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1

ReqTagger: A Rule-Based Tagger for Automatic Glossary of Terms Extraction from Ontology Requirements

Wiśniewski Dawid, Potoniec Jędrzej, Ławrynowicz Agnieszka

Foundations of Computing and Decision Sciences

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2022

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Vol. 47, No. 1

65--86

EN

Glossary of Terms extraction from textual requirements is an impor- tant step in ontology engineering methodologies. Although initially it was intended to be performed manually, last years have shown that some degree of automatization is possible. Based on these promising approaches, we introduce a novel, human inter- pretable, rule-based method named ReqTagger, which can extract candidates for ontology entities (classes or instances) and relations (data or object properties) from textual requirements automatically. We compare ReqTagger to existing automatic methods on an evaluation benchmark consisting of over 550 requirements and tagged with over 1700 entities and relations expected to be extracted. We discuss the quality of ReqTagger and provide details showing why it outperforms other methods. We also publish both the evaluation dataset and the implementation of ReqTagger.

2

Benchmarking high performance architectures with natural language processing algorithms

Kuta M., Kitowski J.

Computer Science

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2011

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Vol. 12

19-31

EN

Natural Language Processing algorithms are resource demanding, especially when tuning to inflective language like Polish is needed. The paper presents time and memory requirements of part of speech tagging and clustering algorithms applied to two corpora of the Polish language. The algorithms are benchmarked on three high performance platforms of different architectures. Additionally sequential versions and OpenMP implementations of clustering algorithms were compared.

PL

Algorytmy przetwarzania języka naturalnego mają duże zapotrzebowanie na zasoby komputerowe, szczególnie gdy wymagane jest dostosowanie algorytmu do języka fleksyjnego jakim jest np. język polski. Artykuł przedstawia wymagania czasowe i pamięciowe algorytmów tagowania częściami mowy oraz algorytmów klasteryzacji zastosowanych do dwóch korpusów języka polskiego. Dokonano benchmarkingu algorytmów na trzech platformach wysokiej wydajności reprezentujących różne architektury. Dodatkowo porównano wersję sekwencyjną oraz implementacje OpenMP algorytmów klasteryzacji.

3

Massive multi lingual corpus compilation: Acquis Communautaire and totale

Erjavec T., Ignat C., Pouliquen B., Steinberger R.

Archives of Control Sciences

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2005

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Vol. 15, no. 4

529-540

EN

Large, uniformly encoded collections of texts, corpora, are an invaluable source of data, not only for linguists, but also for Language Technology tools. Especially useful are multilingual parallel corpora, as they enable, e.g. the induction of translation knowledge in the shape of multilingual lexica or full-fledged machine translation models. But parallel corpora, esp. large ones, are still scare, and have been, so far, difficult to acquire; recently, however, a large new source of paralel texts has become available on the Web, which contains EU law texts (the Acquis Communautaire) in all the languages of the current EU, and more, i.e. parallel texts in over twenty different languages. The paper discusses the compilation of this text collection into the massively multilingual JRC-Acquis corpus, which is freely available for research use.Next, the text annotation tool "totale", which performs multilingual text tokenization, tagging and lemmatisation is presented. The tool implements a simple pipelined architecture ahich is, for the most part, fully trainable, requiring a word-level syntactically annotated text corpus and, optionally, a morphological lexicon. We describe the MULTEXT-East corpus and lexicons, which have been used to train totale for for seven languages, and the application of the tool to the Slovene part of the JRC-Acquis corpus.

4

Tagowanie i dezambiguacja morfosyntaktyczna : przegląd metod i oprogramowania

Dębowski Ł.

Prace Instytutu Podstaw Informatyki Polskiej Akademii Nauk

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2001

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Nr 934

1-31

PL

Przedstawiono aktualne metody i dostępne oprogramowanie do automatycznego tagowania i uczenia się tagerów. Omówiono skuteczność zastosowań przedstawionych metod i oprogramowania do dezambiguacji morfosyntaktycznej tekstów w językach naturalnych.

EN

We present state-of-the-art methods and available software for automatic tagging and tagger learning. Furthermore, we discuss applicability of presented methods and software for morphosyntactic disambiguation of texts in natural languages.