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Dictionary Users Do Look up Frequent Words. a Logfile Analysis
Erschienen in: Müller-Spitzer, Carolin (Hrsg.): Using Online Dictionaries. Berlin/ Boston: de Gruyter, 2014. (Lexicographica: Series Maior 145), S. 229-249. Alexander Koplenig, Peter Meyer, Carolin Müller-Spitzer Dictionary users do look up frequent words. A logfile analysis Abstract: In this paper, we use the 2012 log files of two German online dictionaries (Digital Dictionary of the German Language1 and the German Version of Wiktionary) and the 100,000 most frequent words in the Mannheim German Reference Corpus from 2009 to answer the question of whether dictionary users really do look up fre- quent words, first asked by de Schryver et al. (2006). By using an approach to the comparison of log files and corpus data which is completely different from that of the aforementioned authors, we provide empirical evidence that indicates - contra - ry to the results of de Schryver et al. and Verlinde/Binon (2010) - that the corpus frequency of a word can indeed be an important factor in determining what online dictionary users look up. Finally, we incorporate word dass Information readily available in Wiktionary into our analysis to improve our results considerably. Keywords: log file, frequency, corpus, headword list, monolingual dictionary, multi- lingual dictionary Alexander Koplenig: Institut für Deutsche Sprache, R 5, 6-13, 68161 Mannheim, +49-(0)621-1581- 435, [email protected] Peter Meyer: Institut für Deutsche Sprache, R 5, 6-13, 68161 Mannheim, +49-(0)621-1581-427, [email protected] Carolin Müller-Spitzer: Institut für Deutsche Sprache, R 5, 6-13, 68161 Mannheim, +49-(0)621-1581- 429, [email protected] Introduction We would like to Start this chapter by asking one of the most fundamental questions for any general lexicographical endeavour to describe the words of one (or more) language(s): which words should be included in a dictionary? At first glance, the answer seems rather simple (especially when the primary objective is to describe a language as completely as possible): it would be best to include every word in the dictionary. -
Etytree: a Graphical and Interactive Etymology Dictionary Based on Wiktionary
Etytree: A Graphical and Interactive Etymology Dictionary Based on Wiktionary Ester Pantaleo Vito Walter Anelli Wikimedia Foundation grantee Politecnico di Bari Italy Italy [email protected] [email protected] Tommaso Di Noia Gilles Sérasset Politecnico di Bari Univ. Grenoble Alpes, CNRS Italy Grenoble INP, LIG, F-38000 Grenoble, France [email protected] [email protected] ABSTRACT a new method1 that parses Etymology, Derived terms, De- We present etytree (from etymology + family tree): a scendants sections, the namespace for Reconstructed Terms, new on-line multilingual tool to extract and visualize et- and the etymtree template in Wiktionary. ymological relationships between words from the English With etytree, a RDF (Resource Description Framework) Wiktionary. A first version of etytree is available at http: lexical database of etymological relationships collecting all //tools.wmflabs.org/etytree/. the extracted relationships and lexical data attached to lex- With etytree users can search a word and interactively emes has also been released. The database consists of triples explore etymologically related words (ancestors, descendants, or data entities composed of subject-predicate-object where cognates) in many languages using a graphical interface. a possible statement can be (for example) a triple with a lex- The data is synchronised with the English Wiktionary dump eme as subject, a lexeme as object, and\derivesFrom"or\et- at every new release, and can be queried via SPARQL from a ymologicallyEquivalentTo" as predicate. The RDF database Virtuoso endpoint. has been exposed via a SPARQL endpoint and can be queried Etytree is the first graphical etymology dictionary, which at http://etytree-virtuoso.wmflabs.org/sparql. -
Teaching and Learning Academic Vocabulary
