Sadhana Kumaravel


2022

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DocAMR: Multi-Sentence AMR Representation and Evaluation
Tahira Naseem | Austin Blodgett | Sadhana Kumaravel | Tim O’Gorman | Young-Suk Lee | Jeffrey Flanigan | Ramón Astudillo | Radu Florian | Salim Roukos | Nathan Schneider
Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

Despite extensive research on parsing of English sentences into Abstract Meaning Representation (AMR) graphs, which are compared to gold graphs via the Smatch metric, full-document parsing into a unified graph representation lacks well-defined representation and evaluation. Taking advantage of a super-sentential level of coreference annotation from previous work, we introduce a simple algorithm for deriving a unified graph representation, avoiding the pitfalls of information loss from over-merging and lack of coherence from under merging. Next, we describe improvements to the Smatch metric to make it tractable for comparing document-level graphs and use it to re-evaluate the best published document-level AMR parser. We also present a pipeline approach combining the top-performing AMR parser and coreference resolution systems, providing a strong baseline for future research.

2016

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Cross Sentence Inference for Process Knowledge
Samuel Louvan | Chetan Naik | Sadhana Kumaravel | Heeyoung Kwon | Niranjan Balasubramanian | Peter Clark
Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing