, many resources have now been annotated in context. an unstructured manner within contemporary social In this paper, we will focus on how to benefit from 2 bookmaking services. This paper describes a novel tool social bookmarking services (in particular del.icio.us ), called ‘FolksAnnotation’ that creates annotations with as vehicles to share and add semantic metadata to educational semantics from the del.icio.us bookmarked resources. Thus, the research question we bookmarking service, guided by appropriate domain are tackling is: how folksonomies can support the ontologies. semantic annotation of web resources from an educational perspective ? 1. Introduction The organization of the paper is as follows: Section 2 introduces folksonomies and social bookmarking Metadata standards such as Dublin Core (DC) and services. In section 3, we review some recent research IEEE-LOM 1 have been widely used in e-learning on folksonomies and social bookmarking services. -
Creating and Using Multilingual Corpora in Translation Studies Claudio Fantinuoli and Federico Zanettin
Chapter 1 Creating and using multilingual corpora in translation studies Claudio Fantinuoli and Federico Zanettin 1 Introduction Corpus linguistics has become a major paradigm and research methodology in translation theory and practice, with practical applications ranging from pro- fessional human translation to machine (assisted) translation and terminology. Corpus-based theoretical and descriptive research has investigated written and interpreted language, and topics such as translation universals and norms, ideol- ogy and individual translator style (Laviosa 2002; Olohan 2004; Zanettin 2012), while corpus-based tools and methods have entered the curricula at translation training institutions (Zanettin, Bernardini & Stewart 2003; Beeby, Rodríguez Inés & Sánchez-Gijón 2009). At the same time, taking advantage of advancements in terms of computational power and increasing availability of electronic texts, enormous progress has been made in the last 20 years or so as regards the de- velopment of applications for professional translators and machine translation system users (Coehn 2009; Brunette 2013). The contributions to this volume, which are centred around seven European languages (Basque, Dutch, German, Greek, Italian, Spanish and English), add to the range of studies of corpus-based descriptive studies, and provide exam- ples of some less explored applications of corpus analysis methods to transla- tion research. The chapters, which are based on papers first presented atthe7th congress of the European Society of Translation Studies held in Germersheim in Claudio Fantinuoli & Federico Zanettin. 2015. Creating and using multilin- gual corpora in translation studies. In Claudio Fantinuoli & Federico Za- nettin (eds.), New directions in corpus-based translation studies, 1–11. Berlin: Language Science Press Claudio Fantinuoli and Federico Zanettin July/August 20131, encompass a variety of research aims and methodologies, and vary as concerns corpus design and compilation, and the techniques used to ana- lyze the data. -
Corpus Linguistics As a Tool in Legal Interpretation Lawrence M
BYU Law Review Volume 2017 | Issue 6 Article 5 August 2017 Corpus Linguistics as a Tool in Legal Interpretation Lawrence M. Solan Tammy Gales Follow this and additional works at: https://digitalcommons.law.byu.edu/lawreview Part of the Applied Linguistics Commons, Constitutional Law Commons, and the Legal Profession Commons Recommended Citation Lawrence M. Solan and Tammy Gales, Corpus Linguistics as a Tool in Legal Interpretation, 2017 BYU L. Rev. 1311 (2018). Available at: https://digitalcommons.law.byu.edu/lawreview/vol2017/iss6/5 This Article is brought to you for free and open access by the Brigham Young University Law Review at BYU Law Digital Commons. It has been accepted for inclusion in BYU Law Review by an authorized editor of BYU Law Digital Commons. For more information, please contact [email protected]. 2.GALESSOLAN_FIN.NO HEADERS.DOCX (DO NOT DELETE) 4/26/2018 3:54 PM Corpus Linguistics as a Tool in Legal Interpretation Lawrence M. Solan* & Tammy Gales** In this paper, we set out to explore conditions in which the use of large linguistic corpora can be optimally employed by judges and others tasked with construing authoritative legal documents. Linguistic corpora, sometimes containing billions of words, are a source of information about the distribution of language usage. Thus, corpora and the tools for using them are most likely to assist in addressing legal issues when the law considers the distribution of language usage to be legally relevant. As Thomas R. Lee and Stephen C. Mouritsen have so ably demonstrated in earlier work, corpus analysis is especially helpful when the legal standard for construction is the ordinary meaning of the document’s terms. -
From CHILDES to Talkbank
From CHILDES to TalkBank Brian MacWhinney Carnegie Mellon University MacWhinney, B. (2001). New developments in CHILDES. In A. Do, L. Domínguez & A. Johansen (Eds.), BUCLD 25: Proceedings of the 25th annual Boston University Conference on Language Development (pp. 458-468). Somerville, MA: Cascadilla. a similar article appeared as: MacWhinney, B. (2001). From CHILDES to TalkBank. In M. Almgren, A. Barreña, M. Ezeizaberrena, I. Idiazabal & B. MacWhinney (Eds.), Research on Child Language Acquisition (pp. 17-34). Somerville, MA: Cascadilla. Recent years have seen a phenomenal growth in computer power and connectivity. The computer on the desktop of the average academic researcher now has the power of room-size supercomputers of the 1980s. Using the Internet, we can connect in seconds to the other side of the world and transfer huge amounts of text, programs, audio and video. Our computers are equipped with programs that allow us to view, link, and modify this material without even having to think about programming. Nearly all of the major journals are now available in electronic form and the very nature of journals and publication is undergoing radical change. These new trends have led to dramatic advances in the methodology of science and engineering. However, the social and behavioral sciences have not shared fully in these advances. In large part, this is because the data used in the social sciences are not well- structured patterns of DNA sequences or atomic collisions in super colliders. Much of our data is based on the messy, ill-structured behaviors of humans as they participate in social interactions. Categorizing and coding these behaviors is an enormous task in itself. -
The British National Corpus Revisited: Developing Parameters for Written BNC2014 Abi Hawtin (Lancaster University, UK)
The British National Corpus Revisited: Developing parameters for Written BNC2014 Abi Hawtin (Lancaster University, UK) 1. The British National Corpus 2014 project The ESRC Centre for Corpus Approaches to Social Science (CASS) at Lancaster University and Cambridge University Press are working together to create a new, publicly accessible corpus of contemporary British English. The corpus will be a successor to the British National Corpus, created in the early 1990s (BNC19941). The British National Corpus 2014 (BNC2014) will be of the same order of magnitude as BNC1994 (100 million words). It is currently projected that the corpus will reach completion in mid-2018. Creation of the spoken sub-section of BNC2014 is in its final stages; this paper focuses on the justification and development of the written sub- section of BNC2014. 2. Justification for BNC2014 There are now many web-crawled corpora of English, widely available to researchers, which contain far more data than will be included in Written BNC2014. For example, the English TenTen corpus (enTenTen) is a web-crawled corpus of Written English which currently contains approximately 19 billion words (Jakubíček et al., 2013). Web-crawling processes mean that this huge amount of data can be collected very quickly; Jakubíček et al. (2013: 125) note that “For a language where there is plenty of material available, we can gather, clean and de-duplicate a billion words a day.” So, with extremely large and quickly-created web-crawled corpora now becoming commonplace in corpus linguistics, the question might well be asked why a new, 100 million word corpus of Written British English is needed.