Learning Spanish-Galician Translation Equivalents Using a Comparable Corpus and a Bilingual Dictionary

Gamallo, Pablo; Campos, José Ramom Pichel

doi:10.1007/978-3-540-78135-6_36

Cited by 8 publications

(7 citation statements)

References 18 publications

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“…Most approaches to extract translation equivalents from monolingual corpora define the contextual distribution of a word by considering bilingual pairs of seed words. In most cases, seed words are provided by external bilingual dictionaries (Fung and McKeown 1997;Fung and Yee 1998;Rapp 1999;Chiao and Zweigenbaum 2002;Shao and Ng 2004;Saralegi, Vicente, and Gurrutxaga 2008;Gamallo 2007;Gamallo and Pichel 2008;Yu and Tsujii 2009a;Ismail and Manandhar 2010;Rubino and Linarés 2011;Tamura, Watanabe, and Sumita 2012;Aker, Paramita, and Gaizauskas 2013;Ansari et al 2014). So, a word in the target language is a translation candidate of a word in the source language if it tends to co-occur with the pairs of words from the seed words.…”

Section: Cross-lingual Word Similarity From Monolingual Corporamentioning

confidence: 99%

“…Unlike most approaches to extract word translations from monolingual corpora, which are based on windowing techniques without syntactic information, we will use a method that relies on dependency-based contexts. A significant number of papers report that contexts based on syntactic dependencies outperform window-based strategies in bilingual extraction (Gamallo and Pichel 2008;Yu and Tsujii 2009b;Andrade, Matsuzaki, and Tsujii 2011;Hazem and Morin 2014).…”

Section: Cross-lingual Word Similarity From Monolingual Corporamentioning

confidence: 99%

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Contextualized Translations of Phrasal Verbs with Distributional Compositional Semantics and Monolingual Corpora

Gamallo

Sotelo

Campos

et al. 2019

Computational Linguistics

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This article describes a compositional distributional method to generate contextualized senses of words and identify their appropriate translations in the target language using monolingual corpora. Word translation is modeled in the same way as contextualization of word meaning, but in a bilingual vector space. The contextualization of meaning is carried out by means of distributional composition within a structured vector space with syntactic dependencies, and the bilingual space is created by means of transfer rules and a bilingual dictionary. A phrase in the source language, consisting of a head and a dependent, is translated into the target language by selecting both the nearest neighbor of the head given the dependent, and the nearest neighbor of the dependent given the head. This process is expanded to larger phrases by means of incremental composition. Experiments were performed on English and Spanish monolingual corpora in order to translate phrasal verbs in context. A new bilingual data set to evaluate strategies aimed at translating phrasal verbs in restricted syntactic domains has been created and released.

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Section: Cross-lingual Word Similarity From Monolingual Corporamentioning

confidence: 99%

Section: Cross-lingual Word Similarity From Monolingual Corporamentioning

confidence: 99%

Contextualized Translations of Phrasal Verbs with Distributional Compositional Semantics and Monolingual Corpora

Gamallo

Sotelo

Campos

et al. 2019

Computational Linguistics

View full text Add to dashboard Cite

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“…Distributional similarity is the validation method we used in the two proposed strategies (transitivity and cognates Candidates for translation equivalents: From each very comparable pair of articles, we calculate the distributional similarity and select the most similar word pairs, which are considered to be candidates for translation equivalents (Gamallo / Pichel 2008, Gamallo 2007. We also take into account multiwords.…”

Section: Basic Assumptionsmentioning

confidence: 99%

Strategies for building high quality bilingual lexicons from comparable corpora

Gamallo¹

2019

Parallel Corpora for Contrastive and Translation Studies

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A comparable corpus consists of documents in two or more languages or varieties which are not a translation of each other and deal with similar topics. Comparable corpora are by definition multilingual and cross-lingual text collections. The use of comparable corpora to automatically extract bilingual lexicons has been growing in recent years (Tamura et al. 2012, Aker et al. 2013, Ansari et al 2014, Hazem / Morin 2014). The main advantage of u s i n g comparable corpora to perform this extraction task is that they are easily available and make use of the internet as a huge resource of multilingual texts. Comparable corpora are more easily available than parallel texts, especially for minority languages. However, their main drawback is the low performance of the extraction systems based on them. According to Nakagawa (2001), bilingual lexicon extraction from comparable corpora is an overly difficult and ambitious objective, and much more complex than extraction from parallel and aligned corpora. It is possible, however, to use comparable corpora in a less ambitious way, not to build large and accurate bilingual lexicons from scratch, but just to filter out false bilingual pairs from those selected by other basic bilingual extraction methods. In this paper, we will focus on two basic methods for extracting bilingual lexicons: first, the construction of new bilingual dictionaries by transitivity using intermediary dictionaries and, second, the

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“…More precisely, bilingual vectors are derived from both a bilingual dictionary used to define word contexts and non-parallel corpora used to obtain bilingual word co-occurrences with those contexts. Consequently, to build bilingual word vectors, first we employ the traditional approach to extract translation equivalents from non-parallel texts (Fung and Yee 1998;Rapp 1999;Gamallo 2007;Gamallo and Pichel 2008) and then, bilingual vectors are combined using the compositional model we have defined above in the current paper's section. The vectors were built by making use of a non-parallel corpus that consists of an English part containing the first 200M words from ukWaC corpus (Baroni et al 2009).…”

Section: A Case Study: Translating Polysemous Wordsmentioning

confidence: 99%

The role of syntactic dependencies in compositional distributional semantics

Gamallo

2017

Corpus Linguistics and Linguistic Theory

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This article provides a preliminary semantic framework for Dependency Grammar in which lexical words are semantically defined as contextual distributions (sets of contexts) while syntactic dependencies are compositional operations on word distributions. More precisely, any syntactic dependency uses the contextual distribution of the dependent word to restrict the distribution of the head, and makes use of the contextual distribution of the head to restrict that of the dependent word. The interpretation of composite expressions and sentences, which are analyzed as a tree of binary dependencies, is performed by restricting the contexts of words dependency by dependency in a left-to-right incremental way. Consequently, the meaning of the whole composite expression or sentence is not a single representation, but a list of contextualized senses, namely the restricted distributions of its constituent (lexical) words. We report the results of two large-scale corpus-based experiments on two different natural language processing applications: paraphrasing and compositional translation.

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Learning Spanish-Galician Translation Equivalents Using a Comparable Corpus and a Bilingual Dictionary

Cited by 8 publications

References 18 publications

Contextualized Translations of Phrasal Verbs with Distributional Compositional Semantics and Monolingual Corpora

Contextualized Translations of Phrasal Verbs with Distributional Compositional Semantics and Monolingual Corpora

Strategies for building high quality bilingual lexicons from comparable corpora

The role of syntactic dependencies in compositional distributional semantics

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