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Proceedings of the Fourth Workshop on Computational Models of Reference, Anaphora and Coreference最新文献

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Understanding Mention Detector-Linker Interaction in Neural Coreference Resolution 神经共参分辨中提及检测器-链接器相互作用的理解
Proceedings of the Fourth Workshop on Computational Models of Reference, Anaphora and Coreference Pub Date : 2020-09-20 DOI: 10.18653/v1/2021.crac-1.16
Zhaofeng Wu, Matt Gardner
{"title":"Understanding Mention Detector-Linker Interaction in Neural Coreference Resolution","authors":"Zhaofeng Wu, Matt Gardner","doi":"10.18653/v1/2021.crac-1.16","DOIUrl":"https://doi.org/10.18653/v1/2021.crac-1.16","url":null,"abstract":"Despite significant recent progress in coreference resolution, the quality of current state-of-the-art systems still considerably trails behind human-level performance. Using the CoNLL-2012 and PreCo datasets, we dissect the best instantiation of the mainstream end-to-end coreference resolution model that underlies most current best-performing coreference systems, and empirically analyze the behavior of its two components: mention detector and mention linker. While the detector traditionally focuses heavily on recall as a design decision, we demonstrate the importance of precision, calling for their balance. However, we point out the difficulty in building a precise detector due to its inability to make important anaphoricity decisions. We also highlight the enormous room for improving the linker and show that the rest of its errors mainly involve pronoun resolution. We propose promising next steps and hope our findings will help future research in coreference resolution.","PeriodicalId":447425,"journal":{"name":"Proceedings of the Fourth Workshop on Computational Models of Reference, Anaphora and Coreference","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134526362","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 8
DramaCoref: A Hybrid Coreference Resolution System for German Theater Plays DramaCoref:德国戏剧戏剧的混合共参考分辨率系统
Proceedings of the Fourth Workshop on Computational Models of Reference, Anaphora and Coreference Pub Date : 1900-01-01 DOI: 10.18653/v1/2021.crac-1.4
Janis Pagel, Nils Reiter
{"title":"DramaCoref: A Hybrid Coreference Resolution System for German Theater Plays","authors":"Janis Pagel, Nils Reiter","doi":"10.18653/v1/2021.crac-1.4","DOIUrl":"https://doi.org/10.18653/v1/2021.crac-1.4","url":null,"abstract":"We present a system for resolving coreference on theater plays, DramaCoref. The system uses neural network techniques to provide a list of potential mentions. These mentions are assigned to common entities using generic and domain-specific rules. We find that DramaCoref works well on the theater plays when compared to corpora from other domains and profits from the inclusion of information specific to theater plays. On the best-performing setup, it achieves a CoNLL score of 32% when using automatically detected mentions and 55% when using gold mentions. Single rules achieve high precision scores; however, rules designed on other domains are often not applicable or yield unsatisfactory results. Error analysis shows that the mention detection is the main weakness of the system, providing directions for future improvements.","PeriodicalId":447425,"journal":{"name":"Proceedings of the Fourth Workshop on Computational Models of Reference, Anaphora and Coreference","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115187191","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
A Hybrid Rule-Based and Neural Coreference Resolution System with an Evaluation on Dutch Literature 一种基于规则和神经系统的荷兰文献评价系统
Proceedings of the Fourth Workshop on Computational Models of Reference, Anaphora and Coreference Pub Date : 1900-01-01 DOI: 10.18653/v1/2021.crac-1.5
Andreas van Cranenburgh, Esther Ploeger, Frank van den Berg, Remi Thüss
{"title":"A Hybrid Rule-Based and Neural Coreference Resolution System with an Evaluation on Dutch Literature","authors":"Andreas van Cranenburgh, Esther Ploeger, Frank van den Berg, Remi Thüss","doi":"10.18653/v1/2021.crac-1.5","DOIUrl":"https://doi.org/10.18653/v1/2021.crac-1.5","url":null,"abstract":"We introduce a modular, hybrid coreference resolution system that extends a rule-based baseline with three neural classifiers for the subtasks mention detection, mention attributes (gender, animacy, number), and pronoun resolution. The classifiers substantially increase coreference performance in our experiments with Dutch literature across all metrics on the development set: mention detection, LEA, CoNLL, and especially pronoun accuracy. However, on the test set, the best results are obtained with rule-based pronoun resolution. This inconsistent result highlights that the rule-based system is still a strong baseline, and more work is needed to improve pronoun resolution robustly for this dataset. While end-to-end neural systems require no feature engineering and achieve excellent performance in standard benchmarks with large training sets, our simple hybrid system scales well to long document coreference (>10k words) and attains superior results in our experiments on literature.","PeriodicalId":447425,"journal":{"name":"Proceedings of the Fourth Workshop on Computational Models of Reference, Anaphora and Coreference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129570632","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