Musa Nushi Shahid Beheshti University Homa Jenabzadeh Shahid Beheshti University Teaching and Learning Academic Vocabulary Developing learners' lexical competence through vocabulary instruction has always been high on second language teachers' agenda. This paper will be focusing on the importance of academic vocabulary and how to teach such vocabulary to adult EFL/ESL learners at intermediate and higher levels of proficiency in the English language. It will also introduce several techniques, mostly those that engage students’ cognitive abilities, which can in turn facilitate the process of teaching and learning academic vocabulary. Several online tools that can assist academic vocabulary teaching and learning will also be introduced. The paper concludes with the introduction and discussion of four important academic vocabulary word lists which can help second language teachers with the identification and selection of academic vocabulary in their instructional planning. Keywords: Vocabulary, Academic, Second language, Word lists, Instruction. 1. Introduction Vocabulary is essential to conveying meaning in a second language (L2). Schmitt (2010) notes that L2 learners seem cognizant of the importance of vocabulary in language learning, as evidenced by their tendency to carry dictionaries, and not grammar books, around with them. It has even been suggested that the main difference between intermediate and advanced L2 learners lies not in how complex their grammatical knowledge is but in how expanded and developed their mental lexicon is (Lewis, 1997). Similarly, McCarthy (1990) observes that "no matter how well the student learns grammar, no matter how successfully the sounds of L2 are mastered, without words to express a wide range of meanings, communication in an L2 just cannot happen in any meaningful way" (p. -
User Contributions to Online Dictionaries Andrea Abel and Christian M
The dynamics outside the paper: User Contributions to Online Dictionaries Andrea Abel and Christian M. Meyer Electronic lexicography in the 21st century (eLex): Thinking outside the paper, Tallinn, Estonia, October 17–19, 2013. 18.10.2013 | European Academy of Bozen/Bolzano and Technische Universität Darmstadt | Andrea Abel and Christian M. Meyer | 1 Introduction Online dictionaries rely increasingly on their users and leverage methods for facilitating user contributions at basically any step of the lexicographic process. 18.10.2013 | European Academy of Bozen/Bolzano and Technische Universität Darmstadt | Andrea Abel and Christian M. Meyer | 2 Previous work . Mostly focused on specific type/dimension of user contribution . e.g., Carr (1997), Storrer (1998, 2010), Køhler Simonsen (2005), Fuertes-Olivera (2009), Melchior (2012), Lew (2011, 2013) . Ambiguous, partly overlapping terms: www.wordle.net/show/wrdl/7124863/User_contributions (02.10.2013) www.wordle.net/show/wrdl/7124863/User_contributions http:// 18.10.2013 | European Academy of Bozen/Bolzano and Technische Universität Darmstadt | Andrea Abel and Christian M. Meyer | 3 Research goals and contribution How to effectively plan the user contributions for new and established dictionaries? . Comprehensive and systematic classification is still missing . Mann (2010): analysis of 88 online dictionaries . User contributions roughly categorized as direct / indirect contributions and exchange with other dictionary users . Little detail given, since outside the scope of the analysis . We use this as a basis for our work We propose a novel classification of the different types of user contributions based on many practical examples 18.10.2013 | European Academy of Bozen/Bolzano and Technische Universität Darmstadt | Andrea Abel and Christian M. -
Defining Vocabulary Words Grades
Vocabulary Instruction Booster Session 2: Defining Vocabulary Words Grades 5–8 Vaughn Gross Center for Reading and Language Arts at The University of Texas at Austin © 2014 Texas Education Agency/The University of Texas System Acknowledgments Vocabulary Instruction Booster Session 2: Defining Vocabulary Words was developed with funding from the Texas Education Agency and the support and talent of many individuals whose names do not appear here, but whose hard work and ideas are represented throughout. These individuals include national and state reading experts; researchers; and those who work for the Vaughn Gross Center for Reading and Language Arts at The University of Texas at Austin and the Texas Education Agency. Vaughn Gross Center for Reading and Language Arts College of Education The University of Texas at Austin www.meadowscenter.org/vgc Manuel J. Justiz, Dean Greg Roberts, Director Texas Education Agency Michael L. Williams, Commissioner of