[PDF] Top 20 Methods for Using Textual Entailment in Open Domain Question Answering
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Methods for Using Textual Entailment in Open Domain Question Answering
... original question, all AGQs that do not reach TE are fil- tered from consideration; remaining passages are assigned an entailment confidence score and are sent to the AP module in order to provide an ex- ... See full document
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Overview of the MEDIQA 2019 Shared Task on Textual Inference, Question Entailment and Question Answering
... first open-domain challenge in Recognizing Textual Entailment (RTE) was launched in 2005 (Dagan et ...sentences: Entailment, Neutral, and ...for Question An- swering ...sented ... See full document
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Training a Ranking Function for Open Domain Question Answering
... looks for the answer in the unstructured text cor- pus (Brill et al., 2001). This approach eliminates the need to build and update knowledge bases by taking advantage of the large amount of text data available on the ... See full document
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XQA: A Cross lingual Open domain Question Answering Dataset
... Open-domain question answering (OpenQA) aims to answer questions through text retrieval and reading ...translation-based methods and one zero-shot cross-lingual method (multilin- gual ... See full document
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Open Domain Question Answering Using Early Fusion of Knowledge Bases and Text
... Open Domain Question Answering (QA) is evolving from complex pipelined systems to end-to-end deep neural ...a question-specific subgraph containing text and KB entities and ...tested ... See full document
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Reversing Gradients in Adversarial Domain Adaptation for Question Deduplication and Textual Entailment Tasks
... Adversarial domain adaptation has been re- cently introduced as an effective technique for textual matching tasks, such as question dedu- plication (Shah et ...ial domain adaptation to ... See full document
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Probabilistic Tree Edit Models with Structured Latent Variables for Textual Entailment and Question Answering
... Table 2 presents RTE results. Our model per- forms competitively on both datasets. On RTE2, our model gives second best performance among the methods we compare against, and the differ- ence in accuracy from the ... See full document
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Multi Hop Paragraph Retrieval for Open Domain Question Answering
... each question (above 90% with the top- 32 paragraphs), but fails at retrieving both gold ...SQuAD- Open, the TF-IDF retriever initially retrieves a set of documents, which are then split into paragraphs to ... See full document
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WikiQA: A Challenge Dataset for Open Domain Question Answering
... First, methods purely rely on word match- ing are not sufficient to achieve good ...matching methods and performs slightly better than LCLR, which suggests that semantic under- standing beyond lexical ... See full document
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Learning Strategies for Open Domain Natural Language Question Answering
... the textual source and question, into a world state containing an appropriate ...practiced answering, and its interface to the world (domain sensors and ... See full document
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FriendsQA: Open Domain Question Answering on TV Show Transcripts
... Question answering (QA) has received lots of hype over the recent years as deep learning models have progressively pushed the limit of machine compre- hension to the level of human ...for answering ... See full document
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RECIPE: Applying Open Domain Question Answering to Privacy Policies
... Motivated by their success, we set to apply one such model (Chen et al., 2017) to evaluate an out- of-domain QA task to assist in analysis and un- derstanding of privacy policies. The text in pri- vacy policies is ... See full document
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A Multi Domain Framework for Textual Similarity A Case Study on Question to Question and Question Answering Similarity Tasks
... of question answering websites has led to the emergence of a new area of research called community question answering, which has to deal with two distinct but complementary ...called ... See full document
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Paraphrase for Open Question Answering: New Dataset and Methods
... a question, augmenting the result with semantic infor- mation, and then transforming the result into a logi- cal ...robust, open-domain semantic parsing is that of Berant et ... See full document
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ANU CSIRO at MEDIQA 2019: Question Answering Using Deep Contextual Knowledge
... for textual inference and question entailment in the medical do- main for the ACL BioNLP 2019 Shared Task, ...MEDIQA. Textual inference is the task of find- ing the semantic relationships ... See full document
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Speech Grammars for Textual Entailment Patterns in Multimodal Question Answering
... speech-based question answering (QA) has become very popular in contrast to pure search engine based approaches on a ...desktop. Open-domain QA systems are now much more powerful and precise, ... See full document
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The Role of Lexico Semantic Feedback in Open Domain Textual Question Answering
... the question keywords. By relying on large, open-domain lin- guistic resources such as WordNet we enabled a more precise approach of searching and mining answers from large collections of ... See full document
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Learning to recognize features of valid textual entailments
... robust textual inference in arbitrary domains about which the system has no ...of question answering (Pasca and Harabagiu, 2001; Moldovan et ...Recognizing Textual En- tailment (RTE) Challenge ... See full document
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Experiments with Open Domain Textual Question Answering
... coling2k dvi Experiments with Open Domain Textual Question Answering Sanda M Harabagiu and Marius A Pa?sca and Steven J Maiorano Department of Computer Science and Engineering Southern Methodist Unive[.] ... See full document
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A Comprehensive Resource to Evaluate Complex Open Domain Question Answering
... for textual classification is that an overlap in the structure of two texts indicates a semantic relation, such as ques- tion/answer ...the question and the ... See full document
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