Constraining MGbank: Agreement, L-Selection and Supertagging in Minimalist Grammars (P18-1)
Copied to clipboard
| Challenge: | a deep grammatical formalism that has not been applied to NLP tasks is the Minimalist Grammar (MG) formalism. |
| Approach: | They propose to extend the Minimalist Grammar (MG) formalism with a mechanism for enforcing fine-grained selectional restrictions and agreements. |
| Outcome: | The proposed system is compatible with Markovian supertaggers and enables efficient parsing on key dependency types. |
Similar Papers
Wide-Coverage Neural A* Parsing for Minimalist Grammars (P19-1)
Copied to clipboard
| Challenge: | a new parser for wide-coverage parsing uses a linguistically expressive yet highly constrained grammar . the expected time complexity of the parsers is cubic in the length of the sentence . |
| Approach: | They propose to use a linguistically expressive yet highly constrained grammar to parse a wide-coverage sentence using a bi-LSTM neural network supertagger. |
| Outcome: | The proposed algorithm recovers unbounded long distance dependencies and can recover unbundled long distance dependents. |
Development of a Multilingual CCG Treebank via Universal Dependencies Conversion (2022.lrec-1)
Copied to clipboard
| Challenge: | Combinatory Categorial Grammar (CCG) is a lexicalized grammar formalism that can capture both syntactic and semantic information. |
| Approach: | They propose an algorithm to convert UD treebanks to CCG treebank and propose future extensions. |
| Outcome: | The proposed algorithm performs lexical, sentential, and syntactic rule coverage analysis, as well as CCG parsing experiments. |
Supertagging-based Parsing with Linear Context-free Rewriting Systems (2021.naacl-main)
Copied to clipboard
| Challenge: | a new supertagging-based parser for linear context-free rewriting systems is developed for discontinuous constituents . discontinuous constituencies span non-contiguous sets of positions in a sentence, and can be modelled by CFG . |
| Approach: | They propose a supertagging-based parser for linear context-free rewriting systems . they propose an efficient procedure which induces a lexical LCFRS from any discontinuous treebank . |
| Outcome: | The proposed method outperforms previous LCFRS-based parsers in accuracy and speed by a wide margin. |
Revisiting Supertagging for faster HPSG parsing (2024.emnlp-main)
Copied to clipboard
| Challenge: | a new supertagger for HPSG-based treebanks is used to improve parsing speed and accuracy. |
| Approach: | They propose to integrate the best supertagger into an HPSG-based parser and compare it to an existing system. |
| Outcome: | The proposed system achieves 97.26% accuracy on 950 sentences from WSJ23 and 93.88% on the out-of-domain technical essay The Cathedral and the Bazaar. |
Improving the Extraction of Supertags for Constituency Parsing with Linear Context-Free Rewriting Systems (2022.findings-emnlp)
Copied to clipboard
| Challenge: | a new approach to parsing discontinuous constituency structures uses supertags to improve parsability . traditional approaches use grammar formalisms to model hierarchies of noncontiguous phrases . but supertags are still useful for analyzing these grammars and parsers . |
| Approach: | They propose to reformulate and parameterize extraction process for LCFRS supertags to improve parsing quality. |
| Outcome: | The proposed method improves the quality and speed of parsing with supertags over the previous method. |
LLM-supertagger: Categorial Grammar Supertagging via Large Language Models (2024.findings-emnlp)
Copied to clipboard
| Challenge: | Recent studies have shown that LLMs are underperforming in classification tasks due to their decoder-based nature. |
| Approach: | They propose a method that significantly boosts LLMs' performance in supertagging for both Combinatory Categorial Grammar (CCG) and Lambek Categorian Grammar (LCG). |
| Outcome: | The proposed method outperforms LSTM and encoder-based models and achieves state-of-the-art performance. |
Generalized chart constraints for efficient PCFG and TAG parsing (P18-2)
Copied to clipboard
| Challenge: | Existing pruning techniques limit chart constraints to PCFGs and cannot be applied to more expressive grammars. |
| Approach: | They propose to apply chart constraints to more expressive grammars and a neural tagger which predicts chart constraints at very high precision. |
| Outcome: | The proposed technique accelerates both PCFG and TAG parsing by two orders of magnitude while improving accuracy. |
Efficient Semiring-Weighted Earley Parsing (2023.acl-long)
Copied to clipboard
| Challenge: | Using Earley's context-free parsing algorithm, we show that the speed-ups are effective in practice. |
| Approach: | They propose a context-free parsing algorithm with various known and new speed-ups that improve Earley's (1970) O(N3|G||R|) They also propose 'a binarized version' that achieves runtime of O(M| |G| when the grammar is represented compactly as a single finite-state automaton M. |
| Outcome: | The proposed algorithm can be used to reduce the complexity of CKY on a binarized version of the grammar G. |
Proceedings of the First Workshop on Commonsense Inference in Natural Language Processing (D19-60)
Copied to clipboard
| Challenge: | Workshop on Commonsense Inference in Natural Language Processing focuses on commonsense knowledge representation and application in NLP tasks. |
| Approach: | COIN is a workshop on commonsense inference in natural language processing . workshop included two shared tasks on reading comprehension using commonsensense knowledge . |
| Outcome: | the workshop focused on modeling commonsense knowledge and commonsensing in natural language processing tasks. |
CoNLL-UL: Universal Morphological Lattices for Universal Dependency Parsing (L18-1)
Copied to clipboard
Amir More, Özlem Çetinoğlu, Çağrı Çöltekin, Nizar Habash, Benoît Sagot, Djamé Seddah, Dima Taji, Reut Tsarfaty
| Challenge: | Using the universal dependencies framework, we address the need for a universal representation of morphological analysis that can capture alternative morphology of surface tokens and is compatible with the segmentation and morphologic annotation guidelines prescribed for UD treebanks. |
| Approach: | They propose a new annotation format for word lattices that represent morphological analyses and a resource that obeys this format for a range of typologically different languages. |
| Outcome: | The proposed model can capture alternative morphological analyses of surface tokens and is compatible with the segmentation and morphology guidelines prescribed for UD treebanks. |