Bootstrapping Algorithm

Identifying and classifying personal, geographic, in- stitutional or other names in a text is an impor- tant task for numerous applications. This paper de- scribes and evaluates a language-independent boot- …...

We present an unsupervised method for labelling the arguments of verbs with their semantic roles. Our bootstrapping algorithm makes initial unam- biguous role assignments, and then iteratively up- dates the …...

A challenging problem in open informa- tion extraction and text mining is the learn- ing of the selectional restrictions of se- mantic relations. We propose a mini- mally supervised bootstrapping …...

Event extraction systems typically take ad- vantage of language and domain-specific knowledge bases, including patterns that are used to identify specific facts in text; techniques to acquire these patterns can …...

A common form of sarcasm on Twitter con- sists of a positive sentiment contrasted with a negative situation. For example, many sarcas- tic tweets include a positive sentiment, such as …...

We introduce a bootstrapping algorithm for re- gression that exploits word embedding mod- els. We use it to infer four psycholinguis- tic properties of words: Familiarity, Age of Acquisition, Concreteness …...

AbstractData-driven approaches using neural networks have achieved promising performances in natural language generation (NLG). However, neural generators are prone to make mistakes, e.g., neglecting an input slot value and generating …...

AbstractA fundamental challenge in the current NLP context, dominated by language models, comes from the inflexibility of current architectures to “learn” new information. While model-centric solutions like continual learning or …...