LERIL : Collaborative Effort for Creating Lexical Resources
Akshar Bharati, Dipti M Sharma, Vineet Chaitanya, Amba P Kulkarni, Rajeev Sangal, Durgesh D Rao
备注：
[ To appear in Proceedings of Workshop on Language Resources in Asia, along with NLPRS-2001, Tokyo, 27-30 November 2001] Appeared in the Proceedings of Workshop on Language Resources in Asia, along with NLPRS-2001, Tokyo, 27-30 November 2001. Appeared in the proceedings of Workshop on Language Resources in Asia, along with NLPRS-2001, Tokyo, 27-30 November 2001
The paper reports on efforts taken to create lexical resources pertaining to Indian languages, using the collaborative model. The lexical resources being developed are: (1) Transfer lexicon and grammar from English to several Indian languages. (2) Dependencey tree bank of annotated corpora for several Indian languages. The dependency trees are based on the Paninian model. (3) Bilingual dictionary of 'core meanings'.
This paper examines approaches to generate lexical resources for endangered languages. Our algorithms construct bilingual dictionaries and multilingual thesauruses using public Wordnets and a machine translator (MT). Since our work relies on only one bilingual dictionary between an endangered language and an "intermediate helper" language, it is applicable to languages that lack many existing resources.
This paper presents the steps involved in creating an electronic lexical knowledge base from the 1987 Penguin edition of Roget's Thesaurus. Semantic relations are labelled with the help of WordNet. The two resources are compared in a qualitative and quantitative manner. Differences in the organization of the lexical material are discussed, as well as the possibility of merging both resources.
Bilingual dictionaries are expensive resources and not many are available when one of the languages is resource-poor. In this paper, we propose algorithms for creation of new reverse bilingual dictionaries from existing bilingual dictionaries in which English is one of the two languages. Our algorithms exploit the similarity between word-concept pairs using the English Wordnet to produce reverse dictionary entries. Since our algorithms rely on available bilingual dictionaries, they are applicable to any bilingual dictionary as long as one of the two languages has Wordnet type lexical ontology.
Federal University of Juiz de Fora（茹伊斯迪福拉联邦大学）；Brazilian National Council for Scientific and Technological Development – CNPq（巴西国家科学技术发展委员会（CNPq））；Federal University of Minas Gerais（米纳斯吉拉斯联邦大学）
This paper presents Lutma, a collaborative, semi-constrained, tutorial-based tool for contributing frames and lexical units to the Global FrameNet initiative. The tool parameterizes the process of frame creation, avoiding consistency violations and promoting the integration of frames contributed by the community with existing frames. Lutma is structured in a wizard-like fashion so as to provide users with text and video tutorials relevant for each step in the frame creation process. We argue that this tool will allow for a sensible expansion of FrameNet coverage in terms of both languages and …
University of Cambridge（剑桥大学）；Technion, IIT（以色列理工学院）；CNRS（法国国家科学研究中心）；ENS/PSL（巴黎高等师范学院/巴黎文理研究大学）；Univ. Sorbonne nouvelle/USPC（新索邦大学/巴黎索邦西岱大学）
We introduce Multi-SimLex, a large-scale lexical resource and evaluation benchmark covering datasets for 12 typologically diverse languages, including major languages (e.g., Mandarin Chinese, Spanish, Russian) as well as less-resourced ones (e.g., Welsh, Kiswahili). Each language dataset is annotated for the lexical relation of semantic similarity and contains 1,888 semantically aligned concept pairs, providing a representative coverage of word classes (nouns, verbs, adjectives, adverbs), frequency ranks, similarity intervals, lexical fields, and concreteness levels. Additionally, owing to the…
Creating a Hybrid Rule and Neural Network Based Semantic Tagger using Silver Standard Data: the PyMUSAS framework for Multilingual Semantic Annotation
1 UCREL, Lancaster University, UK；2 Manchester Metropolitan University, UK；3 Centre for Language；Communication Studies, Trinity College, Dublin, Ireland；4 School of English, Communication；Philosophy, Cardiff University, Wales；5 Independent Researcher；6 Fiontar \& Scoil na Gaeilge, Dublin City University, Ireland；7 Hubei University, China
We present the results of an investigation into how the set of elementary trees of a Lexicalized Tree Adjoining Grammar can be represented in the lexical knowledge representation language DATR (Evans & Gazdar 1989a,b). The LTAG under consideration is based on the one described in Abeille et al. (1990). Our approach is similar to that of Vijay-Shanker & Schabes (1992) in that we formulate an inheritance hierarchy that efficiently encodes the elementary trees. However, rather than creating a new representation formalism for this task, we employ techniques of established utility in other lexicall…
Multi-perspective Alignment for Increasing Naturalness in Neural Machine Translation
CLCG, University of Groningen（格罗宁根大学CLCG）；Department of Computer Science, Aalborg University（奥尔堡大学计算机科学系）；Departament de Llenguatges i Sistemes Informàtics, Universitat d’Alacant（阿莱康特大学语言与信息系统系）
Skolkovo Institute of Science and Technology（斯科尔科沃科学技术学院）；Lomonosov Moscow State University（罗蒙诺索夫莫斯科国立大学）
Ontologies, taxonomies, and thesauri are used in many NLP tasks. However, most studies are focused on the creation of these lexical resources rather than the maintenance of the existing ones. Thus, we address the problem of taxonomy enrichment. We explore the possibilities of taxonomy extension in a resource-poor setting and present methods which are applicable to a large number of languages. We create novel English and Russian datasets for training and evaluating taxonomy enrichment models and describe a technique of creating such datasets for other languages.
