Notes:
Textual entailment is a task in natural language processing that involves determining the relationship between two text fragments, one of which (called the “hypothesis”) is assumed to be true, and the other (called the “premise”) is used to determine whether the hypothesis is true or not. This task is often used to evaluate the performance of natural language processing models and to evaluate the coherence and consistency of text.
Textual entailment can be used in a variety of applications, such as question answering, information retrieval, and machine translation. In these applications, a model is often trained to predict the relationship between a given premise and a hypothesis, such as whether the premise “entails” (i.e., logically implies) the hypothesis, contradicts it, or is neutral with respect to it.
Textual entailment can also be used to evaluate the coherence and consistency of text by checking whether a given text fragment is consistent with other known facts or information. For example, a model trained on textual entailment could be used to determine whether a given news article is consistent with other known facts or whether a given piece of text contains contradictions or inconsistencies.
Textual entailment systems can take a variety of forms, depending on the specific task they are designed to perform and the methods used to build them. Some common approaches to building textual entailment systems include:
- Rule-based systems: These systems use a set of predefined rules to determine the relationship between a premise and a hypothesis. For example, a rule-based system might be designed to recognize that the premise “John is a doctor” entails the hypothesis “John is a medical professional.”
- Machine learning-based systems: These systems use machine learning algorithms to learn the relationship between a premise and a hypothesis from a large dataset of annotated examples. For example, a machine learning-based system might be trained on a dataset of premises and hypotheses labeled with their relationship (e.g., entailment, contradiction, neutral) and then be able to predict the relationship between a new premise and hypothesis based on its training.
- Hybrid systems: These systems combine elements of both rule-based and machine learning-based approaches, using a combination of predefined rules and machine learning algorithms to determine the relationship between a premise and a hypothesis.
Regardless of the specific approach used, textual entailment systems typically function by first preprocessing the input text (e.g., tokenizing, stemming, etc.), and then using some combination of rules and machine learning algorithms to determine the relationship between the premise and the hypothesis. The output of a textual entailment system is usually a label indicating the relationship between the premise and the hypothesis (e.g., entailment, contradiction, neutral).
Textual entailment can be used in dialog systems to improve the coherence and consistency of the dialog, as well as to better understand the intentions and goals of the user.
For example, consider a dialog system that is designed to help a user plan a vacation. The system might ask the user a series of questions about their preferences and constraints (e.g., budget, preferred destinations, preferred activities). The system can use textual entailment to ensure that the user’s responses are consistent with each other and with the system’s understanding of the user’s goals. For example, if the user says that they want to go on a beach vacation but also says that they don’t like sand, the system can use textual entailment to recognize that these statements are contradictory and prompt the user for clarification.
Textual entailment can also be used in dialog systems to better understand the user’s intentions and goals. For example, if the user says that they want to go on a “relaxing” vacation, the system can use textual entailment to determine that the user is looking for a vacation that is low-stress and restful, and use this information to suggest appropriate destinations and activities.
