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--- nlp:dependency_parsing [2021/12/06 07:12] – [Unsupervised Dependency Parsing] jmflanig
+++ nlp:dependency_parsing [2023/06/15 07:36] (current) – external edit 127.0.0.1
@@ Line 9: / Line 9: @@
 ==== Neural graph-based dependency parsing ====
-  * [[https://www.aclweb.org/anthology/Q16-1023.pdf|Kiperwasser & Goldberg 2016 - Simple and Accurate Dependency Parsing Using Bidirectional LSTM Feature Representations]]  First neural graph-based parser.  One of the early papers to advocate using BiLSTMs as features in NLP models.
+  * [[https://aclanthology.org/P15-1031.pdf|Pei et al 2015 - An Effective Neural Network Model for Graph-based Dependency Parsing]]
+  * [[https://www.aclweb.org/anthology/Q16-1023.pdf|Kiperwasser & Goldberg 2016 - Simple and Accurate Dependency Parsing Using Bidirectional LSTM Feature Representations]]  An early neural graph-based parser.  One of the early papers to advocate using BiLSTMs as features in NLP models.
   * [[https://arxiv.org/pdf/1606.01280.pdf|Zhang et al 2016 - Dependency Parsing as Head Selection]] Applies MST and Eisner's algorithm to a neural network trained to predict the head of each word.
   * [[https://www.aclweb.org/anthology/P16-1218.pdf|Wang & Chang 2016 - Graph-based Dependency Parsing with Bidirectional LSTM]] Similar and concurrent (but slightly later) than Kiperwasser & Goldberg
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 ===== Software =====
   * [[https://stanfordnlp.github.io/stanza/|Stanza]] This parser is very good, better than Stanford Core NLP, NLTK, or other tools
+===== People =====
+  * [[https://scholar.google.com/citations?user=faXAgZQAAAAJ&hl=en|Zhenghua Li]]
 ===== Related Pages =====