Фоновое знание

Contradiction Detection (CD) in text is a difficult NLP task. We investigate CD over functions (e.g., BornIn(Person)=Place), and present a domain-independent algorithm that automatically discovers phrases denoting functions with high …...

Relation extraction is the task of recog- nizing semantic relations among entities. Given a particular sentence supervised ap- proaches to Relation Extraction employed feature or kernel functions which usu- ally …...

This paper describes a novel approach to the semantic relation detection problem. Instead of relying only on the training instances for a new relation, we leverage the knowledge learned from …...

AbstractAdversarial examples are inputs to machine learning models designed to cause the model to make a mistake. They are useful for understanding the shortcomings of machine learning models, interpreting their …...

AbstractWe propose new BERT-based methods for recognizing event causality such as “smoke cigarettes” –> “die of lung cancer” written in web texts. In our methods, we grasp each annotator’s policy …...

AbstractQuestion answering over dialogue, a specialized machine reading comprehension task, aims to comprehend a dialogue and to answer specific questions. Despite many advances, existing approaches for this task did not …...

AbstractThe goal of text summarization is to compress documents to the relevant information while excluding background information already known to the receiver. So far, summarization researchers have given considerably more …...

AbstractRecently, many studies are emerging towards building a retrieval-based dialogue system that is able to effectively leverage background knowledge (e.g., documents) when conversing with humans. However, it is non-trivial to …...

AbstractIn this paper, we focus on the problem of citing sentence generation, which entails generating a short text to capture the salient information in a cited paper and the connection …...

AbstractProviding conversation models with background knowledge has been shown to make open-domain dialogues more informative and engaging. Existing models treat knowledge selection as a sentence ranking or classification problem where …...