Semantic Role Labeling

By Diego Marcheggiani, Michael Roth, Ivan Titov, Benjamin Van Durme. 2010

305 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Natural Language Processing

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Citations in the corpus

Reasoning about Quantities in Natural Language (2015, methodology): “We develop a rule-based standardization step, that is informed, as needed, by deeper NL processing, including semantic role labeling (SRL, (Palmer et al., 2010)) and Co-reference resolution.”
End-to-end learning of semantic role labeling using recurrent neural networks (2015, background): “determined; next the detail relation type was decided(Palmer et al., 2010).”
Question-Answer Driven Semantic Role Labeling: Using Natural Language to Annotate Natural Language (2015, neutral): “The goal is to determine “who does what to whom,” “when,” and “where,” etc. (Palmer et al., 2010; Johansson and Nugues, 2008).”
Partial Or Complete, That’s The Question (2019, background): “Furthermore, the setting described here addresses natural scenarios where only partial, indirect supervision is available, as in Incidental Supervision 1A subtask of semantic role labeling (SRL) (Palmer et al., 2010) that only classifies the role of an argument.”
Inferring Team Task Plans from Human Meetings: A Generative Modeling Approach with Logic-Based Prior (2015, unknown): “…area (Kruijﬀ, Janıcek, & Lison, 2010; Tellex, Kollar, Dick-erson, Walter, Banerjee, Teller, & Roy, 2011; Koomen, Punyakanok, Roth, & Yih, 2005; Palmer, Gildea, & Xue, 2010; Pradhan, Ward, Hacioglu, Martin, & Jurafsky, 2004), but we view this as a separate problem and do not focus on it in…”
Interactive and interpretable machine learning models for human machine collaboration (2015, background): “Processing human dialogue into more machine-understandable forms is an important research area [86, 124, 84, 104, 110], but I view this as a separate problem and do not focus on it in this thesis.”
Bringing Machine Learning and Compositional Semantics Together (2015, background): “This focus means that we largely neglect many important, relevant developments in semantic representation (de Marneffe et al. 2006; MacCartney & Manning 2009; van Eijck & Unger 2010; Palmer et al. 2010), semantic interpretation (Dagan et al.”
Auditing Deep Learning processes through Kernel-based Explanatory Models (2019, background): “Semantic role labeling (SRL (Palmer et al., 2010)) consists in detecting the semantic arguments associated with the predicate of a sentence and their “ What is viscosity?”
Inferring Robot Task Plans from Human Team Meetings: A Generative Modeling Approach with Logic-Based Prior (2013, background): “Processing human dialogue into more machine understandable forms is an important research area (Kruijff, Janıcek, and Lison 2010; Tellex et al. 2011; Koomen et al. 2005; Palmer, Gildea, and Xue 2010; Pradhan et al. 2004), but we view this as a separate problem and do not focus on it in this paper.”
Challenges in Sentiment Analysis (2017, background): “Detecting these various roles is essentially a semantic rolelabeling problem (Gildea and Jurafsky 2002; Màrquez et al. 2008; Palmer et al. 2010), and it is possible that they can be modeled jointly to improve detection accuracy.”