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- 01HSBD9ZH8MW8RJK4N1ZXKSKZF classification C1.
- 01HSBD9ZH8MW8RJK4N1ZXKSKZF date "2024".
- 01HSBD9ZH8MW8RJK4N1ZXKSKZF language "eng".
- 01HSBD9ZH8MW8RJK4N1ZXKSKZF type conference.
- 01HSBD9ZH8MW8RJK4N1ZXKSKZF hasPart 01HYFNFMHA9RQR1V8TVQQHM6JG.pdf.
- 01HSBD9ZH8MW8RJK4N1ZXKSKZF subject "Languages and Literatures".
- 01HSBD9ZH8MW8RJK4N1ZXKSKZF isbn "9782493814104".
- 01HSBD9ZH8MW8RJK4N1ZXKSKZF issn "2522-2686".
- 01HSBD9ZH8MW8RJK4N1ZXKSKZF presentedAt urn:uuid:2fdbccbf-2488-4af1-9b53-c9b910a39dec.
- 01HSBD9ZH8MW8RJK4N1ZXKSKZF abstract "The study of ancient Middle Eastern cultures is dominated by the vast number of cuneiform texts. Multiple languages and language families were expressed in cuneiform. The most dominant language written in cuneiform is the Semitic Akkadian, which is the focus of this paper. We are specifically focusing on letters written in the dialect used in modern-day Baghdad and south towards the Persian Gulf during the Old Babylonian period (c. 2000-1600 B.C.E.). The Akkadian language was rediscovered in the 19th century and is now being scrutinised by Natural Language Processing (NLP) methods. However, existing Akkadian text publications are not always suitable for digital editions. We therefore risk applying NLP methods onto renderings of Akkadian unfit for the purpose. In this paper we want to investigate the input material and try to initiate a discussion about best-practices in the crossroad where NLP meets cuneiform studies. Specifically, we want to question the use of pre-trained embeddings, sentence segmentation and the type of cuneiform input used to fine-tune language models for the task of fine-grained Part-of-Speech tagging. We examine the issues by theoretical and practical approaches in a way that we hope spurs discussions that are relevant for automatic processing of other ancient languages.".
- 01HSBD9ZH8MW8RJK4N1ZXKSKZF author 5ddbbeb0-c99a-11ec-a040-d9465064cab9.
- 01HSBD9ZH8MW8RJK4N1ZXKSKZF author F589C1DE-F0ED-11E1-A9DE-61C894A0A6B4.
- 01HSBD9ZH8MW8RJK4N1ZXKSKZF author F98A820A-F0ED-11E1-A9DE-61C894A0A6B4.
- 01HSBD9ZH8MW8RJK4N1ZXKSKZF dateCreated "2024-03-19T13:09:43Z".
- 01HSBD9ZH8MW8RJK4N1ZXKSKZF dateModified "2024-12-12T20:44:19Z".
- 01HSBD9ZH8MW8RJK4N1ZXKSKZF editor F93F00BE-F0ED-11E1-A9DE-61C894A0A6B4.
- 01HSBD9ZH8MW8RJK4N1ZXKSKZF editor urn:uuid:0e5682d3-32b3-4e7b-a6f5-29ff7134ae23.
- 01HSBD9ZH8MW8RJK4N1ZXKSKZF editor urn:uuid:2a5289f9-4701-4067-b18c-1e33d6d7259e.
- 01HSBD9ZH8MW8RJK4N1ZXKSKZF editor urn:uuid:9a34f748-3dc6-4e54-ac9a-69328e469491.
- 01HSBD9ZH8MW8RJK4N1ZXKSKZF editor urn:uuid:bb231358-1309-44b1-bfec-19c60d8461ef.
- 01HSBD9ZH8MW8RJK4N1ZXKSKZF editor urn:uuid:d3f5a4e2-cd94-4faa-8aba-e1f0f051ff06.
- 01HSBD9ZH8MW8RJK4N1ZXKSKZF name "At the crossroad of cuneiform and NLP : challenges for fine-grained part-of-speech tagging".
- 01HSBD9ZH8MW8RJK4N1ZXKSKZF pagination urn:uuid:9ad313c2-fae0-42d6-8295-6d94806de8fa.
- 01HSBD9ZH8MW8RJK4N1ZXKSKZF publisher urn:uuid:b7efd2d7-c8c0-4343-9aeb-7f45c91bf7d8.
- 01HSBD9ZH8MW8RJK4N1ZXKSKZF sameAs LU-01HSBD9ZH8MW8RJK4N1ZXKSKZF.
- 01HSBD9ZH8MW8RJK4N1ZXKSKZF sourceOrganization urn:uuid:b1eba3e3-e943-41c1-bf99-e9e777f25c34.
- 01HSBD9ZH8MW8RJK4N1ZXKSKZF type C1.