See also:
Tasks of Natural Language Processing
TEXTUAL ENTAILMENT METHOD FOR LINKING TEXT OF AN ABSTRACT TO TEXT IN THE MAIN BODY OF A DOCUMENT Á Sandor… – US Patent 20,110,276,322, 2011 – freepatentsonline.com … 20070198268, Method for controlling a speech dialog system and speech dialog system, August, 2007, Hennecke. … for each sentence of an abstract of the document, comparing the sentence with sentences of a main body of the document using textual entailment techniques to … Cached – All 2 versions
Recognizing entailment in intelligent tutoring systems [PDF] from rodneynielsen.com RD Nielsen, W Ward… – Natural Language …, 2009 – Cambridge Univ Press … We also discuss the application of this new paradigm to recognition of textual entailment outside the domain of ITSs. … In recent years, there has been a tremendous increase in interest in the areas of paraphrase acquisition and textual entailment recognition. … Cited by 13 – Related articles – All 16 versions
[PDF] Towards effective tutorial feedback for explanation questions: A dataset and baselines [PDF] from aclweb.org MO Dzikovska, RD Nielsen… – … of the 2012 Conference of the …, 2012 – aclweb.org … We further discuss the relationship with the task of recognizing textual entailment in Section 5. In the rest of this section, we describe our … The BEETLE corpus consists of the interactions be- tween students and the BEETLE II tutorial dialogue system (Dzikovska et al., 2010b). … Cited by 1 – View as HTML
The generation of textual entailment with NLML in an intelligent dialogue system for language learning CSIEC [PDF] from arxiv.org J Jia – … Processing and Knowledge Engineering, 2008. NLP- …, 2008 – ieeexplore.ieee.org Abstract This paper introduces the generation of textual entailment within the project CSIEC (computer simulation in educational communication), an interactive Web-based human- computer dialogue system with natural language for English instruction. The generation of … Cited by 2 – Related articles – All 6 versions
CSIEC: A computer assisted English learning chatbot based on textual knowledge and reasoning J Jia – Knowledge-Based Systems, 2009 – Elsevier … NLML parser 3.4. NLDB (Natural Language Database) 3.5. Common sense knowledge 3.6. GTE (Generation of Textual Entailment) mechanism 3.7. … A potential solution to this problem is to apply computer spoken dialogue systems to role play a conversational partner. … Cited by 7 – Related articles – All 2 versions
[PDF] Using Dialogue Corpora to Extend Information Extraction Patterns for Natural Language Understanding of Dialogue [PDF] from psu.edu R Catizone, A Dingli… – Proceedings of the Seventh …, 2010 – Citeseer … The PASCAL Recognising Textual Entailment Challenge. … Workshop on Paraphrasing (IWP2005), South Korea Flycht-Eriksson, A. & Jönsson, A. (2003) Some Empirical Findings on Dialogue Management and Domain Ontologies in Dialogue System – Implications from an … Related articles – View as HTML – All 6 versions
Opinion mining and sentiment analysis [PDF] from iitb.ac.in B Pang… – Foundations and Trends in Information Retrieval, 2008 – dl.acm.org … textual entailment challenge,” in Proceedings of the Second PASCAL Challenges Workshop on Recognising Textual Entailment, 2006. … M. Walker, and R. Prasad, “Learning to generate naturalistic utterances using reviews in spoken dialogue systems,” ACM Transactions on … Cited by 1041 – Related articles – Library Search – All 33 versions
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Question answering B Webber… – The Handbook of Computational …, 2010 – Wiley Online Library … For more detailed discus- sion of the issues and technology underlying dialogue systems, see Chapter 16, COMPUTATIONAL MODELS OF DIALOGUE. … Textual entailment captures the intuition that one piece of text – in this case, text containing a correct answer to a given … Cited by 19 – Related articles
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[PDF] We desperately need linguistic resources!-beased on the users’ pointof view [PDF] from flarenet.eu S Sekine – 2010 – flarenet.eu … appli- cations (machine translation, information extraction, question answering, sentiment analysis, summarization, dialogue systems, etc.) use … paraphrases, hypernyms-hyponyms, semantic class labels, selectional restrictions for predi- cates, textual entailment, inference, word … Cited by 3 – Related articles – View as HTML