Education Monica Martinez, Associate Commissioner, Standards and Programs Development Team Meghan Coleman, Lead Author Phil Capin Karla Estrada David Osman Jennifer B. Schnakenberg Jacob Williams Design and Editing Matthew Slater, Editor Carlos Treviño, Designer Special thanks to Alice Independent School District in Alice, Texas Vaughn Gross Center for Reading and Language Arts at The University of Texas at Austin © 2014 Texas Education Agency/The University of Texas System Vaughn Gross Center for Reading and Language Arts at The University of Texas at Austin © 2014 Texas Education Agency/The University of Texas System Introduction Explicit and robust vocabulary instruction can make a significant difference when we are purposeful in the words we choose to teach our students. -
Wiktionary Matcher
Wiktionary Matcher Jan Portisch1;2[0000−0001−5420−0663], Michael Hladik2[0000−0002−2204−3138], and Heiko Paulheim1[0000−0003−4386−8195] 1 Data and Web Science Group, University of Mannheim, Germany fjan, [email protected] 2 SAP SE Product Engineering Financial Services, Walldorf, Germany fjan.portisch, [email protected] Abstract. In this paper, we introduce Wiktionary Matcher, an ontology matching tool that exploits Wiktionary as external background knowl- edge source. Wiktionary is a large lexical knowledge resource that is collaboratively built online. Multiple current language versions of Wik- tionary are merged and used for monolingual ontology matching by ex- ploiting synonymy relations and for multilingual matching by exploiting the translations given in the resource. We show that Wiktionary can be used as external background knowledge source for the task of ontology matching with reasonable matching and runtime performance.3 Keywords: Ontology Matching · Ontology Alignment · External Re- sources · Background Knowledge · Wiktionary 1 Presentation of the System 1.1 State, Purpose, General Statement The Wiktionary Matcher is an element-level, label-based matcher which uses an online lexical resource, namely Wiktionary. The latter is "[a] collaborative project run by the Wikimedia Foundation to produce a free and complete dic- tionary in every language"4. The dictionary is organized similarly to Wikipedia: Everybody can contribute to the project and the content is reviewed in a com- munity process. Compared to WordNet [4], Wiktionary is significantly larger and also available in other languages than English. This matcher uses DBnary [15], an RDF version of Wiktionary that is publicly available5. The DBnary data set makes use of an extended LEMON model [11] to describe the data. -
Aspects of Idiom*
University of Calgary PRISM: University of Calgary's Digital Repository Calgary (Working) Papers in Linguistics Volume 07, Winter 1982 1982-01 Aspects of idiom* Sayers, Coral University of Calgary Sayers, C. (1982). Aspects of idiom*. Calgary Working Papers in Linguistics, 7(Winter), 13-32. http://hdl.handle.net/1880/51297 journal article Downloaded from PRISM: https://prism.ucalgary.ca Aspects of Idiom* Coral Sayers • 1. Introduction Weinreich (1969) defines an idiom as "a complex expression • whose meaning cannot be derived from the meanings of its elements." This writer has collected examples of idioms from the English, German, Australian English, and Quebec French dialects (Appendix I) in order to examine the properties of the idiom, to explore in the literature the current concepts of idiom, and to relate relevant knowledge gained by these processes to the teaching of English as a Second Language. An idiom may be a word, a "lexical idiom," or, if it has a more complicated constituent structure, a "phrasal idiom." (Katz and Postal, 1964, cited by Fraser, 1970:23) As the lexical idiom, domi nated by a single branch syntactic category (e.g. "squatter," a noun) does not present as much difficulty as does the phrasal idiom, this paper will focus upon the latter. Despite the difficulties presented by idioms to the Trans formational Grammar model, e.g. the contradiction of the claim that virtually all sentences have a low occurrence probability and frequency (Coulmas, 1979), the consensus of opinion seems to be that idioms can be accommodated in the grammatical description. Phrasal idioms of English should be considered as a "more complicated variety of mono morphemic lexical entries." (Fraser, 1970:41) 2. -
