Constituency Parsing
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Benchmarks
Most implemented
Scheduled Sampling for Sequence Prediction with Recurrent Neural Networks
Grammar as a Foreign Language
Recurrent Neural Network Grammars
Constituency Parsing with a Self-Attentive Encoder
Multilingual Constituency Parsing with Self-Attention and Pre-Training
Holographic Neural PCFG for Unsupervised Parsing
Papers
Representing and Parsing Korean Constituency Structure at Different Levels of Granularity
Korean constituency parsing raises a representational challenge because the terminal units of a phrase-structure tree do not straightforwardly correspond to simple surface words. Korean eojeols are morphologically comple…
Constituency ParsingNon-binary bottom-up constituency parsing without arity actions
Non-binary bottom-up constituency parsing commonly uses arity-specific reductions such as \(\textsc{Reduce-}X\#k\), which jointly specify the mother label and number of children. We show that arity need not be a primitiv…
Constituency ParsingHolographic Neural PCFG for Unsupervised Parsing
Unsupervised constituency parsing aims to accurately induce latent tree structures from raw text alone. Recent neural parameterizations of PCFGs achieve strong performance in both supervised and unsupervised parsing, yet…
Constituency ParsingBetter heads do not guarantee better binarized constituency parsing
We revisit punctuation-aware tree binarization for constituency parsing and ask whether dependency-induced headedness improves binary parser supervision. Although learned heads substantially outperform rule-based heads i…
Constituency ParsingExploiting Pre-trained Encoder-Decoder Transformers for Sequence-to-Sequence Constituent Parsing
To achieve deep natural language understanding, syntactic constituent parsing plays a crucial role and is widely required by many artificial intelligence systems for processing both text and speech. A recent approach inv…
Natural Language UnderstandingConstituency ParsingMachine TranslationLexicalized Constituency Parsing for Middle Dutch: Low-resource Training and Cross-Domain Generalization
Recent years have seen growing interest in applying neural networks and contextualized word embeddings to the parsing of historical languages. However, most advances have focused on dependency parsing, while constituency…
Domain GeneralizationConstituency ParsingDependency ParsingDomain Adaptation