Amal Al-Saif

Also published as: Amal Alsaif


2019

pdf bib
The Design of the SauLTC application for the English-Arabic Learner Translation Corpus
Maha Al-Harthi | Amal Alsaif
Proceedings of the 3rd Workshop on Arabic Corpus Linguistics

2018

pdf bib
Annotating Attribution Relations in Arabic
Amal Alsaif | Tasniem Alyahya | Madawi Alotaibi | Huda Almuzaini | Abeer Algahtani
Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)

2011

pdf bib
Modelling Discourse Relations for Arabic
Amal Al-Saif | Katja Markert
Proceedings of the 2011 Conference on Empirical Methods in Natural Language Processing

2010

pdf bib
The Leeds Arabic Discourse Treebank: Annotating Discourse Connectives for Arabic
Amal Al-Saif | Katja Markert
Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)

We present the first effort towards producing an Arabic Discourse Treebank,a news corpus where all discourse connectives are identified and annotated with the discourse relations they convey as well as with the two arguments they relate.We discuss our collection of Arabic discourse connectives as well as principles for identifying and annotating them in context, taking into account properties specific to Arabic. In particular, we deal with the fact that Arabic has a rich morphology: we therefore include clitics as connectives as well as a wide range of nominalizations as potential arguments. We present a dedicated discourse annotation tool for Arabic and a large-scale annotation study. We show that both the human identification of discourse connectives and the determination of the discourse relations they convey is reliable. Our current annotated corpus encompasses a final 5651 annotated discourse connectives in 537 news texts. In future, we will release the annotated corpus to other researchers and use it for training and testing automated methods for discourse connective and relation recognition.