By Adam Przepiórkowski, Maciej Ogrodniczuk
This ebook constitutes the refereed lawsuits of the ninth foreign convention on Advances in common Language Processing, PolTAL 2014, Warsaw, Poland, in September 2014. The 27 revised complete papers and 20 revised brief papers offered have been conscientiously reviewed and chosen from eighty three submissions. The papers are geared up in topical sections on morphology, named entity reputation, time period extraction; lexical semantics; sentence point syntax, semantics, and computing device translation; discourse, coreference solution, computerized summarization, and query answering; textual content type, details extraction and knowledge retrieval; and speech processing, language modelling, and spell- and grammar-checking.
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Extra resources for Advances in Natural Language Processing: 9th International Conference on NLP, PolTAL 2014, Warsaw, Poland, September 17-19, 2014. Proceedings
As a result, the complex word similarity function called NamEnSim2 was constructed, associated with the initial selection of candidates (performed as a simple morphological ﬁltering applied to compared words). Details of the solution and the previous evaluation results are presented in . In the work presented here we decided to apply the same evaluation process as proposed in  in order to show that the solution proposed here outperforms the method combining several similarity functions and the single metric approaches too.
Galiotou, and A. Ralli suﬃx) and for their derivatives [[stemN –o–[bound stem]N ]+derivational suﬃx [32, 33] respectively. A similar debate about the nature of the bound elements has also been going on in English, with three diﬀerent morphological classiﬁcations at play: ‘aﬀﬁxes’, ‘combining forms’ and ‘bound stems’. g. Francophile vs. philanthropic ), the other two are equivalent to the contradictory views in MG. g. –crat, –naut, –phile). This term is usually adopted in order to describe disputable elements that are diﬃcult to appoint to one or the other category , like forms arising from blends, clippings etc.
As expected, although the recall was 100%, the precision of the automated root assignment signiﬁcantly decreased. However, the ﬁnal results of the conducted experiment can be considered satisfactory. 4%) has been correctly assigned to at least one noun from HML, thus enabling the automated expansion of derivational families. On the top of that, we obtained 1,753 new nominal roots through manual evaluation, which can be used in the further processing. From the initial set of 20,554 nouns, this simple automated approach assigned the correct root to more than half (12,227) of the nouns.