Glottocodes: identifiers linking families, languages and dialects

Glottocodes constitute the backbone identification system for the language, dialect and family inventory Glottolog(https://glottolog.org). In this paper, we summarize the motivation and history behind the system of glottocodes and describe theprinciples and practices of data curation, technical infrastructure and update/version-tracking systematics. Since our understandingof the target domain—the dialects, languages and language families of the entire world—is continually evolving, changesand updates are relatively common. The resulting data is assessed in terms of the FAIR (Findable, Accessible, Interoperable,Reusable) Guiding Principles for scientific data management and stewardship. As such the glottocode-system responds to animportant challenge in the realm of Linguistic Linked Data with numerous NLP applications.1. Introduction 2. Motivation and History 3. Glottolog data curation 3.1. Glottolog data is findable 3.2. Glottolog data is accessible 3.3. Glottolog data is interoperable 3.4. Glottolog data is reusable 4. Policies governing glottocode assignment 5. Glottolog versioning 6. Conclusio

Automated identification of borrowings in multilingual wordlists

Although lexical borrowing is an important aspect of language evolution, there have been few attempts to automate the identification of borrowings in lexical datasets. Moreover, none of the solutions which have been proposed so far identify borrowings across multiple languages. This study proposes a new method for the task and tests it on a newly compiled large comparative dataset of 48 South-East Asian languages from Southern China. The method yields very promising results, while it is conceptually straightforward and easy to apply. This makes the approach a perfect candidate for computer-assisted exploratory studies on lexical borrowing in contact areas

Gauge-invariant and infrared-improved variational analysis of the Yang-Mills vacuum wave functional

We study a gauge-invariant variational framework for the Yang-Mills vacuum wave functional. Our approach is built on gauge-averaged Gaussian trial functionals which substantially extend previously used trial bases in the infrared by implementing a general low-momentum expansion for the vacuum-field dispersion (which is taken to be analytic at zero momentum). When completed by the perturbative Yang-Mills dispersion at high momenta, this results in a significantly enlarged trial functional space which incorporates both dynamical mass generation and asymptotic freedom. After casting the dynamics associated with these wave functionals into an effective action for collections of soft vacuum-field orbits, the leading infrared improvements manifest themselves as four-gradient interactions. Those turn out to significantly lower the minimal vacuum energy density, thus indicating a clear overall improvement of the vacuum description. The dimensional transmutation mechanism and the dynamically generated mass scale remain almost quantitatively robust, however, which ensures that our prediction for the gluon condensate is consistent with standard values. Further results include a finite group velocity for the soft gluonic modes due to the higher-gradient corrections and indications for a negative differential color resistance of the Yang-Mills vacuum.Comment: 47 pages, 5 figures (vs2 contains a few minor stylistic adjustments to match the published version