CRAFT Shared Tasks 2019 Overview — Integrated Structure, Semantics, and Coreference (D19-57)
Copied to clipboard
William Baumgartner, Michael Bada, Sampo Pyysalo, Manuel R. Ciosici, Negacy Hailu, Harrison Pielke-Lombardo, Michael Regan, Lawrence Hunter
| Challenge: | CRAFT corpus provides a unique foundation for integrating natural language processing (NLP) tasks involving structure, semantics, and coreference. |
| Approach: | They propose to use the CRAFT corpus to evaluate three fundamental language processing tasks over full-text biomedical articles. |
| Outcome: | The CRAFT corpus provides a unique foundation for integrating natural language processing tasks involving structure, semantics, and coreference. |
Similar Papers
Coreference Resolution in Full Text Articles with BERT and Syntax-based Mention Filtering (D19-57)
Copied to clipboard
| Challenge: | Existing systems for coreference resolution are difficult because of their long coreferent chains. |
| Approach: | They propose to use an existing span-based neural coreference resolution system as a baseline . they filter noisy mentions based on parse trees and integrate a highly expressive language model into the system . |
| Outcome: | The proposed system outperforms the baseline system on the CRAFT Shared Tasks 2019 task. |
Data-driven Coreference-based Ontology Building (2024.findings-emnlp)
Copied to clipboard
| Challenge: | a new ontology is based on coreference resolution, but it is not comprehensive . a recent study found that ontologies categorize concepts into groups and arrange them in a hierarchy . |
| Approach: | They derive coreference chains from a corpus of 30 million biomedical abstracts and construct a graph based on the string phrases within these chains. |
| Outcome: | The proposed ontology overlaps significantly with human-authored ontologies. |
Cross-document Event Coreference Search: Task, Dataset and Modeling (2022.emnlp-main)
Copied to clipboard
| Challenge: | Cross-document Event Coreference resolution is the task of identifying clusters of text mentions that refer to the same event, whether within a single document or across a document collection. |
| Approach: | They propose a cross-document coreference search task that searches for all coreferring mentions for a query event in a large document collection. |
| Outcome: | The proposed model integrates a powerful coreference scoring scheme into the DPR architecture, yielding improved performance. |
Multi-Task Identification of Entities, Relations, and Coreference for Scientific Knowledge Graph Construction (D18-1)
Copied to clipboard
| Challenge: | Existing relation extraction systems are designed for within-sentence relations, but extracting information from scientific articles requires relations across sentences. |
| Approach: | They propose a multi-task setup for identifying entities, relations, and coreference clusters in scientific articles . they develop a unified framework called SciIE with shared span representations to solve this problem . |
| Outcome: | The proposed model outperforms existing models without domain-specific features in scientific information extraction. |
They Exist! Introducing Plural Mentions to Coreference Resolution and Entity Linking (C18-1)
Copied to clipboard
| Challenge: | Unlike singular mentions each of which represents one entity, plural mentions stand for multiple entities. |
| Approach: | They propose a novel coreference resolution algorithm that selectively creates clusters to handle both singular and plural mentions and a deep learning-based entity linking model that jointly handles both types of mentions through multi-task learning. |
| Outcome: | The proposed model outperforms existing models designed for singular mentions and plural mentions. |
CorefUD 1.0: Coreference Meets Universal Dependencies (2022.lrec-1)
Copied to clipboard
| Challenge: | Recent advances in standardization for annotated language resources have led to successful large scale efforts, such as the Universal Dependencies (UD) project for multilingual syntactically annotized data. |
| Approach: | They propose a multilingual collection of corpora and a standardized format for coreference resolution compatible with morphosyntactic annotations in the UD framework. |
| Outcome: | The proposed framework is compatible with morphosyntactic annotations and includes facilities for related tasks such as named entity recognition. |
Bridging Resolution: A Survey of the State of the Art (2020.coling-main)
Copied to clipboard
| Challenge: | bridging resolution is an anaphora resolution task that is less studied than entity coreference resolution. |
| Approach: | This paper presents a survey of the current state of research on bridging resolution . it identifies and resolves bridling/associative anaphors, which are anamorphic references to non-identical associated antecedents. |
| Outcome: | The proposed task is more difficult than entity coreference resolution because of the lack of annotated corpora and lack of standardized evaluation protocols. |
Seq2seq is All You Need for Coreference Resolution (2023.emnlp-main)
Copied to clipboard
| Challenge: | Existing work on coreference resolution suggests task-specific models are necessary . a recent line of work that take an alternative approach leveraging advances in seq2seq-based models is needed . |
| Approach: | They propose a pretrained seq2seq transformer to map an input document to a tagged sequence encoding the coreference annotation. |
| Outcome: | The proposed model outperforms or matches the best coreference systems on an array of datasets. |
Bacteria Biotope at BioNLP Open Shared Tasks 2019 (D19-57)
Copied to clipboard
| Challenge: | The Bacteria Biotope task focuses on the extraction of the locations and phenotypes of microorganisms from PubMed abstracts and full-text excerpts. |
| Approach: | They propose to use PubMed abstracts and full-text excerpts to extract the locations and phenotypes of microorganisms and to characterizations of these entities with respect to reference knowledge sources. |
| Outcome: | The proposed subtasks, the corpus characteristics, and the challenge organization are compared with the previous edition in 2016 and the results are presented in the second edition. |
The Coreference under Transformation Labeling Dataset: Entity Tracking in Procedural Texts Using Event Models (2023.findings-acl)
Copied to clipboard
| Challenge: | et al., 2023) show that entity coreference resolution is improved when events bring about changes in entities that are not reflected in text mentions. |
| Approach: | They propose to perform transformation-based entity linking prior to coreference relation identification to improve entity coreference. |
| Outcome: | The proposed model improves coreference resolution of entities mentioned under a process-oriented model of events. |