资源分类
》 资源 》论文》Narrative Hermeneutic Circle: Improving Character Role Identification from Natural Language Text via Feedback Loops

Narrative Hermeneutic Circle: Improving Character Role Identification from Natural Language Text via Feedback Loops

2019-11-21 | |  47 |   41 |   0
Abstract While most natural language understanding systems rely on a pipeline-based architecture, certain human text interpretation methods are based on a cyclic process between the whole text and its parts: the hermeneutic circle. In the task of automatically identifying characters and their narrative roles, we propose a feedback-loop-based approach where the output of later modules of the pipeline is fed back to earlier ones. We analyze this approach using a corpus of 21 Russian folktales. Initial results show that feeding back high-level narrative information improves the performance of some NLP tasks.

上一篇：Generating all Possible Palindromes from Ngram Corpora

下一篇：Learning to Rap Battle with Bilingual Recursive Neural Networks

用户评价
全部评价

热门资源

  • Learning to Predi...

    Much of model-based reinforcement learning invo...

  • Stratified Strate...

    In this paper we introduce Stratified Strategy ...

  • The Variational S...

    Unlike traditional images which do not offer in...

  • A Mathematical Mo...

    Direct democracy, where each voter casts one vo...

  • Rating-Boosted La...

    The performance of a recommendation system reli...