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Syntactic testsuites and Textual Entailment Recognition [PDF] from inria.fr P Bedaride, C Gardent – 2010 – hal.inria.fr … 1. Introduction The Recognising Textual Entailment (RTE) challenge eval- uates the ability of NLP systems to detect whether one sen- tence implies (textually entails) another. … In Workshop on Affective dialog systems. D. Klein and CD Manning. 2003. … Related articles – All 8 versions
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Speech Acts of Argumentation: Inference Anchors and Peripheral Cues in Dialogue K Budzynska… – Workshops at the Twenty-Fifth AAAI Conference …, 2011 – aaai.org … 4It could do in some contexts, but even this trivially simple ex- ample demonstrates that it need not. 5Here, the use of the term ‘entailment’ is appealing to the strictly logical, proof-theoretic notion, rather than the much broader notion of textual entailment. 6 Page 5. … Related articles – All 2 versions
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15 Computational Semantics [PDF] from ehu.es C FOX – The Handbook of Computational Linguistics and …, 2010 – books.google.com Page 420. “9781405155816_4_015”—2010/5/8—12: 07—page 394—# 1 15 Computational Semantics CHRIS FOX 1 Introduction In this chapter we will generally use ‘semantics’ to refer to a formal analysis of meaning, and … Cited by 38 – Related articles – All 27 versions
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Annotating Modality and Negation for a Machine Reading Evaluation [PDF] from pascal-network.org R Morante… – 2011 – eprints.pascal-network.org … text process- ing (9; 18; 23; 4; 35), opinion mining and sentiment analysis (39), recognizing textual entailment (5; 34 … factual information, including text summarization, question answering, information extraction, and human-computer interaction in the form of dialogue systems. … Cited by 1 – Related articles – All 3 versions
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Preliminaries E Ovchinnikova – Integration of World Knowledge for Natural Language …, 2012 – Springer … of reasoning is intended to facilitate such applications as, for example, question answering, information extraction, and dialog systems. … two text pieces, which facilitates solving semantic problems such as reference resolution, recognizing textual entailment, disambiguation, and …
[CITATION] Natural Language and Knowledge Representation JZ Sukkarieh – Journal of Logic and Computation, 2008 – Oxford Univ Press … Paper 5 describes a two-layer architecture for a dialogue system that uses separate semantic and knowledge representations that benefit from a domain-general ontology … Paper 7 suggests reducing the problem of question answering validation to a textual entailment problem. … Cited by 5 – Related articles – BL Direct – All 8 versions
Semantic matching using predicate-argument structure EM Boschee, M Levit, MR Freedman – US Patent 7,890,539, 2011 – Google Patents … 565-568, Aug. 1992. Andreevskaia, A., et al., “Can Shallow Predicate Argument Struc- tures Determine Entailment?,” Proceedings from the 1st PASCAL Recognising Textual Entailment Challenge (RTE I), 4 pages, Southampton, UK, Apr. 2005. … Related articles – All 5 versions
[TXT] Proceedings of the NAACL HLT 2010 Young Investigators Workshop on Computational Approaches to Languages of the Americas} [TXT] from aclweb.org L Alonso Alemany, G Infante-Lopez… – Proceedings of the …, 2010 – aclweb.org … InProceedings{castillo:2010:YOUNG, author = {Castillo, Julio}, title = {A Machine Learning Approach for Recognizing Textual Entailment in Spanish … areces:2010:YOUNG, author = {Benotti, Luciana and Estrella, Paula and Areces, Carlos}, title = {Dialogue Systems for Virtual … Cached
From annotator agreement to noise models [PDF] from aclweb.org B Beigman Klebanov, E Beigman – Computational Linguistics, 2009 – dl.acm.org … 2006. The PASCAL recognising textual entailment challenge. In The PASCAL Recognising Textual Entailment Challenge, Springer, Berlin, pages 177–190. … 2006. Characterizing and predicting corrections in spoken dialogue systems. Computational Linguistics, 32(3):417–438. … Cited by 11 – Related articles – All 19 versions
