A High-Performance Syntactic and Semantic Dependency Parser
By Anders Björkelund, Bernd Bohnet, Love Hafdell, Pierre Nugues. 2010
182 citations recorded by the source corpus.
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Citations in the corpus
- SMT and Hybrid systems of the QTLeap project in the WMT16 IT-task (2016, methodology): “The dependency parser is based on the MATE-tools (Bjrkelund et al., 2010).”
- Overview of the GermEval 2018 Shared Task on the Identification of Offensive Language (2018, methodology): “Parsing Only two teams used parsing, one the ParZu parser (Sennrich et al., 2013) and the other the mate-tools parser (Björkelund et al., 2010).”
- A Simple and Accurate Syntax-Agnostic Neural Model for Dependency-based Semantic Role Labeling (2017, methodology): “(2009) for Czech and Spanish, and the one used in Björkelund et al. (2009) for Chinese.”
- CommonCOW: Massively Huge Web Corpora from CommonCrawl Data and a Method to Distribute them Freely under Restrictive EU Copyright Laws (2016, methodology): “German is tokenized, tagged, and chunked using the same tools, named entity recognition is performed using the Stanford NER tool and available German models (Faruqui and Padó, 2010), and morphological analysis is performed using Mate tools (Björkelund et al., 2010).”
- Greedy, Joint Syntactic-Semantic Parsing with Stack LSTMs (2016, methodology): “The best reported systems on the CoNLL 2008 task are due to Johansson and Nugues (2008), Che et al. (2008), Ciaramita et al. (2008) and Zhao and Kit (2008), all of which pipeline syntax and semantics; our system’s semantic and overall performance is comparable to these. We fall behind only Johansson”
- A Joint Sequential and Relational Model for Frame-Semantic Parsing (2017, methodology): “Framat is an open-source semantic role labeling tool provided by mate-tools (Björkelund et al., 2010), and Framat+context is an extension of Framat that uses additional context features.”