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A WordNet-based semantic approach to textual entailment and cross-lingual textual entailment
International Journal of Machine Learning and Cybernetics, 2011In this paper we explain how to build a recognizing textual entailment (RTE) system which only uses semantic similarity measures based on WordNet. We show how the widely used WordNet-based semantic measures can be generalized to build sentence level semantic metrics in order to be used in both mono-lingual and cross-lingual textual entailment.
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Entailment analysis for improving Chinese textual entailment system
2013 IEEE 14th International Conference on Information Reuse & Integration (IRI), 2013Textual Entailment (TE) is a critical issue in natural language processing (NLP); many NLP applications can be benefited from the recognition of textual entailment (RTE). In this paper we report our observation on how to improve the Chinese textual entailment system and the experiment results on the NTCIR-10 RITE-2 dataset.
Shih-Hung Wu
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Natural Language Engineering, 2015
AbstractIn this work, we present a novel type of graphs for natural language processing (NLP), namely textual entailment graphs (TEGs). We describe the complete methodology we developed for the construction of such graphs and provide some baselines for this task by evaluating relevant state-of-the-art technology.
Lili Kotlerman +3 more
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AbstractIn this work, we present a novel type of graphs for natural language processing (NLP), namely textual entailment graphs (TEGs). We describe the complete methodology we developed for the construction of such graphs and provide some baselines for this task by evaluating relevant state-of-the-art technology.
Lili Kotlerman +3 more
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Paraphrase Substitution for Recognizing Textual Entailment [PDF]
, 2007 We describe a method for recognizing textual entailment that uses the length of the longest common subsequence (LCS) between two texts as its decision criterion. Rather than requiring strict word matching in the common subsequences, we perform a flexible match using automatically generated paraphrases.
Bosma, W.E., Callison-Burch, C.
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Analysis of a Textual Entailer
2006We present in this paper the structure of a textual entailer, offer a detailed view of lexical aspects of entailment and study the impact of syntactic information on the overall performance of the textual entailer. It is shown that lemmatization has a big impact on the lexical component of our approach and that syntax leads to accurate entailment ...
Vasile Rus +2 more
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Deep Learning for Textual Entailment Recognition
2015 IEEE 27th International Conference on Tools with Artificial Intelligence (ICTAI), 2015In this paper we propose a novel two-step procedure to recognize textual entailment. Firstly, we build a joint Restricted Boltzmann Machines (RBM) layer to learn the joint representation of the text-hypothesis pairs. Then the reconstruction error is calculated by comparing the original representation with reconstructed representation derived from the ...
Chen Lyu 0004 +3 more
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Recognizing Textual Entailment
2013In the last few years, a number of NLP researchers have developed and participated in the task of Recognizing Textual Entailment (RTE). This task encapsulates Natural Language Understanding capabilities within a very simple interface: recognizing when the meaning of a text snippet is contained in the meaning of a second piece of text.
Dagan, I +3 more
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TE4AV: Textual Entailment for Answer Validation
2008 International Conference on Natural Language Processing and Knowledge Engineering, 2008The textual entailment (TE) task consists of discovering unidirectional semantic inferences between the meanings of two text snippets. Taking advantage of this, in this paper we propose using the TE system as an answer validation (AV) engine to improve the performance of question answering (QA) systems and help humans in the assessment of QA systems ...
Óscar Ferrández +2 more
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AORTE for Recognizing Textual Entailment
2009In this paper we present the use of the AORTE system in recognizing textual entailment. AORTE allows the automatic acquisition and alignment of ontologies from text. The information resulted from aligning ontologies created from text fragments is used in classifying textual entailment.
Reda Siblini, Leila Kosseim
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Translators in Textual Entailment
2010This paper presents how the size of Textual Entailment Corpus could be increased by using Translators to generate additional 〈t, h〉 pairs. Also, we show the theoretical upper bound of a Corpus expanded by translators. Then, we propose an algorithm to expand the corpus size using Translator engines starting from a RTE Corpus, and finally we show the ...
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