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[BOOK] Advances in Artificial Intelligence: 10th Mexican International Conference on Artificial Intelligence, Micai 2011, Puebla, Mexico, November 26-December 4, … I Batyrshin… – 2011 – books.google.com … Table of Contents–Part I XVII Contextual Semantic Processing for a Spanish Dialogue System Using Markov Logic….. 258 Aldo Fabian, Manuel Hernandez, Luis Pineda, and Ivan Meza A Statistics-Based Semantic Textual Entailment System….. … All 3 versions
Data-driven response generation in social media [PDF] from washington.edu A Ritter, C Cherry… – … of the Conference on Empirical Methods …, 2011 – dl.acm.org … Currently, most dialogue systems rely on ei- ther canned responses or templates for generation, which can result in utterances which sound very … Alignment is more difficult in conversational data than bilingual data (Brown et al., 1990), or textual entailment data (Brockett, 2006 … Cited by 5 – Related articles – All 12 versions
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Soft computing in intelligent tutoring systems and educational assessment R Nielsen, W Ward… – Soft Computing Applications in Business, 2008 – Springer … et al. 2005; Haghighi et al. 2005; Herrera et al. 2005; Raina et al. 2005). The RTE challenge has brought the issue of textual entailment before a broad community of researchers in a task independent fashion. The challenge … Cited by 2 – Related articles – All 2 versions
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[PDF] Event and Temporal Expression extraction from raw text: first step towards a temporally aware system [PDF] from rochester.edu N UzZaman… – International Journal of Semantic …, 2010 – cs.rochester.edu … document summarization. Our long-term goal is to build complete temporal structure of documents and use the temporal structure in other applications like textual entailment, question answering, visualization, or others. In this … Cited by 6 – Related articles – View as HTML – All 14 versions
[PDF] Intrinsic and Extrinsic Approaches to Recognizing Textual Entailment [PDF] from uni-saarland.de DP der Philosophischen – 2011 – coli.uni-saarland.de … Con- sequently, if we want to build a dialogue system, dealing with this kind of implication or entailment is one of the key challenges. … In general, following Chierchia and McConnell-Ginet (2000), we refer to such a relationship between two texts as Textual Entailment in this dis … Related articles – View as HTML – All 2 versions
Language Technologies: Question Answering in Speech Transcripts J Turmo, M Surdeanu, O Galibert… – Computers in the Human …, 2009 – Springer … 8. S. Harabagiu and A. Hickl. Methods for using textual entailment in open-domain question-answering. In COLING’06, Sydney, Australia, July 2006. … Handling speech input in the Ritel QA dialogue system. In Proceedings of Interspeech’07, Antwerp. Belgium, Aug. 2007. 17. … Cited by 1 – Related articles – All 2 versions
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Does it really matter whether students’ contributions are spoken versus typed in an intelligent tutoring system with natural language? SK D’Mello, N Dowell… – Journal of Experimental …, 2011 – psycnet.apa.org There%20is%20the%20question%20of%20whether%20learning%20differs%20when% 20students%20speak%20versus%20type%20their%20responses%20when%20interacting% 20with%20intelligent%20tutoring%20systems%20with%20natural%20language%20dialogues% … Cited by 3 – Related articles – All 4 versions
[TXT] Coling 2008: Companion volume: Posters} [TXT] from aclweb.org R Agerri, N Asher, F Benamara… – Coling 2008: …, 2008 – aclweb.org … anthology/C08-2} } @InProceedings{agerri:2008:POSTERS, author = {Agerri, Rodrigo}, title = {Metaphor in Textual Entailment}, booktitle = {Coling … Timo and Schlangen, David}, title = {Towards Incremental End-of-Utterance Detection in Dialogue Systems}, booktitle = {Coling … Cached
Capturing consistency between intra-clause and inter-clause relations in knowledge-rich dependency and case structure analysis [PDF] from aclweb.org D Kawahara… – … of the 11th International Conference on …, 2009 – dl.acm.org … systems, a lot of effort has been made to develop world knowledge or inference knowledge … Furthermore, we would like to ex- plore the use of the transition knowledge between case frames to improve NLP applications such as recognizing textual entailment (RTE) and sentence … Related articles – All 13 versions
