datasets.py [107:126]:
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    def load_data_single_split(self, split: str, seed: int = None) -> List[InputExample]:
        """
        Load data for a single split (train, dev, or test).

        This is the default implementation for datasets in the SpERT format
        (see https://github.com/markus-eberts/spert).
        """
        examples = []
        name = self.name if self.data_name is None else self.data_name
        file_path = os.path.join(self.data_dir(), f'{name}_{split}.json')

        with open(file_path, 'r') as f:
            data = json.load(f)
            logging.info(f"Loaded {len(data)} sentences for split {split} of {self.name}")

            for i, x in enumerate(data):
                entities = [
                    Entity(id=j, type=self.entity_types[y['type']], start=y['start'], end=y['end'])
                    for j, y in enumerate(x['entities'])
                ]
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datasets.py [1388:1404]:
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    def load_data_single_split(self, split: str, seed: int = None) -> List[InputExample]:
        """
        Load data for a single split (train, dev, or test).
        """
        examples = []
        name = self.name if self.data_name is None else self.data_name
        file_path = os.path.join(self.data_dir(), f'{name}_{split}.json')
        
        with open(file_path, 'r') as f:
            data = json.load(f)
            logging.info(f"Loaded {len(data)} sentences for split {split} of {self.name}")
            
            for i, x in enumerate(data):
                entities = [
                    Entity(id=j, type=self.entity_types[y['type']], start=y['start'], end=y['end'])
                    for j, y in enumerate(x['entities'])
                ]
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