Camouflaged named entity recognition in 2D sentence representation

Organizing all spans of a sentence into a two-dimensional (2D) representation unfolds a semantic plane. It has the advantage to resolve nested semantic structures and to build linguistic dependencies across a whole sentence. The main problem is that neighboring elements in the semantic plane are span representations referred to overlapped phrases. Because these representations share the same contextual features in a sentence, a true entity representation is early faded into the background surroundings. It leads to camouflaged named entities in the 2D sentence representation. In this paper, we propose a finer-scale and coarse-scale sentence representation to support camouflaged named entity recognition. The mixed-scale representation has the ability to encode differential clues between entity representations. It is effective to distinguish entity representations from the background surroundings for recognizing camouflaged named entities. Compared with the state-of-the-art models, the results show that our method achieves competitive performance on five public datasets.