Explainable Span Extraction System
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An Explainable Span Extraction System is a span extraction system that is an interpretable NLP system implementing explainable extraction algorithms to solve explainable span extraction tasks.
- AKA: Interpretable Span Extractor, Span-Decision Mapping System.
- Context:
- It can typically implement Dual-Output Architectures producing spans and explanations.
- It can typically maintain Decision Graphs linking extractions to outcomes.
- It can typically provide Attention Visualizations for span importance.
- It can typically generate Natural Language Explanations for extraction choices.
- It can typically support Interactive Refinement of span-decision mappings.
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- It can often utilize Multi-Task Learning for joint optimization.
- It can often employ Hierarchical Attention for multi-level explanation.
- It can often incorporate Causal Models for decision pathway.
- It can often implement Counterfactual Analysis for span necessity.
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- It can range from being a Rule-Based Explainable System to being a Neural Explainable System, depending on its implementation approach.
- It can range from being a Post-hoc Explainable System to being an Intrinsic Explainable System, depending on its explanation timing.
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- It can process Unstructured Texts with decision requirements.
- It can output Annotated Spans with purpose explanations.
- It can integrate with Decision Support Systems for end applications.
- It can be evaluated by Explainable Extraction Performance Measures.
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- Example(s):
- Counter-Example(s):
- Black-Box Extraction Systems, which lack explanation capability.
- Pure Performance Systems, which optimize accuracy not interpretability.
- Static Pattern Systems, which use fixed rules without adaptation.
- See: Interpretable NLP System, Explainable AI System, Evidence Extraction System, Decision Support System.