Developing an interlingual translation lexicon using WordNets and Grammatical Framework

Abstract

The Grammatical Framework (GF) offers perfect translation between controlled subsets of natural languages. E.g., an abstract syntax for a set of sentences in school mathematics is the interlingua between the corresponding sentences in English and Hindi, say. GF "resource grammars" specify how to say something in English or Hindi; these are reused with "application grammars" that specify what can be said (mathematics, tourist phrases, etc.). More recent robust parsing and parse-tree disambiguation allow GF to parse arbitrary English text. We report here an experiment to linearise the resulting tree directly to other languages (e.g. Hindi, German, etc.), i.e., we use a languageindependent resource grammar as the interlingua. We focus particularly on the last part of the translation system, the interlingual lexicon and word sense disambiguation (WSD). We improved the quality of the wide coverage interlingual translation lexicon by using the Princeton and Universal WordNet data. We then integrated an existing WSD tool and replaced the usual GF style lexicons, which give one target word per source word, by the WordNet based lexicons. These new lexicons and WSD improve the quality of translation in most cases, as we show by examples. Both WordNets and WSD in general are well known, but this is the first use of these tools with GF.

Abstract Syntax as Interlingua: Scaling Up the Grammatical Framework from Controlled Languages to Robust Pipelines

“…It was first enabled by efficient and scalable parsing techniques (Ljunglöf 2004;Angelov 2009;Angelov and Ljunglöf 2014). The first experiments addressed full-scale morphology implementations (Forsberg and Ranta 2004;Détrez and Ranta 2012), hybrid GF-SMT translation (Enache et al 2012), and multilingual lexicon extraction (Virk et al 2014;Angelov 2014). Much of the focus has been on machine translation, with an early mobile demo (Angelov, Bringert, and Ranta 2014) and an emphasis on explainability rather than optimized BLEU scores.…”

“…From the outside it seems as if the WordNet initiative is building an interlingual lexicon, which fits very well with GF's mission to build an interlingual grammar. This was attempted for instance in Virk et al (2014). There, every synset corresponds to one abstract function and then the function's linearization in each language produces all words in the language as variants.…”