Mining Wikidata for Name Resources for African Languages
This work supports further development of language technology for the languages of Africa by providing a Wikidata-derived resource of name lists corresponding to common entity types (person, location, and organization). While we are not the first to mine Wikidata for name lists, our approach emphasizes scalability and replicability and addresses data quality issues for languages that do not use Latin scripts. We produce lists containing approximately 1.9 million names across 28 African languages. We describe the data, the process used to produce it, and its limitations, and provide the software and data for public use. Finally, we discuss the ethical considerations of producing this resource and others of its kind.
Code (1)
Similar Papers 제목 키워드 기반
Government Domain Named Entity Recognition for South African Languages
This paper describes the named entity language resources developed as part of a development project for the South African languages. The development efforts focused on creating protocols and annotated data sets with at l…
named-entity-recognitionNamed Entity RecognitionNamed Entity Recognition (NER)Building Collaboration-based Resources in Endowed African Languages: Case of NTeALan Dictionaries Platform
In a context where open-source NLP resources and tools in African languages are scarce and dispersed, it is difficult for researchers to truly fit African languages into current algorithms of artificial intelligence. Cre…
ManagementThinking globally, acting locally – Progress in the African Wordnet Project
The African Wordnet Project (AWN) includes all nine indigenous South African languages, namely isiZulu, isiXhosa, Setswana, Sesotho sa Leboa, Tshivenda, Siswati, Sesotho, isiNdebele and Xitsonga. The AWN currently includ…
Collaborative construction of lexicographic and parallel datasets for African languages: first assessment
Faced with a considerable lack of resources in African languages to carry out work in Natural Language Processing (NLP), Natural Language Understanding (NLU) and artificial intelligence, the research teams of NTeALan ass…
Natural Language UnderstandingToward More Meaningful Resources for Lower-resourced Languages
In this paper, we describe our perspective on how meaningful resources for lower-resourced languages can be developed in connection with the speakers of those languages. We examine two massively multilingual resources in…