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[BOOK] Natural Language and Information Systems: 13th International Conference on Applications of Natural Language to Information Systems, NLDB 2008, London, … E Kapetanios – 2008 – books.google.com … Speci?cation Towards Designing Operationalizable Models of Man-Machine Interaction Based on Concepts from Human Dialog Systems….. … Morik Querying and Question Answering Related Posters Improving Question Answering Tasks by Textual Entailment Recognition … Library Search – All 4 versions
A corpus of fine-grained entailment relations [PDF] from upenn.edu RD Nielsen… – … ACL-PASCAL Workshop on Textual Entailment …, 2007 – dl.acm.org … The PASCAL Recognizing Textual Entailment (RTE) challenge (Dagan et al., 2005) has brought the issue of textual entailment before a … References Aleven V, Popescu O, & Koedinger K. (2001) A tutorial dialogue system with knowledge-based understanding and classification … Cited by 4 – Related articles – All 32 versions
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Translating between language and logic: what is easy and what is difficult [PDF] from chalmers.se A Ranta – Automated Deduction–CADE-23, 2011 – Springer Page 1. Translating between Language and Logic: What Is Easy and What Is Difficult Aarne Ranta Department of Computer Science and Engineering Chalmers University of Technology and University of Gothenburg Abstract. … Cited by 1 – Related articles – All 5 versions
A two-dimensional topic-aspect model for discovering multi-faceted topics [PDF] from uiuc.edu M Paul… – Urbana, 2010 – aaai.org … The CL aspect focuses on dialogue systems, with words like dialogue and user. … ideas less prevalent in the CL documents such as pragmatics and metaphor as well as formal semantics, while the CL aspect focuses on semantic representation, inference, and textual entailment. … Cited by 13 – Related articles – All 6 versions
The Limsi QAst systems: comparison between human and automatic rules generation for question-answering on speech transcriptions [PDF] from limsi.fr S Rosset, O Galibert, G Adda… – … Speech Recognition & …, 2007 – ieeexplore.ieee.org … 2003. [5] S. Harabagiu, A. Hickl. Methods for using textual entailment in Open-Domain question-answering. Pro- ceedings of COLING’06. Sydney, Australia. … Handling speech input in the Ritel QA dialogue system. 2007. Proceedings of Interspeech’07. Antwerp. Belgium. … Cited by 9 – Related articles – All 7 versions
Sources of World Knowledge E Ovchinnikova – Integration of World Knowledge for Natural Language …, 2012 – Springer … given in Table 3.2.16 FrameNet has a shorter history in NLP applications than WordNet, but lately more and more researchers demonstrate its potential to improve the quality of question answering (eg, Shen and Lapata, 2007) and recognizing textual entailment (eg, Burchardt …
[PDF] Towards a semantic analysis of bahasa Indonesia for question answering [PDF] from unimelb.edu.au SD Larasati, R Manurung – … of the 10th …, 2007 – mandrake.csse.unimelb.edu.au … Such an approach is exemplified by re- cent work in the textual entailment task, eg Bos and Markert (2006). … believe that our work establishes a foundation that will be of value for future research into, among others, Indonesian machine translation, dialogue systems, and natural … Cited by 7 – Related articles – View as HTML – All 12 versions
Automatic argumentative analysis for interaction mining V Pallotta… – Argument & Computation, 2011 – Taylor & Francis … Harabagiu, S. and Hickl, A. Methods for Using Textual Entailment in Open-domain Question Answering. … May 9–12 , Carry-le-Rouet, France. View all references) or provide better capabilities to dialogue systems (Larsson 200245. Larsson, S. 2002. … Cited by 1 – Related articles
Dependency Analysis and CBR to Bridge the Generation Gap in Template-Based NLG V Francisco, R Hervás… – Computational Linguistics and …, 2007 – Springer … In: Proceedings of the Second PASCAL Challenges Workshop on Recognising Textual Entailment, Venezia, Italia. (2006) 15. … McRoy, S., Channarukul, S., Ali, S.: A Natural Language Generation Component for Dialog Systems. … Cited by 2 – Related articles – BL Direct – All 4 versions
