Maciej Piasecki, Marek Maziarz, Michał Marci´nczuk, Paweł K˛edzia, Adam Radziszewski, Wroclaw University of Technology
Semantic text processing (e.g. semantic text searching or Information Ex- traction) must be well grounded on the analysis performed on the lexical semantic level. Individual text words (at least selected) must be mapped on the repository of lexical senses to provide a basis for the processing of the lexico-semantic structures. The repository can be automatically in- duced from text corpora, but far better can be achieved if it is manually constructed. Thus, for the needs of the CLARIN-PL – the Polish part of the CLARIN infrastructure – we decided to build a system of lexical re- sources organised around plWordNet 3.0 as its fundament. The system comprises:
• plWordNet 3.0 – a huge wordnet for Polish providing description of lex- ical meanings (more than 260 000 planned) and the system of lexico- semantic relations (Maziarz et al. 2013),
• NELexicon 2.0 – a very large dictionary of Polish Proper Names (about 2,5 million PNs) classified into 102 semantic categories (Marci´nczuk et al., 2013),
• mapping of the plWordNet senses to extended SUMO Ontology (K˛edzia and Piasecki 2014),
• a lexicon of lexico-syntactic descriptions of multiword lexical units (about 60 000 descriptions, cf. Kurc et al. 2012),
• and a mapping of plWordNet 3.0 to an extended Princeton WordNet 3.1 for English (cf. Rudnicka et al. 2012).
PlWordNet is a huge network of lexico-semantic relations that provide de- scription for lexical senses that are represented as the network nodes. As plWordNet is exclusively focused on the faithful description of the lexical meanings, the common knowledge description is kept in a separated layer in the form of a combined upper level and middle level ontology. The map- ping between the wordnet nodes and the ontology concepts provides also formalised interpretation for the lexical meanings.
Proper Names are an open class, are not a proper part of a lexicon and represent objects in the reality. That is why they are described in a sepa- rate layer described by 102 semantic categories related to the ontology and partially mapped onto the wordnet.
Multiword lexical units are semantically described as wordnet graph nodes, but the wordnet do not include the description of their lexico-syntactic structure that is necessary for their recognition in text (Radziszewski 2013). Thus, the whole system is supplemented by a dictionary of structural de- scriptions (Kurc et al. 2012). The last element – the mapping to Princeton
WordNet – goes beyond the monolingual system, has been described in (e.g., Rudnicka et al. 2012) and will be omitted here.
As CLARIN infrastructure is meant to provide support for text processing in Humanities and Social Sciences, one can expect practically any texts deliv- ered to the system by the future users. Thus, in order to make the system of the lexical resources a feasible basis, we has to provide extensive coverage for word types and meanings. plWordNet 3.0 is built as a major exten- sion of the previous version 2.0 and it final size was provisionally set to the size approaching the size of the Polish dictionaries ever made. plWordNet 3.0 will cover at least 260 000 lexical meanings that should correspond to about 200 000 morphological base forms (entry forms) described. More- over, plWordNet has been built on the basis of the corpus as the primary knowledge source and its development was supported by a number of tools for extraction of the lexico-semantic knowledge from text. The most im- portant aspects of the plWordNet, its development process and the present state (more than 214 000 senses and 152 000 base forms) will be presented in the talk and the paper.
plWordNet is stored in a network database and is accessible via web service. It can be exported to the XML representation based on the Lexical Markup Framework representation that allows for easy integration with the existing resources of the Linked Open Data initiative.
The described system of lexical resources has been applied in, e.g., Word Sense Disambiguation (e.g. K˛edzia et al. 2014), Named Entity Recogni- tion (Marci´nczuk et al., 2013) Information Extraction (Marci´nczuk and Ptak, 2012) and Open Domain Question Answering (Marci´nczuk et al., 2013). The resource system and constructed language tools are used in several applica- tions for the CLARIN-PL users, e.g. for text semantic classification or iden- tification of text-to-text relations, that will be discussed in the talk.
References
[1] K˛edzia P., and Piasecki M. (2014), Ruled-based, Interlingual Motivated Mapping of plWordNet onto SUMO Ontology. Proceedings of the Ninth International Con- ference on Language Resources and Evaluation (LREC’14), 2014.
[2] K˛edzia P., Piasecki M., Koco´n J., Indyka-Piasecka A. (2014), Distributionally ex- tended network-based Word Sense Disambiguation in semantic clustering of Pol- ish texts, FIA 2014.
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