The Database of Cross-Linguistic Colexifications, reproducible analysis of cross-linguistic polysemies

Rzymski, Christoph; Tresoldi, Tiago; Greenhill, Simon J.; Wu, Mei-Shin; Schweikhard, Nathanael E.; Koptjevskaja‐Tamm, Maria; Gast, Volker; Bodt, Timotheus Adrianus; Hantgan, Abbie; Kaiping, Gereon A.; Chang, S.; Lai, Yunfan; Morozova, Natalia; Arjava, Heini; Hübler, Nataliia; Koile, Ezequiel; Pepper, Steve; Proos, Mariann; Epps, Briana Van; Blanco, Ingrid; Hundt, Carolin; Monakhov, Sergei; Pianykh, Kristina; Ramesh, Sallona; Gray, Russell D.; Forkel, Robert; List, Johann‐Mattis

doi:10.1038/s41597-019-0341-x

Cited by 99 publications

(95 citation statements)

References 81 publications

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“…At the same time, debate on language history is never free of disagreement among scholars, and this is also the case with the reconstruction of Hmong-Mien. 10 As a result, it is not easy to provide a direct evaluation of the performance of the computational part of the workflow presented here. In addition to these theoretical problems, evaluation faces practical problems.…”

Section: Current Performancementioning

confidence: 99%

“…The data we use was originally collected by Chén (2012) [8], later added in digital form to the SEALANG project [9], and was then converted to a computer-readable format as part of the CLICS database (https://clics.clld.org, [10]). Chén's collection comprises 885 concepts translated into 25 Hmong-Mien varieties.…”

Section: Datasetmentioning

confidence: 99%

“…9 The other two cognate sets in Ratliff's data could not be confirmed, because they do not occur in our sample. 10 Compare, for example, the debate about regular epenthesis in Proto-Hmong-Mien among Ratliff [42] and Ostapirat [43]. 11 A specific problem in semi-automated reconstruction consists in the importance of handling conditioning context in sound change.…”

Section: Notesmentioning

confidence: 99%

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Computer-Assisted Language Comparison: State of the Art

Schweikhard

Bodt

et al. 2020

JOHD

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Historical language comparison opens windows onto a human past, long before the availability of written records. Since traditional language comparison within the framework of the comparative method is largely based on manual data comparison, requiring the meticulous sifting through dictionaries, word lists, and grammars, the framework is difficult to apply, especially in times where more and more data have become available in digital form. Unfortunately, it is not possible to simply automate the process of historical language comparison, not only because computational solutions lag behind human judgments in historical linguistics, but also because they lack the flexibility that would allow them to integrate various types of information from various kinds of sources. A more promising approach is to integrate computational and classical approaches within a computer-assisted framework, "neither completely computer-driven nor ignorant of the assistance computers afford" [1, p. 4]. In this paper, we will illustrate what we consider the current state of the art of computer-assisted language comparison by presenting a workflow that starts with raw data and leads up to a stage where sound correspondence patterns across multiple languages have been identified and can be readily presented, inspected, and discussed. We illustrate this workflow with the help of a newly prepared dataset on Hmong-Mien languages. Our illustration is accompanied by Python code and instructions on how to use additional web-based tools we developed so that users can apply our workflow for their own purposes.

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Section: Current Performancementioning

confidence: 99%

Section: Datasetmentioning

confidence: 99%

Section: Notesmentioning

confidence: 99%

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Computer-Assisted Language Comparison: State of the Art

Schweikhard

Bodt

et al. 2020

JOHD

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“…Lists providing concept associations are most typically represented by the WordNet ontology (Fellbaum, 1998). But association data sets, such as the Edinburgh Associative Thesaurus (Kiss, Armstrong, & Milroy, 1973), would also fall under this category as would the recently proposed data sets of cross-linguistic colexifications 3 (Rzymski et al, 2020).…”

Section: Combing Forests Of Datamentioning

confidence: 99%

“…The best practice for storing one's data is, therefore, scientific archiving services, for instance, Zenodo (https://zenodo.org), or the Open Science Framework (https://osf.io). These possibilities enjoy increasing popularity (for studies that store their data on one of the two archives see Kapucu et al, 2018;Lynott et al, 2020;Rzymski et al, 2020).…”

Section: Combing Forests Of Datamentioning

confidence: 99%

Linking Norms, Ratings, and Relations of Words and Concepts Across Multiple Language Varieties

Tjuka¹,

Forkel²,

List³

2020

Preprint

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Psychologists and linguists have collected a great diversity of data for word and concept properties. In psychology, many studies accumulate norms and ratings such as word frequencies or age-of-acquisition often for a large number of words. Linguistics, on the other hand, provides valuable insights into relations of word meanings. We present a collection of those data sets for norms, ratings, and relations that cover different languages: ‘NoRaRe.’ To enable a comparison between the diverse data types, we established workflows that facilitate the expansion of the database. A web application allows convenient access to the data (https://digling.org/norare/). Furthermore, a software API ensures consistent data curation by providing tests to validate the data sets. The NoRaRe collection is linked to the database curated by the Concepticon project (https://concepticon.clld.org) which offers a reference catalog of unified concept sets. The link between words in the data sets and the Concepticon concept sets makes a cross-linguistic comparison possible. In three case studies, we test the validity of our approach, the accuracy of our workflow, and the applicability of our database. The results indicate that the NoRaRe database can be applied for the study of word properties across multiple languages. The data can be used by psychologists and linguists to benefit from the knowledge rooted in both research disciplines.

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From Genitive to Conjunctive: Coordinator li55 in Chongqing Mandarin

Zhong¹,

Dong²

2023

Lecture Notes in Computer Science

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The Database of Cross-Linguistic Colexifications, reproducible analysis of cross-linguistic polysemies

Cited by 99 publications

References 81 publications

Computer-Assisted Language Comparison: State of the Art

Computer-Assisted Language Comparison: State of the Art

Linking Norms, Ratings, and Relations of Words and Concepts Across Multiple Language Varieties

From Genitive to Conjunctive: Coordinator li55 in Chongqing Mandarin

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