Supporting the corpus-based study of Shakespeare’s language: Enhancing a corpus of the First Folio

Abstract This article explores challenges in the corpus linguistic analysis of Shakespeare’s language, and Early Modern English more generally, with particular focus on elaborating possible solutions and the benefits they bring. An account of work that took place within the Encyclopedia of Shakespeare’s Language Project (2016–2019) is given, which discusses the development of the project’s data resources, specifically, the Enhanced Shakespearean Corpus. Topics covered include the composition of the corpus and its subcomponents; the structure of the XML markup; the design of the extensive character metadata; and the word-level corpus annotation, including spelling regularisation, part-of-speech tagging, lemmatisation and semantic tagging. The challenges that arise from each of these undertakings are not exclusive to a corpus-based treatment of Shakespeare’s plays but it is in the context of Shakespeare’s language that they are so severe as to seem almost insurmountable. The solutions developed for the Enhanced Shakespearean Corpus – often combining automated manipulation with manual interventions, and always principled – offer a way through.

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Exploring and categorising the Arabic copula and auxiliary kāna through enhanced part-of-speech tagging

Corpora ◽

10.3366/cor.2021.0225 ◽

2021 ◽

Vol 16 (3) ◽

pp. 305-335

Author(s):

Andrew Hardie ◽

Wesam Ibrahim

Keyword(s):

Foreign Language ◽

Linguistic Analysis ◽

High Rate ◽

Surface Level ◽

Part Of Speech Tagging ◽

The Past ◽

Part Of Speech ◽

The One ◽

Speech Tagging

Arabic syntax has yet to be studied in detail from a corpus-based perspective. The Arabic copula kāna (‘be’), functions also as an auxiliary, creating periphrastic tense–aspect constructions; but the literature on these functions is far from exhaustive. To analyse kāna within the one-million word Corpus of Contemporary Arabic, part-of-speech tagging (using novel, targeted enhancements to a previously described program which improves the accessibility for linguistic analysis of the output of Habash et al.’s [2012] mada disambiguator for the Buckwalter Arabic morphological analyser) is applied to disambiguate copula and auxiliary at a high rate of accuracy. Concordances of both are extracted, and 10 percent samples (499 instances of copula kāna and 387 of auxiliary kāna) are analysed manually to identify surface-level grammatical patterns and meanings. This raw analysis is then systematised according to the more general patterns’ main parameters of variation; special descriptions are developed for specific, apparently fixed-form expressions (including two phraseologies which afford expression of verbal and adjectival modality). Overall, we uncover substantial new detail, not mentioned in existing grammars (e.g., the quantitative predominance of the past imperfect construction over other uses of auxiliary kāna). There exists notable potential for these corpus-based findings to inform and enhance not only grammatical descriptions but also pedagogy of Arabic as a first or second/foreign language.

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Lexical Rule and Lexicon Effect for Part of Speech Tagging Bahasa Madura

Matrik Jurnal Manajemen Teknik Informatika dan Rekayasa Komputer ◽

10.30812/matrik.v18i1.332 ◽

2018 ◽

Vol 18 (1) ◽

pp. 65-72

Author(s):

Nindian Puspa Dewi ◽

Ubaidi Ubaidi

Keyword(s):

Text Processing ◽

Part Of Speech Tagging ◽

Pos Tagging ◽

Part Of Speech ◽

Speech Tagging ◽

Bahasa Indonesia

POS Tagging adalah dasar untuk pengembangan Text Processing suatu bahasa. Dalam penelitian ini kita meneliti pengaruh penggunaan lexicon dan perubahan morfologi kata dalam penentuan tagset yang tepat untuk suatu kata. Aturan dengan pendekatan morfologi kata seperti awalan, akhiran, dan sisipan biasa disebut sebagai lexical rule. Penelitian ini menerapkan lexical rule hasil learner dengan menggunakan algoritma Brill Tagger. Bahasa Madura adalah bahasa daerah yang digunakan di Pulau Madura dan beberapa pulau lainnya di Jawa Timur. Objek penelitian ini menggunakan Bahasa Madura yang memiliki banyak sekali variasi afiksasi dibandingkan dengan Bahasa Indonesia. Pada penelitian ini, lexicon selain digunakan untuk pencarian kata dasar Bahasa Madura juga digunakan sebagai salah satu tahap pemberian POS Tagging. Hasil ujicoba dengan menggunakan lexicon mencapai akurasi yaitu 86.61% sedangkan jika tidak menggunakan lexicon hanya mencapai akurasi 28.95 %. Dari sini dapat disimpulkan bahwa ternyata lexicon sangat berpengaruh terhadap POS Tagging.

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