In spite of being a successful syntactic theory in many respects, Head-driven Phrase Structure Grammar (HPSG) has inadequate coverage for morphological constructions, especially for nonconcatenative morphology, which is prominent in the Semitic languages such as Arabic, Hebrew etc. Among various syntactic and semantic phenomenon, passive constructions draws attention of many researchers in theoretical linguistics due to their diversity. Arabic exhibits lexical passives with nOl\concatenative morphology. In this paper, we extend the IJPSG framework to support the nonconcatenative constru¢tion of Arabic passives along with the necessary lexical rules' and type hierarchy.
Despite impressive improvement in the next-generation sequencing technology, reliable detection of indels is still a difficult endeavour. Recognition of true indels is of prime importance in many applications, such as, personalized health care, disease genomics, population genetics etc. Recently, advanced machine learning techniques have been successfully applied to classification problems with large-scale data. In this paper, we present SICaRiO, a gradient boosting classifier for reliable detection of true indels, trained with goldstandard dataset from genome-in-a-bottle (GIAB) consortium. Our filtering scheme significantly improves the performance of each variant calling pipeline used in GIAB and beyond. SICaRiO uses genomic features which can be computed from publicly available resources, hence, we can apply it on any indel callsets not having sequencing pipeline-specific information (e.g., read depth). This study also sheds lights on prior genomic contexts responsible for indel calling error made by sequencing platforms. We have compared prediction difficulty for three indel categories over different sequencing pipelines. We have also ranked genomic features according to their predictivity in determining false indel calls.
Semitic languages exhibit rich nonconcatenative morphological operations, which can generate a myriad of derived lexemes. Especially, the feature rich, root-driven morphology in the Arabic language demonstrates the construction of several verb-derived nominals (verbal nouns) such as gerunds, active participles, passive participles, locative participles, etc. Although HPSG is a successful syntactic theory, it lacks the representation of complex nonconcatenative morphology. In this paper, we propose a novel HPSG representation for Arabic nominals and various verb-derived nouns. We also present the lexical type hierarchy and derivational rules for generating these verb-derived nominals using the HPSG framework.
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