Waseem Gharbieh


Deep Learning Models For Multiword Expression Identification
Waseem Gharbieh | Virendrakumar Bhavsar | Paul Cook
Proceedings of the 6th Joint Conference on Lexical and Computational Semantics (*SEM 2017)

Multiword expressions (MWEs) are lexical items that can be decomposed into multiple component words, but have properties that are unpredictable with respect to their component words. In this paper we propose the first deep learning models for token-level identification of MWEs. Specifically, we consider a layered feedforward network, a recurrent neural network, and convolutional neural networks. In experimental results we show that convolutional neural networks are able to outperform the previous state-of-the-art for MWE identification, with a convolutional neural network with three hidden layers giving the best performance.


A Word Embedding Approach to Identifying Verb-Noun Idiomatic Combinations
Waseem Gharbieh | Virendra Bhavsar | Paul Cook
Proceedings of the 12th Workshop on Multiword Expressions

UNBNLP at SemEval-2016 Task 1: Semantic Textual Similarity: A Unified Framework for Semantic Processing and Evaluation
Milton King | Waseem Gharbieh | SoHyun Park | Paul Cook
Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016)