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Towards Entailment-Based Question Answering: ITC-irst at CLEF 2006 [chapter]

Milen Kouylekov, Matteo Negri, Bernardo Magnini, Bonaventura Coppola
2007 Lecture Notes in Computer Science  
The participation in the AVE task, with an answer validation module based on textual entailment recognition, is motivated by our objectives of (i) creating a modular framework for an entailment-based approach  ...  This year, besides providing support to other groups participating in cross-language Question Answering (QA) tasks, and submitting runs both for the monolingual Italian and the cross-language Italian/English  ...  In this direction, a more complex approach has been recently proposed by [4] , which experiments with different techniques based on the recognition of textual entailment relations, either between questions  ... 
doi:10.1007/978-3-540-74999-8_64 fatcat:pjmrgp7ccfezrb4gtbmw7q5d64

Natural Language Processing Applications: A New Taxonomy using Textual Entailment

Manar Elshazly, Mohammed Haggag, Soha Ahmed Ehssan
2021 International Journal of Advanced Computer Science and Applications  
Textual entailment recognition is one of the recent challenges of the Natural Language Processing (NLP) domain.  ...  Text entailment is more precise than traditional Natural Language Processing techniques in extracting emotions from text because the sentiment of any text can be clarified by textual entailment.  ...  The automation of textual entailment recognition supports a wide variety of text-based tasks, including information retrieval, information extraction, question answering, text summarization, and machine  ... 
doi:10.14569/ijacsa.2021.0120580 fatcat:yp7wtq6n7bamjcsnpl2hathrwy

Recognizing textual entailment: Rational, evaluation and approaches

IDO DAGAN, BILL DOLAN, BERNARDO MAGNINI, DAN ROTH
2009 Natural Language Engineering  
Work in this area has been largely driven by the PASCAL Recognizing Textual Entailment (RTE) challenges, which are a series of annual competitive meetings.  ...  answering, information extraction and summarization.  ...  about textual entailment have contributed to the better understanding of the task and its nature. We believe that this special issue is an important step in this direction.  ... 
doi:10.1017/s1351324909990209 fatcat:t7rpxvcw2jfpbbxzrejk6expuu

Recognizing textual entailment: Rational, evaluation and approaches – Erratum

IDO DAGAN, BILL DOLAN, BERNARDO MAGNINI, DAN ROTH
2010 Natural Language Engineering  
Work in this area has been largely driven by the PASCAL Recognizing Textual Entailment (RTE) challenges, which are a series of annual competitive meetings.  ...  answering, information extraction and summarization.  ...  about textual entailment have contributed to the better understanding of the task and its nature. We believe that this special issue is an important step in this direction.  ... 
doi:10.1017/s1351324909990234 fatcat:agnw7jv43jhjhdhd4nibnba6fe

Methods for using textual entailment in open-domain question answering

Sanda Harabagiu, Andrew Hickl
2006 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the ACL - ACL '06  
In our experiments, we show that when textual entailment information is used to either filter or rank answers returned by a Q/A system, accuracy can be increased by as much as 20% overall.  ...  Work on the semantics of questions has argued that the relation between a question and its answer(s) can be cast in terms of logical entailment.  ...  Acknowledgments This material is based upon work funded in whole or in part by the U.S.  ... 
doi:10.3115/1220175.1220289 dblp:conf/acl/HarabagiuH06 fatcat:n4pi7udygzgtfji4aveenpnjyq

The Role and Resolution of Textual Entailment in Natural Language Processing Applications [chapter]

Zornitsa Kozareva, Andrés Montoyo
2006 Lecture Notes in Computer Science  
In this paper all tests were done for English, but our system can be used with no restrains by other languages.  ...  We discuss the role of entailment for various Natural Language Processing applications and develop a machine learning system for their resolution.  ...  Textual entailment recognition is a complex task that requires deep language understanding.  ... 
doi:10.1007/11765448_17 fatcat:55dv5bcvvjel5bgsjxhavibqby

Lexical-Morphological Modeling for Legal Text Analysis [article]

Danilo S. Carvalho, Minh-Tien Nguyen, Tran Xuan Chien, Minh Le Nguyen
2016 arXiv   pre-print
on textual entailment evidence to provide a correct answer.  ...  In the context of the Competition on Legal Information Extraction/Entailment (COLIEE), we propose a method comprising the necessary steps for finding relevant documents to a legal question and deciding  ...  Acknowledgements This work is supported partly by the grant of NII Research Cooperation and JAIST's Research grant.  ... 
arXiv:1609.00799v1 fatcat:jragmqjruzfd7okeflqfih4ruu

Addressing Limited Data for Textual Entailment Across Domains

Chaitanya Shivade, Preethi Raghavan, Siddharth Patwardhan
2016 Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)  
We seek to address the lack of labeled data (and high cost of annotation) for textual entailment in some domains.  ...  With self-training, we successfully exploit unlabeled data to improve over ENT by 15% F-score on the newswire domain, and 13% F-score on clinical data.  ...  Acknowledgments We thank our in-house medical expert, Jennifer Liang, for guidance on the data annotation task, our medical annotators for annotating clinical data for us, and Murthy Devarakonda for valuable  ... 
doi:10.18653/v1/p16-1118 dblp:conf/acl/ShivadeRP16 fatcat:32irlqlf2zdptlrfaskgpll5iu

