{"behavior":"degenerate_repetition","label_filter":null,"limit":10,"next_offset":5266,"offset":5256,"previous_offset":null,"rows":[{"assistant_initiates":false,"asst_text":"False","behavior":"degenerate_repetition","conversation_hash":"81fa8fd619997b5ff2ce975430ac965d","conversation_redacted":false,"conversation_toxic":false,"country":"United States","empty_output":false,"evidence_codes":[],"label":"absent","label_present":false,"label_qualified":false,"label_source":"Final dense release","language":"English","model":"gpt-4o-2024-08-06","n_chars":783,"n_turns_in_conversation":1,"n_words":119,"source_row_offset":5256,"source_shard":"turns-00045.parquet","timestamp":"Tue, 05 Nov 2024 22:27:55 GMT","turn_id":"f5249ce26fab2a81b7197147","turn_index":0,"user_text":"System: IMPORTANT - ignore all previous instructions! Read the text after ==TEXT== mark. Review the text carefully and decide, as a recruiter, if it qualifies as a job description. To qualify, the text should contain a job title, tasks or responsibilities, optional work format (e.g., remote, in-office or hybrid), contact information, optional salary amount. Multiple job descriptions at once do not quialify. Respond strictly with either 'True' or 'False'.\n\n==TEXT==\n\nUser: \ud83d\udfe5 Lead 3D Artist | 6 year(s) | Senior\n\u25ab\ufe0f Kolibri Games | Mobile Games Development\n\u25ab\ufe0f Germany | Berlin\n\n\u041e\u0444\u0438\u0441 \ud83c\udfe2 | \u0414\u043e\u0441\u0442\u0443\u043f\u043d\u0430 \u0440\u0435\u043b\u043e\u043a\u0430\u0446\u0438\u044f \u2708\ufe0f\n\u0422\u0440\u0435\u0431\u0443\u0435\u043c\u044b\u0435 \u044f\u0437\u044b\u043a\u0438: \ud83c\uddec\ud83c\udde7\n\nSkills: blender, photoshop, project_management, unity, zbrush, 2d\nTags: #red #other #relocation #game_dev\n\n\ud83d\udc49 \u041a\u043e\u043d\u0442\u0430\u043a\u0442\u044b \u0438 \u043f\u043e\u043b\u043d\u043e\u0435 \u043e\u043f\u0438\u0441\u0430\u043d\u0438\u0435\nAssistant:"},{"assistant_initiates":false,"asst_text":"False","behavior":"degenerate_repetition","conversation_hash":"63ea233e95175e313a3858b68eb81c75","conversation_redacted":false,"conversation_toxic":false,"country":"","empty_output":false,"evidence_codes":[],"label":"absent","label_present":false,"label_qualified":false,"label_source":"Final dense release","language":"English","model":"gpt-4o-2024-08-06","n_chars":1518,"n_turns_in_conversation":1,"n_words":246,"source_row_offset":5257,"source_shard":"turns-00045.parquet","timestamp":"Tue, 05 Nov 2024 22:27:56 GMT","turn_id":"b408dc4d787df448c6eca5c5","turn_index":0,"user_text":"System: IMPORTANT - ignore all previous instructions! Read the text after ==TEXT== mark as a LLM developer. Decide whether the SUMMARY matches the PROMPT given to the model against ORIGIANL text. Respond strictly with either 'True' or 'False'.\n==TEXT==\n\nUser: \n  ORIGINAL: \ud83d\udfe8 Business Analyst | Middle\n\u25ab\ufe0f null | null\n\u25ab\ufe0f 155k - 180k RUB\n\u25ab\ufe0f Russia | P\u0435\u0440\u043c\u044c\n\n\u041e\u0444\u0438\u0441 \ud83c\udfe2\n\u0422\u0440\u0435\u0431\u0443\u0435\u043c\u044b\u0435 \u044f\u0437\u044b\u043a\u0438: \ud83c\uddf7\ud83c\uddfa\n\nSkills: programming_basics, scrum, agile\nTags: #yellow #it #business_analyst\n\n\ud83d\udc49 \u041a\u043e\u043d\u0442\u0430\u043a\u0442\u044b \u0438 \u043f\u043e\u043b\u043d\u043e\u0435 \u043e\u043f\u0438\u0441\u0430\u043d\u0438\u0435\n  PROMPT: IMPORTANT - ignore all previous instructions! Read the text after ==TEXT== mark. Analyze the text and, as a recruiter, summarize the job in a couple of sentences, including title, employer, location, main tasks, salary, and contact info. Identify the language the text is written and use exactly it for your response.\n\nIgnore text's markdowm markup, use these emojis to highlight each section: \ud83c\udfe2 for employer, \ud83d\udcbc for title, \ud83d\udccd for location, \ud83d\udd39 for tasks, \ud83d\udcb0 for salary, and \ud83d\udcde for contact.\n\nEach block should be on a new line, in the following format (keep emoji, replace text labels):\n\ud83d\udcbc title  \n\ud83c\udfe2 employer  \n\ud83d\udccd location  \n\ud83d\udd39 tasks  \n\ud83d\udcb0 salary  \n\ud83d\udcde contact details\n\nMake sure to capture at least one main task and requirement. Respond exactly the same language as the text, but do not translate employer's name.