Benchmark Data

This paper proposes a simple yet effective framework for semi-supervised dependency parsing at entire tree level, referred to as ambiguity-aware ensemble training. Instead of only using 1- best parse trees …...

We propose a novel model for parsing natural language sentences into their for- mal semantic representations. The model is able to perform integrated lexicon ac- quisition and semantic parsing, mapping …...

AbstractThis paper proposes to address the word sense ambiguity issue in an unsupervised manner, where word sense representations are learned along a word sense selection mechanism given contexts. Prior work …...

AbstractEntity resolution (ER) is the task of identifying different representations of the same real-world entities across databases. It is a key step for knowledge base creation and text mining. Recent …...

AbstractRecent work has shown that Aspect-Term Sentiment Analysis (ATSA) can be effectively performed by Gradual Machine Learning (GML). However, the performance of the current unsupervised solution is limited by inaccurate …...