DE eng

Search in the Catalogues and Directories

Hits 1 – 14 of 14

1
Investigating Failures of Automatic Translation in the Case of Unambiguous Gender ...
BASE
Show details
2
On the Relationships Between the Grammatical Genders of Inanimate Nouns and Their Co-Occurring Adjectives and Verbs ...
BASE
Show details
3
SIGMORPHON 2020 Shared Task 0: Typologically Diverse Morphological Inflection ...
BASE
Show details
4
Intrinsic Probing through Dimension Selection ...
BASE
Show details
5
Information-Theoretic Probing for Linguistic Structure ...
BASE
Show details
6
Predicting Declension Class from Form and Meaning ...
BASE
Show details
7
Predicting declension class from form and meaning
BASE
Show details
8
Pareto Probing: Trading Off Accuracy for Complexity ...
BASE
Show details
9
A Tale of a Probe and a Parser ...
BASE
Show details
10
On the Idiosyncrasies of the Mandarin Chinese Classifier System ...
BASE
Show details
11
Quantifying the Semantic Core of Gender Systems ...
BASE
Show details
12
XNLI: Evaluating Cross-lingual Sentence Representations ...
BASE
Show details
13
Verb Argument Structure Alternations in Word and Sentence Embeddings ...
Abstract: Verbs occur in different syntactic environments, or frames. We investigate whether artificial neural networks encode grammatical distinctions necessary for inferring the idiosyncratic frame-selectional properties of verbs. We introduce five datasets, collectively called FAVA, containing in aggregate nearly 10k sentences labeled for grammatical acceptability, illustrating different verbal argument structure alternations. We then test whether models can distinguish acceptable English verb-frame combinations from unacceptable ones using a sentence embedding alone. For converging evidence, we further construct LaVA, a corresponding word-level dataset, and investigate whether the same syntactic features can be extracted from word embeddings. Our models perform reliable classifications for some verbal alternations but not others, suggesting that while these representations do encode fine-grained lexical information, it is incomplete or can be hard to extract. Further, differences between the word- and ... : Accepted to SCiL 2019 ...
Keyword: Computation and Language cs.CL; FOS Computer and information sciences
URL: https://dx.doi.org/10.48550/arxiv.1811.10773
https://arxiv.org/abs/1811.10773
BASE
Hide details
14
The RepEval 2017 Shared Task: Multi-Genre Natural Language Inference with Sentence Representations ...
BASE
Show details

Catalogues
0
0
0
0
0
0
0
Bibliographies
0
0
0
0
0
0
0
0
0
Linked Open Data catalogues
0
Online resources
0
0
0
0
Open access documents
14
0
0
0
0
© 2013 - 2024 Lin|gu|is|tik | Imprint | Privacy Policy | Datenschutzeinstellungen ändern