In the previous two posts (Part 1, Part 2), I took you from a matrix of word lists from fieldwork to a LingPy-compatible CLDF Wordlist with cognate codes and alignments. We can now feed this dataset into existing tools and recipes for visualizing and analyzing CLDF Wordlists.
Continue readingIn 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
The Cross-Linguistic Data Formats initiative (CLDF, https://cldf.clld.org, Forkel et al. 2018) has helped a lot in preparing the CLICS² database of cross-linguistic colexifications (https://clics.lingpy.org, List et al. 2018), since linking our data to Concepticon (https://concepticon.clld.org, List et al. 2016) and Glottolog (https://glottolog.org, Hammarström et al. 2018) has provided incredible help in merging the different datasets into a big comparative dataset.
CLDF, however, is not restricted to lexical data, but can also be successfully used to store structural data, although — due to the nature of structural data — it is much more difficult to compare different datasets.
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.