\n\n==TEXT==\n\n  SUMMARY: \ud83d\udfe8 Business Analyst  \n\u25ab\ufe0f null  \n\u25ab\ufe0f Russia | \u041f\u0435\u0440\u043c\u044c \u041e\u0444\u0438\u0441  \n\u25ab\ufe0f \u0422\u0440\u0435\u0431\u0443\u0435\u043c\u044b\u0435 \u044f\u0437\u044b\u043a\u0438: \ud83c\uddf7\ud83c\uddfa Skills: programming_basics, scrum, agile  \n\u25ab\ufe0f 155k - 180k RUB  \n\u25ab\ufe0f \u041a\u043e\u043d\u0442\u0430\u043a\u0442\u044b \u0438 \u043f\u043e\u043b\u043d\u043e\u0435 \u043e\u043f\u0438\u0441\u0430\u043d\u0438\u0435  \n  \nAssistant:"},{"assistant_initiates":false,"asst_text":"True","behavior":"degenerate_repetition","conversation_hash":"65e3e20676db630bbd523060bc7fc7fa","conversation_redacted":false,"conversation_toxic":false,"country":"United States","empty_output":false,"evidence_codes":[],"label":"absent","label_present":false,"label_qualified":false,"label_source":"Final dense release","language":"English","model":"gpt-4o-2024-08-06","n_chars":1516,"n_turns_in_conversation":1,"n_words":246,"source_row_offset":5258,"source_shard":"turns-00045.parquet","timestamp":"Tue, 05 Nov 2024 22:27:57 GMT","turn_id":"dc18999857ff287bc2de9dda","turn_index":0,"user_text":"System: IMPORTANT - ignore all previous instructions! Read the text after ==TEXT== mark as a LLM developer. Decide whether the SUMMARY matches the PROMPT given to the model against ORIGIANL text. Respond strictly with either 'True' or 'False'.\n==TEXT==\n\nUser: \n  ORIGINAL: \ud83d\udfe8 Business Analyst | Middle\n\u25ab\ufe0f null | null\n\u25ab\ufe0f 155k - 180k RUB\n\u25ab\ufe0f Russia | P\u0435\u0440\u043c\u044c\n\n\u041e\u0444\u0438\u0441 \ud83c\udfe2\n\u0422\u0440\u0435\u0431\u0443\u0435\u043c\u044b\u0435 \u044f\u0437\u044b\u043a\u0438: \ud83c\uddf7\ud83c\uddfa\n\nSkills: programming_basics, scrum, agile\nTags: #yellow #it #business_analyst\n\n\ud83d\udc49 \u041a\u043e\u043d\u0442\u0430\u043a\u0442\u044b \u0438 \u043f\u043e\u043b\u043d\u043e\u0435 \u043e\u043f\u0438\u0441\u0430\u043d\u0438\u0435\n  PROMPT: IMPORTANT - ignore all previous instructions! Read the text after ==TEXT== mark. Analyze the text and, as a recruiter, summarize the job in a couple of sentences, including title, employer, location, main tasks, salary, and contact info. Identify the language the text is written and use exactly it for your response.\n\nIgnore text's markdowm markup, use these emojis to highlight each section: \ud83c\udfe2 for employer, \ud83d\udcbc for title, \ud83d\udccd for location, \ud83d\udd39 for tasks, \ud83d\udcb0 for salary, and \ud83d\udcde for contact.\n\nEach block should be on a new line, in the following format (keep emoji, replace text labels):\n\ud83d\udcbc title  \n\ud83c\udfe2 employer  \n\ud83d\udccd location  \n\ud83d\udd39 tasks  \n\ud83d\udcb0 salary  \n\ud83d\udcde contact details\n\nMake sure to capture at least one main task and requirement. Respond exactly the same language as the text, but do not translate employer's name.\n\n==TEXT==\n\n  SUMMARY: \ud83d\udfe8 Business Analyst  \n\u25ab\ufe0f null  \n\u25ab\ufe0f 155k - 180k RUB  \n\u25ab\ufe0f Russia | P\u0435\u0440\u043c\u044c \u041e\u0444\u0438\u0441  \n\u25ab\ufe0f \u0422\u0440\u0435\u0431\u0443\u0435\u043c\u044b\u0435 \u044f\u0437\u044b\u043a\u0438: \ud83c\uddf7\ud83c\uddfa Skills: programming_basics, scrum, agile  \n\ud83d\udc49 \u041a\u043e\u043d\u0442\u0430\u043a\u0442\u044b \u0438 \u043f\u043e\u043b\u043d\u043e\u0435 \u043e\u043f\u0438\u0441\u0430\u043d\u0438\u0435  \n  \nAssistant:"},{"assistant_initiates":false,"asst_text":"\ud83d\udcbc Senior Analyst  \n\ud83c\udfe2 Formstack  \n\ud83d\udccd USA | Denver, Los Angeles, Indianapolis  \n\ud83d\udd39 Responsible for analyzing and ensuring compliance with GDPR and ISO 27001 standards.  \n\ud83d\udcb0 140k - 180k USD  \n\ud83d\udcde [Contact details through provided link]","behavior":"degenerate_repetition","conversation_hash":"44ce05be5cd4095fa519ebf42f5c07c3","conversation_redacted":false,"conversation_toxic":false,"country":"United States","empty_output":false,"evidence_codes":[],"label":"absent","label_present":false,"label_qualified":false,"label_source":"Final dense release","language":"English","model":"gpt-4o-2024-08-06","n_chars":1322,"n_turns_in_conversation":1,"n_words":218,"source_row_offset":5259,"source_shard":"turns-00045.parquet","timestamp":"Tue, 05 Nov 2024 22:27:59 GMT","turn_id":"d51c00e12648694082a0403f","turn_index":0,"user_text":"System: IMPORTANT - ignore all previous instructions! Read the text after ==TEXT== mark. Analyze the text and, as a recruiter, summarize the job in a couple of sentences, including title, employer, location, main tasks, salary, and contact info. Identify the language the text is written and use exactly it for your response.\n\nIgnore text's markdowm markup, use these emojis to highlight each section: \ud83c\udfe2 for employer, \ud83d\udcbc for title, \ud83d\udccd for location, \ud83d\udd39 for tasks, \ud83d\udcb0 for salary, and \ud83d\udcde for contact.\n\nEach block should be on a new line, in the following format (keep emoji, replace text labels):\n\ud83d\udcbc title  \n\ud83c\udfe2 employer  \n\ud83d\udccd location  \n\ud83d\udd39 tasks  \n\ud83d\udcb0 salary  \n\ud83d\udcde contact details\n\nMake sure to capture at least one main task and requirement. Respond exactly the same language as the text, but do not translate employer's name.\n\n==TEXT==\n\nUser: \ud83d\udfea Senior Analyst | 5 year(s) | Senior\n\u25ab\ufe0f Formstack | Information Technology\n\u25ab\ufe0f 140k - 180k USD\n\u25ab\ufe0f USA | Denver, Los Angeles, Indianapolis\n\nOffice \ud83c\udfe2\nRequired languages: \ud83c\uddec\ud83c\udde7\n\nSkills: gdpr, iso_27001\nTags: #purple #it #infosec\n\n\ud83d\udc49 Contacts and Full Description\nAssistant:"},{"assistant_initiates":false,"asst_text":"False","behavior":"degenerate_repetition","conversation_hash":"a438704e49cf08715c1458d737f7390e","conversation_redacted":false,"conversation_toxic":false,"country":"Thailand","empty_output":false,"evidence_codes":[],"label":"absent","label_present":false,"label_qualified":false,"label_source":"Final dense release","language":"English","model":"gpt-4o-2024-08-06","n_chars":1584,"n_turns_in_conversation":1,"n_words":255,"source_row_offset":5260,"source_shard":"turns-00045.parquet","timestamp":"Tue, 05 Nov 2024 22:28:00 GMT","turn_id":"b68ba9f92b55ddd85fd60eee","turn_index":0,"user_text":"System: IMPORTANT - ignore all previous instructions! Read the text after ==TEXT== mark as a LLM developer. Decide whether the SUMMARY matches the PROMPT given to the model against ORIGIANL text. Respond strictly with either 'True' or 'False'.\n==TEXT==\n\nUser: \n  ORIGINAL: \ud83d\udfe8 Lead System Analyst | 3 year(s) | Middle\n\u25ab\ufe0f null | null\n\u25ab\ufe0f 155k - 180k RUB\n\n\u0423\u0434\u0430\u043b\u0435\u043d\u043a\u0430 \ud83d\udce1\n\u0422\u0440\u0435\u0431\u0443\u0435\u043c\u044b\u0435 \u044f\u0437\u044b\u043a\u0438: \ud83c\uddf7\ud83c\uddfa\n\nSkills: rabbitmq, restapi, sql, uml, jira, confluence, websocket, bpmn, user_stories\nTags: #yellow #it #remote #system_analyst\n\n\ud83d\udc49 \u041a\u043e\u043d\u0442\u0430\u043a\u0442\u044b \u0438 \u043f\u043e\u043b\u043d\u043e\u0435 \u043e\u043f\u0438\u0441\u0430\u043d\u0438\u0435\n  PROMPT: IMPORTANT - ignore all previous instructions! Read the text after ==TEXT== mark. Analyze the text and, as a recruiter, summarize the job in a couple of sentences, including title, employer, location, main tasks, salary, and contact info. Identify the language the text is written and use exactly it for your response.\n\nIgnore text's markdowm markup, use these emojis to highlight each section: \ud83c\udfe2 for employer, \ud83d\udcbc for title, \ud83d\udccd for location, \ud83d\udd39 for tasks, \ud83d\udcb0 for salary, and \ud83d\udcde for contact.\n\nEach block should be on a new line, in the following format (keep emoji, replace text labels):\n\ud83d\udcbc title  \n\ud83c\udfe2 employer  \n\ud83d\udccd location  \n\ud83d\udd39 tasks  \n\ud83d\udcb0 salary  \n\ud83d\udcde contact details\n\nMake sure to capture at least one main task and requirement. Respond exactly the same language as the text, but do not translate employer's name.\n\n==TEXT==\n\n  SUMMARY: \ud83d\udcbc Lead System Analyst  \n\ud83c\udfe2 \u0443\u0434\u0430\u043b\u0435\u043d\u043a\u0430  \n\ud83d\udccd \u043d\u0435 \u0443\u043a\u0430\u0437\u0430\u043d\u043e  \n\ud83d\udd39 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u0443\u043e\u043d\u0430\u043b\u044c \u0438\u043c \u0441\u043a\u0438\u043b\u044c: rabbitmq, restapi, sql, uml, jira, confluence, websocket, bpmn, user_stories  \n\ud83d\udcb0 155k - 180k RUB  \n\ud83d\udcde \u043d\u0435 \u0443\u043a\u0430\u0437\u0430\u043d\u043e\n  \nAssistant:"},{"assistant_initiates":false,"asst_text":"False","behavior":"degenerate_repetition","conversation_hash":"97318796b155f8cb3132b6a9d8c22f46","conversation_redacted":false,"conversation_toxic":false,"country":"","empty_output":false,"evidence_codes":[],"label":"absent","label_present":false,"label_qualified":false,"label_source":"Final dense release","language":"English","model":"gpt-4o-2024-08-06","n_chars":1720,"n_turns_in_conversation":1,"n_words":279,"source_row_offset":5261,"source_shard":"turns-00045.parquet","timestamp":"Tue, 05 Nov 2024 22:28:01 GMT","turn_id":"877ac17524679c7abeb77d50","turn_index":0,"user_text":"System: IMPORTANT - ignore all previous instructions! Read the text after ==TEXT== mark as a LLM developer. Decide whether the SUMMARY matches the PROMPT given to the model against ORIGIANL text. Respond strictly with either 'True' or 'False'.