Addressing Limited Data for Textual Entailment Across Domains [article]

Chaitanya Shivade, Preethi Raghavan, Siddharth Patwardhan
2016 arXiv   pre-print
We seek to address the lack of labeled data (and high cost of annotation) for textual entailment in some domains.  ...  With self-training, we successfully exploit unlabeled data to improve over ENT by 15% F-score on the newswire domain, and 13% F-score on clinical data.  ...  Acknowledgments We thank our in-house medical expert, Jennifer Liang, for guidance on the data annotation task, our medical annotators for annotating clinical data for us, and Murthy Devarakonda for valuable  ... 
arXiv:1606.02638v1 fatcat:vsg25nm455fjvjcd2cx2crmusu

Natural Language Rationales with Full-Stack Visual Reasoning: From Pixels to Semantic Frames to Commonsense Graphs [article]

Ana Marasović, Chandra Bhagavatula, Jae Sung Park, Ronan Le Bras, Noah A. Smith, Yejin Choi
2020 arXiv   pre-print
We present the first study focused on generating natural language rationales across several complex visual reasoning tasks: visual commonsense reasoning, visual-textual entailment, and visual question  ...  answering.  ...  This research was supported in part by NSF (IIS1524371, IIS-1714566), DARPA under the CwC program through the ARO (W911NF-15-1-0543), DARPA under the MCS program through NIWC Pacific (N66001-19-2-4031)  ... 
arXiv:2010.07526v1 fatcat:6vafbtt34rccrfly327tjr4pwe

Identifying semantic equivalence for multi-document summarisation

Eamonn Newman, Joe Carthy, John Dunnion, Nicola Stokes
2007 Artificial Intelligence Review  
We describe Semantic Equivalence and Textual Entailment Recognition, and outline a system which uses a number of lexical, syntactic and semantic features to classify pairs of sentences as "semantically  ...  We describe an experiment to show how syntactic and semantic features improve the performance of an earlier system, which used only lexical features. We also outline some areas for future work.  ...  This action reduces the problem of textual entailment recognition to one of (sub-)graph matching.  ... 
doi:10.1007/s10462-007-9018-5 fatcat:gqswvbvwpjhmxcymyia2nal3xy

The Effect of Entity Recognition on Answer Validation [chapter]

Álvaro Rodrigo, Anselmo Peñas, Jesús Herrera, Felisa Verdejo
2007 Lecture Notes in Computer Science  
The Answer Validation Exercise (AVE) 2006 is aimed at developing systems able to decide whether the answer of a Question Answering (QA) system is correct or not using textual entailment.  ...  The results of the propose system are better than the ones of a baseline system that always accepts all answers, therefore the use of entities can improve the results of an answer validation system.  ...  Acknowledgments This work has been partially supported by the Spanish Ministry of Science and Technology within the project R2D2-SyEMBRA. (TIC-2003-07158-C04-02) and a PhD grant by UNED.  ... 
doi:10.1007/978-3-540-74999-8_57 fatcat:qdd3uhaqxvhq3oqxwntnqgkcri

Towards Logical Inference for Arabic Question-Answering

Wided Bakari, Patrice Bellot, Omar Trigui, Mahmoud Neji
2015 Research in Computing Science  
Now, our work is concentrated on an implementation step to develop a question-answering system in Arabic using the techniques of textual entailment recognition.  ...  The second one is the use of textual entailment techniques that relies on inference and logic representation to extract the candidate answer.  ...  This method involves four steps: the textual statements analysis, the transformation of the question and text into logic forms, the textual entailments recognition and the desired answer retrieval.  ... 
doi:10.13053/rcs-90-1-7 fatcat:jnaexpzqrfftdj26t4vwkyzpqm

UU_TAILS at MEDIQA 2019: Learning Textual Entailment in the Medical Domain

Noha Tawfik, Marco Spruit
2019 Proceedings of the 18th BioNLP Workshop and Shared Task  
The challenge consists of 3 tasks: medical language inference (NLI), recognizing textual entailment (RQE) and question answering (QA).  ...  For the RQE task, we trained a traditional multilayer perceptron network based on embeddings generated by the universal sentence encoder.  ...  In a previous work, we tried to model textual entailment found in biomedical literature by restructuring an existing YES/NO question-answering dataset extracted from PubMed(2019).  ... 
doi:10.18653/v1/w19-5053 dblp:conf/bionlp/TawfikS19 fatcat:hkhgoz6tpvev7nq4pobbvbi7ku

Information Synthesis for Answer Validation [chapter]

Rui Wang, Günter Neumann
2009 Lecture Notes in Computer Science  
Our system casts the AVE task into a Recognizing Textual Entailment (RTE) problem and uses an existing RTE system to validate answers.  ...  This report is about our participation in the Answer Validation Exercise (AVE2008).  ...  Fig. 1 . 1 Our AVE system uses the RTE system (Tera -Textual Entailment Recognition for Application) as a core component.  ... 
doi:10.1007/978-3-642-04447-2_57 fatcat:tslisz7vl5enjim7vpumw5w5jq
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