Publication
AMR Parsing with an Incremental Joint Model
Junsheng Zhou; Feiyu Xu; Hans Uszkoreit; Weighing QU; Ran Li; Yanhui Gu
In: Proceedings of EMNLP 2016. Conference on Empirical Methods in Natural Language Processing (EMNLP-2016), November 1-5, Austin, Texas, USA, Springer, 2016.
Abstract
To alleviate the error propagation in the traditional
pipelined models for Abstract Meaning
Representation (AMR) parsing, we formulate
AMR parsing as a joint task that performs the
two subtasks: concept identification and relation
identification simultaneously. To this end,
we first develop a novel component-wise
beam search algorithm for relation identification
in an incremental fashion, and then incorporate
the decoder into a unified framework
based on multiple-beam search, which
allows for the bi-directional information flow
between the two subtasks in a single incremental
model. Experiments on the public datasets
demonstrate that our joint model significantly
outperforms the previous pipelined
counterparts, and also achieves better performance
than other approaches to AMR parsing,
without utilizing external semantic resources.