Terminology Alignment faces big challenges in NLP because of the dynamic nature of terms. Fortunately, over these last few years, Deep Learning models showed very good progress with several NLP tasks such as multilingual data resourcing, glossary building, terminology understanding. . . etc. In this work, we propose a new method for terminology alignment from a comparable corpus (Arabic/French languages) for the Algerian culture field. We aim to improve bilingual alignment based on contextual information of a term and to create a significant term bank i.e. a bilingual Arabic-French dictionary. We propose to create word embeddings for both Arabic and French languages using ELMO model focusing on contextual features of terms. Then, we mapp those embeddings using Seq2seq model. We use multilingual-BERT and All-MiniLM-L6 as baseline mod- els to compare terminology alignment results. Lastly we study the performance of these models by applying evaluation methods. Experimentation’s showed quite satisfying alignment results.

Despite Arabic is the language of hundred millions of people over the world, little has been done in terms of computerized linguistic resources, tools or applications. In this paper we describe a project which aim is to contribute filling this gap. The project consists in building an ontology centered infrastructure for Arabic Language resources and applications. The core of this infrastructure is a linguistic ontology that is founded on Arabic Traditional Grammar. The methodology we have chosen consists in reusing an existing ontology, namely the Gold linguistic ontology. GOLD is the first ontology being designed for linguistic description on the semantic web. We first construct our ontology manually by relating our concepts from Arabic Linguistics to the upper concepts of GOLD, furthermore an information extraction algorithm is implemented to automatically enrich the ontology. We discuss the development of the ontology and present our vision for the whole project which aims at using this ontology for creating tools and resources for both linguists and NLP Researchers. Indeed, the ontology is seen , not only as a domain ontology but also as a resource for different linguistic and NLP applications.