[[abstract]]Recognizing Textual Entailment (RTE) is a task in which two text fragments are processed by system to determine whether the meaning of hypothesis is entailed from another text or not. Although a considerable number of studies have been made on recognizing textual entailment, little is known about the power of linguistic phenomenon for recognizing inference in text. The objective of this paper is to provide a comprehensive analysis of identifying linguistic phenomena for recognizing inference in text (RITE). In this paper, we focus on RITE-VAL System Validation subtask and propose a model by using an analysis of identifying linguistic phenomena for Recognizing Inference in Text (RITE) using the development dataset of NTCIR-11 RIT...
Textual entailment among sentences is an important part of applied semantic inference. In this paper...
[[abstract]]In this paper, we describe the IMTKU (Information Management at TamKang University) text...
Min-Yuh Day, Ya-Jung Wang, Che-Wei Hsu, En-Chun Tu, Shang-Yu Wu, Huai-Wen Hsu, Yu-An Lin, Yu-Hsuan T...
To prepare an evaluation dataset for textual entailment (TE) recognition, human annotators label ric...
In this paper, we introduce our Recognizing Textual Entailment (RTE) system developed on the basis o...
[[abstract]]Recognizing Textual Entailment (RTE) is a PASCAL/TAC task in which two text fragments ar...
Textual Entailment (TE) aims at capturing major semantic inference needs across applications in Natu...
While semantic inference has always been a major focus in Computational Linguistics, the topic has b...
Since 2005, researchers have worked on a broad task called Recognizing Textual Entailment (RTE), whi...
The goal of identifying textual entailment – whether one piece of text can be plausibly inferred fr...
Textual Entailment is a directional relation between two text fragments. The relation holds whenever...
In this paper, we explore the application of inference rules for recogniz-ing textual entailment (RT...
Recognition of textual entailment is not an easy task. In fact, early experimental evidences in [1] ...
This paper aims at understanding what hu-man think in textual entailment (TE) recogni-tion process a...
The textual entailment recognition system that we discuss in this paper represents a perspective-bas...
Textual entailment among sentences is an important part of applied semantic inference. In this paper...
[[abstract]]In this paper, we describe the IMTKU (Information Management at TamKang University) text...
Min-Yuh Day, Ya-Jung Wang, Che-Wei Hsu, En-Chun Tu, Shang-Yu Wu, Huai-Wen Hsu, Yu-An Lin, Yu-Hsuan T...
To prepare an evaluation dataset for textual entailment (TE) recognition, human annotators label ric...
In this paper, we introduce our Recognizing Textual Entailment (RTE) system developed on the basis o...
[[abstract]]Recognizing Textual Entailment (RTE) is a PASCAL/TAC task in which two text fragments ar...
Textual Entailment (TE) aims at capturing major semantic inference needs across applications in Natu...
While semantic inference has always been a major focus in Computational Linguistics, the topic has b...
Since 2005, researchers have worked on a broad task called Recognizing Textual Entailment (RTE), whi...
The goal of identifying textual entailment – whether one piece of text can be plausibly inferred fr...
Textual Entailment is a directional relation between two text fragments. The relation holds whenever...
In this paper, we explore the application of inference rules for recogniz-ing textual entailment (RT...
Recognition of textual entailment is not an easy task. In fact, early experimental evidences in [1] ...
This paper aims at understanding what hu-man think in textual entailment (TE) recogni-tion process a...
The textual entailment recognition system that we discuss in this paper represents a perspective-bas...
Textual entailment among sentences is an important part of applied semantic inference. In this paper...
[[abstract]]In this paper, we describe the IMTKU (Information Management at TamKang University) text...
Min-Yuh Day, Ya-Jung Wang, Che-Wei Hsu, En-Chun Tu, Shang-Yu Wu, Huai-Wen Hsu, Yu-An Lin, Yu-Hsuan T...