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PropBank

PropBank is a corpus that is annotated with verbal propositions and their arguments—a "proposition bank". Although "PropBank" refers to a specific… 
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Broader (2)

Computational linguisticsNatural language processing
FrameNetMachine learningOutline of natural language processingSemantic role labeling

Papers overview

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2018
2018
The New Propbank: Aligning Propbank with AMR through POS Unification
We present a corpus which converts the sense labels of existing Propbank resources to a new unified format which is more… 
2013
2013
Applying semantic knowledge to the automatic processing of temporal expressions and events in natural language
2010
2010
Joint Inference for Bilingual Semantic Role Labeling
We show that jointly performing semantic role labeling (SRL) on bitext can improve SRL results on both sides. In our approach, we… 
2010
2010
Building the Basque PropBank
This paper presents the work that has been carried out to annotate semantic roles in the Basque Dependency Treebank (BDT). We… 
2008
2008
Improving Chinese Semantic Role Classification with Hierarchical Feature Selection Strategy
In recent years, with the development of Chinese semantically annotated corpus, such as Chinese Proposition Bank and… 
2008
2008
Improved Tree-to-String Transducer for Machine Translation
We propose three enhancements to the tree-to-string (TTS) transducer for machine translation: first-level expansion-based… 
2008
2008
Extracting and Annotating Wikipedia Sub-Domains — Towards a New eScience Community Resource
We suggest a simple procedure for the extraction of Wikipedia sub-domains, propose a plain-text (human and machine readable… 
2006
2006
A Preliminary Study for Building the Basque PropBank
This paper presents a methodology for adding a layer of semantic annotation to a syntactically annotated corpus of Basque (EPEC… 
2005
2005
Guidelines for Propbank framers
Frame files provide guidelines for Propbank annotators and include a list of framesets, or coarse-grained senses of the verbs. A… 
2004
2004
Mixing Weak Learners in Semantic Parsin
This paper shows results from the application of a novel variant of Random Forests to the shallow semantic parsing problem. 
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