Named entity recognition architecture combining contextual and global features

We propose the combination of contextual features from XLNet and global features from Graph Convolution Network (GCN) to enhance NER performance. Experiments over a widely-used dataset, CoNLL 2003, show the benefits of our strategy, with results (93.82% in F1-score) competitive with the state...

JSI at SemEval-2022 Task 1: CODWOE-Reverse Dictionary: Monolingual and cross-lingual approaches

We evaluate the Transformer-based model with the added LSTM layer for the task at hand in a monolingual, multilingual, and cross-lingual zero-shot setting in the reverse dictionary task. Our work partially improves the current baseline of the CODWOE competition and offers insight into the...