The Proposition Bank project adds semantic role labels to the syntactic structures of the Penn Treebank, providing a resource for semantic representation. It is considered shallow as it does not represent coreference or quantification, but broad as it covers all instances of verbs in the corpus. The project defines semantic roles for each verb and annotates occurrences in the original Penn Treebank. The resulting resource enables the development of better language understanding systems and the study of syntactic alternations. The project uses a rule-based tagger followed by manual correction to annotate semantic roles. The Proposition Bank focuses on the argument structure of verbs and provides a complete corpus annotated with semantic roles, including roles traditionally viewed as arguments and adjuncts. It allows for the first time to determine the frequency of syntactic variations in practice, the problems they pose for natural language understanding, and the strategies to which they may be susceptible. The project aims to provide a useful level of representation and a corpus of annotated data to enable empirical study of these issues. The Proposition Bank defines semantic roles on a verb-by-verb basis, with numbered arguments for each verb. The project also defines several more general roles that can apply to any verb. The use of numbered arguments and their mnemonic names was instituted for a number of reasons, including mapping to various theoretical viewpoints. The project also includes general, adjunct-like arguments (ArgMs) and distinguishes them by function tags. The project also includes secondary predication (PRD) and subsumed arguments. The project also includes role labels and syntactic trees, with semantic roles assigned to nodes in the syntactic trees of the Penn Treebank. The project also includes a development process with framing and annotation, using a rule-based argument tagger followed by manual correction. The project also includes a comparison with FrameNet, which focuses on semantic frames. The project also includes a discussion of the implications for natural language research. The project also includes a detailed description of the annotation process, including the criteria used in assigning roles. The project also includes a discussion of the interannotator agreement, with high levels of agreement on role identification and role classification. The project also includes a discussion of the financial subcorpus, which was completely annotated and adjudicated. The project also includes a discussion of the distribution of verbs and framesets, with a Zipfian distribution. The project also includes a discussion of the use of stand-off notation for annotations. The project also includes a discussion of the use of the Penn Treebank for semantic annotation. The project also includes a discussion of the use of the Proposition Bank for training statistical systems. The project also includes a discussion of the use of the Proposition Bank for information extraction, question answering, and machine translation. The project also includes a discussion of the use of the Proposition Bank for linguistic research. The project also includes a discussion of the use of the Proposition Bank for computational linguistics. The project also includes a discussion of the use of the Proposition Bank for natural language processingThe Proposition Bank project adds semantic role labels to the syntactic structures of the Penn Treebank, providing a resource for semantic representation. It is considered shallow as it does not represent coreference or quantification, but broad as it covers all instances of verbs in the corpus. The project defines semantic roles for each verb and annotates occurrences in the original Penn Treebank. The resulting resource enables the development of better language understanding systems and the study of syntactic alternations. The project uses a rule-based tagger followed by manual correction to annotate semantic roles. The Proposition Bank focuses on the argument structure of verbs and provides a complete corpus annotated with semantic roles, including roles traditionally viewed as arguments and adjuncts. It allows for the first time to determine the frequency of syntactic variations in practice, the problems they pose for natural language understanding, and the strategies to which they may be susceptible. The project aims to provide a useful level of representation and a corpus of annotated data to enable empirical study of these issues. The Proposition Bank defines semantic roles on a verb-by-verb basis, with numbered arguments for each verb. The project also defines several more general roles that can apply to any verb. The use of numbered arguments and their mnemonic names was instituted for a number of reasons, including mapping to various theoretical viewpoints. The project also includes general, adjunct-like arguments (ArgMs) and distinguishes them by function tags. The project also includes secondary predication (PRD) and subsumed arguments. The project also includes role labels and syntactic trees, with semantic roles assigned to nodes in the syntactic trees of the Penn Treebank. The project also includes a development process with framing and annotation, using a rule-based argument tagger followed by manual correction. The project also includes a comparison with FrameNet, which focuses on semantic frames. The project also includes a discussion of the implications for natural language research. The project also includes a detailed description of the annotation process, including the criteria used in assigning roles. The project also includes a discussion of the interannotator agreement, with high levels of agreement on role identification and role classification. The project also includes a discussion of the financial subcorpus, which was completely annotated and adjudicated. The project also includes a discussion of the distribution of verbs and framesets, with a Zipfian distribution. The project also includes a discussion of the use of stand-off notation for annotations. The project also includes a discussion of the use of the Penn Treebank for semantic annotation. The project also includes a discussion of the use of the Proposition Bank for training statistical systems. The project also includes a discussion of the use of the Proposition Bank for information extraction, question answering, and machine translation. The project also includes a discussion of the use of the Proposition Bank for linguistic research. The project also includes a discussion of the use of the Proposition Bank for computational linguistics. The project also includes a discussion of the use of the Proposition Bank for natural language processing