Extracting an Etymological Database from Wiktionary Benoît Sagot
Extracting an Etymological Database from Wiktionary Benoît Sagot To cite this version: Benoît Sagot. Extracting an Etymological Database from Wiktionary. Electronic Lexicography in the 21st century (eLex 2017), Sep 2017, Leiden, Netherlands. pp.716-728. hal-01592061 HAL Id: hal-01592061 https://hal.inria.fr/hal-01592061 Submitted on 22 Sep 2017 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Extracting an Etymological Database from Wiktionary Benoît Sagot Inria 2 rue Simone Iff, 75012 Paris, France E-mail: [email protected] Abstract Electronic lexical resources almost never contain etymological information. The availability of such information, if properly formalised, could open up the possibility of developing automatic tools targeted towards historical and comparative linguistics, as well as significantly improving the automatic processing of ancient languages. We describe here the process we implemented for extracting etymological data from the etymological notices found in Wiktionary. We have produced a multilingual database of nearly one million lexemes and a database of more than half a million etymological relations between lexemes. Keywords: Lexical resource development; etymology; Wiktionary 1. Introduction Electronic lexical resources used in the fields of natural language processing and com- putational linguistics are almost exclusively synchronic resources; they mostly include information about inflectional, derivational, syntactic, semantic or even pragmatic prop- erties of their entries. -
Wiktionary Matcher Results for OAEI 2020
Wiktionary Matcher Results for OAEI 2020 Jan Portisch1;2[0000−0001−5420−0663] and Heiko Paulheim1[0000−0003−4386−8195] 1 Data and Web Science Group, University of Mannheim, Germany fjan, [email protected] 2 SAP SE Product Engineering Financial Services, Walldorf, Germany [email protected] Abstract. This paper presents the results of the Wiktionary Matcher in the Ontology Alignment Evaluation Initiative (OAEI) 2020. Wiktionary Matcher is an ontology matching tool that exploits Wiktionary as exter- nal background knowledge source. Wiktionary is a large lexical knowl- edge resource that is collaboratively built online. Multiple current lan- guage versions of Wiktionary are merged and used for monolingual on- tology matching by exploiting synonymy relations and for multilingual matching by exploiting the translations given in the resource. This is the second OAEI participation of the matching system. Wiktionary Matcher has been improved and is the best performing system on the knowledge graph track this year.3 Keywords: Ontology Matching · Ontology Alignment · External Re- sources · Background Knowledge · Wiktionary 1 Presentation of the System 1.1 State, Purpose, General Statement The Wiktionary Matcher is an element-level, label-based matcher which uses an online lexical resource, namely Wiktionary. The latter is "[a] collaborative project run by the Wikimedia Foundation to produce a free and complete dic- tionary in every language"4. The dictionary is organized similarly to Wikipedia: Everybody can contribute to the project and the content is reviewed in a com- munity process. Compared to WordNet [2], Wiktionary is significantly larger and also available in other languages than English. This matcher uses DBnary [13], an RDF version of Wiktionary that is publicly available5. -
SELECTING and CREATING a WORD LIST for ENGLISH LANGUAGE TEACHING by Deny A
Teaching English with Technology, 17(1), 60-72, http://www.tewtjournal.org 60 SELECTING AND CREATING A WORD LIST FOR ENGLISH LANGUAGE TEACHING by Deny A. Kwary and Jurianto Universitas Airlangga Dharmawangsa Dalam Selatan, Surabaya 60286, Indonesia d.a.kwary @ unair.ac.id / [email protected] Abstract Since the introduction of the General Service List (GSL) in 1953, a number of studies have confirmed the significant role of a word list, particularly GSL, in helping ESL students learn English. Given the recent development in technology, several researchers have created word lists, each of them claims to provide a better coverage of a text and a significant role in helping students learn English. This article aims at analyzing the claims made by the existing word lists and proposing a method for selecting words and a creating a word list. The result of this study shows that there are