Towards the Detection and Formal Representation of Semantic Shifts in Inflectional Morphology

Dagmar Gromann, Thierry Declerck

In: Maria Eskevich , Gerard de Melo , Christian Fäth , John P. McCrae , Paul Buitelaar , Christian Chiarcos , Bettina Klimek , Milan Dojchinovski (Hrsg.). 2nd Conference on Language, Data and Knowledge (LDK). Conference on Language, Data and Knowledge (LDK-2019) May 20-23 Leipzig Germany Seiten 21-1 OpenAccess Series in Informatics (OASIcs) (OASIcs) 70 ISBN 978-3-95977-105-4} Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik Dagstuhl, Germany 5/2019.


Semantic shifts caused by derivational morphemes is a common subject of investigation in language modeling, while inflectional morphemes are frequently portrayed as semantically more stable. This study is motivated by the previously established observation that inflectional morphemes can be just as variable as derivational ones. For instance, the English plural “-s” can turn the fabric "silk" into the garments of a jockey, "silks". While humans know that "silk" in this sense has no plural, it takes more for machines to arrive at this conclusion. Frequently utilized computational language resources,such as WordNet, or models for representing computational lexicons, like OntoLex-Lemon, have no descriptive mechanism to represent such inflectional semantic shifts. To investigate this phenomenon,we extract word pairs of different grammatical number from WordNet that feature additional senses in the plural and evaluate their distribution in vector space, i.e., pre-trained word2vec and fastText embeddings. We then propose an extension of OntoLex-Lemon to accommodate this phenomenon that we call inflectional morpho-semantic variation to provide a formal representation accessible to algorithms, neural networks, and agents. While the exact scope of the problem is yet to be determined, this first dataset shows that it is not negligible.


OASIcs-LDK-2019-21.pdf (pdf, 436 KB )

Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence