Improving Arabic Dependency Parsing with Lexical and Inflectional Morphological Features
By Yuval Marton, Nizar Habash, Owen Rambow. 2010
60 citations recorded by the source corpus.
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
- Sarah Alkuhlani
- Nizar Habash
- Djamé Seddah
- Sandra Kübler
- Reut Tsarfaty
- Yoav Goldberg
- Yannick Versley
- Jennifer Foster
Citations in the corpus
- Statistical Parsing of Morphologically Rich Languages (SPMRL) What, How and Whither (2010, methodology): “…information is available, but substantially hurt results when it is not. machine learning features, agreement features benefit dependency parsing for Arabic (Marton et al., 2010), but not Hindi (dependency) (Ambati et al., 2010a; Ambati et al., 2010b) or Hebrew (Goldberg and Elhadad, 2010).”
- Book Reviews: Introduction to Arabic Natural Language Processing by Nizar Y. Habash (2010, methodology): “An automatically deterministically extended version of CATiB tag set, dubbed catibEx, has also been shown useful for parsing [110].”
- Identifying Broken Plurals, Irregular Gender, and Rationality in Arabic Text (2012, methodology): “In this paper we use the parser of Marton et al. (2010) as our source of syntactic learning features.”