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 reading “From Fieldwork to Trees 3: CLDF recipes”
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 “From Fieldwork to Trees 2: Cognate coding”
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.