[{"id": 617167, "created": "2025-08-08T07:15:42.813425", "project_id": 294, "task_id": 649358, "user_id": 315, "user_ip": null, "finish_time": "2025-08-08T07:15:56.388372", "timeout": null, "calibration": null, "external_uid": null, "media_url": null, "info": {"id": 1913, "src": "in this paper , we alleviate the above issue by utilizing the alignments ( human annotated data or machine alignments ) of the training set .", "target": "in this paper , we improve the attention or alignment accuracy of neural machine translation by utilizing the alignments of training .", "clarity": "very_clear", "faithfulness": "faithful", "plausibility": "plausible", "informativeness": "very_informative"}}, {"id": 626356, "created": "2025-08-18T02:39:54.371071", "project_id": 294, "task_id": 649358, "user_id": 325, "user_ip": null, "finish_time": "2025-08-18T02:40:20.418295", "timeout": null, "calibration": null, "external_uid": null, "media_url": null, "info": {"id": 1913, "src": "in this paper , we alleviate the above issue by utilizing the alignments ( human annotated data or machine alignments ) of the training set .", "target": "in this paper , we improve the attention or alignment accuracy of neural machine translation by utilizing the alignments of training .", "clarity": "neutral", "faithfulness": "moderately_faithful", "plausibility": "moderately_plausible", "informativeness": "moderately_informative"}}]