Empirical Analysis for Unsupervised Universal Dependency Parse Tree Aggregation

arXiv:2403.19183v1 Announce Type: new
Abstract: Dependency parsing is an essential task in NLP, and the quality of dependency parsers is crucial for many downstream tasks. Parsers' quality often varies depending on the domain and the language involved. Therefore, it is essential to combat the issue of varying quality to achieve stable performance. In various NLP tasks, aggregation methods are used for post-processing aggregation and have been shown to combat the issue of varying quality. However, aggregation methods for post-processing aggregation …

abstract aggregation analysis arxiv cs.cl domain issue language nlp parsing quality tasks tree type universal unsupervised