We also present an open-domain human-machine conversation dataset with manually completed user utterances and annotated semantic role labeling after manual completion. VARIOUS: Too Tough to Die (Aging Punx Anthology) - 20 Diane ZHOU: Only - 18 Diane ZHOU: Ellipsis - 8 RESTOCKS: KILLOFFER: 676 Apparitions - 26 LAST COPIES ON EARTH Ron REGE Jr: The Awake Field - 8 Josh SIMMONS: Ghouls 0-3 - Misc. Our approach improves dialog act prediction and semantic role labeling by 1.3% and 2.5% in F1 score respectively in social conversations. Finally, we combine the prediction results from these two utterances using a selection model that is guided by expert knowledge. We then train a prediction model using both utterances containing ellipsis and our automatically completed utterances. Specifically, we first complete user utterances to resolve ellipsis using an end-to-end pointer network model. To address this issue, we propose a method which considers both the original utterance that has ellipsis and the automatically completed utterance in dialog act and semantic role labeling tasks. However, automatic ellipsis completion can result in output which does not accurately reflect user intent. We propose to resolve ellipsis through automatic sentence completion to improve language understanding. Ellipsis increases the difficulty of a series of downstream language understanding tasks, such as dialog act prediction and semantic role labeling. The story and page layouts of this comic were inspired by the characters generated when Zhou used an Optical Character Recognition program to interpret family photos.
The phenomenon of ellipsis is prevalent in social conversations. Following a Chinese egg farmer who becomes a goddess when struck through the head by a piece of hail, Ellipsis is a contemporary fable by Brooklyn-based cartoonist Diane Zhou.
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