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We have developed a novel, publicly available annotation tool for the semantic encoding of texts, especially those in the narrative domain. Users can create formal propositions to represent spans of text, as well as temporal relations and other aspects of narrative. A built-in naturallanguage generation component regenerates text from the formal structures, which eases the annotation process. We have run collection experiments with the tool and shown that non-experts can easily create semantic encodings of short fables. . | A Tool for Deep Semantic Encoding of Narrative Texts David K. Elson Columbia University New York City delson@cs.columbia.edu Kathleen R. McKeown Columbia University New York City kathy@cs.columbia.edu Abstract We have developed a novel publicly available annotation tool for the semantic encoding of texts especially those in the narrative domain. Users can create formal propositions to represent spans of text as well as temporal relations and other aspects of narrative. A built-in naturallanguage generation component regenerates text from the formal structures which eases the annotation process. We have run collection experiments with the tool and shown that non-experts can easily create semantic encodings of short fables. We present this tool as a stand-alone reusable resource for research in semantics in which formal encoding of text especially in a narrative form is required. 1 Introduction Research in language processing has benefited greatly from the collection of large annotated corpora such as Penn PropBank Kingsbury and Palmer 2002 and Penn Treebank Marcus et al. 1993 . Such projects typically involve a formal model such as a controlled vocabulary of thematic roles and a corpus of text that has been annotated against the model. One persistent tradeoff in building such resources however is that a model with a wider scope is more challenging for annotators. For example part-of-speech tagging is an easier task than PropBank annotation. We believe that careful user interface design can alleviate difficulties in annotating texts against deep semantic models. In this demonstration we present a tool we have developed Scheherazade for deep annotation of text.1 We are using the tool to collect semantic representations of narrative text. This domain occurs Available athttp www.cs.columbia.edu delson. frequently yet is rarely studied in computational linguistics. Narrative occurs with every other discourse type including dialogue news blogs and multi-party interaction.
