Extracting Lexical Semantic Knowledge from Wikipedia and Wiktionary

By Torsten Zesch, Christof Müller, Iryna Gurevych. International Conference on Language Resources and Evaluation, 2008

400 citations recorded by the source corpus.

Recently, collaboratively constructed resources such as Wikipedia and Wiktionary have been discovered as valuable lexical semantic knowledge bases with a high potential in diverse Natural Language Processing (NLP) tasks. Collaborative knowledge bases however significantly differ from traditional linguistic knowledge bases in various respects, and this constitutes both an asset and an impediment for research in NLP. This paper addresses one such major impediment, namely the lack of suitable programmatic access mechanisms to the knowledge stored in these large semantic knowledge bases. We present two application programming interfaces for Wikipedia and Wiktionary which are especially designed for mining the rich lexical semantic information dispersed in the knowledge bases, and provide efficient and structured access to the available knowledge. As we believe them to be of general interest to the NLP community, we have made them freely available for research purposes.

Subfields: Artificial Intelligence, Communication

View Paper: https://www.semanticscholar.org/paper/354a726f4c0a438a0ba8bb1a09d81c30d4b06862

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Citations in the corpus

Wiki-40B: Multilingual Language Model Dataset (2020, methodology): “The available libraries to clean up Wikipedia text (Zesch et al., 2008; Milne and Witten, 2013) do not provide download-able dumps of the results, so we were left with two options: TensorFlow Datasets or Google’s internal cleaned-up version of Wikipedia’s text.”
An open-source toolkit for mining Wikipedia (2013, methodology): “To demonstrate this, we evaluate the measures in English using the WordSimilarity-353 collection [8], and in German using the Gur 350 dataset [30].”
Wiktionary: a new rival for expert-built lexicons? Exploring the possibilities of collaborative lexicography (2012, methodology): “Notwithstanding, Wiktionary has been successfully employed in multiple natural language processing applications including information retrieval, semantic relatedness calculation, and speech synthesis (Etzioni et al., 2007; Müller and Gurevych, 2009; Zesch et al., 2008b; Schlippe et al., 2010).”
DBnary: Wiktionary as a Lemon-based multilingual lexical resource in RDF (2015, background): “tion initiatives like [12] (contained in UBY [5]) or Wiktionary2RDF [6].”
A Monolingual Tree-based Translation Model for Sentence Simplification (2010, methodology): “Plain Text Extraction We use JWPL (Zesch et al., 2008) to extract plain texts from Wikipedia articles by removing speciﬁc Wiki tags.”