By Adam Przepiórkowski, Maciej Ogrodniczuk
This booklet constitutes the refereed complaints of the ninth foreign convention on Advances in usual Language Processing, PolTAL 2014, Warsaw, Poland, in September 2014. The 27 revised complete papers and 20 revised brief papers offered have been rigorously reviewed and chosen from eighty three submissions. The papers are geared up in topical sections on morphology, named entity attractiveness, time period extraction; lexical semantics; sentence point syntax, semantics, and computing device translation; discourse, coreference answer, automated summarization, and query answering; textual content type, info extraction and data retrieval; and speech processing, language modelling, and spell- and grammar-checking.
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Extra info for Advances in Natural Language Processing: 9th International Conference on NLP, PolTAL 2014, Warsaw, Poland, September 17-19, 2014. Proceedings
However, it does not take into account the analysis of the morphological structure of lexemes nor the recognition of mutual lexical morphemes within derivational families. An accurate and linguistically justiﬁed analysis of Croatian lexemes in terms of morphemes and aﬃxes used in their derivation is one of our main objectives in the building of CroDeriV. In the next section we brieﬂy describe its structure and design. 2 CroDeriV CroDeriV is a morphological database built by means of combining rule-based processing with manual checking of results.
This paper deals with the processing of derivational morphology in Croatian and focuses on the expansion of CroDeriV – a resource with data on morphological structure and derivational relations. The purpose of CroDeriV is to systematically present the morphological structure and derivational relations of Croatian lexemes, and to use this data for the enrichment and development of existing resources and tools, as well as of new ones. One of the objectives in this ongoing project is to build an analyzer for Croatian capable of analyzing both inﬂectional and derivational morphemes.
The proposed solution outperforms several state-of-the-art methods that are based on word-to-word similarity functions. Keywords: Morphological generator, similarity of proper names, word similarity metric, Named Entity Recognition, Information Extraction. 1 Introduction Lexicons of proper names (henceforth, PNs) are valuable resources for many natural language processing tasks, especially for Named Entity Recognition (henceforth, NER). Most PN inﬂected forms in text cannot be straightforwardly matched in lexicon.