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  1. absa_evaluator.py +13 -9
absa_evaluator.py CHANGED
@@ -12,29 +12,33 @@ _CITATION = """
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  """
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  _DESCRIPTION = """
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- Evaluation metrics for Aspect-Based Sentiment Analysis (ABSA) including precision, recall, and F1 score for aspect terms and polarities.
 
 
 
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  """
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  _KWARGS_DESCRIPTION = """
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- Computes precision, recall, and F1 score for aspect terms and polarities in Aspect-Based Sentiment Analysis (ABSA).
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  Args:
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  predictions: List of ABSA predictions with the following structure:
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  - 'aspects': Sequence of aspect annotations, each with the following keys:
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  - 'term': Aspect term
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  - 'polarity': Polarity of the aspect term
 
 
 
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  references: List of ABSA references with the same structure as predictions.
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  Returns:
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- aspect_precision: Precision score for aspect terms
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- aspect_recall: Recall score for aspect terms
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- aspect_f1: F1 score for aspect terms
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- polarity_precision: Precision score for aspect polarities
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- polarity_recall: Recall score for aspect polarities
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- polarity_f1: F1 score for aspect polarities
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  """
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- class AbsaEvaluatorTest(evaluate.Metric):
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  def _info(self):
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  return evaluate.MetricInfo(
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  description=_DESCRIPTION,
 
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  """
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  _DESCRIPTION = """
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+ This module provides evaluation metrics for Aspect-Based Sentiment Analysis (ABSA).
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+ The metrics include precision, recall, and F1 score for both aspect terms and category detection.
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+ Additionally it calculates de accuracy for polarities from aspect terms and category detection.
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+ ABSA evaluates the capability of a model to identify and correctly classify the sentiment of specific aspects within a text.
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  """
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  _KWARGS_DESCRIPTION = """
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+ Computes precision, recall, and F1 score for aspect terms and category detection in Aspect-Based Sentiment Analysis (ABSA). Also calculates de accuracy for polarities on each task.
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  Args:
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  predictions: List of ABSA predictions with the following structure:
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  - 'aspects': Sequence of aspect annotations, each with the following keys:
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  - 'term': Aspect term
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  - 'polarity': Polarity of the aspect term
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+ - 'category': Sequence of category annotations, each with the following keys:
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+ - 'category': Category
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+ - 'polarity': polarity of the category
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  references: List of ABSA references with the same structure as predictions.
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  Returns:
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+ term_extraction_results: f1 score, precision and recall for aspect terms
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+ term_polarity_results_accuracy: accuracy for polarities on aspect terms
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+ category_detection_results: f1 score, precision and recall for category detection
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+ category_polarity_results_accuracy: accuracy for polarities on categories
 
 
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  """
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+ class AbsaEvaluator(evaluate.Metric):
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  def _info(self):
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  return evaluate.MetricInfo(
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  description=_DESCRIPTION,