0. Introduction The World Atlas of Language Structures (WALS, Haspelmath et al. 2005) is a large-scale “database of databases” consisting of 141 typological databases, covering a wide range of grammatical features, joined into one composite resource through the use of a common metadata scheme. While this metadata scheme ensures interoperability among databases across some dimensions (e.g., lang...

The world atlas of language structures (WALS) originally appealed to the linguistics community as a resource for research. However, the relevance of the feature chapters to teaching environments and the user-friendly nature of the Interactive Reference Tool also make it suitable for university classrooms. Based on our experiences using WALS in two typology courses at the University of Mancheste...

The ease with which WALS allows users to combine features from two maps and determine numbers of languages of the resulting types means that there is a danger of misusing the data from WALS to arrive at unsupported conclusions regarding typological correlations. I examine two instances where the overall numbers suggest a correlation and show that in only one of the two instances is there any re...

Many statistical and econometric learning methods rely on Bayesian ideas. When applied in a frequentist setting, their precision is often assessed using the posterior variance. This permissible asymptotically, but not necessarily finite samples. We explore this issue focusing weighted-average least squares (WALS), Bayesian-frequentist ‘fusion’. Exploiting sampling properties of mean normal loca...

A core part of linguistic typology is the classification of languages according to linguistic properties, such as those detailed in the World Atlas of Language Structure (WALS). Doing this manually is prohibitively time-consuming, which is in part evidenced by the fact that only 100 out of over 7,000 languages spoken in the world are fully covered in WALS. We learn distributed language represen...

With massively parallel corpora of hundreds or thousands of translations of the same text, it is possible to automatically perform typological studies of language structure using very large language samples. We investigate the domain of word order using multilingual word alignment and high-precision annotation transfer in a corpus with 1144 translations in 986 languages of the New Testament. Re...

This paper presents a comparison of classification methods for linguistic typology for the purpose of expanding an extensive, but sparse language resource: the World Atlas of Language Structures (WALS) (Dryer and Haspelmath, 2013). We experimented with a variety of regression and nearest-neighbor methods for use in classification over a set of 325 languages and six syntactic rules drawn from WA...