2021/07/27 by Vivek Kalyan, Kalyan, Vivek, Sam Witteveen +3
Computer Science · #Advanced Graph Neural Networks #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #Information Retrieval (cs.IR) #Topic Modeling
paper · pdf · doi:10.48550/arxiv.2107.13031
openalex publication_date 2021/07/27 · openalex created_date 2021/08/02 · openalex updated_date 2026/07/28
Creating explanations for answers to science questions is a challenging task that requires multi-hop inference over a large set of fact sentences. This year, to refocus the Textgraphs Shared Task on the problem of gathering relevant statements (rather than solely finding a single 'correct path'), the WorldTree dataset was augmented with expert ratings of 'relevance' of statements to each overall explanation. Our system, which achieved second place on the Shared Task leaderboard, combines initial statement retrieval; language models trained to predict the relevance scores; and ensembling of a number of the resulting rankings. Our code implementation is made available at https://github.com/mdda/worldtreecorpus/tree/textgraphs2021