Lune

EMNLP2021顶会

Evaluating the Morphosyntactic Well-formedness of Generated Texts

Adithya Pratapa, Antonios Anastasopoulos, Shruti Rijhwani, Aditi Chaudhary, David R. Mortensen, Graham Neubig, Yulia Tsvetkov

2021年份
6被引次数
2顶会引用

摘要

Text generation systems are ubiquitous in natural language processing applications. However, evaluation of these systems remains a challenge, especially in multilingual settings. In this paper, we propose L'AMBRE -a metric to evaluate the morphosyntactic wellformedness of text using its dependency parse and morphosyntactic rules of the language. We present a way to automatically extract various rules governing morphosyntax directly from dependency treebanks. To tackle the noisy outputs from text generation systems, we propose a simple methodology to train robust parsers. We show the effectiveness of our metric on the task of machine translation through a diachronic study of systems translating into morphologically-rich languages. 1

问问这篇 Paper

智能体会读完全文。

Lune 把这篇 Paper 索引到了最后一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。

可以从这些问题问起

智能体调用

Luneget_paper_fulltext

在 Lune 里问

免费开始,无需绑卡

lune papers fulltext e07ad57f-9ecd-4aa3-8a27-d9de5acff859

引用它的顶会 Paper2

问问它们各自怎么用它

它引用的顶会 Paper7

相关 Paper

黄昏的海面,两侧是细线勾勒的悬崖