| Challenge: | Existing work on treebank conversion focuses on unsupervised treebanks . lack of manually labeled data means that sentences have two syntactic trees at the same time. |
| Approach: | They propose supervised treebank conversion using bi-tree aligned sentences . they propose two conversion approaches based on state-of-the-art deep biaffine parser . |
| Outcome: | The proposed method outperforms the state-of-the-art deep biaffine parser on the English WSJ dataset by 0.97 (93.76% -92.79%) |
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| Challenge: | In the 2017 CoNLL Shared Task on Universal Dependency Parsing, 25 languages have more than one treebank . many teams did not take advantage of the multiple treebanks, however, and trained one model per treebank instead of one model for each language. |
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Treebank Embedding Vectors for Out-of-Domain Dependency Parsing (2020.acl-main)
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| Challenge: | a recent advance in monolingual dependency parsing is the idea of a treebank embedding vector . this allows the model to prefer training data from one treebank over another at test time . |
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| Challenge: | scalable Universal Dependency (UD) treebank synthesis techniques are used to improve production-grade parsers. |
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The Tembusu Treebank: An English Learner Treebank (2022.lrec-1)
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| Challenge: | a new treebank is created to help diagnose ungrammatical sentences using mal-rules . the Tembusu Learner Treebank is an open treebank created from the corpus of Learner English . |
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