Developing an Arabic treebank

Maamouri, Mohamed; Bies, Ann

doi:10.3115/1621804.1621808

Cited by 63 publications

(38 citation statements)

References 4 publications

(2 reference statements)

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“…The Penn Arabic Treebank Maamouri et al, 2009) is a Linguistic Data Consortium (LDC) project, for which there are currently 12 parts for MSA. PATB consists of constituency trees, the sources of which are newswire articles from a variety of news sources.…”

Section: Patbmentioning

confidence: 99%

Proceedings of the Third Arabic Natural Language Processing Workshop

Habash¹,

Diab²,

Darwish³

et al. 2017

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A number of Arabic NLP (or Arabic NLP-related) workshops and conferences have taken place in the last few years, both in the Arab World and in association with international conferences. The Arabic NLP workshop at EACL 2017 follows in the footsteps of these previous efforts to provide a forum for researchers to share and discuss their ongoing work. This particular workshop is the third in a series, following the First Arabic NLP workshop held at EMNLP 2014 in Doha, Qatar; and the Second Arabic NLP workshop held at ACL 2015 in Beijing, China.We received 47 submissions and selected 22 (47% acceptance rate) for presentation in the workshop. All papers were reviewed by three reviewers on average. The number of submissions is over twice that of the previous workshop in Beijing, which also had a higher acceptance rate (65%). Ten papers will be presented orally and 12 as part of a poster session. The presentation mode is independent of the ranking of the papers. The papers cover a diverse set of topics from Maltese and Arabic dialect processing to models of semantic similarity and credibility analysis, advances in Arabic treebanking, and error annotation for dyslexic texts.The quantity and quality of the contributions to the workshop are strong indicators that there is a continued need for this kind of dedicated Arabic NLP workshop.We would like to acknowledge all the hard work of the submitting authors and thank the reviewers for the valuable feedback they provided. We hope these proceedings will serve as a valuable reference for researchers and practitioners in the field of Arabic NLP and NLP in general.Nizar Habash, General Chair, on behalf of the organizers of the workshop. AbstractThis paper presents a language identification system designed to detect the language of each word, in its context, in a multilingual documents as generated in social media by bilingual/multilingual communities, in our case speakers of Algerian Arabic. We frame the task as a sequence tagging problem and use supervised machine learning with standard methods like HMM and Ngram classification tagging. We also experiment with a lexicon-based method. Combining all the methods in a fall-back mechanism and introducing some linguistic rules, to deal with unseen tokens and ambiguous words, gives an overall accuracy of 93.14%. Finally, we introduced rules for language identification from sequences of recognised words.

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Section: Patbmentioning

confidence: 99%

Proceedings of the Third Arabic Natural Language Processing Workshop

Habash¹,

Diab²,

Darwish³

et al. 2017

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“…The ATB [11], is the richest Arabic treebank in reliable annotations (POS tags, syntactic and semantic hashtags), which are also compatible to consensus developed and validated by linguists. Its source documents are relevant, varied and large.…”

Section: Related Workmentioning

confidence: 99%

“…Table 1. The examples of the Arabic sentences parsed according to the annotation of the ATB In Table 1 above, the meanings of the symbols S, T, G and P are respectively as follows: the Arabic Sentences, the Buckwalter Transliterations 1 of the sentences, their Gloss in English language and their Parsing representations according to the ATB annotations [11]. In the following, we present some structure examples extracted from these sentences to explain the application of different syntactic properties of the GP formalism.…”

Section: Arabic Linguistic Study Within the Gp Formalismmentioning

confidence: 99%

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A Property Grammar-Based Method to Enrich the Arabic Treebank ATB

Bahloul¹,

Haddar²,

Blache³

2016

Communications in Computer and Information Science

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Abstract. We present a method based on the formalism of Property Grammars to enrich the Arabic treebank ATB with syntactic constraints (so-called properties). The Property Grammar formalism is an effectively constraint-based approach that directly specifies the constraints on information categories. This can facilitate the enrichment process. The latter is based on three phases: the problem formalization, the Property Grammar induction from the ATB and the treebank regeneration with a new syntactic property-based representation. The enrichment of the ATB can make it more useful for many NLP applications such as the ambiguity resolution. This allows also the acquisition of new linguistic resources and the ease of the probabilistic parsing process. This enrichment process is purely automatic and independent from any language and source corpus formalism. This motivates its reuse. We obtained good and encouraging experiment results and various properties of different types.

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“…The Penn Arabic Treebank (Maamouri et al, 2004;Maamouri et al, 2009) is a Linguistic Data Consortium (LDC) project, for which there are currently 12 parts for MSA. PATB consists of constituency trees, the sources of which are newswire articles from a variety of news sources.…”

Section: Patbmentioning

confidence: 99%

Universal Dependencies for Arabic

Taji¹,

Habash²,

Zeman³

2017

Proceedings of the Third Arabic Natural Language Processing Workshop

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We describe the process of creating NUDAR, a Universal Dependency treebank for Arabic. We present the conversion from the Penn Arabic Treebank to the Universal Dependency syntactic representation through an intermediate dependency representation. We discuss the challenges faced in the conversion of the trees, the decisions we made to solve them, and the validation of our conversion. We also present initial parsing results on NUDAR.

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Developing an Arabic treebank

Cited by 63 publications

References 4 publications

Proceedings of the Third Arabic Natural Language Processing Workshop

Proceedings of the Third Arabic Natural Language Processing Workshop

A Property Grammar-Based Method to Enrich the Arabic Treebank ATB

Universal Dependencies for Arabic

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