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Knowing False Negatives: An Adversarial Training Method for Distantly Supervised Relation Extraction ...
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Extend, donÕt rebuild: Phrasing conditional graph modification as autoregressive sequence labelling ...
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23 |
Treasures Outside Contexts: Improving Event Detection via Global Statistics ...
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24 |
Cost-effective End-to-end Information Extraction for Semi-structured Document Images ...
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Monitoring geometrical properties of word embeddings for detecting the emergence of new topics. ...
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Coarse2Fine: Fine-grained Text Classification on Coarsely-grained Annotated Data ...
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27 |
Robust Retrieval Augmented Generation for Zero-shot Slot Filling ...
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28 |
Zero-Shot Information Extraction as a Unified Text-to-Triple Translation ...
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Document-level Entity-based Extraction as Template Generation ...
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Abstract:
Anthology paper link: https://aclanthology.org/2021.emnlp-main.426/ Abstract: Document-level entity-based extraction (EE), aiming at extracting entity-centric information such as entity roles and entity relations, is key to automatic knowledge acquisition from text corpora for various domains. Most document-level EE systems build extractive models, which struggle to model long-term dependencies among entities at the document level. To address this issue, we propose a generative framework for two document-level EE tasks: role-filler entity extraction (REE) and relation extraction (RE). We first formulate them as a template generation problem, allowing models to efficiently capture cross-entity dependencies, exploit label semantics, and avoid the exponential computation complexity of identifying N-ary relations. A novel cross-attention guided copy mechanism, TopK Copy, is incorporated into a pre-trained sequence-to-sequence model to enhance the capabilities of identifying key information in the input document. ...
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Keyword:
Computational Linguistics; Information Extraction; Machine Learning; Machine Learning and Data Mining; Natural Language Processing
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URL: https://dx.doi.org/10.48448/m09e-nx19 https://underline.io/lecture/37467-document-level-entity-based-extraction-as-template-generation
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31 |
TEBNER: Domain Specific Named Entity Recognition with Type Expanded Boundary-aware Network ...
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Synchronous Dual Network with Cross-Type Attention for Joint Entity and Relation Extraction ...
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33 |
Data Augmentation for Cross-Domain Named Entity Recognition ...
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34 |
Speaker-Oriented Latent Structures for Dialogue-Based Relation Extraction ...
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Joint Multi-modal Aspect-Sentiment Analysis with Auxiliary Cross-modal Relation Detection ...
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38 |
Incorporating medical knowledge in BERT for clinical relation extraction ...
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39 |
Crosslingual Transfer Learning for Relation and Event Extraction via Word Category and Class Alignments ...
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ECONET: Effective Continual Pretraining of Language Models for Event Temporal Reasoning ...
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