[PDF] Top 20 Learning Named Entity Hyponyms for Question Answering
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Learning Named Entity Hyponyms for Question Answering
... of named entity hyponyms is feasible and that bootstrapping and feature augmentation can signif- icantly improve classifier ...tion answering, and we measured the benefit on TREC QA ...NE ... See full document
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LasigeBioTM at MEDIQA 2019: Biomedical Question Answering using Bidirectional Transformers and Named Entity Recognition
... Biomedical Question Answering (QA) aims at providing automated answers to user ques- tions, regarding a variety of biomedical ...ognizing Question Entailment (RQE), which would then result in ... See full document
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A Graph based Semi Supervised Learning for Question Answering
... Named-Entity Recognizer (NER): This com- ponent identifies and classifies basic entities such as proper names of person, organization, prod- uct, location; time and numerical expressions such as year, day, ... See full document
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Entity Relation Extraction as Multi Turn Question Answering
... the entity-relation ex- traction task to a multi-turn QA task, introduces sig- nificant performance boost over existing ...reinforcement learning (just as in multi-turn dialog systems) to gain additional ... See full document
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Named Entity Recognition for Novel Types by Transfer Learning
... fine-grained entity typol- ogy has been shown to improve other tasks such as re- lation extraction (Ling and Weld, 2012) and question answering (Lee et ...Transfer Learning for ... See full document
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Multi Task Learning for Conversational Question Answering over a Large Scale Knowledge Base
... conversational question answering over a large-scale knowl- edge ...huge entity vocabulary of a large-scale knowledge base, recent neu- ral semantic parsing based approaches usu- ally decompose the ... See full document
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Paraphrase Driven Learning for Open Question Answering
... plex questions that could not be represented as a query for various reasons. We categorized these questions into groups. The largest group (14%) were questions that need n-ary or higher-order database relations, for ... See full document
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Interactive Language Learning by Question Answering
... Third, most existing MRC studies focus on declarative knowledge — the knowledge of facts or events that can be stated explicitly (i.e., de- clared) in short text snippets. Given a static de- scription of an ... See full document
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A Voting Mechanism for Named Entity Translation in English–Chinese Question Answering
... Moreover, it is possible to have multiple explanations for a term. In order to discover as many question-related documents as possible, alternative translations found by VMNET are also used as additional query ... See full document
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A Model of Vietnamese Person Named Entity Question Answering System
... for question analysis as basic system to compare with our ...of answering: knowledge-based (KLB), search engine-based (SEB) and hybrid method of these two strategies ...experiment named Baseline, ... See full document
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QUALIFIER: Question Answering by Lexical Fabric and External Resources
... working on question answering also employ a variety of linguistic resources, such as the part- of-speech tagging, syntactic parsing, semantic relations, named entity extraction, dictiona[r] ... See full document
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Supervised and Unsupervised Transfer Learning for Question Answering
... answer choices for each question. The stories in this dataset are in audio form. Each story comes with two transcripts: manual and ASR transcrip- tions, where the latter is obtained by running the CMU Sphinx ... See full document
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Multi step Entity centric Information Retrieval for Multi Hop Question Answering
... of entity seeking queries (Liu and Fang, ...use entity-based language modeling for document ...off-the-shelf entity tagger, where as we jointly perform linking and ...ter entity ... See full document
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Bundschus, Markus (2010): From Text to Knowledge: Bridging the Gap with Probabilistic Graphical Models. Dissertation, LMU München: Fakultät für Mathematik, Informatik und Statistik
... The performance of the cascaded CRF on the data set provided by [163] is on par with the multilayer NN and superior to the best GM. This may be due to the discriminative nature of CRFs and NNs, which could be an ... See full document
170
Learning to Compose Neural Networks for Question Answering
... geographical question-answering task first introduced by Krishnamurthy and Kollar ...sual question answering task much simpler than the one just discussed, and is appealing for a number of ... See full document
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Scalable graph based method for individual named entity identification
... atorial optimization problem is NP-hard with re- spect to the number of nodes, since they gener- alize Steiner-tree problem (Hoffart et al., 2011). However heuristics to solve this problem have been experimented: ... See full document
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Stopping Criteria for Active Learning of Named Entity Recognition
... statistical learning methods are impor- tant and widely successful tools for natural lan- guage ...Active learning (AL) reduces this annota- tion effort by selecting unlabeled examples that are maximally ... See full document
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Question Generation for Question Answering
... for question pattern prediction, both retrieval-based and generation-based methods per- form ...QG, question top- ic selection is based on the attention mechanis- m, which is optimized together with ... See full document
9
Learning surface text patterns for a Question Answering System
... (the question term) in the candidate answer ...of question that require multiple words from the question to be in the answer sentence, possibly apart from each ...the question and the ... See full document
7
Named Entity Recognition Using Machine Learning Approaches
... Shipra Dingare, MalvinaNissim Jenny Finkel, Christopher Manning and Claire Grover [3], the author presents a Named Entity Recognition based on maximum entropy system for extracting entities present in the ... See full document
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