21 |
Predicting Declension Class from Form and Meaning
|
|
|
|
In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (2020)
|
|
BASE
|
|
Show details
|
|
22 |
A Tale of a Probe and a Parser
|
|
|
|
In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (2020)
|
|
BASE
|
|
Show details
|
|
23 |
Intrinsic Probing through Dimension Selection
|
|
|
|
In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) (2020)
|
|
BASE
|
|
Show details
|
|
24 |
Information-Theoretic Probing for Linguistic Structure
|
|
|
|
In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (2020)
|
|
BASE
|
|
Show details
|
|
28 |
Measuring the Similarity of Grammatical Gender Systems by Comparing Partitions ...
|
|
|
|
Abstract:
A grammatical gender system divides a lexicon into a small number of relatively fixed grammatical categories. How similar are these gender systems across languages? To quantify the similarity, we define gender systems extensionally, thereby reducing the problem of comparisons between languages’ gender systems to cluster evaluation. We borrow a rich inventory of statistical tools for cluster evaluation from the field of community detection (Driver and Kroeber, 1932; Cattell, 1945), that enable us to craft novel information theoretic metrics for measuring similarity between gender systems. We first validate our metrics, then use them to measure gender system similarity in 20 languages. We then ask whether our gender system similarities alone are sufficient to reconstruct historical relationships between languages. Towards this end, we make phylogenetic predictions on the popular, but thorny, problem from historical linguistics of inducing a phylogenetic tree over extant Indo-European languages. Of particular ... : Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) ...
|
|
URL: http://hdl.handle.net/20.500.11850/462323 https://dx.doi.org/10.3929/ethz-b-000462323
|
|
BASE
|
|
Hide details
|
|
30 |
Definiteness across languages
|
|
|
|
In: Language Science Press; (2019)
|
|
BASE
|
|
Show details
|
|
31 |
Definiteness across languages
|
|
|
|
In: Language Science Press; (2019)
|
|
BASE
|
|
Show details
|
|
32 |
Definiteness across languages
|
|
|
|
In: Language Science Press; (2019)
|
|
BASE
|
|
Show details
|
|
33 |
Definiteness across languages
|
|
|
|
In: Language Science Press; (2019)
|
|
BASE
|
|
Show details
|
|
34 |
Definiteness across languages
|
|
|
|
In: Language Science Press; (2019)
|
|
BASE
|
|
Show details
|
|
35 |
Definiteness across languages
|
|
|
|
In: Language Science Press; (2019)
|
|
BASE
|
|
Show details
|
|
36 |
Definiteness across languages
|
|
|
|
In: Language Science Press; (2019)
|
|
BASE
|
|
Show details
|
|
37 |
On the Idiosyncrasies of the Mandarin Chinese Classifier System ...
|
|
|
|
BASE
|
|
Show details
|
|
39 |
Definiteness across languages
|
|
|
|
In: Language Science Press; (2019)
|
|
BASE
|
|
Show details
|
|
40 |
Definiteness across languages
|
|
|
|
In: Language Science Press; (2019)
|
|
BASE
|
|
Show details
|
|
|
|