Báo cáo khoa học: A Tool for Deep Semantic Encoding of Narrative Texts

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. ...
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Báo cáo khoa học: "A Tool for Deep Semantic Encoding of Narrative Texts" A Tool for Deep Semantic Encoding of Narrative Texts David K. Elson Kathleen R. McKeown Columbia University Columbia University New York City New York City delson@cs.columbia.edu kathy@cs.columbia.edu Abstract frequently, yet is rarely studied in computational linguistics. Narrative occurs with every other dis- We have developed a novel, publicly avail- course type, including dialogue, news, blogs and able annotation tool for the semantic en- multi-party interaction. Given the volume of nar- coding of texts, especially those in the rative prose on the Web, a system competent at un- narrative domain. Users can create for- derstanding narrative structures would be instru- mal propositions to represent spans of text, mental in a range of text processing tasks, such as well as temporal relations and other as summarization or the generation of biographies aspects of narrative. A built-in natural- for question answering. language generation component regener- In the pursuit of a complete and connected rep- ates text from the formal structures, which resentation of the underlying facts of a story, our eases the annotation process. We have annotation process involves the labeling of verb run collection experiments with the tool frames, thematic roles, temporal structure, modal- and shown that non-experts can easily cre- ity, causality and other features. This type of anno- ate semantic encodings of short fables. tation allows for machine learning on the thematic We present this tool as a stand-alone, re- dimension of narrative – that is, the aspects that usable resource for research in semantics unite a series of related facts into an engaging and in which formal encoding of text, espe- fulfilling experience for a reader. Our methodol- cially in a narrative form, is required. ogy is novel in its synthesis of several annotation1 Introduction goals and its focus on content rather than expres- sion. We aim to separate the narrative’s fabula, theResearch in language processing has benefited content dimension of the story, from the rhetori-greatly from the collection of large annotated cal presentation at the textual surface (sjuˇet) (Bal, zcorpora such as Penn PropBank (Kingsbury and 1997). To this end, our model incorporates formalPalmer, 2002) and Penn Treebank (Marcus et al., elements found in other discourse-level annotation1993). Such projects typically involve a formal projects such as Penn Discourse Treebank (Prasadmodel (such as a controlled vocabulary of thematic et al., 2008) and temporal markup languages suchroles) and a corpus of text that has been anno- as TimeML (Mani and Pustejovsky, 2004). Wetated against the model. One persistent tradeoff in call the representation a story graph, because thesebuilding such resources, however, is that a model elements are embodied by nodes and connected bywith a wider scope is more challenging for anno- arcs that represent relationships such as temporaltators. For example, part-of-speech tagging is an order and motivation.easier task than PropBank annotation. We believe More specifically, our annotation process in-that careful user interface design can alleviate dif- ...