MorphyNet: a Large Multilingual Database of Derivational and Inflectional Morphology

Batsuren, Khuyagbaatar; Bella, Gábor; Giunchiglia, Fausto

doi:10.18653/v1/2021.sigmorphon-1.5

Cited by 15 publications

(13 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Our database of choice is the Universal Knowledge Core (UKC) 2 (Giunchiglia, Batsuren, & Bella, 2017), due to its wide linguistic, lexical, and conceptual coverage (120 thousand word meanings, 2 million words in 1,127 languages). The UKC has been used in several stud-ies in computational linguistics and lexical semantics, such as the computation of cognates (Batsuren, Bella, & Giunchiglia, 2019, 2021a and multilingual morphology (Batsuren, Bella, & Giunchiglia, 2021b).…”

Section: Methodsmentioning

confidence: 99%

Metonymy as a Universal Cognitive Phenomenon: Evidence from Multilingual Lexicons

Brochhagen¹

2022

Preprint

Self Cite

View full text Add to dashboard Cite

Metonymy is regarded as a universally shared cognitive phenomenon; as such, humans are taken to effortlessly produce and comprehend metonymic senses. However, experimental studies on metonymy have been focused on Western societies, and the linguistic data backing up claims of universality has not been large enough to provide conclusive evidence. We introduce a large-scale analysis of metonymy based on a lexical corpus of 20~thousand metonymy instances from 189 languages and 69 genera. No prior study, to our knowledge, is based on linguistic coverage as broad as ours. Drawing on corpus and statistical analysis, evidence of universality is found at three levels: systematic metonymy in general, particular metonymy patterns, and specific metonymy concepts. These findings imply that a shared conceptual structure for these patterns and concepts holds across societies.

show abstract

Section: Methodsmentioning

confidence: 99%

Metonymy as a Universal Cognitive Phenomenon: Evidence from Multilingual Lexicons

Brochhagen¹

2022

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…no overlapping tokens), resulting in 12,028 entries. MorphyNet (Batsuren et al, 2021) provides derivational and inflectional morphology for words across 15 languages, expanding on the UniMorph dataset (McCarthy et al, 2020). Taking only those derivational morphology entries in English with a concatenative parse gives 193,945 entries.…”

Section: Intrinsic Evaluation: Morphological Correctnessmentioning

confidence: 99%

Improving Tokenisation by Alternative Treatment of Spaces

Edward¹,

Madabushi²,

Scarton³

et al. 2022

Preprint

View full text Add to dashboard Cite

Tokenisation is the first step in almost all NLP tasks, and state-of-the-art transformer-based language models all use subword tokenisation algorithms to process input text. Existing algorithms have problems, often producing tokenisations of limited linguistic validity, and representing equivalent strings differently depending on their position within a word. We hypothesise that these problems hinder the ability of transformer-based models to handle complex words, and suggest that these problems are a result of allowing tokens to include spaces. We thus experiment with an alternative tokenisation approach where spaces are always treated as individual tokens. Specifically, we apply this modification to the BPE and Unigram algorithms. We find that our modified algorithms lead to improved performance on downstream NLP tasks that involve handling complex words, whilst having no detrimental effect on performance in general natural language understanding tasks. Intrinsically, we find our modified algorithms give more morphologically correct tokenisations, in particular when handling prefixes. Given the results of our experiments, we advocate for always treating spaces as individual tokens as an improved tokenisation method.

show abstract

“…Language-specific editions of Wiktionary contain large amounts of derivational data, typically in two forms: etymology templates and derived terms (see Figure 2). Building on prior results from the MorphyNet project (Batsuren et al, 2021), we have implemented an extraction mechanism from both kinds of sections, covering 12 Wiktionary editions and 30 languages. We managed to extract 4.3 million preliminary derivations, as reported in Table 5.…”

Section: Derivational Paradigmsmentioning

confidence: 99%

UniMorph 4.0: Universal Morphology

Batsuren¹,

Goldman²,

Khalifa³

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

The Universal Morphology (UniMorph) project is a collaborative effort providing broad-coverage instantiated normalized morphological inflection tables for hundreds of diverse world languages. The project comprises two major thrusts: a languageindependent feature schema for rich morphological annotation and a type-level resource of annotated data in diverse languages realizing that schema. This paper presents the expansions and improvements made on several fronts over the last couple of years (since McCarthy et al. (2020)). Collaborative efforts by numerous linguists have added 67 new languages, including 30 endangered languages. We have implemented several improvements to the extraction pipeline to tackle some issues, e.g. missing gender and macron information. We have also amended the schema to use a hierarchical structure that is needed for morphological phenomena like multiple-argument agreement and case stacking, while adding some missing morphological features to make the schema more inclusive. In light of the last UniMorph release, we also augmented the database with morpheme segmentation for 16 languages. Lastly, this new release makes a push towards inclusion of derivational morphology in UniMorph by enriching the data and annotation schema with instances representing derivational processes from MorphyNet.

show abstract

MorphyNet: a Large Multilingual Database of Derivational and Inflectional Morphology

Cited by 15 publications

References 22 publications

Metonymy as a Universal Cognitive Phenomenon: Evidence from Multilingual Lexicons

Metonymy as a Universal Cognitive Phenomenon: Evidence from Multilingual Lexicons

Improving Tokenisation by Alternative Treatment of Spaces

UniMorph 4.0: Universal Morphology

Contact Info

Product

Resources

About