[PDF] Top 20 Performance Issues and Error Analysis in an Open Domain Question Answering System
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Performance Issues and Error Analysis in an Open Domain Question Answering System
... Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics ACL, Philadelphia, July 2002, pp... Question System Modules.[r] ... See full document
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Learning Strategies for Open Domain Natural Language Question Answering
... Deep Read reading comprehension system (Hirschman et al., 1999) uses a statistical bag-of- words approach, matching the question with the lexically most similar sentence in the story. Quarc (Riloff and ... See full document
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End to End Open Domain Question Answering with BERTserini
... the analysis in Figure 2, in our demonstration system we set k = 10 under the paragraph con- ...per question, while BERT processing time (on the GPU) aver- ages ... See full document
6
Training a Ranking Function for Open Domain Question Answering
... level performance in SQuAD which is a reading comprehension-style question an- swering (QA) ...tackle open-domain ...in open-domain ... See full document
8
Evaluation of baseline information retrieval for Polish open-domain Question Answering system
... Figure 1 presents all steps of question analysis. First, a question is tagged with WCRFT tagger. All punctuation marks and words from a stoplist (including 145 prepositions) are discarded. We as- ... See full document
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Multi Hop Paragraph Retrieval for Open Domain Question Answering
... Recall Analysis We analyze the per- formance of the TF-IDF retriever for HotpotQA in Figure ...each question (above 90% with the top- 32 paragraphs), but fails at retrieving both gold ...the ... See full document
14
XQA: A Cross lingual Open domain Question Answering Dataset
... Open-domain question answering (OpenQA) aims to answer questions through text retrieval and reading ...the performance of cross-lingual OpenQA is still much lower than that of ...Our ... See full document
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The Structure and Performance of an Open Domain Question Answering System
... Documents Answers Question Question Processing Question Type Answer Type.. Answer Processing Parse.[r] ... See full document
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Denoising Distantly Supervised Open Domain Question Answering
... these issues, we propose a coarse- to-fine denoising model for ...our system first retrieves paragraphs ac- cording to the question from a large-scale corpus via information ... See full document
10
FriendsQA: Open Domain Question Answering on TV Show Transcripts
... Many datasets have been presented for various QA tasks (Section 2.1). While numerous models have shown remarkable results with these datasets (Sec- tion 2.2), the evidence passages, where the contexts of questions are ... See full document
10
Systematic Error Analysis of the Stanford Question Answering Dataset
... tion answering (QA) models applied to the Stanford Question Answering Dataset (SQuAD) to identify the core challenges for QA systems on this data ...qualitative analysis of the common ... See full document
9
Real Time Open Domain Question Answering with Dense Sparse Phrase Index
... DrQA by 3.6% EM while achieving 68 times faster inference speed. We previously reported 6K times faster speed in Section 6.1; there is a signif- icant difference largely because D EN SPI is cover- ing a larger number of ... See full document
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ANU CSIRO at MEDIQA 2019: Question Answering Using Deep Contextual Knowledge
... the question might be about treatment rather than the ...is Question A: Glaucoma: Can you mail me patient information about Glau- coma, I was recently diagnosed and want to learn all I can about the ...and ... See full document
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The Role of Lexico Semantic Feedback in Open Domain Textual Question Answering
... of question Q221: “Who killed Martin Luther King ?”, by considering the synonym of killer, the noun assassin, the Q&A system retrieved paragraphs with the correct ...the question Q206: “How far ... See full document
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Open domain Factoid Question Answering via Knowledge Graph Search
... Knowledge graphs contain large amounts of factual information about entities (i.e., well-known places, people and things) and their attributes such as place of birth or profession. Large knowledge graphs gen- erally ... See full document
7
Evolution of Techniques for Question Answering over Knowledge Base: A Survey
... visual answering of questions (VQA) with organized representations of both scene material and queries, using graphs over scene objects and query terms, and a deep neural network that exploits the structure in ... See full document
6
A Comprehensive Resource to Evaluate Complex Open Domain Question Answering
... learning algorithms exploiting to the robustness of Support Vector Machines (SVMs) to irrelevant features (Vapnik, 1995). More recent work, e.g. (Shen and Lapata, 2007) has shown that shallow semantic information in the ... See full document
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Open Domain Voice Activated Question Answering
... ????????? ??? ???????????????????????? ?"!#?$?%?'&)(+*,?' ? ?/???0?1?, 324??56???,7 8?9 ?;?94<=9?>@9?A?9?BDCFE?G?H?I?JK9 MLONDPF;'N3Q%9 R,SUT G?V?WYX S HZW\[?] ^?[`X T%a W S Vcbedgf S H?d S h H?fji S[.] ... See full document
7
An Analysis of the AskMSR Question Answering System
... the question-derived features de- scribed earlier, the score of the number one rank- ing answer, as well as a number of additional features describing the state of the system in proc- essing a particular ... See full document
8
Open Domain Why Question Answering with Adversarial Learning to Encode Answer Texts
... (17,000 question-passage pairs) obtained from 600 million Japanese web pages using the answer- retrieval method of Murata et ...a question-passage pair is composed of a single- sentence question and ... See full document
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