Adapting Coreference Resolution for Processing Violent Death Narratives
Coreference resolution is an important component in analyzing narrative text from administrative data (e.g., clinical or police sources). However, existing coreference models trained on general language corpora suffer from poor transferability due to domain gaps, especially when they are applied to gender-inclusive data with lesbian, gay, bisexual, and transgender (LGBT) individuals. In this paper, we analyzed the challenges of coreference resolution in an exemplary form of administrative text written in English: violent death narratives from the USA's Centers for Disease Control's (CDC) National Violent Death Reporting System. We developed a set of data augmentation rules to improve model performance using a probabilistic data programming framework. Experiments on narratives from an administrative database, as well as existing gender-inclusive coreference datasets, demonstrate the effectiveness of data augmentation in training coreference models that can better handle text data about LGBT individuals.
Code (0)
등록된 구현이 없습니다.
Tasks
coreference-resolutionCoreference ResolutionData AugmentationSimilar Papers 제목 키워드 기반
Adapting Coreference Resolution for Narrative Processing
An Exercise in Reuse of Resources: Adapting General Discourse Coreference Resolution for Detecting Lexical Chains in Patent Documentation
The Stanford Coreference Resolution System (StCR) is a multi-pass, rule-based system that scored best in the CoNLL 2011 shared task on general discourse coreference resolution. We describe how the StCR has been adapted t…
coreference-resolutionCoreference ResolutionDomain AdaptationNamed Entity Recognition (NER)Adapting Coreference Resolution Models through Active Learning
Neural coreference resolution models trained on one dataset may not transfer to new, low-resource domains. Active learning mitigates this problem by sampling a small subset of data for annotators to label. While active l…
Active LearningClusteringcoreference-resolutionCoreference ResolutionAdapting an Entity Centric Model for Portuguese Coreference Resolution
This paper presents the adaptation of an Entity Centric Model for Portuguese coreference resolution, considering 10 named entity categories. The model was evaluated on named e using the HAREM Portuguese corpus and the re…
coreference-resolutionCoreference ResolutionNeural Coreference Resolution with Limited Lexical Context and Explicit Mention Detection for Oral French
We propose an end-to-end coreference resolution system obtained by adapting neural models that have recently improved the state-of-the-art on the OntoNotes benchmark to make them applicable to other paradigms for this ta…
coreference-resolutionCoreference Resolution