Structured Prediction as Translation between Augmented Natural Languages

We propose a new framework, Translation between Augmented Natural Languages (TANL), to solve many structured prediction language tasks including joint entity and relation extraction, nested named entity recognition, relation classification, semantic role labeling, event extraction, coreference resolution, and dialogue state tracking. Instead of tackling the problem by training task-specific discriminative classifiers, we frame it as a translation task between augmented natural languages, from which the task-relevant information can be easily extracted. Our approach can match or outperform task-specific models on all tasks, and in particular, achieves new state-of-the-art results on joint entity and relation extraction (CoNLL04, ADE, NYT, and ACE2005 datasets), relation classification (FewRel and TACRED), and semantic role labeling (CoNLL-2005 and CoNLL-2012). We accomplish this while using the same architecture and hyperparameters for all tasks and even when training a single model to solve all tasks at the same time (multi-task learning). Finally, we show that our framework can also significantly improve the performance in a low-resource regime, thanks to better use of label semantics. INTRODUCTION Structured prediction refers to inference tasks where the output space consists of structured objects, for instance graphs representing entities and relations between them. In the context of natural language processing (NLP), structured prediction covers a wide range of problems such as entity and relation extraction, semantic role labeling, and coreference resolution. For example, given the input sentence "Tolkien's epic novel The Lord of the Rings was published in 1954-1955, years after the book was completed" we might seek to extract the following graphs (respectively in a joint entity and relation extraction, and a coreference resolution task): c novel [ The Lord of the Rings ] was published in 1954-1955, book was completed. e Lord of the Rings | subject] e ] [ in 1954-1955 | temporal], book was completed. novel [ The Lord of the Rings | 54-1955, years after the [ book Rings ] was completed.