Building Swahili Resource Grammars for the Grammatical Framework

Nganga, Wanjiku

doi:10.1007/978-3-642-30773-7_13

Cited by 3 publications

(1 citation statement)

References 2 publications

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“…GF has also been used to model language resources for Bantu Languages. Kiswahili language has a partial morphology analyzer [12] while the Tswana Language from South Africa has a mini resource grammar [13]. Hence, no wide-coverage grammar for a Bantu Language has been made in GF so far.…”

Section: Introductionmentioning

confidence: 99%

Towards Kikamba Computational Grammar

Kituku¹,

Nganga²,

Muchemi³

2019

JDAIP

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The under-resourced Kikamba language has few language technology tools since the more efficient and popular data driven approaches for developing them suffer from data sparseness due to lack of digitized corpora. To address this challenge, we have developed a computational grammar for the Kikamba language within the multilingual Grammatical Framework (GF) toolkit. GF uses the Interlingua rule-based translation approach. To develop the grammar, we used the morphology driven strategy. Therefore, we first developed regular expressions for morphology inflection and thereafter developed the syntax rules. Evaluation of the grammar was done using one hundred sentences in both English and Kikamba languages. The results were an encouraging four n-gram BLEU score of 83.05% and the Position independent error rate (PER) of 10.96%. Finally, we have made a contribution to the language technology resources for Kikamba including multilingual machine translation, a morphology analyzer, a computational grammar which provides a platform for development of multilingual applications and the ability to generate a variety of bilingual corpora for Kikamba for all languages currently defined in GF, making it easier to experiment with data driven approaches.

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Section: Introductionmentioning

confidence: 99%

Towards Kikamba Computational Grammar

Kituku¹,

Nganga²,

Muchemi³

2019

JDAIP

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Creating language resources for under-resourced languages: methodologies, and experiments with Arabic

El-Haj

Kruschwitz

Fox

2014

Lang Resources & Evaluation

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Language resources are important for those working on computational methods to analyse and study languages. These resources are needed to help advancing the research in fields such as natural language processing, machine learning, information retrieval and text analysis in general. We describe the creation of useful resources for languages that currently lack them, taking resources for Arabic summarisation as a case study. We illustrate three different paradigms for creating language resources, namely: (1) using crowdsourcing to produce a small resource rapidly and relatively cheaply; (2) translating an existing gold-standard dataset, which is relatively easy but potentially of lower quality; and (3) using manual effort with appropriately skilled human participants to create a resource that is more expensive but of high quality. The last of these was used as a test collection for TAC-2011. An evaluation of the resources is also presented.The current paper describes and extends the resource creation activities and evaluations that underpinned experiments and findings that have previously appeared as an LREC workshop paper (El-Haj et al 2010), a student conference paper (El-Haj et al 2011b), and a description of a multilingual summarisation pilot (El-Haj et al 2011c;.

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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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Building Swahili Resource Grammars for the Grammatical Framework

Cited by 3 publications

References 2 publications

Towards Kikamba Computational Grammar

Towards Kikamba Computational Grammar

Creating language resources for under-resourced languages: methodologies, and experiments with Arabic

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

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