Confidence Driven Unsupervised Semantic Parsing

By Dan Goldwasser, Roi Reichart, James Clarke, Dan Roth. 2011

83 citations recorded by the source corpus.

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In Natural Language Processing

Citations in the corpus

Semantic Parsing on Freebase from Question-Answer Pairs (2013, background): “Recent developments aim to lift these limitations, either by reducing the amount of supervision (Clarke et al., 2010; Liang et al., 2011; Goldwasser et al., 2011; Artzi and Zettlemoyer, 2011) or by increasing the number of logical Occidental College, Columbia University Execute on Database Type.”
MCTest: A Challenge Dataset for the Open-Domain Machine Comprehension of Text (2013, background): “…(as opposed to spoken) natural language queries against a database (Zelle and Mooney, 1996) and it also continues to spur research (see for example Goldwasser et al., 2011), as does the similar Jobs database, which provides mappings of 640 sentences to a listing of jobs (Tang and Mooney, 2001).”
Learning to Solve Arithmetic Word Problems with Verb Categorization (2014, background): “More recent work (Eisenstein et al., 2009; Kate and Mooney, 2007; Goldwasser and Roth, 2011; Poon and Domingos, 2009; Goldwasser et al., 2011; Kushman and Barzilay, 2013) reduce the amount of required supervision in mapping sentences to meaning representations while taking advantage of special…”
Learning Dependency-Based Compositional Semantics (2011, background): “Other researchers have also pushed in this direction in various ways: learning a semantic parser based on bootstrapping and estimating the confidence of its own predictions (Goldwasser et al. 2011), learning a semantic parser from user interactions with a dialog system (Artzi and Zettlemoyer 2011), ”
Weakly Supervised Learning of Semantic Parsers for Mapping Instructions to Actions (2013, background): “…approaches for learning semantic parsers from sentences paired with responses, Krishnamurthy and Mitchell (2012) describe using distant supervision, Artzi and Zettlemoyer (2011) use weak supervision from conversational logs and Goldwasser et al. (2011) present work on unsupervised learning.”
Large-scale Semantic Parsing without Question-Answer Pairs (2014, background): “…learning from conversational logs (Artzi and Zettlemoyer, 2011), from sentences paired with system behavior (Chen and Mooney, 2011; Goldwasser and Roth, 2011; Artzi and Zettlemoyer, 2013), via distant supervision (Krishnamurthy and Mitchell, 2012; Cai and Yates, 2013), from questions (Goldwasser…”
From Natural Language Specifications to Program Input Parsers (2013, background): “Examples of meaning representations considered in prior research include logical forms based on database query (Tang and Mooney, 2000; Zettlemoyer and Collins, 2005; Kate and Mooney, 2007; Wong and Mooney, 2007; Poon and Domingos, 2009; Liang et al., 2011; Goldwasser et al., 2011), semantic frames (”
Fast Online Lexicon Learning for Grounded Language Acquisition (2012, methodology): “Finally, Goldwasser et al. (2011) pre-”
Grounded Unsupervised Semantic Parsing (2013, background): “In contrast, Goldwasser et al. (2011) proposed a self-supervised approach, which iteratively chose high-confidence parses to retrain the parser.”
Bootstrapping Semantic Parsers from Conversations (2011, background): “Clarke et al. (2010) and Liang et al. (2011) describe approaches for learning semantic parsers from questions paired with database answers, while Goldwasser et al. (2011) presents work on unsupervised learning.”
Weakly Supervised Training of Semantic Parsers (2012, background): “It is also possible to self-train a semantic parser without any labeled data (Goldwasser et al., 2011).”
Lexical Generalization in CCG Grammar Induction for Semantic Parsing (2011, background): “Goldwasser et al. (2011) present work on unsupervised learning of logical form structure.”
Large-scale Semantic Parsing via Schema Matching and Lexicon Extension (2013, methodology): “66 (Goldwasser et al., 2011), impressive in its own right and slightly better than our F1 score.”
Semantic Parsing as Machine Translation (2013, background): “, 2003), supervised (Zelle, 1995), unsupervised (Goldwasser et al., 2011), and response-based (Liang et al.”
Learning an Executable Neural Semantic Parser (2017, unknown): “2011; Artzi and Zettlemoyer 2013), and from questions (Goldwasser et al. 2011).”
Probabilistic Models for Learning a Semantic Parser Lexicon (2016, background): “Other work has avoided the lexicon learning problem altogether by searching over all possible meaning representations (Kate and Mooney, 2006; Clarke et al., 2010; Goldwasser et al., 2011; Berant and Liang, 2014; Pasupat and Liang, 2015; Reddy et al., 2014).”
Deep Contextualized Self-training for Low Resource Dependency Parsing (2019, background): “, 2018), neural machine translation (Imamura and Sumita, 2018), semantic parsing (Goldwasser et al., 2011) and sentiment analysis (He and Zhou, 2011).”