Python Abstract Meaning Representation 工具的实现 一、引言 在自然语言处理(NLP)领域,抽象意义表示(Abstract Meaning Representation, AMR)是一种用来表示句子意义的图结构。构建一个Python工具来处理AMR的重要性不言而喻,但对于新手来说,这个过程可能会显得复杂。本文将分步骤引导你实现一个简单的Python AMR工具,结构...
In our work, we aim to tackle such shortcomings by representing legal texts in the form of abstract meaning representation (AMR), a graph-based semantic representation that gains lots of polarity in NLP community recently. We present our study in AMR Parsing (producing AMR from natural language...
背景:Concept-to-text Natural Language Generation is the task of expressing an input meaning representation in natural language. 问题:Previous approaches in this task have been able to generalise to rare or unseen instances by relying on a...
背景:Concept-to-text Natural Language Generation is the task of expressing an input meaning representation in natural language. 问题:Previous approaches in this task have been able to generalise to rare or unseen instances by relying on a delexicalisation of the input. 多语言生成——Multilingual G...
Semantic parsingis the task of converting anatural languageutteranceto alogical form: a machine-understandable representation of its meaning[2]. 第一个例子: Utterance show me the fare from ci0 to ci1 Logic Form lambda $0 e ( exists $1 ( and ( from $1 ci0 ) ( to $1 ci1 ) ( = (...
2,"How to make unsupervised language pre-training more efficient and less resource-intensive is an important research direction in NLP. In this paper, we focus on improving the efficiency of language pre-training methods through providing better data utilization. It is well-known that in language...
It is also known that dependency structures provide rich syntactic information for various NLP applications. Yet, few applications use dependency structures in an underlying neural network framework. This dissertation introduces a complete framework designed to parse Abstract Meaning Representations (AMRs), ...
The NLP Techniques for Automatic Multi-article News Summarization Based on Abstract Meaning Representationdoi:10.1007/978-981-13-2285-3_31The analysis of natural language texts is one of the most important knowledge discovery tasks for any organization. Automated text summarization systems can reduce ...
背景和问题:Pre-trained language models have been applied to various NLP tasks with considerable performance gains. However, the large model sizes, together with the long inference time, limit the deployment of such models in realtime applications. ...