Towards detecting intra- and inter-sentential negation scope and focus in dialogue
We present in this paper a study on negation in dialogues. In particular, we analyze the peculiarities of negation in dialogues and propose a new method to detect intra-sentential and inter-sentential negation scope and focus in dialogue context. A key element of the solution is to use dialogue context in the form of previous utterances, which is often needed for proper interpretation of negation in dialogue compared to literary, non-dialogue texts. We have modeled the negation scope and focus detection tasks as a sequence labeling tasks and used Conditional Random Field models to label each token in an utterance as being within the scope/focus of negation or not. The proposed negation scope and focus detection method is evaluated on a newly created corpus (called the DeepTutor Negation corpus; DT-Neg). This dataset was created from actual tutorial dialogue interactions between high school students and a state-of-the-art intelligent tutoring system.
Proceedings of the 29th International Florida Artificial Intelligence Research Society Conference, FLAIRS 2016
Banjade, R., Niraula, N., & Rus, V. (2016). Towards detecting intra- and inter-sentential negation scope and focus in dialogue. Proceedings of the 29th International Florida Artificial Intelligence Research Society Conference, FLAIRS 2016, 198-203. Retrieved from https://digitalcommons.memphis.edu/facpubs/3290