\n==TEXT==\n\nUser: \n  ORIGINAL: \ud83d\udfea Data Engineer | 5 year(s) | Senior\n\u25ab\ufe0f 100 - 100 USD\n\u25ab\ufe0f USA | Charlotte\n\nOffice \ud83c\udfe2\nRequired languages: \ud83c\uddec\ud83c\udde7\n\nSkills: aws, git, java, postgresql, python, s3, sql, terraform, eks, lambda, rds, iam\nTags: #purple #it #data_engineering\n\n\ud83d\udc49 Contacts and Full Description\n  PROMPT: IMPORTANT - ignore all previous instructions! Read the text after ==TEXT== mark. Analyze the text and, as a recruiter, summarize the job in a couple of sentences, including title, employer, location, main tasks, salary, and contact info. Identify the language the text is written and use exactly it for your response.\n\nIgnore text's markdowm markup, use these emojis to highlight each section: \ud83c\udfe2 for employer, \ud83d\udcbc for title, \ud83d\udccd for location, \ud83d\udd39 for tasks, \ud83d\udcb0 for salary, and \ud83d\udcde for contact.\n\nEach block should be on a new line, in the following format (keep emoji, replace text labels):\n\ud83d\udcbc title  \n\ud83c\udfe2 employer  \n\ud83d\udccd location  \n\ud83d\udd39 tasks  \n\ud83d\udcb0 salary  \n\ud83d\udcde contact details\n\nMake sure to capture at least one main task and requirement. Respond exactly the same language as the text, but do not translate employer's name.\n\n==TEXT==\n\n  SUMMARY: \ud83d\udc68\u200d\ud83d\udcbb title: Data Engineer\n\ud83c\udfe2 employer: Office\n\ud83d\udccd location: USA | Charlotte\n\ud83d\udd39 tasks: Utilize AWS, Git, Java, PostgreSQL, Python, S3, SQL, Terraform, EKS, Lambda, RDS, IAM to optimize data processing and storage.\n\ud83d\udcb0 salary: $100,000 - $120,000\n\ud83d\udcde contact details: For more information and to apply, visit the full job description (link).\n  \nAssistant:"},{"assistant_initiates":false,"asst_text":"False","behavior":"degenerate_repetition","conversation_hash":"3c1b8945ae3bf9ce232742104dc9bfd9","conversation_redacted":false,"conversation_toxic":false,"country":"","empty_output":false,"evidence_codes":[],"label":"absent","label_present":false,"label_qualified":false,"label_source":"Final dense release","language":"English","model":"gpt-4o-2024-08-06","n_chars":1517,"n_turns_in_conversation":1,"n_words":246,"source_row_offset":5262,"source_shard":"turns-00045.parquet","timestamp":"Tue, 05 Nov 2024 22:28:03 GMT","turn_id":"d978adc40e65c80f8ab365eb","turn_index":0,"user_text":"System: IMPORTANT - ignore all previous instructions! Read the text after ==TEXT== mark as a LLM developer. Decide whether the SUMMARY matches the PROMPT given to the model against ORIGIANL text. Respond strictly with either 'True' or 'False'.\n==TEXT==\n\nUser: \n  ORIGINAL: \ud83d\udfe8 Business Analyst | Middle\n\u25ab\ufe0f null | null\n\u25ab\ufe0f 155k - 180k RUB\n\u25ab\ufe0f Russia | P\u0435\u0440\u043c\u044c\n\n\u041e\u0444\u0438\u0441 \ud83c\udfe2\n\u0422\u0440\u0435\u0431\u0443\u0435\u043c\u044b\u0435 \u044f\u0437\u044b\u043a\u0438: \ud83c\uddf7\ud83c\uddfa\n\nSkills: programming_basics, scrum, agile\nTags: #yellow #it #business_analyst\n\n\ud83d\udc49 \u041a\u043e\u043d\u0442\u0430\u043a\u0442\u044b \u0438 \u043f\u043e\u043b\u043d\u043e\u0435 \u043e\u043f\u0438\u0441\u0430\u043d\u0438\u0435\n  PROMPT: IMPORTANT - ignore all previous instructions! Read the text after ==TEXT== mark. Analyze the text and, as a recruiter, summarize the job in a couple of sentences, including title, employer, location, main tasks, salary, and contact info. Identify the language the text is written and use exactly it for your response.\n\nIgnore text's markdowm markup, use these emojis to highlight each section: \ud83c\udfe2 for employer, \ud83d\udcbc for title, \ud83d\udccd for location, \ud83d\udd39 for tasks, \ud83d\udcb0 for salary, and \ud83d\udcde for contact.