FrameNet II: Extended theory and practice

By Josef Ruppenhofer, Michael Ellsworth, Miriam R. L. Petruck, Christopher R. Johnson, J. Scheffczyk. 2006

951 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/10f39897f091090acc385b8fac5d14e30152abc2

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Citations in the corpus

Frame- and Entity-Based Knowledge for Common-Sense Argumentative Reasoning (2018, unknown): “The Berkeley FrameNet (Baker et al., 1998; Ruppenhofer et al., 2016) is an ongoing project for manually building a large lexical-semantic resource with expert annotations.”
Knowledge will Propel Machine Understanding of Content: Extrapolating from Current Examples (2016, methodology): “,19]. These early eorts were centered around understanding the language. Hence, the major focus was towards representing linguistic knowledge. The most popular artifacts of these eorts are FrameNet [25] and WordNet [17], which were developed by realizing the ideas of frame semantics [10] and lexical”
RoboFrameNet: Verb-centric semantics for actions in robot middleware (2012, background): “Programs developed for ROS are separated into constructs called nodes, which interact with each other via inter-process communication.”
Large-Scale QA-SRL Parsing (2018, background): “, 2010) and FrameNet (Ruppenhofer et al., 2016) annotation guides are 89 and 119 pages, respectively.”
Modeling Biological Processes for Reading Comprehension (2014, methodology): “However, in contrast to PropBank and FrameNet, we do not allow all verbs to trigger events and instead let the an-notators decide on biologically important triggers, which are not restricted to verbs (unlike BioProp, where 30 pre-speciﬁed verbs were selected for annotation).”
A Survey of Available Corpora For Building Data-Driven Dialogue Systems: The Journal Version (2015, background): “These include lexical databases such as WordNet (Miller, 1995), which contains lexical relationships between words for over a hundred thousand words, VerbNet (Schuler, 2005) which contains lexical relations between verbs, and FrameNet (Ruppenhofer et al., 2006), which contains ’word senses’ for over”
Question-Answer Driven Semantic Role Labeling: Using Natural Language to Annotate Natural Language (2015, background): “, 2010), and the FrameNet guide is 119 pages (Ruppenhofer et al., 2006).”
Hate Lingo: A Target-based Linguistic Analysis of Hate Speech in Social Media (2018, methodology): “To analyze frame semantics of hate speech, we use S EMA F OR (Chen et al. 2010), which annotates text with their evoked frames as deﬁned by F RAME N ET (Baker, Fillmore, and Lowe 1998; Ruppenhofer et al. 2006).”
Construction of an annotated corpus to support biomedical information extraction (2009, background): “frame information, which deal with both verbs and nominalised verbs [29-32].”