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Related papers: The distribution of syntactic dependency distances

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Writing style is a combination of consistent decisions at different levels of language production including lexical, syntactic, and structural associated to a specific author (or author groups). While lexical-based models have been widely…

Computation and Language · Computer Science 2019-02-28 Fereshteh Jafariakinabad , Sansiri Tarnpradab , Kien A. Hua

Most compositional distributional semantic models represent sentence meaning with a single vector. In this paper, we propose a Structured Distributional Model (SDM) that combines word embeddings with formal semantics and is based on the…

Computation and Language · Computer Science 2019-06-19 Emmanuele Chersoni , Enrico Santus , Ludovica Pannitto , Alessandro Lenci , Philippe Blache , Chu-Ren Huang

Conventional graph-based dependency parsers guarantee a tree structure both during training and inference. Instead, we formalize dependency parsing as the problem of independently selecting the head of each word in a sentence. Our model…

Computation and Language · Computer Science 2016-12-23 Xingxing Zhang , Jianpeng Cheng , Mirella Lapata

While language is a complex adaptive system, most work on syntactic variation observes a few individual constructions in isolation from the rest of the grammar. This means that the grammar, a network which connects thousands of structures…

Computation and Language · Computer Science 2023-09-22 Jonathan Dunn

A theory of systems with long-range correlations based on the consideration of binary N-step Markov chains is developed. In the model, the conditional probability that the i-th symbol in the chain equals zero (or unity) is a linear function…

Data Analysis, Statistics and Probability · Physics 2016-09-08 O. V. Usatenko , V. A. Yampol'skii , K. E. Kechedzhy , S. S. Mel'nyk

We define a dynamic model of random networks, where new vertices are connected to old ones with a probability proportional to a sublinear function of their degree. We first give a strong limit law for the empirical degree distribution, and…

Probability · Mathematics 2008-07-31 Steffen Dereich , Peter Morters

The thesis presents an attempt at using the syntactic structure in natural language for improved language models for speech recognition. The structured language model merges techniques in automatic parsing and language modeling using an…

Computation and Language · Computer Science 2007-05-23 Ciprian Chelba

Language is hierarchically organized: words are built into phrases, sentences, and paragraphs to represent complex ideas. Here we ask whether the organization of language in written text displays the fractal hierarchical architecture common…

Physics and Society · Physics 2018-10-26 Lucy R. Chai , Danielle S. Bassett

The frequency of the preferred order for a noun phrase formed by demonstrative, numeral, adjective and noun has received significant attention over the last two decades. We investigate the actual distribution of the 24 possible orders.…

Computation and Language · Computer Science 2026-01-23 Ramon Ferrer-i-Cancho

A set of independence statements may define the independence structure of interest in a family of joint probability distributions. This structure is often captured by a graph that consists of nodes representing the random variables and of…

Methodology · Statistics 2011-07-15 Nanny Wermuth

Natural language exhibits statistical dependencies at a wide range of scales. For instance, the mutual information between words in natural language decays like a power law with the temporal lag between them. However, many statistical…

Computation and Language · Computer Science 2019-12-17 Aakash Sarkar , Marc Howard

A central question in psycholinguistics is the timing of syntax in sentence processing. Much of the existing evidence comes from violation paradigms, which conflate two separable processes - syntactic category detection and phrase structure…

Computation and Language · Computer Science 2025-09-30 Nan Wang , Jiaxuan Li

We present a probabilistic language model for time-stamped text data which tracks the semantic evolution of individual words over time. The model represents words and contexts by latent trajectories in an embedding space. At each moment in…

Machine Learning · Statistics 2017-07-19 Robert Bamler , Stephan Mandt

In this work, we propose a novel constituency parsing scheme. The model predicts a vector of real-valued scalars, named syntactic distances, for each split position in the input sentence. The syntactic distances specify the order in which…

Computation and Language · Computer Science 2018-06-13 Yikang Shen , Zhouhan Lin , Athul Paul Jacob , Alessandro Sordoni , Aaron Courville , Yoshua Bengio

This study investigates human and ChatGPT text simplification and its relationship to dependency distance. A set of 220 sentences, with increasing grammatical difficulty as measured in a prior user study, were simplified by a human expert…

Computation and Language · Computer Science 2024-06-27 Sumi Lee , Gondy Leroy , David Kauchak , Melissa Just

The distances between words calculated in word units are studied and compared with the distributions of the Random Matrix Theory (RMT). It is found that the distribution of distance between the same words can be well described by the…

Computation and Language · Computer Science 2021-10-27 Bogdan Łobodziński

Dependency distance minimization (DDm) is a well-established principle of word order. It has been predicted theoretically that DDm implies compression, namely the minimization of word lengths. This is a second order prediction because it…

Computation and Language · Computer Science 2023-10-16 Ramon Ferrer-i-Cancho , Carlos Gómez-Rodríguez

As speakers turn their thoughts into sentences, they maintain a balance between the complexity of words and syntax. However, it is unclear whether this syntax-lexicon tradeoff is unique to the spoken language production that is under the…

Computation and Language · Computer Science 2022-06-28 Neguine Rezaii

In order to build efficient deep recurrent neural architectures, it is essential to analyze the complexityof long distance dependencies (LDDs) of the dataset being modeled. In this paper, we presentdetailed analysis of the dependency decay…

Machine Learning · Computer Science 2020-12-09 Abhijit Mahalunkar , John D. Kelleher

We analyze here a particular kind of linguistic network where vertices representwords and edges stand for syntactic relationships between words. The statisticalproperties of these networks have been recently studied and various features…

Statistical Mechanics · Physics 2007-05-23 Ramon Ferrer i Cancho , Andrea Capocci , Guido Caldarelli