Sara Hassan


Unified Guidelines and Resources for Arabic Dialect Orthography
Nizar Habash | Fadhl Eryani | Salam Khalifa | Owen Rambow | Dana Abdulrahim | Alexander Erdmann | Reem Faraj | Wajdi Zaghouani | Houda Bouamor | Nasser Zalmout | Sara Hassan | Faisal Al-Shargi | Sakhar Alkhereyf | Basma Abdulkareem | Ramy Eskander | Mohammad Salameh | Hind Saddiki
Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)


A Morphological Analyzer for Gulf Arabic Verbs
Salam Khalifa | Sara Hassan | Nizar Habash
Proceedings of the Third Arabic Natural Language Processing Workshop

We present CALIMAGLF, a Gulf Arabic morphological analyzer currently covering over 2,600 verbal lemmas. We describe in detail the process of building the analyzer starting from phonetic dictionary entries to fully inflected orthographic paradigms and associated lexicon and orthographic variants. We evaluate the coverage of CALIMA-GLF against Modern Standard Arabic and Egyptian Arabic analyzers on part of a Gulf Arabic novel. CALIMA-GLF verb analysis token recall for identifying correct POS tag outperforms both the Modern Standard Arabic and Egyptian Arabic analyzers by over 27.4% and 16.9% absolute, respectively.


A Large Scale Corpus of Gulf Arabic
Salam Khalifa | Nizar Habash | Dana Abdulrahim | Sara Hassan
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)

Most Arabic natural language processing tools and resources are developed to serve Modern Standard Arabic (MSA), which is the official written language in the Arab World. Some Dialectal Arabic varieties, notably Egyptian Arabic, have received some attention lately and have a growing collection of resources that include annotated corpora and morphological analyzers and taggers. Gulf Arabic, however, lags behind in that respect. In this paper, we present the Gumar Corpus, a large-scale corpus of Gulf Arabic consisting of 110 million words from 1,200 forum novels. We annotate the corpus for sub-dialect information at the document level. We also present results of a preliminary study in the morphological annotation of Gulf Arabic which includes developing guidelines for a conventional orthography. The text of the corpus is publicly browsable through a web interface we developed for it.