Problem
Research questions and friction points this paper is trying to address.
Multilingual FrameNet Corpus
Frame Semantic Parsers
multilingual training data
The Multilingual FrameNet Corpus
🤖 AI Summary
本文通过构建包含九种语言的多语种FrameNet语料库，训练不同架构模型，以超越现有框架语义解析器性能，解决多语种和跨语种设置下的语义解析问题。
📝 Abstract
This paper introduces the Multilingual FrameNet Corpus (mFNC), a novel resource that extends the English Berkeley FrameNet corpus by collecting and harmonizing existing language-specific corpora across nine additional languages: Brazilian Portuguese, Chinese, Dutch, French, German, Italian, Korean, Latvian and Swedish. By training models that rely on different architectures on the mFNC, we consistently outperform existing state-of-the-art Frame Semantic Parsers in both multilingual and cross-lingual settings, underscoring the importance of multilingual training data. The mFNC and our trained FSP models are openly available at https://github.com/beatrice-f/mFNC.
Innovation
Methods, ideas, or system contributions that make the work stand out.
Multilingual FrameNet Corpus
multilingual training data
Frame Semantic Parsers
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