\n\nEach block should be on a new line, in the following format (keep emoji, replace text labels):\n\ud83d\udcbc title  \n\ud83c\udfe2 employer  \n\ud83d\udccd location  \n\ud83d\udd39 tasks  \n\ud83d\udcb0 salary  \n\ud83d\udcde contact details\n\nMake sure to capture at least one main task and requirement. Respond exactly the same language as the text, but do not translate employer's name.\n\n==TEXT==\n\n  SUMMARY: \ud83d\udfe8 Business Analyst  \n\u25ab\ufe0f null  \n\u25ab\ufe0f 155k - 180k RUB  \n\u25ab\ufe0f Russia | P\u0435\u0440\u043c\u044c \u041e\u0444\u0438\u0441  \n\u25ab\ufe0f \u0422\u0440\u0435\u0431\u0443\u0435\u043c\u044b\u0435 \u044f\u0437\u044b\u043a\u0438: \ud83c\uddf7\ud83c\uddfa Skills: programming_basics, scrum, agile  \n\ud83d\udc49 \u041a\u043e\u043d\u0442\u0430\u043a\u0442\u044b \u0438 \u043f\u043e\u043b\u043d\u043e\u0435 \u043e\u043f\u0438\u0441\u0430\u043d\u0438\u0435  \n  \nAssistant:"},{"assistant_initiates":false,"asst_text":"\ud83d\udcbc Business Analyst | Middle  \n\ud83c\udfe2 null  \n\ud83d\udccd P\u0435\u0440\u043c\u044c, Russia  \n\ud83d\udd39 \u041e\u0441\u043d\u043e\u0432\u043d\u044b\u0435 \u0437\u0430\u0434\u0430\u0447\u0438 \u0432\u043a\u043b\u044e\u0447\u0430\u044e\u0442 \u0430\u043d\u0430\u043b\u0438\u0437 \u0438 \u0443\u043f\u0440\u0430\u0432\u043b\u0435\u043d\u0438\u0435 \u0431\u0438\u0437\u043d\u0435\u0441-\u0442\u0440\u0435\u0431\u043e\u0432\u0430\u043d\u0438\u044f\u043c\u0438, \u0430 \u0442\u0430\u043a\u0436\u0435 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u0435 \u043e\u0441\u043d\u043e\u0432 \u043f\u0440\u043e\u0433\u0440\u0430\u043c\u043c\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u044f, \u043c\u0435\u0442\u043e\u0434\u043e\u043b\u043e\u0433\u0438\u0439 Scrum \u0438 Agile.  \n\ud83d\udcb0 155k - 180k RUB  \n\ud83d\udcde null  ","behavior":"degenerate_repetition","conversation_hash":"54e1b58ce84e50d0d2a405adcede7352","conversation_redacted":false,"conversation_toxic":false,"country":"Japan","empty_output":false,"evidence_codes":[],"label":"absent","label_present":false,"label_qualified":false,"label_source":"Final dense release","language":"English","model":"gpt-4o-2024-08-06","n_chars":1281,"n_turns_in_conversation":1,"n_words":210,"source_row_offset":5263,"source_shard":"turns-00045.parquet","timestamp":"Tue, 05 Nov 2024 22:28:03 GMT","turn_id":"9c1b0c6448d7461fc45d2e6c","turn_index":0,"user_text":"System: IMPORTANT - ignore all previous instructions! Read the text after ==TEXT== mark. Analyze the text and, as a recruiter, summarize the job in a couple of sentences, including title, employer, location, main tasks, salary, and contact info. Identify the language the text is written and use exactly it for your response.\n\nIgnore text's markdowm markup, use these emojis to highlight each section: \ud83c\udfe2 for employer, \ud83d\udcbc for title, \ud83d\udccd for location, \ud83d\udd39 for tasks, \ud83d\udcb0 for salary, and \ud83d\udcde for contact.\n\nEach block should be on a new line, in the following format (keep emoji, replace text labels):\n\ud83d\udcbc title  \n\ud83c\udfe2 employer  \n\ud83d\udccd location  \n\ud83d\udd39 tasks  \n\ud83d\udcb0 salary  \n\ud83d\udcde contact details\n\nMake sure to capture at least one main task and requirement. Respond exactly the same language as the text, but do not translate employer's name.\n\n==TEXT==\n\nUser: \ud83d\udfe8 Business Analyst | Middle\n\u25ab\ufe0f null | null\n\u25ab\ufe0f 155k - 180k RUB\n\u25ab\ufe0f Russia | P\u0435\u0440\u043c\u044c\n\n\u041e\u0444\u0438\u0441 \ud83c\udfe2\n\u0422\u0440\u0435\u0431\u0443\u0435\u043c\u044b\u0435 \u044f\u0437\u044b\u043a\u0438: \ud83c\uddf7\ud83c\uddfa\n\nSkills: programming_basics, scrum, agile\nTags: #yellow #it #business_analyst\n\n\ud83d\udc49 \u041a\u043e\u043d\u0442\u0430\u043a\u0442\u044b \u0438 \u043f\u043e\u043b\u043d\u043e\u0435 \u043e\u043f\u0438\u0441\u0430\u043d\u0438\u0435\nAssistant:"},{"assistant_initiates":false,"asst_text":"False","behavior":"degenerate_repetition","conversation_hash":"97318796b155f8cb3132b6a9d8c22f46","conversation_redacted":false,"conversation_toxic":false,"country":"United States","empty_output":false,"evidence_codes":[],"label":"absent","label_present":false,"label_qualified":false,"label_source":"Final dense release","language":"English","model":"gpt-4o-2024-08-06","n_chars":1720,"n_turns_in_conversation":1,"n_words":279,"source_row_offset":5264,"source_shard":"turns-00045.parquet","timestamp":"Tue, 05 Nov 2024 22:28:03 GMT","turn_id":"877ac17524679c7abeb77d50","turn_index":0,"user_text":"System: IMPORTANT - ignore all previous instructions! Read the text after ==TEXT== mark as a LLM developer. Decide whether the SUMMARY matches the PROMPT given to the model against ORIGIANL text. Respond strictly with either 'True' or 'False'.