UoW: NLP techniques developed at the University of Wolverhampton for Semantic Similarity and Textual Entailment
نویسندگان
چکیده
This paper presents the system submitted by University of Wolverhampton for SemEval-2014 task 1. We proposed a machine learning approach which is based on features extracted using Typed Dependencies, Paraphrasing, Machine Translation evaluation metrics, Quality Estimation metrics and Corpus Pattern Analysis. Our system performed satisfactorily and obtained 0.711 Pearson correlation for the semantic relatedness task and 78.52% accuracy for the textual entailment task.
منابع مشابه
Recognizing Textual Entailment Using Description Logic and Semantic Relatedness
Recognizing Textual Entailment using Description Logic and Semantic Relatedness Reda Siblini, Ph.D. Concordia University, 2014 Textual entailment (TE) is a relation that holds between two pieces of text where one reading the first piece can conclude that the second is most likely true. Accurate approaches for textual entailment can be beneficial to various natural language processing (NLP) appl...
متن کاملMachine Learning Based Semantic Inference: Experiments and Observations at RTE-3
Textual Entailment Recognition is a semantic inference task that is required in many natural language processing (NLP) applications. In this paper, we present our system for the third PASCAL recognizing textual entailment (RTE-3) challenge. The system is built on a machine learning framework with the following features derived by state-of-the-art NLP techniques: lexical semantic similarity (LSS...
متن کاملMethods for measuring semantic similarity of texts
Measuring semantic similarity is a task needed in many Natural Language Processing (NLP) applications. For example, in Machine Translation evaluation, semantic similarity is used to assess the quality of the machine translation output by measuring the degree of equivalence between a reference translation and the machine translation output. The problem of semantic similarity (Corley and Mihalcea...
متن کاملSAGAN: An approach to Semantic Textual Similarity based on Textual Entailment
In this paper we report the results obtained in the Semantic Textual Similarity (STS) task, with a system primarily developed for textual entailment. Our results are quite promising, getting a run ranked 39 in the official results with overall Pearson, and ranking 29 with the Mean metric.
متن کاملAnswering Yes-No Questions by Keyword Distribution: KJP System at NTCIR-11 RITEVal Task
Textual entailment is normally regarded as a deeper analysis issue among other NLP techniques. Most textual entailment approaches employ deeper syntactic and semantic analyses. In contrast to such approaches, we used a simple, but fundamentally important, keyword based technique. Our system architecture was built on our observation that many of textual entailment issues are knowledge search iss...
متن کامل