Reorder and then Parse, Fast and Accurate Discontinuous Constituency Parsing (2022.emnlp-main)
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| Challenge: | Discontinuous constituency parsing is still being developed for its efficiency and accuracy are far behind its continuous counterparts. |
| Approach: | They propose to transform a discontinuous constituent tree into a pseudo-continuous one by reordering words in the sentence. |
| Outcome: | The proposed method can transform a discontinuous constituent tree into a pseudo-continuous one by parsing and performing actions on three classical discontinuous constituency treebanks. |
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| Challenge: | Discontinuous parsing is more challenging than continuous parsers because children can group with syntactic cousins in the sentence rather than its two adjacent neighbors. |
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| Challenge: | Constituency parsing is a fundamental task in natural language processing, having many applications in downstream tasks such as language modeling. |
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| Challenge: | a novel chart-based parser for discontinuous constituency trees is proposed for span-based span parsing . it can process discontinuous constituent trees of block degree two, including ill-nested structures . |
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| Challenge: | Recent results show that pretrained language models can be used for many tasks with high accuracy and high performance. |
| Approach: | They propose two methods for automatically analysing discontinuous parsers' errors. |
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| Challenge: | Compared to traditional shift-reduce parsing schemes, our approach is free from the potentially disastrous compounding error. |
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| Challenge: | Sequence-to-sequence models have been used for natural language generation tasks such as machine translation and summarization. |
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| Challenge: | Using constituency and dependency trees, syntactic representations are preferred for tasks such as nominal phrase extraction and identification of terminology. |
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