Story Fragment Stitching: The Case of the Story of Moses
Story Fragment Stitching: The Case of the Story of Moses
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发表时间：
2020
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通讯作者：
Mohammed Aldawsari;Ehsaneddin Asgari;Mark A. Finlayson
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作者：
Mohammed Aldawsari;Ehsaneddin Asgari;Mark A. Finlayson
我们介绍了故事片段拼接的任务，这是自动对齐和合并故事的部分讲述的事件序列的过程（即，故事片段）。我们假设每个片段包含至少一个感兴趣的故事中的事件，并且每个片段与另一个片段共享至少一个事件。我们提出了一个基于图的无监督的方法来解决这个问题，其中提到的事件表示为图中的节点，并使用模型合并的变体来压缩图以联合收割机节点。目标是最终图中的每个节点只包含相关事件提及。为了找到核心事件，我们使用BERT上下文嵌入结合tf-idf向量表示。对合并压缩的约束保留了故事的整体时间轴，最终图表示完整的故事时间轴。我们使用一个新的注释语料库来评估我们的方法，这些语料库是我们在古兰经中发现的摩西故事的部分讲述，我们将其发布供公众使用。我们的方法实现了0.63 F1得分的性能。
We introduce the task of story fragment stitching , which is the process of automatically aligning and merging event sequences of partial tellings of a story (i.e., story fragments ). We assume that each fragment contains at least one event from the story of interest, and that every fragment shares at least one event with another fragment. We propose a graph-based unsupervised approach to solving this problem in which events mentions are represented as nodes in the graph, and the graph is compressed using a variant of model merging to combine nodes. The goal is for each node in the final graph to contain only coreferent event mentions. To find coref-erent events, we use BERT contextualized embedding in conjunction with a tf-idf vector representation. Constraints on the merge compression preserve the overall timeline of the story, and the final graph represents the full story timeline. We evaluate our approach using a new annotated corpus of the partial tellings of the story of Moses found in the Quran, which we release for public use. Our approach achieves a performance of 0.63 F 1 score.