no code implementations • EMNLP 2020 • Maryam Aminian, Mohammad Sadegh Rasooli, Mona Diab
We describe a method for developing broad-coverage semantic dependency parsers for languages for which no semantically annotated resource is available.
no code implementations • 30 Apr 2020 • Maryam Aminian, Mohammad Sadegh Rasooli, Mona Diab
We make use of supervised syntactic parsing as an auxiliary task in a multitask learning framework, and show that with different multitask learning settings, we consistently improve over the single-task baseline.
no code implementations • WS 2019 • Maryam Aminian, Mohammad Sadegh Rasooli, Mona Diab
We describe a transfer method based on annotation projection to develop a dependency-based semantic role labeling system for languages for which no supervised linguistic information other than parallel data is available.
no code implementations • IJCNLP 2017 • Maryam Aminian, Mohammad Sadegh Rasooli, Mona Diab
Our paper addresses the problem of annotation projection for semantic role labeling for resource-poor languages using supervised annotations from a resource-rich language through parallel data.
no code implementations • WS 2016 • Maryam Aminian, Mohamed Al-Badrashiny, Mona Diab
We present an approach for automatic verification and augmentation of multilingual lexica.
no code implementations • LREC 2014 • Mona Diab, Mohamed Al-Badrashiny, Maryam Aminian, Mohammed Attia, Heba Elfardy, Nizar Habash, Abdelati Hawwari, Wael Salloum, Pradeep Dasigi, Esk, Ramy er
Multiple levels of quality checks are performed on the output of each step in the creation process.