We show that the quality of sentence-level subjectivity classification, i.e. the task of deciding whether a sentence is subjective or objective, can be improved by incorporating hitherto unused features: readability measures. Hence we investigate in 6 different readability formulae and propose an own. Their performance is evaluated in a 10-fold cross validation setting using machine learning. T...

Many NLP tasks involve sentence-level annotation yet the relevant information is not encoded at sentence level but at some relevant parts of the sentence. Such tasks include but are not limited to: sentiment expression annotation, product feature annotation, and template annotation for Q&A systems. However, annotation of the full corpus sentence by sentence is resource intensive. In this paper,...

We study the problem of jointly aligning sentence constituents and predicting their similarities. While extensive sentence similarity data exists, manually generating reference alignments and labeling the similarities of the aligned chunks is comparatively onerous. This prompts the natural question of whether we can exploit easy-to-create sentence level data to train better aligners. In this pa...

Named entity recognition (NER) is one fundamental task in natural language processing, which usually viewed as a sequence labeling problem and typically addressed by neural conditional random field (CRF) models, such BiLSTM-CRF. Intuitively, the types contain rich semantic information type sentence can globally reflect sentence-level semantics. However, most previous works recognize named entit...

Oscillatory neural dynamics have been steadily receiving more attention as a robust and temporally precise signature of network activity related to language processing. We have recently proposed that oscillatory dynamics in the beta and gamma frequency ranges measured during sentence-level comprehension might be best explained from a predictive coding perspective. Under our proposal we related ...

The performance of Information Retrieval in the Question Answering system is not satisfactory from our experiences in TREC QA Track. In this article, we take a comparative study to re-examine IR techniques on document retrieval and sentence level retrieval respectively. Our study shows: 1) query reformulation should be a necessary step to achieve a better retrieval performance; 2) The technique...

In this paper, we propose a method for obtaining sentence-level embeddings. While the problem of word-level embeddings is very well studied, novel This obtained by simple in context solving paraphrase generation task. If use sequential encoder-decoder model generating paraphrase, would like generated to be semantically close original sentence. One way ensure adding constraints true and unrelate...