| Challenge: | Existing approaches to discontinuous parsing are complex and low-level. |
| Approach: | They propose to encode discontinuities as nearly ordered permutations of the input sequence. |
| Outcome: | The proposed model is fast and accurate under the right representation. |
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| Challenge: | Constituent parsing is a core problem in NLP where the goal is to obtain the syntactic structure of sentences expressed as a phrase structure tree. |
| Approach: | They propose a method to reduce constituent parsing to sequence labeling by using a tree with unary branches. |
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Viable Dependency Parsing as Sequence Labeling (N19-1)
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| Challenge: | Existing work on dependency parsing by sequence labeling suggested that it was impractical. |
| Approach: | They propose to use dependency trees as sequence labels to obtain fast and accurate parsers using a conventional BILSTM-based model. |
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A Unifying Theory of Transition-based and Sequence Labeling Parsing (2020.coling-main)
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| Challenge: | Existing parsers that read sentences from left to right are not learning to parse them. |
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Reducing Discontinuous to Continuous Parsing with Pointer Network Reordering (2021.emnlp-main)
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| Challenge: | Existing discontinuous constituent parsers are slow and lack accuracy and speed . however, discontinuous parsing can be solved by any off-the-shelf continuous parser . |
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Better, Faster, Stronger Sequence Tagging Constituent Parsers (N19-1)
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| Challenge: | Existing efforts to speed up constituent parsing have focused on chart-based or shift-reduce parsers. |
| Approach: | They propose to use auxiliary losses and sentence-level fine-tuning to mitigate greedy decoding issues. |
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Dependency Graph Parsing as Sequence Labeling (2024.emnlp-main)
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| Challenge: | Various linearizations have been proposed to cast syntactic dependency parsing as sequence labeling, but they cannot handle reentrancy or cycles. |
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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. |
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Generic refinement of expressive grammar formalisms with an application to discontinuous constituent parsing (C18-1)
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| Challenge: | a split/merge algorithm for interpreted regular tree grammars is a generalization of Petrov et al. (2006) . |
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Enriched In-Order Linearization for Faster Sequence-to-Sequence Constituent Parsing (2020.acl-main)
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| Challenge: | Sequence-to-sequence constituent parsing requires a linearization to represent trees as sequences. Top-down tree linearizations have achieved the best accuracy to date. |
| Approach: | They propose to use an in-order shift-reduce linearization instead of a top-down tree linearization to represent trees as sequences. |
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Hierarchical Bracketing Encodings for Dependency Parsing as Tagging (2025.acl-long)
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| Challenge: | Existing encodings for dependency parsing use suboptimal number of labels and a limited number of symbols. |
| Approach: | They propose a family of encodings for sequence labeling dependency parsing based on hierarchical bracketing . they propose an optimal hierarchically bracketing which minimizes the number of symbols used and encodes projective trees using only 12 distinct labels . |
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