WordNet-LMF: Lexical Markup Framework

Main article is in [6]. Its abstract and introduction are copied. The goal of "KYOTO" project is also attached below.

References for Lexical Markup Framework
[1] http://www.lexicalmarkupframework.org/
[2] http://www.vossen.info/docs/2009/iwic.pdf
Claudia Eoria, Monica Monachini and Piek Vossen. 2009. Wordnet-LMF: Fleshing out a Standardized Format for Wordnet Interoperability. Proc. of ACM Workshop on Intercultural Collaboration.
- http://www.kyoto-project.eu/
[3] http://wordnetweb.princeton.edu/perl/webwn, Wordnet, online
[4] http://cwn.ling.sinica.edu.tw/, Chinese WordNet
[5] NEDO project, Takenobu Tokunaga, Virach Sornlertlamvanich, Thatsanee Charoenporn, Nicoletta Calzolari, Monica Monachini, Claudia Soria, Chu-Ren Huan, Ying-Ju Yu, Hao Yu and Laurent Prevot. 2006. Infrastructure for Standardization of Asian Language Resources, Proc. of COLING/ACL Main Conference Poster Session.
- http://www.tech.nedo.go.jp/PDF/100013569.pdf datacategory is specified!
- http://www.tech.nedo.go.jp/PDF/100011472.pdf
[6] Chinese WordNet - LMF (submitted paper) - link available until 17/Jun/2009

Abstract
Lexical Markup Framework (LMF, ISO-24613) is the ISO standard which provides a common standardized framework for the construction of natural language processing lexicons. LMF facilitates data exchange among computational linguistic resources, and also promises a convenient uniformity for future application. This study describes the design and implementation of the WordNet-LMF used to represent lexical semantics in Chinese WordNet. The compiled CWN-LMF will be released to public for linguistic researches.

Princeton WordNet[1] is an English lexical database that groups nouns, verbs, adjectives and adverbs into sets of cognitive synonyms, which are named as synsets (Fellbaum, 1998; Miller, 1995). The Global WordNet Association (GWA)[2] built on the results of Princeton WordNet and Euro WordNet (Vossen, 2004) is a free and public association that provides a platform to share and connect all languages in the world. For Mandarin Chinese in Taiwan, Huang et al. (2004) constructed the Academia Sinica Bilingual Ontological Wordnet (Sinica BOW) which integrates WordNet, English-Chinese Translation Equivalents Database (ECTED) and SUMO for cross-language linguistic studies. As a follow-up, Chinese WordNet (CWN) has been built as a robust lexical knowledge system which also embodies a precise expression of sense relations (Huang et al., 2008). In recent years, WordNet-like resources have become one of the most reliable and essential resources for linguistic studies for all languages (Magnini and Cavaglia, 2000; Soria et al. 2009; Strapparava and Valitutti, 2004).
Lexical Markup Framework (LMF, ISO-24613) is the ISO standard which provides a common standardized framework for the construction of natural language processing lexicons (Francopoulo et al., 2009). One important purpose of LMF is to define a standard for lexicons which covers multilingual lexical information (Francopoulo et al., 2006b). In this study, we describe the design and implementation of the Wordnet-LMF (Soria et al. 2009) to represent lexical semantics in Chinese WordNet.

[1] Wordnet, available online at http://wordnetweb.princeton.edu/perl/webwn

[2] Global WordNet Association (GWA), available online at http://www.globalwordnet.org/

KYOTO
The goal of KYOTO is a system that allows people in communities to define the meaning of their words and terms in a shared Wiki platform so that it becomes anchored across languages and cultures but also so that a computer can use this knowledge to detect knowledge and facts in text. Whereas the current Wikipedia uses free text to share knowledge, KYOTO will represent this knowledge so that a computer can understand it. For example, the notion of environmental footprint will become defined in the same way in all these languages but also in such a way that the computer knows what information is necessary to calculate a footprint. With these definitions it will be possible to find information on footprints in documents, websites and reports so that users can directly ask the computer for actual information in their environment, e.g. what is the footprint of their town, their region or their company.