Grammar Engineering for a Customer: a Case Study with Five Languages

Ranta, Aarne; Unger, Christina; Hussey, Daniel Vidal

doi:10.18653/v1/w15-3301

Cited by 3 publications

(3 citation statements)

References 15 publications

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“…But this is in fact the very point: since GF grammars are easy to adapt to specific domains, they are a useful technique when high quality is expected and the coverage can be limited. This way of using grammars has also shown commercial potential (Ranta et al, 2015).…”

Section: Discussionmentioning

confidence: 99%

Proceedings of the Eighth SIGHAN Workshop on Chinese Language Processing

Yu¹,

Zhi-fang²,

Zhang³

et al. 2015

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Discourse in linguistics refers to a unit of language longer than a single sentence. It has not been well studied in the research community of computational linguistics, but it has attracted more and more attention in very recent years. This talk consists of two parts, i.e., discourse and machine translation. We will first give an overview about discourse and review the research state-of-the-art of discourse from both linguistics and computational viewpoints, and then discuss how machine translation can benefit from discourse-level information. Finally, we conclude the talk with some future direction discussions. BiographyZHANG Min: a distinguished professor and vice dean of the school of computer science and technology, director of the research Institute for Human Language Technology at Soochow University (China), received his Ph.D. degree in computer science from Harbin Institute of Technology (China) in 1997. He has studied and worked oversea in industry and academy at South Korea and Singapore since 1997 to 2013. His current research interests include machine translation and natural language processing. He has co-authored 2 Springer books and more than 130 papers in leading journals and conferences, and co-edited 13 books published by Springer and IEEE. He is an associate editor of IEEE T-ASLP (2015-2017).SONG Rou: a professor and Ph.D. supervisor at Applied Linguistics and Computer Application in Beijing Language and Culture University, received his Bachelor degree in mathematics and mechanics from Beijing University in 1968 and his mater Master degree in computer science from Beijing University in 1981. He has been working on Chinese Information Processing study for tens of years as the PIs of more than 10 national-level projects with the research focuses on discourse analysis, Chinese word segmentation, Computer-aided proofreading, Chinese word attribute, Chinese Orthographic Computing and Chinese POS and so on. He has published more than 100 papers at leading journals and conferences in computer science and linguistics. He has developed and commercialized several softwares with two patents. He has received several awards from Beijing City and MOE, China. He has been appointed as guest professors in a few domestic and oversea universities and research institutes. v

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Section: Discussionmentioning

confidence: 99%

Proceedings of the Eighth SIGHAN Workshop on Chinese Language Processing

Yu¹,

Zhi-fang²,

Zhang³

et al. 2015

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“…Correct BLEU, GF BLEU, Google for descriptions of buildings from a text database, with Swedish as source and Finnish, German, and Spanish as target languages (Ranta, Unger, and Vidal Hussey 2015). The input was not pure CNL, but free texts written by many different humans, containing typos and often in telegraphic style dropping articles, etc.…”

Section: Languagementioning

confidence: 99%

“…Going down to lower levels of interlingua expectedly lowers the quality of translation. The first comprehensive experiment in this direction was a translation system Table 6 Quality evaluation for layered translation in Ranta, Unger, and Vidal Hussey (2015). "CNL" means translation with the semantic grammar, "robust" means CNL with other layers.…”

Section: Evaluations Of Layered Translationmentioning

confidence: 99%

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

Ranta

Angelov

Grūzītis

et al. 2020

Computational Linguistics

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Abstract syntax is an interlingual representation used in compilers. Grammatical Framework (GF) applies the abstract syntax idea to natural languages. The development of GF started in 1998, first as a tool for controlled language implementations, where it has gained an established position in both academic and commercial projects. GF provides grammar resources for over 40 languages, enabling accurate generation and translation, as well as grammar engineering tools and components for mobile and Web applications. On the research side, the focus in the last ten years has been on scaling up GF to wide-coverage language processing. The concept of abstract syntax offers a unified view on many other approaches: Universal Dependencies, WordNets, FrameNets, Construction Grammars, and Abstract Meaning Representations. This makes it possible for GF to utilize data from the other approaches and to build robust pipelines. In return, GF can contribute to data-driven approaches by methods to transfer resources from one language to others, to augment data by rule-based generation, to check the consistency of hand-annotated corpora, and to pipe analyses into high-precision semantic back ends. This article gives an overview of the use of abstract syntax as interlingua through both established and emerging NLP applications involving GF.

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Chinese in the Grammatical Framework: Grammar, Translation, and Other Applications Anonymous

Ranta¹,

Tian²,

Qiao³

2015

Proceedings of the Eighth SIGHAN Workshop on Chinese Language Processing

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Grammatical Framework (GF) is a grammar formalism based on type theory and functional programming. It is also a platform for multilingual applications such as translation, localization, and information retrieval. To enable non-linguist programmers to build linguistically precise applications, GF provides a Resource Grammar Library (RGL), which defines the basic syntax, morphology, and lexicon of languages in the form of easily usable software libraries. The RGL is an open-source collaborative project, which currently covers 30 languages with a shared tree structure. Chinese, in addition to basic RGL, has a translation lexicon of over 30,000 lemmas and a mobile translation app. This paper gives an overview of GF, emphasizing applications where Chinese is related to other languages. We also address the theoretical question how Chinese fits into the framework with a shared tree structure.

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Grammar Engineering for a Customer: a Case Study with Five Languages

Cited by 3 publications

References 15 publications

Proceedings of the Eighth SIGHAN Workshop on Chinese Language Processing

Proceedings of the Eighth SIGHAN Workshop on Chinese Language Processing

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

Chinese in the Grammatical Framework: Grammar, Translation, and Other Applications Anonymous

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