The first challenge on generating instructions in virtual environments [PDF] from uni-potsdam.de A Koller, K Striegnitz, D Byron, J Cassell… – Empirical Methods in …, 2010 – dl.acm.org … More recently, the Recognizing Textual Entailment challenge3 has revived broad interest in computational semantics. … DARPA Communicator challenge [28] and its (telephone-based) evaluation methodology were tied to evaluating end-to-end spoken dialogue systems and too … Cited by 20 – Related articles – All 10 versions
[TXT] Proceedings of the 12th Conference of the European Chapter of the ACL (EACL 2009)} [TXT] from aclweb.org A Copestake, F de Jong, S Abdul-Rauf… – Proceedings of the 12th …, 2009 – aclweb.org … Georgiana and Wang, Rui}, title = {Inference Rules and their Application to Recognizing Textual Entailment}, booktitle = {Proceedings of … Konstas, Ioannis}, title = {User Simulations for Context-Sensitive Speech Recognition in Spoken Dialogue Systems}, booktitle = {Proceedings … Cached
Gerald Penn DG Hays – Philosophy of Linguistics, 2012 – books.google.com … Dialogue systems research attempts to recognize plans and intentions in speech transcripts and to respond to them constructively and naturally. … Another notable exception has been the Pascal Recognising Textual Entailment (RTE) Challenge [Dagan et al., 2005; Bar-Haim et al … Related articles – All 2 versions
Fact-based question decomposition in DeepQA A Kalyanpur, S Patwardhan… – IBM Journal of …, 2012 – ieeexplore.ieee.org … In the literature, we find descriptions of strategies such as local decomposition and meronymy decomposition [9], semantic decomposition using knowledge templates [1], and textual entailment [7] to connect, through semantics and discourse, the original question with its … Cited by 4
[PDF] A bayesian approach to unsupervised semantic role induction [PDF] from aclweb.org I Titov… – Proceedings of the Conference of the European …, 2012 – aclweb.org … to be beneficial in question answering (Shen and Lapata, 2007; Kaisser and Webber, 2007), textual entailment (Sammons et al., 2009), machine translation (Wu and Fung, 2009; Liu and Gildea, 2010; Wu et al., 2011; Gao and Vogel, 2011), and dialogue systems (Basili et al … Cited by 2 – View as HTML
Toward Spoken Human–Computer Tutorial Dialogues [PDF] from google.com SK D’Mello, A Graesser… – Human–Computer Interaction, 2010 – Taylor & Francis … It is conceivable that ASR errors are less problematic in spoken dialogue systems if the content of the user’s utterance (response) can be linked to an appropriate tutor action. … In Proceedings of the Workshop on Tutorial Dialogue Systems: With a View toward the Classroom. … Cited by 7 – Related articles – All 5 versions
[BOOK] Learner answer assessment in intelligent tutoring systems [PDF] from rodneynielsen.com RD Nielsen – 2007 – books.google.com … contrasted with automated tutoring technology. I also describe the relevance of some current active areas of natural language processing research such as paraphrase recognition and textual entailment. I then detail my semantic … Cited by 1 – Related articles – All 8 versions
Measuring Degrees of Semantic Opposition [PDF] from nrc-cnrc.gc.ca SM Mohammad, BJ Dorr, G Hirst… – 2011 – nparc.cisti-icist.nrc-cnrc.gc.ca … This is in turn useful in effectively re-ranking target language hypotheses in machine translation, and for re-ranking query responses in information retrieval. r Understanding discourse structure and improving dialogue systems. … Cited by 2 – Related articles – All 2 versions
[PDF] Taxonomy induction based on a collaboratively built knowledge repository [PDF] from uniroma1.it SP Ponzetto… – Artificial Intelligence, 2011 – wwwusers.di.uniroma1.it Page 1. Artificial Intelligence 175 (2011) 1737–1756 Contents lists available at ScienceDirect Artificial Intelligence www.elsevier.com/locate/artint Taxonomy induction based on a collaboratively built knowledge repository Simone Paolo Ponzettoa,* , Michael Strube b … Cited by 5 – Related articles – View as HTML – All 9 versions
[PDF] Automatic Factual Question Generation from Text [PDF] from cmu.edu M Heilman – 2011 – lti.cs.cmu.edu … tions deal with the analysis of student responses rather than the generation of instructional content. For example, tutorial dialogue systems (Litman and Silliman, 2004; Graesser et al., 2005; Boyer et … generation and dialogue systems. … Cited by 2 – Related articles – View as HTML – All 5 versions
