| from pyabsa import AspectTermExtraction as ATEPC | |
| from pyabsa import TaskCodeOption | |
| from pyabsa.utils.data_utils.dataset_manager import detect_infer_dataset | |
| def load_atepc_examples(dataset_name: str) -> list[str]: | |
| task = TaskCodeOption.Aspect_Polarity_Classification | |
| atepc_dataset_item = ATEPC.ATEPCDatasetList().__getattribute__(dataset_name) | |
| dataset_files = detect_infer_dataset(atepc_dataset_item, task) | |
| all_lines = [] | |
| if isinstance(dataset_files, str): | |
| dataset_files = [dataset_files] | |
| for fpath in dataset_files: | |
| print(f"Loading ATEPC examples from: {fpath}") | |
| try: | |
| with open(fpath, "r", encoding="utf-8") as fin: | |
| lines = fin.readlines() | |
| for line in lines: | |
| cleaned_line = line.split("$LABEL$")[0] if "$LABEL$" in line else line | |
| cleaned_line = cleaned_line.replace("[B-ASP]", "").replace("[E-ASP]", "").strip() | |
| if cleaned_line: | |
| all_lines.append(cleaned_line) | |
| except FileNotFoundError: | |
| print(f"Warning: Dataset file not found: {fpath}") | |
| except Exception as e: | |
| print(f"Error loading {fpath}: {e}") | |
| seen = set() | |
| unique_ordered_lines = [] | |
| for line in all_lines: | |
| if line not in seen: | |
| unique_ordered_lines.append(line) | |
| seen.add(line) | |
| return unique_ordered_lines | |