The Mental Lexicon - Volume 17, Issue 3, 2022

Distributional semantics offers new ways to study the semantics of morphology. This study focuses on the semantics of noun singulars and their plural inflectional variants in English. Our goal is to compare two models for the conceptualization of plurality. One model (FRACSS) proposes that all singular-plural pairs should be taken into account when predicting plural semantics from singular semantics. The other model (CCA) argues that conceptualization for plurality depends primarily on the semantic class of the base word. We compare the two models on the basis of how well the speech signal of plural tokens in a large corpus of spoken American English aligns with the semantic vectors predicted by the two models. Two measures are employed: the performance of a form-to-meaning mapping and the correlations between form distances and meaning distances. Results converge on a superior alignment for CCA. Our results suggest that usage-based approaches to pluralization in which a given word’s own semantic neighborhood is given priority outperform theories according to which pluralization is conceptualized as a process building on high-level abstraction. We see that what has often been conceived of as a highly abstract concept, [+plural], is better captured via a family of mid-level partial generalizations.

Finnish nouns are characterized by rich inflectional variation, with obligatory marking of case and number, with optional possessive suffixes and with the possibility of further cliticization. We present a model for the conceptualization of Finnish inflected nouns, using pre-compiled fasttext embeddings (300-dimensional semantic vectors that approximate words’ meanings). Instead of deriving the semantic vector of an inflected word from another word in its paradigm, we propose that an inflected word is conceptualized by means of summation of latent vectors representing the meanings of its lexeme and its inflectional features. We tested this model on the 2,000 most frequent Finnish nouns and their inflected word forms from a corpus of Finnish (84 million tokens). Visualization of the semantic space of Finnish using t-SNE clarified that a ‘main effects’ additive model does not do justice to the semantics of inflection. In Finnish, how number is realized turns out to vary substantially with case. Further interactions emerged with the possessive suffixes and the clitics. By taking these interactions into account, the accuracy of our model, evaluated with the fasttext embeddings as gold standard, improved from 76% to 89%. Analyses of the errors made by the model clarified that 7.5% of errors are due to overabundance (and hence not true errors), and that 16.5% of the errors involved exchanges of semantically highly similar stems (lexemes). Our results indicate, first, that the semantics of Finnish noun inflection are more intricate than assumed thus far, and second, that these intricacies can be captured with surprisingly high accuracy by a simple generating model based on imputed semantic vectors for lexemes, inflectional features, and interactions of inflectional features.

This study investigates the phenomenon of defectiveness in Russian case and number noun paradigms from the perspective of distributional semantics. We made use of word embeddings, high-dimensional vectors trained from large text corpora, and compared the observed paradigms of nouns that are defective in the genitive plural, as suggested by Zaliznjak (1977), with the observed paradigms for non-defective nouns. When the embeddings of about 20,000 inflected forms were projected onto a two-dimensional space, clusters of case and number within case were found, suggesting global semantic similarity for words with the same inflectional features. Moreover, defective lexemes were characterized by lower semantic transparency, in that inflected forms of the same lexeme are semantically less similar to each other, and their meanings are also more idiosyncratic. Furthermore, compared to non-defective lexemes, inflected forms from defective lexemes are further away from the idealized average case-number meanings, obtained by averaging over the vectors of all inflected forms of the same case-number combination. As a consequence, the semantics of defective forms are predicted less precisely by a simple model of conceptualization that assumes that the meaning of a given Russian inflected form is approximated well by the sum of pertinent embeddings of the lexeme, case, and number within case. We conclude that the relationship between defectiveness and semantics, at least the kind captured by word embeddings, is stronger than has been anticipated previously.

This study addresses the relation between morphological productivity and semantic transparency. Using distributional semantics, we compare German word formation using particles with derivational word formation. We observed that derivational suffixes, but not particles, tend to make strong independent semantic contributions to their carrier words. In two-dimensional t-SNE maps, complex words show clustering by affix, but not by particle. Furthermore, the semantic vectors of suffixed words are predictable from their base words with higher accuracy than is possible for particle verbs. For particle verbs, but not affixed verbs, semantic similarity within the set of complex words correlated negatively with the number of types. Furthermore, only for particle verbs, a greater number of observed types predicted a reduced probability of observing unseen types. We propose that particle verbs primarily serve the onomasiological function of labeling, resulting in relatively idiosyncratic semantic vectors. By contrast, words sharing derivational affixes form distinct clusters in semantic space while maintaining strong and consistent semantic relations with their base words. This enables these words to serve not only as labels, but also allows them to be used with an anaphoric function in discourse.

We used word embeddings to study the relation between productivity and semantic transparency. We compiled a dataset with around 2700 two-syllable compounds that shared position-specific constituents (henceforth pivots) and some 1100 suffixed words. For each pivot and suffix, we calculated measures of productivity as well as measures of semantic transparency. For compounds, productivity (P) was negatively correlated with the number of types (V) and with the semantic similarity between non-pivot constituents and their compounds. Conversely, the greater semantic similarity of the pivot with either the compound or the non-pivot constituent predicted higher degrees of productivity. Visualization with t-SNE revealed clustering of suffixed words’ embeddings, but no by-pivot clustering for compounds, except for a minority of pivots whose regions in semantic space did not contain intruding unrelated compounds. A subset of these pivots was found to realize a fixed shift in semantic space from the base word to the corresponding compound, a property that also emerged for several suffixes. For these pivots, no correlation between P and V was present. Thus, Mandarin compounds appear to realize, at one extreme, motivated but unsystematic concept formation (where other pivots could just as well have been used), and at the other extreme, systematic suffix-like semantics.