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Related Questions
- How does entity recognition help to distinguish between literal and figurative language in sentiment analysis?
- Can you explain how entity recognition can identify and separate sarcastic or ironic comments from genuine ones in text data?
- What are some common external factors that entity recognition can help mitigate in sentiment analysis, aside from sarcasm and irony?
- How does entity recognition influence the accuracy of sentiment analysis when dealing with idiomatic expressions or figurative language?
- Can entity recognition be used to identify and flag potential bias or ambiguity in sentiment analysis, particularly in cases where language is intentionally vague or open to interpretation?
- In what ways can entity recognition improve the reliability of sentiment analysis in noisy or unstructured data, such as social media posts or customer reviews?
- How does entity recognition contribute to the overall robustness of sentiment analysis models, particularly in scenarios where external factors like sentiment drift or context-dependent meaning are present?
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