paper-with-me

Papers

The Distribution of Dependency Distance and Hierarchical Distance in Contemporary Written Japanese and Its Influencing Factors

2025-04-30 · Linxuan Wang, Shuiyuan Yu

To explore the relationship between dependency distance (DD) and hierarchical distance (HD) in Japanese, we compared the probability distributions of DD and HD with and without sentence length fixed, and analyzed the changes in mean dependency distance (MDD) and mean hierarchical distance (MHD) as sentence length increases, along with their correlation coefficient based on the Balanced Corpus of Contemporary Written Japanese. It was found that the valency of the predicates is the underlying factor behind the trade-off relation between MDD and MHD in Japanese. Native speakers of Japanese regulate the linear complexity and hierarchical complexity through the valency of the predicates, and the relative sizes of MDD and MHD depend on whether the threshold of valency has been reached. Apart from the cognitive load, the valency of the predicates also affects the probability distributions of DD and HD. The effect of the valency of the predicates on the distribution of HD is greater than on that of DD, which leads to differences in their probability distributions and causes the mean of MDD to be lower than that of MHD.

📄 PDF Abstract BibTeX arXiv:2504.21421

Code (0)

등록된 구현이 없습니다.

Tasks

Sentence

Similar Papers 제목 키워드 기반

Modelling dependency completion in sentence comprehension as a Bayesian hierarchical mixture process: A case study involving Chinese relative clauses

2017-02-02 · Shravan Vasishth, Nicolas Chopin, Robin Ryder, Bruno Nicenboim

We present a case-study demonstrating the usefulness of Bayesian hierarchical mixture modelling for investigating cognitive processes. In sentence comprehension, it is widely assumed that the distance between linguistic …

RetrievalSentence

Mean Hierarchical Distance Augmenting Mean Dependency Distance

2015-08-01 · WS 2015 8 · Yingqi Jing, Haitao Liu

Hierarchical Optimal Transport for Robust Multi-View Learning

2020-06-04 · Dixin Luo, Hongteng Xu, Lawrence Carin

Traditional multi-view learning methods often rely on two assumptions: ($i$) the samples in different views are well-aligned, and ($ii$) their representations in latent space obey the same distribution. Unfortunately, th…

ClusteringMULTI-VIEW LEARNING

Evaluating a Dependency Parser on DeReKo

2020-05-01 · LREC 2020 5 · Peter Fankhauser, Bich-Ngoc Do, Marc Kupietz

We evaluate a graph-based dependency parser on DeReKo, a large corpus of contemporary German. The dependency parser is trained on the German dataset from the SPMRL 2014 Shared Task which contains text from the news domai…

The influence of Chunking on Dependency Crossing and Distance

2015-09-03 · Qian Lu, Chunshan Xu, Haitao Liu

This paper hypothesizes that chunking plays important role in reducing dependency distance and dependency crossings. Computer simulations, when compared with natural languages,show that chunking reduces mean dependency d…

Chunking