[PDF] Crowd-supervised Training of Spoken Language Systems [PDF] from mit.edu IC McGraw – 2012 – groups.csail.mit.edu … 33 2-4 The plot above depicts two years of development early in the life of the Jupiter weather information dialogue system. … The second experiment conducted was for a multimodal spoken dialogue system, which we deployed directly inside the mTurk interface. This time, how- … View as HTML
Mining association language patterns using a distributional semantic model for negative life event classification LC Yu, CL Chan, CC Lin… – Journal of Biomedical Informatics, 2011 – Elsevier … A dialog system could generate supportive responses if it could understand the negative life events embedded in users input. … Artif. Intell. 2009; 173(7-8): 817-829. [56] Zanzotto FM, Pennacchiotti M. Expanding textual entailment corpora from Wikipedia using co-training. In: Proc. … Cited by 1 – Related articles – All 3 versions
[BOOK] Computational Linguistics and Intelligent Text Processing: 13th International Conference, Cicling 2012, New Delhi, India, March 11-17, 2012, Proceedings A Gelbukh – 2012 – books.google.com … representation Symbolic and linguistic methods Other Statistical methods (mathematics) Morphology Named entity recognition POS tagging Machine translation and multilingualism Question answering Noisy text processing and cleaning Textual entailment Text generation …
Multimodal semi-automated affect detection from conversational cues, gross body language, and facial features [PDF] from google.com SK D’Mello… – User Modeling and User-Adapted Interaction, 2010 – Springer Page 1. User Model User-Adap Inter (2010) 20:147–187 DOI 10.1007/s11257-010-9074-4 ORIGINAL PAPER Multimodal semi-automated affect detection from conversational cues, gross body language, and facial features Sidney K. D’Mello · Arthur Graesser … Cited by 47 – Related articles – All 9 versions
Language modeling approaches to question answering [PDF] from drexel.edu P Banerjee – 2009 – dspace.library.drexel.edu Page 1. Language Modeling Approaches to Question Answering A Dissertation Submitted to the Faculty of Drexel University by Protima Banerjee in partial fulfillment of the requirements for the degree of Doctor of Philosophy July 2009 Page 2. … Cited by 1 – Related articles – Library Search – All 11 versions
[BOOK] Integration of World Knowledge for Natural Language Understanding E Ovchinnikova – 2012 – books.google.com … 184 8.3 Results of recognizing textual entailment by the Nutcracker system for the 39 RTE-2 pairs annotated with “medical” frames in … this type of reasoning is intended to facilitate such applications as, for example, question answering, information extraction, and dialog systems. … Related articles
Ontological reasoning for improving the treatment of emotions in text V Francisco, P Gervás… – Knowledge and information systems, 2010 – Springer … These relations compose a tree (the dependency tree). Dependency analysis has been used successfully for several applications: multilingual machine translation [19], recognizing textual entailment [16], and automatic evaluation of question–answer systems [11]. … Cited by 5 – Related articles – All 7 versions
[BOOK] Flat but not shallow: towards flatter representations in deep semantic parsing for precise and feasible inferencing [PDF] from leidenuniv.nl HHGB Reckman – 2009 – openaccess.leidenuniv.nl … that we focus on, and some work that has been done in the context of the Pascal Recognizing Textual Entailment (RTE) challenge. … The project aims at the development of a natural language dialogue system that discloses personal narratives to facilitate patients (and their … Related articles – Library Search – All 5 versions
[PDF] Knowledge Mining over Scientific Literature and Technical Documentation [PDF] from uzh.ch F Rinaldi – 2008 – files.ifi.uzh.ch Page 1. Knowledge Mining over Scientific Literature and Technical Documentation Fabio Rinaldi March 3, 2008 Page 2. Page 3. Contents 1 Introduction 15 1.1 Background . . . . . 21 1.2 Methodologies . . . . . 27 … Related articles – View as HTML – All 7 versions
