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...
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), ...
We propose a novel, Abstract Meaning Representation-based approach to identi- fying molecular events/interactions in bio- medical text. Our key contributions are: (1) an empirical validation of our hypoth- esis that an event is a subgraph of the AMR graph, (2) a neural network-based model ...
Abstraction permits structural neutralizations that facilitate learning of translation examples across languages with radically different surface structure characteristics, and allows MT development to proceed within a largely languageindependent NLP architecture. Comparative evaluation indicates that after training ...
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 ) ( = ( ...
机器学习算法与自然语言处理(ML-NLP)是国内外最大的自然语言处理社区之一,汇聚超过50w订阅者,受众覆盖国内外NLP硕博生、高校老师、以及企业研究人员。 社区的愿景是促进国内外自然语言处理学术界、产业界和广大爱好者之间的交流和进步。 转载自 | RUC AI...
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. ...
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...
(Borghi & Binkofski,2014). However, this power also engenders the challenge of reconciling the disparities in the visual representation of abstract concepts. For instance, a single abstract concept can be evoked by widely diverse visual data, as in Fig.2. The diversity and divergence present in...
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...