@article{LopukhinaLopukhinLaurinavichyute2021,
  author    = {Lopukhina, Anastasiya and Lopukhin, Konstantin and Laurinavichyute, Anna},
  title     = {Morphosyntactic but not lexical corpus-based probabilities can substitute for cloze probabilities in reading experiments},
  series = {PLOS ONE / Public Library of Science},
  volume    = {16},
  journal   = {PLOS ONE / Public Library of Science},
  number    = {1},
  publisher = {PLoS},
  address   = {San Fransisco},
  issn      = {1932-6203},
  doi       = {10.1371/journal.pone.0246133},
  pages     = {26},
  year      = {2021},
  abstract  = {During reading or listening, people can generate predictions about the lexical and morphosyntactic properties of upcoming input based on available context. Psycholinguistic experiments that study predictability or control for it conventionally rely on a human-based approach and estimate predictability via the cloze task. Our study investigated an alternative corpus-based approach for estimating predictability via language predictability models. We obtained cloze and corpus-based probabilities for all words in 144 Russian sentences, correlated the two measures, and found a strong correlation between them. Importantly, we estimated how much variance in eye movements registered while reading the same sentences was explained by each of the two probabilities and whether the two probabilities explain the same variance. Along with lexical predictability (the activation of a particular word form), we analyzed morphosyntactic predictability (the activation of morphological features of words) and its effect on reading times over and above lexical predictability. We found that for predicting reading times, cloze and corpus-based measures of both lexical and morphosyntactic predictability explained the same amount of variance. However, cloze and corpus-based lexical probabilities both independently contributed to a better model fit, whereas for morphosyntactic probabilities, the contributions of cloze and corpus-based measures were interchangeable. Therefore, morphosyntactic but not lexical corpus-based probabilities can substitute for cloze probabilities in reading experiments. Our results also indicate that in languages with rich inflectional morphology, such as Russian, when people engage in prediction, they are much more successful in predicting isolated morphosyntactic features than predicting the particular lexeme and its full morphosyntactic markup.},
  language  = {en}
}
@article{LopukhinaLaurinavichyuteLopukhinetal.2018,
  author    = {Lopukhina, Anastasiya and Laurinavichyute, Anna and Lopukhin, Konstantin and Dragoy, Olga V.},
  title     = {The Mental Representation of Polysemy across Word Classes},
  series = {Frontiers in psychology},
  volume    = {9},
  journal   = {Frontiers in psychology},
  publisher = {Frontiers Research Foundation},
  address   = {Lausanne},
  issn      = {1664-1078},
  doi       = {10.3389/fpsyg.2018.00192},
  pages     = {16},
  year      = {2018},
  abstract  = {Experimental studies on polysemy have come to contradictory conclusions on whether words with multiple senses are stored as separate or shared mental representations. The present study examined the semantic relatedness and semantic similarity of literal and non-literal (metonymic and metaphorical) senses of three word classes: nouns, verbs, and adjectives. Two methods were used: a psycholinguistic experiment and a distributional analysis of corpus data. In the experiment, participants were presented with 6-12 short phrases containing a polysemous word in literal, metonymic, or metaphorical senses and were asked to classify them so that phrases with the same perceived sense were grouped together. To investigate the impact of professional background on their decisions, participants were controlled for linguistic vs. non-linguistic education. For nouns and verbs, all participants preferred to group together phrases with literal and metonymic senses, but not any other pairs of senses. For adjectives, two pairs of senses were often grouped together: literal with metonymic, and metonymic with metaphorical. Participants with a linguistic background were more accurate than participants with non-linguistic backgrounds, although both groups shared principal patterns of sense classification. For the distributional analysis of corpus data, we used a semantic vector approach to quantify the similarity of phrases with literal, metonymic, and metaphorical senses in the corpora. We found that phrases with literal and metonymic senses had the highest degree of similarity for the three word classes, and that metonymic and metaphorical senses of adjectives had the highest degree of similarity among all word classes. These findings are in line with the experimental results. Overall, the results suggest that the mental representation of a polysemous word depends on its word class. In nouns and verbs, literal and metonymic senses are stored together, while metaphorical senses are stored separately; in adjectives, metonymic senses significantly overlap with both literal and metaphorical senses.},
  language  = {en}
}
@misc{LopukhinaLaurinavichyuteLopukhinetal.2018,
  author    = {Lopukhina, Anastasiya and Laurinavichyute, Anna and Lopukhin, Konstantin and Dragoy, Olga V.},
  title     = {The mental representation of polysemy across word classes},
  series = {Postprints der Universit{\"a}t Potsdam : Humanwissenschaftliche Reihe},
  journal   = {Postprints der Universit{\"a}t Potsdam : Humanwissenschaftliche Reihe},
  number    = {637},
  issn      = {1866-8364},
  doi       = {10.25932/publishup-44563},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-445637},
  pages     = {18},
  year      = {2018},
  abstract  = {Experimental studies on polysemy have come to contradictory conclusions on whether words with multiple senses are stored as separate or shared mental representations. The present study examined the semantic relatedness and semantic similarity of literal and non-literal (metonymic and metaphorical) senses of three word classes: nouns, verbs, and adjectives. Two methods were used: a psycholinguistic experiment and a distributional analysis of corpus data. In the experiment, participants were presented with 6-12 short phrases containing a polysemous word in literal, metonymic, or metaphorical senses and were asked to classify them so that phrases with the same perceived sense were grouped together. To investigate the impact of professional background on their decisions, participants were controlled for linguistic vs. non-linguistic education. For nouns and verbs, all participants preferred to group together phrases with literal and metonymic senses, but not any other pairs of senses. For adjectives, two pairs of senses were often grouped together: literal with metonymic, and metonymic with metaphorical. Participants with a linguistic background were more accurate than participants with non-linguistic backgrounds, although both groups shared principal patterns of sense classification. For the distributional analysis of corpus data, we used a semantic vector approach to quantify the similarity of phrases with literal, metonymic, and metaphorical senses in the corpora. We found that phrases with literal and metonymic senses had the highest degree of similarity for the three word classes, and that metonymic and metaphorical senses of adjectives had the highest degree of similarity among all word classes. These findings are in line with the experimental results. Overall, the results suggest that the mental representation of a polysemous word depends on its word class. In nouns and verbs, literal and metonymic senses are stored together, while metaphorical senses are stored separately; in adjectives, metonymic senses significantly overlap with both literal and metaphorical senses.},
  language  = {en}
}