范式发现问题
The Paradigm Discovery Problem
摘要：
这项工作对待范式发现问题（PDP），学习的曲折形态系统从未注释的句子的任务。我们形式化的PDP和判断系统开发的评估指标。使用当前可用的资源，我们为任务构建数据集。我们还设计了一个启发式的基准PDP和报告实证结果五种不同的语言。我们的基准测试系统首先利用词嵌入和字符串相似性来按单元格和范式聚类形式。然后，我们在集群数据之上引导神经传感器来预测单词，以实现空范式槽。对我们系统的错误分析表明，跨不同拐点类的细胞聚类是未来工作最紧迫的挑战。我们的代码和数据可供公众使用。
英文摘要：
This work treats the paradigm discovery problem (PDP), the task of learning an inflectional morphological system from unannotated sentences. We formalize the PDP and develop evaluation metrics for judging systems. Using currently available resources, we construct datasets for the task. We also devise a heuristic benchmark for the PDP and report empirical results on five diverse languages. Our benchmark system first makes use of word embeddings and string similarity to cluster forms by cell and by paradigm. Then, we bootstrap a neural transducer on top of the clustered data to predict words to realize the empty paradigm slots. An error analysis of our system suggests clustering by cell across different inflection classes is the most pressing challenge for future work. Our code and data are available for public use.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
