As one of the most morphologically conservative branches of the Sino-Tibetan language family, most of the Rgyalrongic languages are still understudied and poorly understood, not to mention their vulnerable or endangered status. It is therefore important for available data of these languages to be made accessible. The lexical data sets the authors have assembled provide comparative word lists of 20 modern and medieval Rgyalrongic languages, consisting of word lists from fieldwork carried out by the first author and other colleagues as well as published word lists by other authors. In particular, data of the two Khroskyabs varieties were collected by the first author from 2011 to 2016. Cognate identification is based on the authors' expertise in Rgyalrong historical linguistics through application of the comparative method. We curated the data by conducting phonemic segmentation and partial cognate annotation. The data sets can be used by historical linguists interested in the etymology and the phylogeny of the languages in question, and they can use them to answer questions regarding individual word histories or the subgrouping of languages in this important branch of Sino-Tibetan.

Computer-assisted approaches to historical language comparison have made great progress during the past two decades. Scholars can now routinely use computational tools to annotate cognate sets, align words, and search for regularly recurring sound correspondences. However, computational approaches still suffer from a very rigid sequence model of the form part of the linguistic sign, in which words and morphemes are segmented into fixed sound units which cannot be modified. In order to bring the representation of sound sequences in computational historical linguistics closer to the research practice of scholars who apply the traditional comparative method, we introduce improved sound sequence representations in which individual sound segments can be grouped into evolving sound units in order to capture language-specific sound laws more efficiently. We illustrate the usefulness of this enhanced representation of sound sequences in concrete examples and complement it by providing a small software library that allows scholars to convert their data from forms segmented into sound units to forms segmented into evolving sound units and vice versa.

The Indo-European Cognate Relationships (IE-CoR) dataset is an open-access relational dataset showing how related, inherited words ('cognates') pattern across 160 languages of the Indo-European family. IE-CoR is intended as a benchmark dataset for computational research into the evolution of the Indo-European languages. It is structured around 170 reference meanings in core lexicon, and contains 25731 lexeme entries, analysed into 4981 cognate sets. Novel, dedicated structures are used to code all known cases of horizontal transfer. All 13 main documented clades of Indo-European, and their main subclades, are well represented. Time calibration data for each language are also included, as are relevant geographical and social metadata. Data collection was performed by an expert consortium of 89 linguists drawing on 355 cited sources. The dataset is extendable to further languages and meanings and follows the Cross-Linguistic Data Format (CLDF) protocols for linguistic data. It is designed to be interoperable with other cross-linguistic datasets and catalogues, and provides a reference framework for similar initiatives for other language families.

Large-scale lexical and grammatical datasets nowadays play an important role in comparative linguistics. However, the lack of standardization remains a challenge exacerbating extension and reuse of published data. We present an updated version of Lexibank, a large-scale lexical dataset, expanding on previous efforts to standardize and unify cross-linguistic data. This new version includes over 3,100 languages and more than one-and-a-half million word forms, substantially broadening the scope and utility of the previous resource. Our dataset has been systematically curated using a dedicated computer-assisted workflow designed specifically for the lifting of published wordlist data to the standards recommended by the Cross-Linguistic Data Formats initiative. The expanded dataset features standardized references to language varieties, standardized semantic glosses that reference the concepts expressed by individual word forms, and standardized phonetic transcriptions for all word forms that our repository contains. Based on those standardizations we pre-compute semantic and phonological features, which can be used to carry out extensive automated analyses. We illustrate this potential by providing dedicated database queries to (1) infer words that are similar in pronunciation and meaning, (2) identify concepts that are colexified across languages in our sample, and (3) assess the semantic diversity of etymologically related words. These queries are not only fast to execute but also global in their scope, due to the largescale coverage provided by Lexibank 2. The queries are also easy to extend, thus having the potential to contribute to various studies in historical linguistics, linguistic typology, and related disciplines. The updated dataset is a substantial step forward in the effort to create comprehensive, standardized, and accessible linguistic resources.

"Why do some languages wither and die, while others prosper and spread? Around the turn of the millennium a number of archaeologists such as Colin Renfrew and Peter Bellwood made the controversial claim that many of the world's major language families owe their dispersal to the adoption of agriculture by their early speakers. In this volume, their proposal is reassessed by linguists, investigating to what extent the economic dependence on plant cultivation really impacted language spread in various parts of the world. Special attention is paid to "tricky" language families such as Eskimo-Aleut

We study the correlation between phylogenetic and geographic distances for the languages of the Andic branch of the East Caucasian (Nakh-Daghestanian) language family. For several alternative phylogenies, we find that geographic distances correlate with linguistic divergence. Notably, qualitative classifications show a better fit with geography than cognacy-based phylogenies. We interpret this result as follows: The better fit may be due to implicit geographic bias in qualitative classifications. We conclude that approaches to classification other than those based on cognacy run a risk to impl

Enigma de la Lingüística Indoeuropea es la falta de una raíz común para el verbo ‘tener’, pues las lenguas indoeuropeas debieron procurarse cada una tal verbo desde otros, sobre todo desde los que significaban ‘coger’, ‘asir’, ‘tomar’ o ‘agarrar’. Ello no es una particularidad de las lenguas indoeuropeas sino un fenómeno seguramente común a todos los grupos lingüísticos. Tan llamativo rasgo se explicaría bien desde la posibilidad de que aquellos grupos se hubieran conformado en el Paleolítico, cuando el hombre no tenía un claro concepto de la posesión y el lexema no era tan perentorio como en