41 - Cross-Sentence N-ary Relation Extraction with Graph LSTMs, with Nanyun (Violet) Peng
TACL 2017 paper, by Nanyun Peng, Hoifung Poon, Ch…
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vor 8 Jahren
TACL 2017 paper, by Nanyun Peng, Hoifung Poon, Chris Quirk,
Kristina Toutanova, and Wen-tau Yih. Most relation extraction work
focuses on binary relations, like (Seattle, located in,
Washington), because extracting n-ary relations is difficult.
Nanyun (Violet) and her colleagues came up with a model to extract
n-ary relations, focusing on drug-mutation-gene interactions, using
graph LSTMs (a construct pretty similar to graph CNNs, which was
developed around the same time). Nanyun comes on the podcast to
tell us about her work.
https://www.semanticscholar.org/paper/Cross-Sentence-N-ary-Relation-Extraction-with-Grap-Peng-Poon/03a2f871cc841e8047ab3291806dc301c5144bec
Kristina Toutanova, and Wen-tau Yih. Most relation extraction work
focuses on binary relations, like (Seattle, located in,
Washington), because extracting n-ary relations is difficult.
Nanyun (Violet) and her colleagues came up with a model to extract
n-ary relations, focusing on drug-mutation-gene interactions, using
graph LSTMs (a construct pretty similar to graph CNNs, which was
developed around the same time). Nanyun comes on the podcast to
tell us about her work.
https://www.semanticscholar.org/paper/Cross-Sentence-N-ary-Relation-Extraction-with-Grap-Peng-Poon/03a2f871cc841e8047ab3291806dc301c5144bec
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