WASA: A Web Application for Sequence Annotation

WASA: A Web Application for Sequence Annotation Fahad AlGhamdi, and Mona Diab Department of Computer Science The George Washington University Washington, DC {fghamdi, mtdiab}@gwu.edu Abstract Data annotation is an important and necessary task for all NLP applications. Designing and implementing a web-based application that enables many annotators to annotate and enter their input into one central database is not a trivial task. These kinds of web-based applications require a consistent and robust backup for the underlying database and support to enhance the efficiency and speed of the annotation. Also, they need to ensure that the annotations are stored with a minimal amount of redundancy in order to take advantage of the available resources(e.g, storage space). In this paper, we introduce WASA, a web-based annotation system for managing large-scale multilingual Code Switching (CS) data annotation. Although WASA has the ability to perform the annotation for any token sequence with arbitrary tag sets, we will focus on how WASA is used for CS annotation. The system supports concurrent annotation, handles multiple encodings, allows for several levels of management control, and enables quality control measures while seamlessly reporting annotation statistics from various perspectives and at different levels of granularity. Moreover, the system is integrated with a robust language specific date prepossessing tool to enhance the speed and efficiency of the annotation. We describe the annotation and the administration interfaces as well as the backend engine. Keywords: : Code Switching, Annotation, Web Application, Sociolinguistics 1. Introduction Code Switching (CS) is a phenomenon that occurs when multilingual speakers alternate between more than one lan- guage or dialect. This phenomenon can be observed in dif- ferent linguistic levels of representation for different lan- guage pairs: phonological, morphological, lexical, syntac- tic, semantic, and discourse/pragmatics. CS presents seri- ous challenges for language technologies, including pars- ing, Machine Translation (MT), Information Retrieval (IR) and others. A major barrier to research on CS has been the lack of large multilingual, multi-genre CS-annotated corpora. Creating such corpora involves managing many annotators working on multiple tasks at different times, consistent and robust backups of the underlying database, quality control, etc. In this paper, we present our effort in building an annotation system, WASA, that can manage and facilitate large-scale CS data annotation. WASA dif- fers from other annotation systems in several respects. Our system has an option that can provide initial automatic tag- ging for specific tokens such as Latin words, URL, punc- tuation, digits, diacritics, emoticons, and speech effect to- kens. This option increases the quality and the speed of an- notation substantially. Moreover, the system is integrated with language-specific date preprocessing tool Smart Pre- processing (Quasi) Language Independent Tool (SPLIT) (Al-Badrashiny et al., 2016) to streamline raw data cleaning and preparation. The remainder of this paper is organized as follows: Sec- tion 2 provides an overview of related work. Section 3 describes the System Architecture. Types of users includ- ing permissions and users tasks are introduced in Section 4. The data preprocessing and cleaning are discussed in Section 5. We …

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