In lexicography, there are two commonly used types of semantic data categorization: semantic domains and semantic labels. The difference between the two approaches is simple: semantic domains presume that each lexical meaning belongs to one and only one group (or sub-group of a larger group). Semantic labels do not have such limitations.
Endangered language documentation and endangered language revitalisation have been two hot topics in recent years. For instance, the United Nations Educational, Scientific and Cultural Organization (UNESCO) declared the year 2019 as the International Year of Indigenous Languages. However, although the UNESCO and many other organizations (e.g. The Endangered Languages Documentation Programme or SIL International) urge the public to be aware of the rapidly decreasing number of languages in the world, it does not slow down the annual rate of language loss. For example, the total number of speakers of the Kusunda language, a moribund language spoken in Nepal, decreased to only one person in 2020.
In a previous post (Kaiping 2018), I described how to convert matrix-shape word lists given in Excel into the long format LingPy and other software can work with. My motivation for this was to provide my colleague Yunus Sulistyono with a good way to compare the lexicon of his Alorese [alor1247] dialects, and to understand the relationship between them. In this post, the data is automatically cognate coded and converted into CLDF. Continue reading
A colleague of mine has recently returned from his fieldwork, where he collected data on on the dialectal variation of the Alorese language of Alor and Pantar in the East Nusa Tenggara province of Indonesia. He collected data on 13 Alorese varieties, including word list data. One obvious step for comparing the dialects is to mark which forms are obviously cognate and then use a standard tree (or network) construction algorithm to display the shared signal in the data. With standard tools and a bit of Python glue, this is an easy task. A script for 3 steps can be found in my repository on github. In this first part, I will describe how to get an Excel file into a format LingPy can deal with.
Wiktionary is a project for creating a multilingual, web-based free dictionary of all words in all languages. Like its sister project Wikipedia, since its inception it has been subject to criticism both in terms of its lexicographic approaches and in terms of reliability, content, procedures, and community operation (see Lepore 2006, Fuertes-Olivera 2009, Meyer 2012). Faults have also been pointed in terms of its structure which is confusing for newcomers, with parallel and unaligned information shared among the various language dictionaries, and differences in accuracy and depth among languages. Notwithstanding, data from Wiktionary is routinely employed with successful results in natural language processing and, occasionally, in linguistic research (see Otte 2011, Schlippe 2012, Medero 2009, Li 2012), as it constitutes, by far, the largest free multilingual lexical source.