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4 results for “hypernym”

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zenodo44/100

Hypernym-LIBre: A free Web-based corpus from Hypernym Detection [ Hearst Pattern extractions from Hypernym-LIBre]

<p>Hypernym-LIBre ( DOI: 10.5281/zenodo.3662204 ) is a free Web-based corpus for Hypernym detection.</p> <p>Its part-of-speech tagged and dependency annotated version is present at this: (DOI: 10.5281/zenodo.3689303)</p> <p>Here we provide the hypernym-hyponym pairs that were extracted from Hypernym-LIBre using Hearst patterns. This is to further the usage of these extractions with more techniques and methods. We also provide the counts of each pattern in a separate file.</p> <p>&nbsp;</p> <p>Format:</p> <p>hyponym \t hypernym</p> <p>&nbsp;</p> <p>Format for the counts file:</p> <p>pair \t frequency of extraction</p> <p>&nbsp;</p> <p>There are 2 files, one with the pairs, one with unique pair and its counts. Both total ~430MB.</p>

opencc-by-4.0Mar 2020View details →
zenodo36/100

Hypernym-LIBre: A free Web-based Corpus for Hypernym Detection

<p>The task of finding hypernyms from large text corpora is a fundamental problem in NLP. It provides a basis for the main-stream natural language problems in AI. In our paper, we introduce a free new web-based corpus for hypernym detection and we show that using this corpus we achieve similar results to the state-of-the-art pattern-based methods achieved by a well known corpus that is not freely available.&nbsp; The dataset provided here is the one we use in our paper and we provide it with an open license so others can apply different methods and techniques for hypernym detection.</p> <p>&nbsp;</p> <p>The dataset is a combination of UMBC corpus and the Wikipedia corpus. Its dependency parsed and POS-tagged versions are available at this DOI:&nbsp; 10.5281/zenodo.3689303</p> <p>Contents:</p> <p>Hypernym-LIBre.zip&nbsp; 11.3GB compresssed, 32GB uncompressed raw text</p> <p>288 files of ~110 MB each</p> <p>&nbsp;</p> <p>10.5281/zenodo.3689303</p> <p>PoS and dep annotated</p> <p>~15GB compressed, 80GB uncompressed, 442 files of ~180MB each</p> <p>&nbsp;</p> <pre>10.5281/zenodo.3695237</pre> <p>hyponym-hypernym pairs extracted from Hypernym-LIBre using Hearst patterns</p>

opencc-by-4.0Feb 2020View details →
zenodo36/100

Hypernyms extracted from a large text corpus using Hearst lexical-syntactic patterns

<p><br> The list of hyponym-hypernym pairs was obtained by applying lexical-syntactic patterns described in &nbsp;Hearst (1992) &nbsp;on the corpus prepared by Panchenko et al. (2016). This corpus is a concatenation of the English Wikipedia (2016 dump), Gigaword, ukWaC &nbsp;and English news corpora from the Leipzig Corpora Collection. The lexical-syntactic patterns proposed by Marti Hearst (1992) and further extended and implemented in the form of FSTs by Panchenko et al. (2012) for extracting (noisy) hyponym-hypernym pairs are as follows -- (i) such&nbsp;NP as NP, NP[,] and/or NP; (ii) NP such as NP, NP[,] and/or NP; (iii) NP, NP [,] or other NP; (iv) NP, NP [,] and other NP; (v) NP, including NP, NP [,] and/or NP; (vi) NP, especially NP, NP [,] and/or NP. Pattern extraction on the corpus yields a list of 27.6 million hyponym-hypernym pairs along with the frequency of their occurrence in the corpus.&nbsp;</p>

opencc-by-4.0May 2019View details →
zenodo32/100

Hypernym-LIBre: A free Web-based Corpus for Hypernym Detection [PoS and Dep-parsed Version]

<p>Hypernym-LIBre ( DOI: 10.5281/zenodo.3662204 ) is a free Web-based corpus for Hypernym detection.</p> <p>Here we provide its part-of-speech tagged and dependency-parsed version. Both have been annotated in the text as follows:</p> <p>For every word in the corpus, there is a PoS tag and dependency annotation separated by a &#39;-&#39;.</p> <p>Example: corrected-VERB-ROOT where corrected is the raw word followed by its PoS and dependency annotation.</p> <p>&nbsp;</p> <p>The file is provided as a zip file:</p> <p>Compressed File Size: ~15GB</p> <p>Total Size: 80.6GB uncompressed</p> <p>Number of Files: 442 files, ~180MB each</p> <p>&nbsp;</p> <pre>10.5281/zenodo.3695237</pre> <p>hyponym-hypernym pairs extracted from Hypernym-LIBre using Hearst patterns</p>

opencc-by-4.0Feb 2020View details →

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