This article surveys and organizes research works in a new paradigm in natural language
processing, which we dub “prompt-based learning.” Unlike traditional supervised learning …

Recently, there has been a surge of interest in the NLP community on the use of pretrained
Language Models (LMs) as Knowledge Bases (KBs). Researchers have shown that LMs …

We present a simple and effective scheme for dependency parsing which is based on
bidirectional-LSTMs (BiLSTMs). Each sentence token is associated with a BiLSTM vector …

Almost all current dependency parsers classify based on millions of sparse indicator
features. Not only do these features generalize poorly, but the cost of feature computation …

Transition-based dependency parsers usually use transition systems that monotonically
extend partial parse states until they identify a complete parse tree. Honnibal et al.(2013) …

We propose a technique for learning representations of parser states in transition-based
dependency parsers. Our primary innovation is a new control structure for sequence-to …

This paper presents the current status of OPUS, a growing language resource of parallel
corpora and related tools. The focus in OPUS is to provide freely available data sets in …

We present a new collection of treebanks with homogeneous syntactic dependency
annotation for six languages: German, English, Swedish, Spanish, French and Korean. To …

WebQuestions and SimpleQuestions are two benchmark data-sets commonly used in recent
knowledge-based question answering (KBQA) work. Most questions in them are …

We introduce a novel architecture for dependency parsing:\emph {stack-pointer
networks}(\textbf {\textsc {StackPtr}}). Combining pointer networks~\citep …