Robust Knowledge Graph Completion with Stacked Convolutions and a Student Re-Ranking Network

1 code implementation • ACL 2021 • Justin Lovelace, Denis Newman-Griffis, Shikhar Vashishth, Jill Fain Lehman, Carolyn Penstein Rosé

We develop a deep convolutional network that utilizes textual entity representations and demonstrate that our model outperforms recent KG completion methods in this challenging setting.

Knowledge Graph Completion Re-Ranking

Translational NLP: A New Paradigm and General Principles for Natural Language Processing Research

no code implementations • NAACL 2021 • Denis Newman-Griffis, Jill Fain Lehman, Carolyn Rosé, Harry Hochheiser

Natural language processing (NLP) research combines the study of universal principles, through basic science, with applied science targeting specific use cases and settings.

MedFilter: Improving Extraction of Task-relevant Utterances from Doctor-Patient Conversations through Integration of Discourse Structure and Ontological Knowledge

1 code implementation • EMNLP 2020 • Sopan Khosla, Shikhar Vashishth, Jill Fain Lehman, Carolyn Rose

In this paper, we propose the novel modeling approach MedFilter, which addresses these insights in order to increase performance at identifying and categorizing task-relevant utterances, and in so doing, positively impacts performance at a downstream information extraction task.