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Distant supervision for relation extraction without labeled data
TLDR
We use Freebase, a large semantic database of several thousand relations, to provide distant supervision for relation extraction. Expand
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Speech and Language Processing
is one of the most recognizablecharacters in 20th century cinema. HAL is an artificial agent capable of such advancedlanguage behavior as speaking and understanding English, and at a crucial momentExpand
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Speech and language processing - an introduction to natural language processing, computational linguistics, and speech recognition
TLDR
This book takes an empirical approach to language processing, based on applying statistical and other machine-learning algorithms to large corpora. Expand
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Cheap and Fast - But is it Good? Evaluating Non-Expert Annotations for Natural Language Tasks
TLDR
We explore the use of Amazon's Mechanical Turk system, a significantly cheaper and faster method for collecting annotations from non-expert contributors over the Web. Expand
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Deep Reinforcement Learning for Dialogue Generation
TLDR
We introduce a neural conversational model based on the long-term success of dialogues to model future reward in dialogue generation. Expand
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Diachronic Word Embeddings Reveal Statistical Laws of Semantic Change
TLDR
We develop a robust methodology for quantifying semantic change by evaluating word embeddings (PPMI, SVD, word2vec) against known historical changes. Expand
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Dialogue Act Modeling for Automatic Tagging and Recognition of Conversational Speech
TLDR
We describe a statistical approach for modeling dialogue acts in conversational speech, i.e., speech-act-like units such as STATEMENT, Question, BACKCHANNEL, Agreement, Disagreement, and Apology. Expand
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Predictability Effects on Durations of Content and Function Words in Conversational English
In a regression study of conversational speech, we show that frequency, contextual predictability, and repetition have separate contributions to word duration, despite their substantial correlations.Expand
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Automatic Labeling of Semantic Roles
TLDR
We present a system for identifying the semantic relationships, or semantic roles, filled by constituents of a sentence within a semantic frame. Expand
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Adversarial Learning for Neural Dialogue Generation
TLDR
We apply adversarial training to open-domain dialogue generation, training a system to produce sequences that are indistinguishable from human-generated dialogue utterances. Expand
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