Papers with Global Context Layer

1 papers
Context-Aware Neural Model for Temporal Information Extraction (P18-1)

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Challenge: Existing temporal information extraction systems rely on statistical learning with feature-engineered task-specific models.
Approach: They propose a context-aware neural network model for temporal information extraction using a global context layer.
Outcome: The proposed model outperforms existing models in terms of performance and performance . it is the first model to use NTM-like architecture to process the information from global context in discourse-scale natural text processing.

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