Coreference by Appearance: Visually Grounded Event Coreference Resolution 通过外观的共同参考:视觉上基于事件的共同参考分辨率
Proceedings of the Fourth Workshop on Computational Models of Reference, Anaphora and Coreference Pub Date : 1900-01-01 DOI: 10.18653/v1/2021.crac-1.14
Liming Wang, Shengyu Feng, Xudong Lin, Manling Li, Heng Ji, Shih-Fu Chang
{"title":"Coreference by Appearance: Visually Grounded Event Coreference Resolution","authors":"Liming Wang, Shengyu Feng, Xudong Lin, Manling Li, Heng Ji, Shih-Fu Chang","doi":"10.18653/v1/2021.crac-1.14","DOIUrl":"https://doi.org/10.18653/v1/2021.crac-1.14","url":null,"abstract":"Event coreference resolution is critical to understand events in the growing number of online news with multiple modalities including text, video, speech, etc. However, the events and entities depicting in different modalities may not be perfectly aligned and can be difficult to annotate, which makes the task especially challenging with little supervision available. To address the above issues, we propose a supervised model based on attention mechanism and an unsupervised model based on statistical machine translation, capable of learning the relative importance of modalities for event coreference resolution. Experiments on a video multimedia event dataset show that our multimodal models outperform text-only systems in event coreference resolution tasks. A careful analysis reveals that the performance gain of the multimodal model especially under unsupervised settings comes from better learning of visually salient events.","PeriodicalId":447425,"journal":{"name":"Proceedings of the Fourth Workshop on Computational Models of Reference, Anaphora and Coreference","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127122690","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Lazy Low-Resource Coreference Resolution: a Study on Leveraging Black-Box Translation Tools 懒惰的低资源共同参考解析:利用黑盒翻译工具的研究
Proceedings of the Fourth Workshop on Computational Models of Reference, Anaphora and Coreference Pub Date : 1900-01-01 DOI: 10.18653/v1/2021.crac-1.6
Semere Kiros Bitew, Johannes Deleu, Chris Develder, Thomas Demeester
{"title":"Lazy Low-Resource Coreference Resolution: a Study on Leveraging Black-Box Translation Tools","authors":"Semere Kiros Bitew, Johannes Deleu, Chris Develder, Thomas Demeester","doi":"10.18653/v1/2021.crac-1.6","DOIUrl":"https://doi.org/10.18653/v1/2021.crac-1.6","url":null,"abstract":"Large annotated corpora for coreference resolution are available for few languages. For machine translation, however, strong black-box systems exist for many languages. We empirically explore the appealing idea of leveraging such translation tools for bootstrapping coreference resolution in languages with limited resources. Two scenarios are analyzed, in which a large coreference corpus in a high-resource language is used for coreference predictions in a smaller language, i.e., by machine translating either the training corpus or the test data. In our empirical evaluation of coreference resolution using the two scenarios on several medium-resource languages, we find no improvement over monolingual baseline models. Our analysis of the various sources of error inherent to the studied scenarios, reveals that in fact the quality of contemporary machine translation tools is the main limiting factor.","PeriodicalId":447425,"journal":{"name":"Proceedings of the Fourth Workshop on Computational Models of Reference, Anaphora and Coreference","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123031290","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
FantasyCoref: Coreference Resolution on Fantasy Literature Through Omniscient Writer’s Point of View 从无所不知的作家的角度看奇幻文学的共涉解析
Proceedings of the Fourth Workshop on Computational Models of Reference, Anaphora and Coreference Pub Date : 1900-01-01 DOI: 10.18653/v1/2021.crac-1.3
Sooyoun Han, Sumin Seo, Mi-gyu Kang, Jongin Kim, Nayoung Choi, Minyue Song, Jinho D. Choi
{"title":"FantasyCoref: Coreference Resolution on Fantasy Literature Through Omniscient Writer’s Point of View","authors":"Sooyoun Han, Sumin Seo, Mi-gyu Kang, Jongin Kim, Nayoung Choi, Minyue Song, Jinho D. Choi","doi":"10.18653/v1/2021.crac-1.3","DOIUrl":"https://doi.org/10.18653/v1/2021.crac-1.3","url":null,"abstract":"This paper presents a new corpus and annotation guideline for a novel coreference resolution task on fictional texts, and analyzes its unique characteristics. FantasyCoref contains 211 stories of Grimms’ Fairy Tales and 3 other fantasy literature annotated in the omniscient writer’s point of view (OWV) to handle distinctive aspects in this genre. This task is more challenging than general coreference resolution in two ways. First, documents in our corpus are 2.5 times longer than the ones in OntoNotes, raising a new layer of difficulty in resolving long-distant referents. Second, annotation of literary styles and concepts raise several issues which are not sufficiently addressed in the existing annotation guidelines. Hence, considerations on such issues and the concept of OWV are necessary to achieve high inter-annotator agreement (IAA) in coreference resolution of fictional texts. We carefully conduct annotation tasks in four stages to ensure the quality of our annotation. As a result, a high IAA score of 87% is achieved using the standard coreference evaluation metric. Finally, state-of-the-art coreference resolution approaches are evaluated on our corpus. After training with our annotated dataset, there was a 2.59% and 3.06% improvement over the model trained on the OntoNotes dataset. Also, we observe that the portion of errors specific to fictional texts declines after the training.","PeriodicalId":447425,"journal":{"name":"Proceedings of the Fourth Workshop on Computational Models of Reference, Anaphora and Coreference","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121876788","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Event and Entity Coreference using Trees to Encode Uncertainty in Joint Decisions 用树来编码联合决策中的不确定性
