| Challenge: | This paper addresses the task of entity resolution in email conversations. |
| Approach: | They propose to create an annotated seed corpus of email threads labeled with entity coreference chains and evaluate their models for the task. |
| Outcome: | The proposed model performs well on the entity resolution task for email conversations. |
Similar Papers
CEREC: A Corpus for Entity Resolution in Email Conversations (2020.coling-main)
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| Challenge: | e-mail corpus for entity resolution in email conversations is first large scale annotated corpus . ecc is a two-step process with minimal manual effort. |
| Approach: | They present the first large scale corpus for entity resolution in email conversations . they use 6001 email threads and 38,996 entity coreference chains to construct the corpus . |
| Outcome: | The proposed corpus is the first large scale annotated corpus for entity resolution in email conversations. |
Conundrums in Entity Coreference Resolution: Making Sense of the State of the Art (2020.emnlp-main)
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| Challenge: | despite significant progress on entity coreference resolution, there is a general lack of understanding of what has been improved. |
| Approach: | They present an empirical analysis of entity coreference resolvers to provide an understanding of what has been improved. |
| Outcome: | The proposed model improves the performance of entity coreference resolvers. |
Evaluating the Impact of a Hierarchical Discourse Representation on Entity Coreference Resolution Performance (2021.naacl-main)
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| Challenge: | Recent work on entity coreference resolution (CR) follows current trends in Deep Learning . traditional approaches do not make use of hierarchical representations of discourse structure . |
| Approach: | They propose to leverage automatically constructed discourse parse trees within a neural approach to generate anaphoric mentions. |
| Outcome: | The proposed model improves on two benchmark entity coreference-resolution datasets. |
Improving Event Coreference Resolution by Modeling Correlations between Event Coreference Chains and Document Topic Structures (P18-1)
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| Challenge: | a novel approach for event coreference resolution models correlations between event chains and document topical structures. |
| Approach: | They propose a novel approach that models correlations between event coreference chains and document topical structures through an Integer Linear Programming formulation. |
| Outcome: | The proposed approach improves performance across a dataset of document topics . it shows that the models can identify and link event mentions that refer to the same event . |
Coherence Modeling of Asynchronous Conversations: A Neural Entity Grid Approach (P18-1)
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| Challenge: | Existing coherence models are not able to distinguish coherent discourses from incoherent ones. |
| Approach: | They propose a novel coherence model for written asynchronous conversations . they propose to lexicalize the model's entity transitions and extend it to asynchron conversations based on conversational structure . |
| Outcome: | The proposed model outperforms existing models on coherence assessment and thread reconstruction tasks. |
Bridging Resolution: A Survey of the State of the Art (2020.coling-main)
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| 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. |
Revisiting Joint Modeling of Cross-document Entity and Event Coreference Resolution (P19-1)
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| Challenge: | Recognizing that various textual spans across multiple texts refer to the same entity or event is an important NLP task. |
| Approach: | They propose a neural architecture for cross-document coreference resolution by representing an event mention using its lexical span, surrounding context, and relation to other mentions via predicate-arguments structures. |
| Outcome: | The proposed model outperforms the state-of-the-art event coreference model on ECB+ while providing the first entity coreference results on this corpus. |
Adapting Coreference Resolution to Twitter Conversations (2020.findings-emnlp)
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| Challenge: | Existing studies on coreference resolution for Twitter texts show that performance is low. |
| Approach: | They propose to use Twitter conversations to train a system that is originally trained on OntoNotes to improve coreference resolution. |
| Outcome: | The proposed system outperforms existing systems on Twitter by 21.6%. |
End-to-End Neural Discourse Deixis Resolution in Dialogue (2022.emnlp-main)
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| Challenge: | Lexical overlap is a strong indicator of entity coreference, both among names and in the resolution of nominals. |
| Approach: | They propose to extend their span-based entity coreference model to exploit task-specific characteristics of discourse deixis resolution in dialogue. |
| Outcome: | The proposed model achieves state-of-the-art results on the four datasets in the CODI-CRAC 2021 shared task. |
Coreference Resolution with Entity Equalization (P19-1)
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| Challenge: | Existing approaches to coreference resolution capture the properties of entity clusters and use them in the resolution process. |
| Approach: | They propose an approach that captures entities and uses them in coreference resolution . they propose an "Entity Equalization" mechanism that represents each mention in a cluster . |
| Outcome: | The proposed approach improves the CoNLL-2012 coreference resolution task by 3.6%. |