@conference {17826,
	title = {Ontological Knowledge for Rhetorical Move Analysis},
	booktitle = {International Conference on Computational Linguistics and Intelligent Text},
	volume = {23},
	year = {2019},
	month = {07 April 2019},
	address = { 20th International Conference on Computational Linguistics and Intelligent Text Processing, La Rochelle, France},
	abstract = {<div>
	Scholarly writing in the experimental biomedical sciences follows the IMRaD (Introduction, Methods, Results, and Discussion) structure. Many Biomedical Natural Language Processing tasks take advantage of this structure. Recently, a new challenging information extraction task has been introduced as a means of obtaining these types of detailed information: identifying the argumentation structure in biomedical articles. Argumentation mining can be used to validate scientic claimsand experimental methodology, and to plot deeper chains of scienti creasoning. One subtask in identifying the argumentation structure is the identication of rhetorical moves, text segments that are rhetorical and perform specic communicative goals, in the Methods section. Based on a descriptive taxonomy of rhetorical moves structured around IMRaD, the foundational linguistic knowledge needed for a computationally feasible model of the rhetorical moves is described: semantic roles. One goal is to provide FrameNet and VerbNet-like ontologies for the specializeddo main of biochemistry. Using the observation that the structure of scholarly writing in the laboratory-based experimental sciences closely follows the laboratory procedures, we focus on the procedural verbs inthe Methods section. Occasionally, the text does not contain llers forall of the semantic role slots that are needed to perform an adequate analysis of a verb. To overcome this problem, an ontology of experimental procedures can be interrogated to provide a most likely candidate for the missing semantic role(s).
</div>
},
	url = {https://www.cys.cic.ipn.mx/ojs/index.php/CyS/article/view/3282},
	author = {Mohmmed Alliheedi and Robert E. Mercer and Sandor Haas-Neill}
}