differences in the coverage of the word lists due to the difference in the corpora and the source text analysed. This article also suggests that we should create our own word list, which is both personalized and comprehensive. This means that the word list is not just a list of words. The word list needs to be accompanied with the senses and the patterns of the words, in order to really help ESL students learn English. Keywords: English; GSL; NGSL; vocabulary; word list 1. Introduction A word list has been noted as an essential resource for language teaching, especially for second language teaching. The main purpose for the creation of a word list is to determine the words that the learners need to know, in order to provide more focused learning materials. -
S Wiktionary Wikisource Wikibooks Wikiquote Wikimedia Commons
SCHWESTERPROJEKTE Wiktionary S Das Wiktionary ist der lexikalische Partner der freien Enzyklopädie Wikipedia: ein Projekt zur Erstellung freier Wörterbücher und Thesau- ri. Während die Wikipedia inhaltliche Konzepte beschreibt, geht es in ihrem ältesten Schwester- projekt, dem 2002 gegründeten Wiktionary um Wörter, ihre Grammatik und Etymologie, Homo- nyme und Synonyme und Übersetzungen. Wikisource Wikisource ist eine Sammlung von Texten, die entweder urheberrechtsfrei sind oder unter ei- ner freien Lizenz stehen. Das Projekt wurde am 24. November 2003 gestartet. Der Wiktionary-EIntrag zum Wort Schnee: Das Wörterbuch präsen- Zunächst mehrsprachig auf einer gemeinsamen tiert Bedeutung, Deklination, Synonyme und Übersetzungen. Plattform angelegt, wurde es später in einzel- ne Sprachversionen aufgesplittet. Das deutsche Teilprojekt zählte im März 2006 über 2000 Texte Wikisource-Mitarbeiter arbeiten an einer digitalen, korrekturge- und über 100 registrierte Benutzer. lesenen und annotierten Ausgabe der Zimmerischen Chronik. Wikibooks Das im Juli 2003 aus der Taufe gehobene Projekt Wikibooks dient der gemeinschaftlichen Schaf- fung freier Lehrmaterialien – vom Schulbuch über den Sprachkurs bis zum praktischen Klet- terhandbuch oder der Go-Spielanleitung Wikiquote Wikiquote zielt darauf ab, auf Wiki-Basis ein freies Kompendium von Zitaten und Das Wikibooks-Handbuch Go enthält eine ausführliche Spielanleitung Sprichwörtern in jeder Sprache zu schaffen. Die des japanischen Strategiespiels. Artikel über Zitate bieten (soweit bekannt) eine Quellenangabe und werden gegebenenfalls in die deutsche Sprache übersetzt. Für zusätzliche Das Wikimedia-Projekt Wikiquote sammelt Sprichwörter und Informationen sorgen Links in die Wikipedia. Zitate, hier die Seite zum Schauspieler Woody Allen Wikimedia Commons Wikimedia Commons wurde im September 2004 zur zentralen Aufbewahrung von Multime- dia-Material – Bilder, Videos, Musik – für alle Wi- kimedia-Projekte gegründet. -
Resources for Freelancers
Resources for Freelancers Organizations, websites and a list citation guide; online subscription available) ACES (blog, news, resources, jobs, and the Quick Check Editorial Reference Cards ACES forums): www.copydesk.org (from Copyediting.com) Copyediting Newsletter (Links, blog, jobs, Purdue’s Online Writing Lab (guides to resources, training): www.copyediting.com Chicago, MLA and APA style) Editorial Freelancers Association (Training, Garner’s Modern American Usage resources, jobs): www.the-efa.org Merriam-Webster’s Dictionary of English Usage Journalists’ Toolbox (Compendium of links The Gregg Reference Manual to useful sites) www.journaliststoolbox.org Grammar Girl’s Quick & Dirty Tips for Better Copyeditor’s Knowledge Base (Links to Writing resources for freelance copyeditors): http://www.kokedit.com/ckb.php Elephants of Style and Lapsing into a Comma (Bill Walsh) Common Errors in English Usage (Big list of quick-hit usage tips): OnlineStylebooks.com www.wsu.edu/~brians/errors/errors.html Grammar Girl’s Quick and Dirty Tips Dictionaries (transcripts of all the podcasts, more): http://www.quickanddirtytips.com Merriam-Webster Collegiate 11th (Chicago’s preferred; online free, on CD-ROM, and as a Grant Barrett’s searches (word-related sites, free app; Unabridged by subscription) Google books): http://www.copyediting.com/two-copy- Webster’s New World College (AP’s desk-power-searches preferred; also as an app) CE-L (mailing list for copyeditors): Sign up Oxford dictionaries (New Oxford American at http://www.copyediting-l.info/ free