Тәуелділік ағашы

We describe a method for generating sentences from “keywords” or “headwords”. This method consists of two main parts, candidate-text con- struction and evaluation. The construction part generates text sentences in …...

In this paper, a novel semantic role labeler based on dependency trees is developed. This is ac- complished by formulating the semantic role la- beling as a classification problem of …...

We propose a novel method for Japanese de- pendency analysis, which is usually reduced to the construction of a dependency tree. In deterministic approaches to this task, depen- dency trees …...

Deterministic dependency parsers use pars- ing actions to construct dependencies. These parsers do not compute the probabil- ity of the whole dependency tree. They only determine parsing actions stepwisely by …...

Phrase-based decoding produces state-of-the- art translations with no regard for syntax. We add syntax to this process with a cohesion constraint based on a dependency tree for the source sentence. …...

The extent to which the organization of nat- ural language grammars reflects a drive to minimize dependency length remains little explored. We present the first algorithm polynomial-time in sentence length …...

AbstractThis paper reports on the annotation of a corpus of 1 million words with four semantic annotation layers, including named entities, co- reference relations, semantic roles and spatial and temporal …...

Sentence compression techniques often assemble output sentences using frag- ments of lexical sequences such as n- grams or units of syntactic structure such as edges from a dependency tree repre- …...

We developed a system to participate in shared tasks on the analyzing clinical text. Our system approaches are both machine learning-based and rule-based. We applied the machine learning-based approach for …...

Dependency tree-to-tree translation models are powerful because they can naturally han- dle long range reorderings which is important for distant language pairs. The translation pro- cess is easy if it …...

Long Short-Term Memory (LSTM) networks, a type of recurrent neural network with a more complex computational unit, have been successfully applied to a variety of sequence modeling tasks. In this …...

AbstractDue to their inherent capability in semantic alignment of aspects and their context words, attention mechanism and Convolutional Neural Networks (CNNs) are widely applied for aspect-based sentiment classification. However, these …...

AbstractSyntactic relations are broadly used in many NLP tasks. For event detection, syntactic relation representations based on dependency tree can better capture the interrelations between candidate trigger words and related …...

AbstractWe present a new method for transition-based parsing where a solution is a pair made of a dependency tree and a derivation graph describing the construction of the former. From …...

AbstractWe present a bracketing-based encoding that can be used to represent any 2-planar dependency tree over a sentence of length n as a sequence of n labels, hence providing almost …...

AbstractRecent studies on event detection (ED) have shown that the syntactic dependency graph can be employed in graph convolution neural networks (GCN) to achieve state-of-the-art performance. However, the computation of …...

AbstractThis paper describes our efforts in tackling Task 5 of SemEval-2020. The task involved detecting a class of textual expressions known as counterfactuals and separating them into their constituent elements. …...

AbstractDependency trees have been shown to be effective in capturing long-range relations between target entities. Nevertheless, how to selectively emphasize target-relevant information and remove irrelevant content from the tree is …...

AbstractVision language navigation is the task that requires an agent to navigate through a 3D environment based on natural language instructions. One key challenge in this task is to ground …...

AbstractThe connection between the maximum spanning tree in a directed graph and the best dependency tree of a sentence has been exploited by the NLP community. However, for many dependency …...

Relation extraction is an important task in in- formation extraction and retrieval that aims to extract relations among the given entities from running texts. To achieve a good performance for …...

AbstractWe study the problem of leveraging the syntactic structure of text to enhance pre-trained models such as BERT and RoBERTa. Existing methods utilize syntax of text either in the pre-training …...

AbstractRelational triple extraction is a critical task for natural language processing. Existing methods mainly focused on capturing semantic information, but suffered from ignoring the syntactic structure of the sentence, which …...

AbstractMedical Relation Extraction (MRE) task aims to extract relations between entities in medical texts. Traditional relation extraction methods achieve impressive success by exploring the syntactic information, e.g., dependency tree. However, …...

AbstractMost computational models of dependency syntax consist of distributions over spanning trees. However, the majority of dependency treebanks require that every valid dependency tree has a single edge coming out …...