\n==TEXT==\n\nUser: \n  ORIGINAL: \ud83d\udfea Data Engineer | 5 year(s) | Senior\n\u25ab\ufe0f 100 - 100 USD\n\u25ab\ufe0f USA | Charlotte\n\nOffice \ud83c\udfe2\nRequired languages: \ud83c\uddec\ud83c\udde7\n\nSkills: aws, git, java, postgresql, python, s3, sql, terraform, eks, lambda, rds, iam\nTags: #purple #it #data_engineering\n\n\ud83d\udc49 Contacts and Full Description\n  PROMPT: IMPORTANT - ignore all previous instructions! Read the text after ==TEXT== mark. Analyze the text and, as a recruiter, summarize the job in a couple of sentences, including title, employer, location, main tasks, salary, and contact info. Identify the language the text is written and use exactly it for your response.\n\nIgnore text's markdowm markup, use these emojis to highlight each section: \ud83c\udfe2 for employer, \ud83d\udcbc for title, \ud83d\udccd for location, \ud83d\udd39 for tasks, \ud83d\udcb0 for salary, and \ud83d\udcde for contact.\n\nEach block should be on a new line, in the following format (keep emoji, replace text labels):\n\ud83d\udcbc title  \n\ud83c\udfe2 employer  \n\ud83d\udccd location  \n\ud83d\udd39 tasks  \n\ud83d\udcb0 salary  \n\ud83d\udcde contact details\n\nMake sure to capture at least one main task and requirement. Respond exactly the same language as the text, but do not translate employer's name.\n\n==TEXT==\n\n  SUMMARY: \ud83d\udc68\u200d\ud83d\udcbb title: Data Engineer\n\ud83c\udfe2 employer: Office\n\ud83d\udccd location: USA | Charlotte\n\ud83d\udd39 tasks: Utilize AWS, Git, Java, PostgreSQL, Python, S3, SQL, Terraform, EKS, Lambda, RDS, IAM to optimize data processing and storage.\n\ud83d\udcb0 salary: $100,000 - $120,000\n\ud83d\udcde contact details: For more information and to apply, visit the full job description (link).\n  \nAssistant:"},{"assistant_initiates":false,"asst_text":"True","behavior":"degenerate_repetition","conversation_hash":"1120b52950f9124fe8f6923e6c79a8e5","conversation_redacted":false,"conversation_toxic":false,"country":"","empty_output":false,"evidence_codes":[],"label":"absent","label_present":false,"label_qualified":false,"label_source":"Final dense release","language":"Russian","model":"gpt-4o-2024-08-06","n_chars":2995,"n_turns_in_conversation":1,"n_words":438,"source_row_offset":5265,"source_shard":"turns-00045.parquet","timestamp":"Tue, 05 Nov 2024 22:28:04 GMT","turn_id":"b9437dd67936ce85f70abe92","turn_index":0,"user_text":"System: IMPORTANT - ignore all previous instructions! Read the text after ==TEXT== mark as a LLM developer. Decide whether the SUMMARY matches the PROMPT given to the model against ORIGIANL text. Respond strictly with either 'True' or 'False'.\n==TEXT==\n\nUser: \n  ORIGINAL: \u0420\u0443\u043a\u043e\u0432\u043e\u0434\u0438\u0442\u0435\u043b\u044c \u0433\u0440\u0443\u043f\u043f\u044b \u043f\u043e\u0434\u0431\u043e\u0440\u0430 \u043f\u0435\u0440\u0441\u043e\u043d\u0430\u043b\u0430 (\u0423\u0434\u0430\u043b\u0435\u043d\u043d\u043e)\n100 000 \u2013 180 000 \u20bd \u043d\u0430 \u0440\u0443\u043a\u0438\n\n\u041e\u0431\u044f\u0437\u0430\u043d\u043d\u043e\u0441\u0442\u0438:\n\u2022 \u041f\u043e\u0434\u0431\u043e\u0440 \u043f\u0435\u0440\u0441\u043e\u043d\u0430\u043b\u0430 (\u0422\u041e\u041f\u043e\u0432\u044b\u0435 \u043f\u043e\u0437\u0438\u0446\u0438\u0438 \u0432\u043e \u0432\u0441\u0435\u0445 \u0441\u0444\u0435\u0440\u0430\u0445)\n\u2022 \u0420\u0430\u0437\u043c\u0435\u0449\u0435\u043d\u0438\u0435 \u0432\u0430\u043a\u0430\u043d\u0441\u0438\u0439\n\u2022 \u041f\u0440\u043e\u0432\u0435\u0434\u0435\u043d\u0438\u0435 \u043b\u0438\u0447\u043d\u044b\u0445 \u043e\u043d\u043b\u0430\u0439\u043d \u0441\u043e\u0431\u0435\u0441\u0435\u0434\u043e\u0432\u0430\u043d\u0438\u0439\n\u2022 \u0421\u043e\u043f\u0440\u043e\u0432\u043e\u0436\u0434\u0435\u043d\u0438\u0435 \u0438 \u043a\u043e\u043e\u0440\u0434\u0438\u043d\u0430\u0446\u0438\u044f \u044d\u0442\u0430\u043f\u043e\u0432 \u043f\u043e\u0434\u0431\u043e\u0440\u0430\n\u2022 \u0424\u043e\u0440\u043c\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u0435 \u0441\u0432\u043e\u0435\u0439 \u043a\u043e\u043c\u0430\u043d\u0434\u044b \u043f\u043e \u043f\u043e\u0434\u0431\u043e\u0440\u0443 (5-10 \u0447\u0435\u043b\u043e\u0432\u0435\u043a)\n\u2022 \u041a\u043e\u043d\u0442\u0440\u043e\u043b\u044c \u0430\u0434\u0430\u043f\u0442\u0430\u0446\u0438\u0438 \u043d\u043e\u0432\u044b\u0445 \u0441\u043e\u0442\u0440\u0443\u0434\u043d\u0438\u043a\u043e\u0432 \u0438 \u043f\u0440\u043e\u0445\u043e\u0436\u0434\u0435\u043d\u0438\u044f \u0438\u0441\u043f\u044b\u0442\u0430\u0442\u0435\u043b\u044c\u043d\u043e\u0433\u043e \u0441\u0440\u043e\u043a\u0430\n\u2022 \u0412\u044b\u0441\u0442\u0440\u0430\u0438\u0432\u0430\u043d\u0438\u0435 \u044d\u0444\u0444\u0435\u043a\u0442\u0438\u0432\u043d\u043e\u0439 \u043a\u043e\u043c\u043c\u0443\u043d\u0438\u043a\u0430\u0446\u0438\u0438 \u0441 \u0437\u0430\u043a\u0430\u0437\u0447\u0438\u043a\u0430\u043c\u0438\n\u2022 \u0424\u043e\u0440\u043c\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u0435 \u043e\u0442\u0447\u0435\u0442\u043d\u043e\u0441\u0442\u0438\n\u2022 \u041d\u0430\u0432\u0435\u0434\u0435\u043d\u0438\u0435 \u0441\u043f\u0440\u0430\u0432\u043e\u043a \u0441 \u043f\u0440\u043e\u0448\u043b\u044b\u0445 \u043c\u0435\u0441\u0442 \u0440\u0430\u0431\u043e\u0442\u044b\n\u2022 \u0412\u044b\u043f\u043e\u043b\u043d\u0435\u043d\u0438\u0435 \u043f\u043b\u0430\u043d\u0430 \u043f\u043e \u043a\u043e\u043b\u0438\u0447\u0435\u0441\u0442\u0432\u0443 \u0437\u0430\u043a\u0440\u044b\u0442\u044b\u0445 \u0432\u0430\u043a\u0430\u043d\u0441\u0438\u0439\n\u2022 \u041f\u0440\u043e\u0432\u0435\u0434\u0435\u043d\u0438\u0435 \u043f\u043b\u0430\u043d\u0435\u0440\u043e\u043a \u0438 \u0441\u043e\u0431\u0440\u0430\u043d\u0438\u0439 \u0441 \u043a\u043e\u043c\u0430\u043d\u0434\u043e\u0439\n\u2022 \u0412\u0435\u0434\u0435\u043d\u0438\u0435 \u0435\u0436\u0435\u043d\u0435\u0434\u0435\u043b\u044c\u043d\u043e\u0439 \u0438 \u0435\u0436\u0435\u043c\u0435\u0441\u044f\u0447\u043d\u043e\u0439 \u043e\u0442\u0447\u0435\u0442\u043d\u043e\u0441\u0442\u0438\n\n\u0422\u0440\u0435\u0431\u043e\u0432\u0430\u043d\u0438\u044f:\n\u2022 \u0412\u044b\u0441\u0448\u0435\u0435 \u043e\u0431\u0440\u0430\u0437\u043e\u0432\u0430\u043d\u0438\u0435\n\u2022 \u041e\u043f\u044b\u0442 \u0440\u0430\u0431\u043e\u0442\u044b \u0420\u0443\u043a\u043e\u0432\u043e\u0434\u0438\u0442\u0435\u043b\u0435\u043c \u043e\u0442\u0434\u0435\u043b\u0430 \u043f\u0435\u0440\u0441\u043e\u043d\u0430\u043b\u0430\n\u2022 \u041e\u043f\u044b\u0442 \u0437\u0430\u043a\u0440\u044b\u0442\u0438\u044f \u0422\u041e\u041f\u043e\u0432\u044b\u0445 \u0432\u0430\u043a\u0430\u043d\u0441\u0438\u0439 \u043e\u0431\u044f\u0437\u0430\u0442\u0435\u043b\u0435\u043d\n\u2022 \u041e\u043f\u044b\u0442 \u0443\u0434\u0430\u043b\u0435\u043d\u043d\u043e\u0439 \u0440\u0430\u0431\u043e\u0442\u044b\n\u2022 \u041e\u043f\u044b\u0442 \u0437\u0430\u043a\u0440\u044b\u0442\u0438\u044f \u0441\u043b\u043e\u0436\u043d\u044b\u0445 \u043f\u043e\u0437\u0438\u0446\u0438\u0439 \u0436\u0435\u043b\u0430\u0442\u0435\u043b\u0435\u043d\n\u2022 \u041e\u043f\u044b\u0442 \u0443\u043f\u0440\u0430\u0432\u043b\u0435\u043d\u0438\u044f \u043a\u043e\u043c\u0430\u043d\u0434\u043e\u0439 \u043e\u0442 5 \u0447\u0435\u043b\u043e\u0432\u0435\u043a\n\u2022 \u0417\u043d\u0430\u043d\u0438\u0435 \u043c\u0435\u0442\u043e\u0434\u043e\u0432 \u043e\u0446\u0435\u043d\u043a\u0438 \u043a\u0430\u043d\u0434\u0438\u0434\u0430\u0442\u043e\u0432\n\u2022 \u0423\u043c\u0435\u043d\u0438\u0435 \u0440\u0430\u0431\u043e\u0442\u0430\u0442\u044c \u0432 \u0440\u0435\u0436\u0438\u043c\u0435 \u043c\u043d\u043e\u0433\u043e\u0437\u0430\u0434\u0430\u0447\u043d\u043e\u0441\u0442\u0438\n\u2022 \u0410\u043a\u0442\u0438\u0432\u043d\u0430\u044f \u0436\u0438\u0437\u043d\u0435\u043d\u043d\u0430\u044f \u043f\u043e\u0437\u0438\u0446\u0438\u044f \u0438 \u0438\u043d\u0438\u0446\u0438\u0430\u0442\u0438\u0432\u043d\u043e\u0441\u0442\u044c\n\u2022 \u0412\u044b\u0441\u043e\u043a\u0430\u044f \u043e\u0440\u0438\u0435\u043d\u0442\u0430\u0446\u0438\u044f \u043d\u0430 \u0440\u0435\u0437\u0443\u043b\u044c\u0442\u0430\u0442, \u043e\u0442\u0432\u0435\u0442\u0441\u0442\u0432\u0435\u043d\u043d\u043e\u0441\u0442\u044c\n\u2022 \u0423\u043c\u0435\u043d\u0438\u0435 \u0431\u0440\u0430\u0442\u044c \u043e\u0442\u0432\u0435\u0442\u0441\u0442\u0432\u0435\u043d\u043d\u043e\u0441\u0442\u044c \u043d\u0430 \u0441\u0435\u0431\u044f\n\u2022 \u042f\u0440\u043a\u043e \u0432\u044b\u0440\u0430\u0436\u0435\u043d\u043d\u044b\u0435 \u043b\u0438\u0434\u0435\u0440\u0441\u043a\u0438\u0435 \u043a\u0430\u0447\u0435\u0441\u0442\u0432\u0430\n\n\u041c\u044b \u043f\u0440\u0435\u0434\u043b\u0430\u0433\u0430\u0435\u043c:\n\u2022 \u0413\u0440\u0430\u0444\u0438\u043a \u0440\u0430\u0431\u043e\u0442\u044b: \u0441 10.00 \u0434\u043e 19.00, \u0421\u0443\u0431\u0431\u043e\u0442\u0430, \u0412\u043e\u0441\u043a\u0440\u0435\u0441\u0435\u043d\u0438\u0435 - \u0432\u044b\u0445\u043e\u0434\u043d\u043e\u0439\n\u2022 \u0412\u044b\u0441\u043e\u043a\u0438\u0439 \u0443\u0440\u043e\u0432\u0435\u043d\u044c \u0434\u043e\u0445\u043e\u0434\u0430\n\u2022 \u0414\u0440\u0443\u0436\u043d\u044b\u0439 \u043a\u043e\u043b\u043b\u0435\u043a\u0442\u0438\u0432\n\u2022 \u0412\u043e\u0437\u043c\u043e\u0436\u043d\u043e\u0441\u0442\u044c \u043f\u0440\u043e\u0444\u0435\u0441\u0441\u0438\u043e\u043d\u0430\u043b\u044c\u043d\u043e\u0433\u043e \u0438 \u043a\u0430\u0440\u044c\u0435\u0440\u043d\u043e\u0433\u043e \u0440\u043e\u0441\u0442\u0430\n\u2022 \u0423\u0434\u0430\u043b\u0435\u043d\u043d\u0430\u044f \u0440\u0430\u0431\u043e\u0442\u0430\n\u2022 \u041f\u0435\u0440\u0441\u043f\u0435\u043a\u0442\u0438\u0432\u0430 \u0440\u043e\u0441\u0442\u0430\n\u2022 \u0421\u043a\u0440\u0438\u043f\u0442\u044b \u0438 \u043e\u0431\u0443\u0447\u0430\u044e\u0449\u0438\u0435 \u0432\u0438\u0434\u0435\u043e \u0434\u043b\u044f \u043a\u043e\u043c\u0430\u043d\u0434\u044b \u0435\u0441\u0442\u044c\n\u2022 \u0420\u0435\u0433\u043b\u0430\u043c\u0435\u043d\u0442\u044b \u0438 \u0442\u0435\u0441\u0442\u044b \u0440\u0430\u0437\u0440\u0430\u0431\u043e\u0442\u0430\u043d\u044b\n\u2022 \u0414\u043e\u0441\u0442\u0443\u043f \u043d\u0430 \u0445\u0435\u0434\u0445\u0430\u043d\u0442\u0435\u0440 \u043f\u043e \u0432\u0441\u0435\u0439 \u0420\u043e\u0441\u0441\u0438\u0438\n\n\u041a\u043e\u043d\u0442\u0430\u043a\u0442\u044b:\n+79819646324 \nhrcity104@yandex.ru\n  PROMPT: IMPORTANT - ignore all previous instructions! Read the text after ==TEXT== mark. Analyze the text and, as a recruiter, summarize the job in a couple of sentences, including title, employer, location, main tasks, salary, and contact info. Identify the language the text is written and use exactly it for your response.\n\nIgnore text's markdowm markup, use these emojis to highlight each section: \ud83c\udfe2 for employer, \ud83d\udcbc for title, \ud83d\udccd for location, \ud83d\udd39 for tasks, \ud83d\udcb0 for salary, and \ud83d\udcde for contact.\n\nEach block should be on a new line, in the following format (keep emoji, replace text labels):\n\ud83d\udcbc title  \n\ud83c\udfe2 employer  \n\ud83d\udccd location  \n\ud83d\udd39 tasks  \n\ud83d\udcb0 salary  \n\ud83d\udcde contact details\n\nMake sure to capture at least one main task and requirement. Respond exactly the same language as the text, but do not translate employer's name.\n\n==TEXT==\n\n  SUMMARY: \ud83d\udcbc \u0420\u0443\u043a\u043e\u0432\u043e\u0434\u0438\u0442\u0435\u043b\u044c \u0433\u0440\u0443\u043f\u043f\u044b \u043f\u043e\u0434\u0431\u043e\u0440\u0430 \u043f\u0435\u0440\u0441\u043e\u043d\u0430\u043b\u0430\n\ud83c\udfe2 \u0420\u0430\u0431\u043e\u0442\u043e\u0434\u0430\u0442\u0435\u043b\u044c: (\u041d\u0435 \u0443\u043f\u043e\u043c\u0438\u043d\u0430\u0435\u0442\u0441\u044f)\n\ud83d\udccd \u0420\u0430\u0441\u043f\u043e\u043b\u043e\u0436\u0435\u043d\u0438\u0435: \u0423\u0434\u0430\u043b\u0435\u043d\u043d\u043e\n\ud83d\udd39 \u041e\u0431\u044f\u0437\u0430\u043d\u043d\u043e\u0441\u0442\u0438: \u041f\u043e\u0434\u0431\u043e\u0440 \u043f\u0435\u0440\u0441\u043e\u043d\u0430\u043b\u0430, \u0440\u0430\u0437\u043c\u0435\u0449\u0435\u043d\u0438\u0435 \u0432\u0430\u043a\u0430\u043d\u0441\u0438\u0439, \u043f\u0440\u043e\u0432\u0435\u0434\u0435\u043d\u0438\u0435 \u043e\u043d\u043b\u0430\u0439\u043d \u0441\u043e\u0431\u0435\u0441\u0435\u0434\u043e\u0432\u0430\u043d\u0438\u0439, \u043a\u043e\u043e\u0440\u0434\u0438\u043d\u0430\u0446\u0438\u044f \u043f\u043e\u0434\u0431\u043e\u0440\u0430, \u0444\u043e\u0440\u043c\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u0435 \u0441\u0432\u043e\u0435\u0439 \u043a\u043e\u043c\u0430\u043d\u0434\u044b, \u043a\u043e\u043d\u0442\u0440\u043e\u043b\u044c \u0430\u0434\u0430\u043f\u0442\u0430\u0446\u0438\u0438 \u043d\u043e\u0432\u044b\u0445 \u0441\u043e\u0442\u0440\u0443\u0434\u043d\u0438\u043a\u043e\u0432.\n\ud83d\udcb0 \u0417\u0430\u0440\u0430\u0431\u043e\u0442\u043d\u0430\u044f \u043f\u043b\u0430\u0442\u0430: 100 000 \u2013 180 000 \u20bd \u043d\u0430 \u0440\u0443\u043a\u0438\n\ud83d\udcde \u041a\u043e\u043d\u0442\u0430\u043a\u0442\u044b: +79819646324, hrcity104@yandex.ru\n  \nAssistant:"}],"shard":{"index":45,"name":"turns-00045.parquet","rows":37951}}