| 1. |
- Basirat, Ali, Postdoctoral Researcher, 1982-, et al.
(författare)
-
An empirical study on the contribution of formal and semantic features to the grammatical gender of nouns
- 2021
-
Ingår i: Linguistics Vanguard. - : Walter de Gruyter. - 2199-174X. ; 7:1
-
Tidskriftsartikel (refereegranskat)abstract
- This study conducts an experimental evaluation of two hypotheses about the contributions of formal and semantic features to the grammatical gender assignment of nouns. One of the hypotheses (Corbett and Fraser, 2000) claims that semantic features dominate formal ones. The other hypothesis, formulated within the optimal gender assignment theory (Rice, 2006), states that form and semantics contribute equally. Both hypotheses claim that the combination of formal and semantic features yields the most accurate gender identification. In this paper, we operationalize and test these hypotheses by trying to predict grammatical gender using only character-based embeddings (that capture only formal features), only context-based embeddings (that capture only semantic features) and the combination of both. We performed the experiment using data from three languages with different gender systems (French, German and Russian). Formal features are a significantly better predictor of gender than semantic ones, and the difference in prediction accuracy is very large. Overall, formal features are also significantly better than the combination of form and semantics, but the difference is very small and the results for this comparison are not entirely consistent across languages.
|
|
| 2. |
- Basirat, Ali, Postdoctoral Researcher, 1982-, et al.
(författare)
-
Syntactic Nuclei in Dependency Parsing – : A Multilingual Exploration
- 2021
-
Ingår i: Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics. - Stroudsburg, PA, USA : Association for Computational Linguistics. - 9781954085022 ; , s. 1376-1387
-
Konferensbidrag (refereegranskat)abstract
- Standard models for syntactic dependency parsing take words to be the elementary units that enter into dependency relations. In this paper, we investigate whether there are any benefits from enriching these models with the more abstract notion of nucleus proposed by Tesniere. We do this by showing how the concept of nucleus can be defined in the framework of Universal Dependencies and how we can use composition functions to make a transition-based dependency parser aware of this concept. Experiments on 12 languages show that nucleus composition gives small but significant improvements in parsing accuracy. Further analysis reveals that the improvement mainly concerns a small number of dependency relations, including relations of coordination, direct objects, nominal modifiers, and main predicates.
|
|
| 3. |
|
|
| 4. |
|
|
| 5. |
- Veeman, Hartger, et al.
(författare)
-
Cross-lingual Embeddings Reveal Universal and Lineage-Specific Patterns in Grammatical Gender Assignment
- 2020
-
Ingår i: Proceedings of the the 24th Conference on Computational Natural Language Learning. - Stroudsburg, PA, USA : Association for Computational Linguistics. ; , s. 265-275
-
Konferensbidrag (refereegranskat)abstract
- Grammatical gender is assigned to nouns differently in different languages. Are all factors that influence gender assignment idiosyncratic to languages or are there any that are universal? Using cross-lingual aligned word embeddings, we perform two experiments to address these questions about language typology and human cognition. In both experiments, we predict the gender of nouns in language X using a classifier trained on the nouns of language Y, and take the classifier{'}s accuracy as a measure of transferability of gender systems. First, we show that for 22 Indo-European languages the transferability decreases as the phylogenetic distance increases. This correlation supports the claim that some gender assignment factors are idiosyncratic, and as the languages diverge, the proportion of shared inherited idiosyncrasies diminishes. Second, we show that when the classifier is trained on two Afro-Asiatic languages and tested on the same 22 Indo-European languages (or vice versa), its performance is still significantly above the chance baseline, thus showing that universal factors exist and, moreover, can be captured by word embeddings. When the classifier is tested across families and on inanimate nouns only, the performance is still above baseline, indicating that the universal factors are not limited to biological sex.
|
|
