81 |
SIGMORPHON 2020 Shared Task 0: Typologically Diverse Morphological Inflection ...
|
|
|
|
BASE
|
|
Show details
|
|
83 |
SIGTYP 2020 Shared Task: Prediction of Typological Features ...
|
|
|
|
BASE
|
|
Show details
|
|
86 |
It’s Easier to Translate out of English than into it: Measuring Neural Translation Difficulty by Cross-Mutual Information ...
|
|
|
|
BASE
|
|
Show details
|
|
89 |
Generalized Entropy Regularization or: There’s Nothing Special about Label Smoothing ...
|
|
|
|
BASE
|
|
Show details
|
|
94 |
Investigating Cross-Linguistic Adjective Ordering Tendencies with a Latent-Variable Model ...
|
|
|
|
BASE
|
|
Show details
|
|
96 |
Predicting Declension Class from Form and Meaning ...
|
|
|
|
Abstract:
The noun lexica of many natural languages are divided into several declension classes with characteristic morphological properties. Class membership is far from deterministic, but the phonological form of a noun and/or its meaning can often provide imperfect clues. Here, we investigate the strength of those clues. More specifically, we operationalize this by measuring how much information, in bits, we can glean about declension class from knowing the form and/or meaning of nouns. We know that form and meaning are often also indicative of grammatical gender---which, as we quantitatively verify, can itself share information with declension class---so we also control for gender. We find for two Indo-European languages (Czech and German) that form and meaning respectively share significant amounts of information with class (and contribute additional information above and beyond gender). The three-way interaction between class, form, and meaning (given gender) is also significant. Our study is important for two ... : 14 pages, 2 figures, the is the camera-ready version accepted at the 2020 Annual Conference of the Association for Computational Linguistics (ACL 2020) ...
|
|
Keyword:
Computation and Language cs.CL; FOS Computer and information sciences
|
|
URL: https://arxiv.org/abs/2005.00626 https://dx.doi.org/10.48550/arxiv.2005.00626
|
|
BASE
|
|
Hide details
|
|
98 |
Please Mind the Root: Decoding Arborescences for Dependency Parsing
|
|
|
|
In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) (2020)
|
|
BASE
|
|
Show details
|
|
99 |
Measuring the Similarity of Grammatical Gender Systems by Comparing Partitions
|
|
|
|
In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) (2020)
|
|
BASE
|
|
Show details
|
|
100 |
Investigating Cross-Linguistic Adjective Ordering Tendencies with a Latent-Variable Model
|
|
|
|
In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) (2020)
|
|
BASE
|
|
Show details
|
|
|
|