What are knowledge graphs and how can they support under-resourced languages?
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| Format: | Recurso digital |
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2024
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| _version_ | 1866901887387697152 |
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| author | Huaman, Elwin |
| author_facet | Huaman, Elwin |
| contents | <p><span>Presented by Elwin Huaman at the Language Documentation and Archiving Conference, Berlin & Online, 4-6 Sept, 2024.</span></p> <p><span>Knowledge graphs are large semantic nets that integrate and represent knowledge from var- ious domains [1], and have proven to be very important for supporting the development of applications in high-resourced languages. For instance, major technology companies such as Amazon1, Google2, and Microsoft3 and others have been collecting all the data and knowledge from the web with the aim of building knowledge graphs that can support their applications and services [2] in English, Spanish, and a few other languages. However, there are about 7000 languages in the world4 and only a few of them have the necessary resources to be further implemented on language technologies [3]. Therefore, the creation of interoperable linguistic resources is nowadays more urgent in order to save and help under-resourced languages, and their communities. In this paper, we present our approach for building knowledge graphs that can support under-resourced languages. We adopted a task-based approach to knowledge graph generation, covering the creation, hosting, curation, and deployment phases. We conclude that the methodology and tools adopted, on building an under-resourced language knowledge graph, could enhance the presence of under-resourced languages on the web through the representa- tion of data, text, and media in these languages. Finally, we provide insights, directions, and best practices toward a better architecture for building under-resourced language knowledge graphs.</span></p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_13882234 |
| institution | Zenodo |
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| publishDate | 2024 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | What are knowledge graphs and how can they support under-resourced languages? Huaman, Elwin knowledge graphs under-resourced languages <p><span>Presented by Elwin Huaman at the Language Documentation and Archiving Conference, Berlin & Online, 4-6 Sept, 2024.</span></p> <p><span>Knowledge graphs are large semantic nets that integrate and represent knowledge from var- ious domains [1], and have proven to be very important for supporting the development of applications in high-resourced languages. For instance, major technology companies such as Amazon1, Google2, and Microsoft3 and others have been collecting all the data and knowledge from the web with the aim of building knowledge graphs that can support their applications and services [2] in English, Spanish, and a few other languages. However, there are about 7000 languages in the world4 and only a few of them have the necessary resources to be further implemented on language technologies [3]. Therefore, the creation of interoperable linguistic resources is nowadays more urgent in order to save and help under-resourced languages, and their communities. In this paper, we present our approach for building knowledge graphs that can support under-resourced languages. We adopted a task-based approach to knowledge graph generation, covering the creation, hosting, curation, and deployment phases. We conclude that the methodology and tools adopted, on building an under-resourced language knowledge graph, could enhance the presence of under-resourced languages on the web through the representa- tion of data, text, and media in these languages. Finally, we provide insights, directions, and best practices toward a better architecture for building under-resourced language knowledge graphs.</span></p> |
| title | What are knowledge graphs and how can they support under-resourced languages? |
| topic | knowledge graphs under-resourced languages |
| url | https://doi.org/10.5281/zenodo.13882234 |