Semi-automatic Annotation of Arabic Corpus: A Morpho-syntactic Study
Authors: Mahyoob Mohammad 
Published: March 2022

AbstractThe most important objective of our study was to build and construct a complete and comprehensive morphological analyzing scheme, tagging, and parsing system which can be used for annotating Arabic corpora. In our dissertation, we did an analytical study, implementation, and evaluation of Arabic morphological analysis, tagging, and syntactic analysis starting from raw text. The three different systems were implemented in various methods; for morphological analysis, we use finite-state automaton as discussed in chapter four, after doing the process of tokenization and segmentation of the raw text as explained in chapter three. The tagging system was implemented under a new very rich tag set, which was designed and developed by us. It consists of 30 tags in addition to some other features and linguistic information as described in chapter five. An appropriate set of tags has a direct influence on the accuracy and the usefulness of tagging system. So, the smaller the tag set, the higher the accuracy, and the larger the tag set, the lower the accuracy. Regarding syntactic annotation, we started with developing a syntactic tag for the Arabic language as explained in chapter six. Based on the syntactic tag we started developing chunker by analyzing sentence structure categories that are identified using some grammatical theory. And the last step is parsing which is very common for sentence structure annotation. We tried to bring in as many details as possible for sentence analysis as described in chapter six as well. This thesis provides an overview and annotation scheme for representing the NLP analysis, at the most important stages, such as lexical internal structure level, part-of-speech level, chunk level, and parsing at the sentence level. The main reason for our dissertation was to annotate Arabic corpora morpho-syntactically. The annotation was done semi-automatically which is more efficient and significant to tackle and present solutions for most of the Arabic language problems. The importance of annotated corpora in the present day of natural language processing is widely known. The main idea behind corpus annotation is to add value to a corpus and that will help to be a source of linguistic information for future research and development. Annotated corpora serve as an important tool for investigators of natural language processing, speech recognition, information retrieval, and other related areas. It proves to be a basic building block for developing and constructing different models, tools, and programs for automatic and semi-automatic processing of natural languages.It is very hard and difficult to encode manually all the information needed to encode the natural language to develop and build a tool or program that will annotate text with some necessary information (Brill, E, 1994). Annotation of corpora can be done at various levels such as part of speech, phrase/clause level, dependency level, etc. Part of speech tagging forms the basic step towards building an annotated corpus. Chunking can form the next level of tagging and then parsing the full sentence. Parsing is usually performed after basic morphosyntactic categories have been identified in a text, it brings these categories into higher-level syntactic relationships with one another. Corpora that have been parsed are sometimes known as treebanks as discussed in chapter six.There are various advantages of studying corpus, particularly for the areas of NLP; Machine Translation, Computational Lexicography, Stylistics, etc. It is extremely useful not only in building and formulating rules but also in testing them. Studies on a corpus with a focus on a particular linguistic structure can lead to a better understanding of the problems involved. Corpus can be used as an immediate source to extract and retrieve useful information in building natural language applications.