SPEECH-BASED SPEAKER RECOGNITION SYSTEMS AND METHODS SO Seyfetdinov – US Patent 20,110,276,323, 2011 – freepatentsonline.com … 20090326938, MULTIWORD TEXT CORRECTION, December, 2009, Marila et al. 20080133240, Spoken dialog system, terminal device, speech information management device and recording medium with program recorded thereon, June, 2008, Miyata et al. … Cached – All 2 versions
[PDF] Methods for Pronunciation Assessment in Computer Aided Language Learning [PDF] from mit.edu MA Peabody – 2011 – groups.csail.mit.edu … We make several assumptions about the nature of the learning activity: it takes place using a dialogue system, it is a task- or game-oriented activity, the student should not be interrupted by the pronunciation feedback system, and that the goal of the feedback system is to identify … Cited by 1 – Related articles – View as HTML
Methods for pronunciation assessment in computer aided language learning [PDF] from mit.edu S Seneff, MA Peabody – 2011 – dspace.mit.edu … We make several assumptions about the nature of the learning activity: it takes place using a dialogue system, it is a task- or game-oriented activity, the student should not be interrupted by the pronunciation feedback system, and that the goal of the feedback system is to identify … Related articles – All 2 versions
[PDF] Content assessment in intelligent computer-aided language learning: Meaning error diagnosis for English as a second language [PDF] from psu.edu SM Bailey – 2008 – Citeseer Page 1. CONTENT ASSESSMENT IN INTELLIGENT COMPUTER-AIDED LANGUAGE LEARNING: MEANING ERROR DIAGNOSIS FOR ENGLISH AS A SECOND LANGUAGE DISSERTATION Presented in Partial Fulfillment of the Requirements for … Cited by 9 – Related articles – View as HTML – Library Search – All 10 versions
[PDF] Shaping the Future of the Multilingual Digital Europe [PDF] from flarenet.eu N Calzolari, N Bel, G Budin, K Choukri, J Mariani… – 2009 – flarenet.eu Page 1. The European Language Resources and Technologies Forum Shaping the Future of the Multilingual Digital Europe Vienna, 12 -13 February 2009 Proceedings Edited by: N. Calzolari, P. Baroni, N. Bel, G. Budin, K. Choukri … Cited by 3 – Related articles – View as HTML – All 2 versions
[BOOK] Linguistically informed question answering [PDF] from uni-saarland.de G Fliedner – 2007 – coli.uni-saarland.de … 113 3.4 RecognisingTextualEntailment . . . . . 113 3.4.1 The Textual Entailment Task and its Relevance for QuestionAnswering . . . . . 114 3.4.2 CircumscribingtheTask . . . . . 115 3.4.3 SystemDescriptions . . . . . … Cited by 6 – Related articles – View as HTML – Library Search
[PDF] Event-Based Modelling in Quesion Answering [PDF] from uni-saarland.de M Wiegand – 2007 – coli.uni-saarland.de … This question type determines how the retrieved information from the corpus has to be processed further in order to find an appropriate answer for the question. This component may become even more complex if the QA system is a component in a dialogue system. In this 14 … Cited by 2 – Related articles – View as HTML
[PDF] Hat Categories: Representing Form and Function Simultaneously in Combinatory Categorial Grammar [PDF] from usyd.edu.au M Honnibal – 2010 – it.usyd.edu.au Page 1. Hat Categories: Representing Form and Function Simultaneously in Combinatory Categorial Grammar Matthew Honnibal Doctor of Philosophy School of Information Technologies The University of Sydney 2010 Page 2. Page 3. 3 Abstract … Cited by 1 – Related articles – View as HTML – Library Search – All 2 versions
[HTML] Natural Language Processing [HTML] from googlecode.com S Bird, E Klein, E Loper, CC Attribution… – 2007 – nltk.googlecode.com Natural Language Processing. Authors: Steven Bird, Ewan Klein, Edward Loper. Version: 0.9.6 (draft only, please send feedback to authors). Copyright: © 2001-2008 the authors. License: Creative Commons Attribution-Noncommercial … Cited by 5 – Related articles – Cached – All 3 versions
[BOOK] Learning for semantic parsing and natural language generation using statistical machine translation techniques [PDF] from utexas.edu YW Wong – 2007 – books.google.com … 9 Page 26. with various hypothetical travel planning scenarios to solve. The resulting spon- taneous spoken queries were recorded as the subjects interacted with automated dialog systems to solve the scenarios. The recorded … Cited by 7 – Related articles – Library Search – All 24 versions