TASK	DATASET	MODEL	METRIC NAME	METRIC VALUE	GLOBAL RANK	REMOVE
AMR Parsing	LDC2014T12	Transition-based parser-Stack-LSTM	F1 Full	63	# 11
AMR Parsing	LDC2014T12	Transition-based parser-Stack-LSTM	F1 Newswire	68	# 5

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AMR Parsing using Stack-LSTMs

EMNLP 2017 · Miguel Ballesteros, Yaser Al-Onaizan ·

We present a transition-based AMR parser that directly generates AMR parses from plain text. We use Stack-LSTMs to represent our parser state and make decisions greedily. In our experiments, we show that our parser achieves very competitive scores on English using only AMR training data. Adding additional information, such as POS tags and dependency trees, improves the results further.

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Ranked #11 on AMR Parsing on LDC2014T12

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Task	Dataset	Model	Metric Name	Metric Value	Global Rank	Result	Benchmark
AMR Parsing	LDC2014T12	Transition-based parser-Stack-LSTM	F1 Full	63	# 11		Compare
AMR Parsing	LDC2014T12	Transition-based parser-Stack-LSTM	F1 Newswire	68	# 5		Compare

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