论文标题
从SPMRL到NMRL：我们在十年解析形态丰富的语言（MRL）中学到了什么？
From SPMRL to NMRL: What Did We Learn (and Unlearn) in a Decade of Parsing Morphologically-Rich Languages (MRLs)?
论文作者
论文摘要
自第一次建立SPMRL以来，这已经是十年了，这是一项研究倡议，该计划统一了多项研究工作，以应对统计解析的统计解析挑战（MRLS）（MRLS）。在这里，我们反思了在那十年中解析MRL，在那十年中解释，强调了对建筑和质量挑战的挑战，并在这些挑战中所学到的解决方案，并在范围内挑战，并在这些挑战中挑战了，并在范围内进行了挑战。 MRL的神经体系结构。然后，我们的目标是提供一个高潮，这表明将SPMRL术语中提出的象征观念纳入当今的神经体系结构有可能将NLP推向新的水平。我们绘制了设计MRLS（NMRL）神经模型的策略，并通过调查Hebrew中的多标记的任务来展示这些策略的初步支持，这是一种形态上丰富的，高融合，语言
It has been exactly a decade since the first establishment of SPMRL, a research initiative unifying multiple research efforts to address the peculiar challenges of Statistical Parsing for Morphologically-Rich Languages (MRLs).Here we reflect on parsing MRLs in that decade, highlight the solutions and lessons learned for the architectural, modeling and lexical challenges in the pre-neural era, and argue that similar challenges re-emerge in neural architectures for MRLs. We then aim to offer a climax, suggesting that incorporating symbolic ideas proposed in SPMRL terms into nowadays neural architectures has the potential to push NLP for MRLs to a new level. We sketch strategies for designing Neural Models for MRLs (NMRL), and showcase preliminary support for these strategies via investigating the task of multi-tagging in Hebrew, a morphologically-rich, high-fusion, language
