Papers Coreference Resolution
“Coreference Resolution” 태그가 달린 논문 924편 · 필터 해제
Universal Natural Language Processing with Limited Annotations: Try Few-shot Textual Entailment as a Start
A standard way to address different NLP problems is by first constructing a problem-specific dataset, then building a model to fit this dataset. To build the ultimate artificial intelligence, we desire a single machine t…
coreference-resolutionCoreference ResolutionNatural Language InferenceQuestion AnsweringA Brief Survey and Comparative Study of Recent Development of Pronoun Coreference Resolution
Pronoun Coreference Resolution (PCR) is the task of resolving pronominal expressions to all mentions they refer to. Compared with the general coreference resolution task, the main challenge of PCR is the coreference rela…
coreference-resolutionCoreference ResolutionNatural Language UnderstandingRelation Prediction+1DWIE: an entity-centric dataset for multi-task document-level information extraction
This paper presents DWIE, the 'Deutsche Welle corpus for Information Extraction', a newly created multi-task dataset that combines four main Information Extraction (IE) annotation subtasks: (i) Named Entity Recognition (…
coreference-resolutionCoreference ResolutionEntity Linkingnamed-entity-recognition+5Revealing the Myth of Higher-Order Inference in Coreference Resolution
This paper analyzes the impact of higher-order inference (HOI) on the task of coreference resolution. HOI has been adapted by almost all recent coreference resolution models without taking much investigation on its true …
AvgClusteringcoreference-resolutionCoreference Resolution+1Streamlining Cross-Document Coreference Resolution: Evaluation and Modeling
Recent evaluation protocols for Cross-document (CD) coreference resolution have often been inconsistent or lenient, leading to incomparable results across works and overestimation of performance. To facilitate proper fut…
coreference-resolutionCoreference ResolutionCross Document Coreference ResolutionEntity Cross-Document Coreference Resolution+1Event Coreference Resolution via a Multi-loss Neural Network without Using Argument Information
Event coreference resolution(ECR) is an important task in Natural Language Processing (NLP) and nearly all the existing approaches to this task rely on event argument information. However, these methods tend to suffer fr…
coreference-resolutionCoreference ResolutionEvent Argument ExtractionEvent Coreference ResolutionUnderstanding Mention Detector-Linker Interaction in Neural Coreference Resolution
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…
coreference-resolutionCoreference ResolutionNatural Language UnderstandingEnd-to-End Neural Event Coreference Resolution
Traditional event coreference systems usually rely on pipeline framework and hand-crafted features, which often face error propagation problem and have poor generalization ability. In this paper, we propose an End-to-End…
coreference-resolutionCoreference ResolutionEvent Coreference ResolutionEvent DetectionCoreference Resolution System for Indonesian Text with Mention Pair Method and Singleton Exclusion using Convolutional Neural Network
Neural network has shown promising performance on coreference resolution systems that uses mention pair method. With deep neural network, it can learn hidden and deep relations between two mentions. However, there is no …
coreference-resolutionCoreference ResolutionWord EmbeddingsImproving Coreference Resolution by Leveraging Entity-Centric Features with Graph Neural Networks and Second-order Inference
One of the major challenges in coreference resolution is how to make use of entity-level features defined over clusters of mentions rather than mention pairs. However, coreferent mentions usually spread far apart in an e…
coreference-resolutionCoreference ResolutionGraph Neural NetworkIntermediate-Task Transfer Learning with Pretrained Language Models: When and Why Does It Work?
While pretrained models such as BERT have shown large gains across natural language understanding tasks, their performance can be improved by further training the model on a data-rich intermediate task, before fine-tunin…
coreference-resolutionCoreference ResolutionNatural Language UnderstandingTransfer LearningDiscourse as a Function of Event: Profiling Discourse Structure in News Articles around the Main Event
Understanding discourse structures of news articles is vital to effectively contextualize the occurrence of a news event. To enable computational modeling of news structures, we apply an existing theory of functional dis…
Argument MiningArticlescoreference-resolutionCoreference Resolution+2CorefQA: Coreference Resolution as Query-based Span Prediction
In this paper, we present CorefQA, an accurate and extensible approach for the coreference resolution task. We formulate the problem as a span prediction task, like in question answering: A query is generated for each ca…
coreference-resolutionCoreference ResolutionData AugmentationPrediction+1Segmentation Approach for Coreference Resolution Task
In coreference resolution, it is important to consider all members of a coreference cluster and decide about all of them at once. This technique can help to avoid losing precision and also in finding long-distance relati…
Allcoreference-resolutionCoreference ResolutionPosition+1AMALGUM -- A Free, Balanced, Multilayer English Web Corpus
We present a freely available, genre-balanced English web corpus totaling 4M tokens and featuring a large number of high-quality automatic annotation layers, including dependency trees, non-named entity annotations, core…
coreference-resolutionCoreference ResolutionUnderstanding Points of Correspondence between Sentences for Abstractive Summarization
Fusing sentences containing disparate content is a remarkable human ability that helps create informative and succinct summaries. Such a simple task for humans has remained challenging for modern abstractive summarizers,…
Abstractive Text Summarizationcoreference-resolutionCoreference ResolutionSentence+1A Cross-Task Analysis of Text Span Representations
Many natural language processing (NLP) tasks involve reasoning with textual spans, including question answering, entity recognition, and coreference resolution. While extensive research has focused on functional architec…
coreference-resolutionCoreference ResolutionQuestion AnsweringDeBERTa: Decoding-enhanced BERT with Disentangled Attention
Recent progress in pre-trained neural language models has significantly improved the performance of many natural language processing (NLP) tasks. In this paper we propose a new model architecture DeBERTa (Decoding-enhanc…
Common Sense ReasoningCoreference ResolutionLinguistic AcceptabilityMath Word Problem Solving+9A Pairwise Probe for Understanding BERT Fine-Tuning on Machine Reading Comprehension
Pre-trained models have brought significant improvements to many NLP tasks and have been extensively analyzed. But little is known about the effect of fine-tuning on specific tasks. Intuitively, people may agree that a p…
Boundary Detectioncoreference-resolutionCoreference ResolutionMachine Reading Comprehension+1Nurse is Closer to Woman than Surgeon? Mitigating Gender-Biased Proximities in Word Embeddings
Word embeddings are the standard model for semantic and syntactic representations of words. Unfortunately, these models have been shown to exhibit undesirable word associations resulting from gender, racial, and religiou…
coreference-resolutionCoreference ResolutionWord Embeddings