Proceedings of the Fourth Workshop on Computational Models of Reference, Anaphora and Coreference Pub Date : 1900-01-01 DOI: 10.18653/v1/2021.crac-1.11
Nishant Yadav, Nicholas Monath, Rico Angell, A. McCallum
{"title":"Event and Entity Coreference using Trees to Encode Uncertainty in Joint Decisions","authors":"Nishant Yadav, Nicholas Monath, Rico Angell, A. McCallum","doi":"10.18653/v1/2021.crac-1.11","DOIUrl":"https://doi.org/10.18653/v1/2021.crac-1.11","url":null,"abstract":"Coreference decisions among event mentions and among co-occurring entity mentions are highly interdependent, thus motivating joint inference. Capturing the uncertainty over each variable can be crucial for inference among multiple dependent variables. Previous work on joint coreference employs heuristic approaches, lacking well-defined objectives, and lacking modeling of uncertainty on each side of the joint problem. We present a new approach of joint coreference, including (1) a formal cost function inspired by Dasgupta’s cost for hierarchical clustering, and (2) a representation for uncertainty of clustering of event and entity mentions, again based on a hierarchical structure. We describe an alternating optimization method for inference that when clustering event mentions, considers the uncertainty of the clustering of entity mentions and vice-versa. We show that our proposed joint model provides empirical advantages over state-of-the-art independent and joint models.","PeriodicalId":447425,"journal":{"name":"Proceedings of the Fourth Workshop on Computational Models of Reference, Anaphora and Coreference","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121272695","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
Resources and Evaluations for Danish Entity Resolution 丹麦实体决议的资源和评价
Proceedings of the Fourth Workshop on Computational Models of Reference, Anaphora and Coreference Pub Date : 1900-01-01 DOI: 10.18653/v1/2021.crac-1.7
Maria Barrett, Hieu Lam, Martin Wu, Ophélie Lacroix, Barbara Plank, Anders Søgaard
{"title":"Resources and Evaluations for Danish Entity Resolution","authors":"Maria Barrett, Hieu Lam, Martin Wu, Ophélie Lacroix, Barbara Plank, Anders Søgaard","doi":"10.18653/v1/2021.crac-1.7","DOIUrl":"https://doi.org/10.18653/v1/2021.crac-1.7","url":null,"abstract":"Automatic coreference resolution is understudied in Danish even though most of the Danish Dependency Treebank (Buch-Kromann, 2003) is annotated with coreference relations. This paper describes a conversion of its partial, yet well-documented, coreference relations into coreference clusters and the training and evaluation of coreference models on this data. To the best of our knowledge, these are the first publicly available, neural coreference models for Danish. We also present a new entity linking annotation on the dataset using WikiData identifiers, a named entity disambiguation (NED) dataset, and a larger automatically created NED dataset enabling wikily supervised NED models. The entity linking annotation is benchmarked using a state-of-the-art neural entity disambiguation model.","PeriodicalId":447425,"journal":{"name":"Proceedings of the Fourth Workshop on Computational Models of Reference, Anaphora and Coreference","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117019114","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Exploring Pre-Trained Transformers and Bilingual Transfer Learning for Arabic Coreference Resolution 探索预训练变形器和双语迁移学习在阿拉伯语共同参考解决中的应用
Proceedings of the Fourth Workshop on Computational Models of Reference, Anaphora and Coreference Pub Date : 1900-01-01 DOI: 10.18653/v1/2021.crac-1.10
Bonan Min
{"title":"Exploring Pre-Trained Transformers and Bilingual Transfer Learning for Arabic Coreference Resolution","authors":"Bonan Min","doi":"10.18653/v1/2021.crac-1.10","DOIUrl":"https://doi.org/10.18653/v1/2021.crac-1.10","url":null,"abstract":"In this paper, we develop bilingual transfer learning approaches to improve Arabic coreference resolution by leveraging additional English annotation via bilingual or multilingual pre-trained transformers. We show that bilingual transfer learning improves the strong transformer-based neural coreference models by 2-4 F1. We also systemically investigate the effectiveness of several pre-trained transformer models that differ in training corpora, languages covered, and model capacity. Our best model achieves a new state-of-the-art performance of 64.55 F1 on the Arabic OntoNotes dataset. Our code is publicly available at https://github.com/bnmin/arabic_coref.","PeriodicalId":447425,"journal":{"name":"Proceedings of the Fourth Workshop on Computational Models of Reference, Anaphora and Coreference","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132600192","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
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