2022
DOI: 10.1163/22105832-bja10019
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The dialect chain of the Timor-Alor-Pantar language family

Abstract: This paper refines the subgroupings of the Timor-Alor-Pantar (TAP) family of Papuan languages, using a systematic Bayesian phylogenetics study. While recent work indicates that the TAP family comprises a Timor (T) branch and an Alor-Pantar (AP) branch (Holton et al., 2012; Schapper et al., 2017), the internal structure of the AP branch has proven to be a challenging issue, and earlier studies leave large gaps in our understanding. Our Bayesian inference study is based on an extensive set of TAP lexical data fr… Show more

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Cited by 6 publications
(2 citation statements)
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“…Kaiping [16] proposed a relatively innovative classification of the Alor-Pantar languages based on a systematic Bayesian phylogenetic approach, which adds up to the ongoing research inherent in the categorization and 'branching' of this Papuan sub-family.…”
Section: Literature Reviewmentioning
confidence: 99%
“…Kaiping [16] proposed a relatively innovative classification of the Alor-Pantar languages based on a systematic Bayesian phylogenetic approach, which adds up to the ongoing research inherent in the categorization and 'branching' of this Papuan sub-family.…”
Section: Literature Reviewmentioning
confidence: 99%
“…Quite a few new methods have been proposed to address the detection of lexical borrowings (Problem 2). Among these are supervised approaches (which I had deliberately excluded, since I consider unsupervised approaches as more useful when it comes to inference problems) that made use of recurrent neural networks ( Miller et al , 2020 ), there are tree-based approaches that even try to identify the direction of borrowings ( Neureiter et al , 2022 ), 6 and there are numerous attempts to handle very specific cases of lexical borrowing, such as contact across language families ( Hantgan et al , 2022 ; List & Forkel, 2022 ) or contact induced by dominant languages ( Kaiping & Klamer, 2022 ; Miller & List, 2023 ).…”
Section: New and Old Open Problemsmentioning
confidence: 99%