Is resolutioner a word mods#

This reduces the complexity of the coreference model to O(n²) and allows it to consider all potential mentions without pruning any of them out. We propose instead to consider coreference links between individual words rather than word spans and then reconstruct the word spans. As the number of spans is O(n²) in the length of text and the number of potential links is O(n⁴), various pruning techniques are necessary to make this approach computationally feasible. Recent coreference resolution models rely heavily on span representations to find coreference links between word spans. Online and Punta Cana, Dominican Republic Proceedings of the 2021 Conference on Empirical Methods in Natural Language ProcessingĪssociation for Computational Linguistics While being highly efficient, our model performs competitively with recent coreference resolution systems on the OntoNotes benchmark.', We also demonstrate that, with these changes, SpanBERT for coreference resolution will be significantly outperformed by RoBERTa. This reduces the complexity of the coreference model to $O(n^2)$ and allows it to consider all potential mentions without pruning any of them out. As the number of spans is $O(n^2)$ in the length of text and the number of potential links is $O(n^4)$, various pruning techniques are necessary to make this approach computationally feasible. Publisher = 'Association for Computational Linguistics',Ībstract = 'Recent coreference resolution models rely heavily on span representations to find coreference links between word spans.

Is resolutioner a word mods#

Cite (Informal): Word-Level Coreference Resolution (Dobrovolskii, EMNLP 2021) Copy Citation: BibTeX Markdown MODS XML Endnote More options… PDF: Video: Code vdobrovolskii/wl-coref Data CoNLL-2012, OntoNotes = 'Word-Level Coreference Resolution',īooktitle = 'Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing',Īddress = 'Online and Punta Cana, Dominican Republic', Association for Computational Linguistics. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, pages 7670–7675, Online and Punta Cana, Dominican Republic. Anthology ID: 2021.emnlp-main.605 Volume: Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing Month: November Year: 2021 Address: Online and Punta Cana, Dominican Republic Venue: EMNLP SIG: Publisher: Association for Computational Linguistics Note: Pages: 7670–7675 Language: URL: DOI: 10.18653/v1/2021.emnlp-main.605 Bibkey: dobrovolskii-2021-word Cite (ACL): Vladimir Dobrovolskii.

While being highly efficient, our model performs competitively with recent coreference resolution systems on the OntoNotes benchmark.

This reduces the complexity of the coreference model to O(n 2) and allows it to consider all potential mentions without pruning any of them out. As the number of spans is O(n 2) in the length of text and the number of potential links is O(n 4), various pruning techniques are necessary to make this approach computationally feasible. Abstract Recent coreference resolution models rely heavily on span representations to find coreference links between word spans.