File size: 30,520 Bytes
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size_categories: n<1K
dataset_info:
- config_name: easy_keywords
features:
- name: Sector
dtype: string
- name: Track
dtype: string
- name: Job Role
dtype: string
- name: anchor
dtype: string
- name: Performance Expectation
dtype: string
- name: positive
dtype: string
- name: negative
dtype: string
- name: distilabel_metadata
struct:
- name: raw_input_easy_keywords
list:
- name: content
dtype: string
- name: role
dtype: string
- name: raw_output_easy_keywords
dtype: string
- name: statistics_easy_keywords
struct:
- name: input_tokens
dtype: int64
- name: output_tokens
dtype: int64
- name: model_name
dtype: string
splits:
- name: train
num_bytes: 7764057
num_examples: 1885
download_size: 2073415
dataset_size: 7764057
- config_name: easy_triplets
features:
- name: Sector
dtype: string
- name: Track
dtype: string
- name: Job Role
dtype: string
- name: anchor
dtype: string
- name: Performance Expectation
dtype: string
- name: positive
dtype: string
- name: negative
dtype: string
- name: distilabel_metadata
struct:
- name: raw_input_easy_triplets
list:
- name: content
dtype: string
- name: role
dtype: string
- name: raw_output_easy_triplets
dtype: string
- name: statistics_easy_triplets
struct:
- name: input_tokens
dtype: int64
- name: output_tokens
dtype: int64
- name: model_name
dtype: string
splits:
- name: train
num_bytes: 15428132
num_examples: 1885
download_size: 4409729
dataset_size: 15428132
- config_name: hard_keywords
features:
- name: Sector
dtype: string
- name: Track
dtype: string
- name: Job Role
dtype: string
- name: anchor
dtype: string
- name: Performance Expectation
dtype: string
- name: positive
dtype: string
- name: negative
dtype: string
- name: distilabel_metadata
struct:
- name: raw_input_hard_keywords
list:
- name: content
dtype: string
- name: role
dtype: string
- name: raw_output_hard_keywords
dtype: string
- name: statistics_hard_keywords
struct:
- name: input_tokens
dtype: int64
- name: output_tokens
dtype: int64
- name: model_name
dtype: string
splits:
- name: train
num_bytes: 8409152
num_examples: 1885
download_size: 2148912
dataset_size: 8409152
- config_name: hard_triplets
features:
- name: Sector
dtype: string
- name: Track
dtype: string
- name: Job Role
dtype: string
- name: anchor
dtype: string
- name: Performance Expectation
dtype: string
- name: positive
dtype: string
- name: negative
dtype: string
- name: distilabel_metadata
struct:
- name: raw_input_hard_triplets
list:
- name: content
dtype: string
- name: role
dtype: string
- name: raw_output_hard_triplets
dtype: string
- name: statistics_hard_triplets
struct:
- name: input_tokens
dtype: int64
- name: output_tokens
dtype: int64
- name: model_name
dtype: string
splits:
- name: train
num_bytes: 90077
num_examples: 10
download_size: 66784
dataset_size: 90077
configs:
- config_name: easy_keywords
data_files:
- split: train
path: easy_keywords/train-*
- config_name: easy_triplets
data_files:
- split: train
path: easy_triplets/train-*
- config_name: hard_keywords
data_files:
- split: train
path: hard_keywords/train-*
- config_name: hard_triplets
data_files:
- split: train
path: hard_triplets/train-*
tags:
- synthetic
- distilabel
- rlaif
---
<p align="left">
<a href="https://github.com/argilla-io/distilabel">
<img src="https://raw.githubusercontent.com/argilla-io/distilabel/main/docs/assets/distilabel-badge-light.png" alt="Built with Distilabel" width="200" height="32"/>
</a>
</p>
# Dataset Card for ssf-dataset-v8
This dataset has been created with [distilabel](https://distilabel.argilla.io/).
## Dataset Summary
This dataset contains a `pipeline.yaml` which can be used to reproduce the pipeline that generated it in distilabel using the `distilabel` CLI:
```console
distilabel pipeline run --config "https://huggingface.co/datasets/Fatin757/ssf-dataset-v8/raw/main/pipeline.yaml"
```
or explore the configuration:
```console
distilabel pipeline info --config "https://huggingface.co/datasets/Fatin757/ssf-dataset-v8/raw/main/pipeline.yaml"
```
## Dataset structure
The examples have the following structure per configuration:
<details><summary> Configuration: hard_keywords </summary><hr>
```json
{
"Job Role": "Audit Associate / Audit Assistant Associate",
"Performance Expectation": "In accordance with: Singapore Standards on Auditing, Ethics Pronouncements in Singapore, Singapore Companies Act, and Singapore Financial Reporting Standards",
"Sector": "Accountancy",
"Track": "Assurance",
"anchor": "The Audit Associate/Audit Assistant Associate undertakes specific stages of audit work under supervision. He/She begins to appreciate the underlying principles behind the tasks assigned to him as part of the audit plan. He is also able to make adjustments to the application of skills to improve the work tasks or solve non-complex issues. The Audit Associate/Audit Assistant Associate operates in a structured work environment. He is able to build relationships, work in a team and identify ethical issues with reference to the code of professional conduct and ethics. He is able to select and apply from a range of known solutions to familiar problems and takes responsibility for his own learning and performance. He is a trustworthy and meticulous individual.",
"distilabel_metadata": {
"raw_input_hard_keywords": [
{
"content": "Your task is to generate a positive and a negative sentence given an anchor sentence. Take into account the context given. The positive sentence has to be a query for the anchor sentence, while the negative sentence is a \u0027hard negative\u0027 that meets the following criteria:\n- Uses similar keywords or phrases as the anchor sentence\n- Has a similar grammatical structure or syntax\n- Is not related to the anchor sentence, but could be mistaken for it\nTry to create a negative sentence that would be challenging for a model to distinguish from the positive sentence. You must output only two new sections: `## Positive` and `## Negative`.",
"role": "system"
},
{
"content": "## Context\n\n\nThe text below is a job description from the Singapore SkillsFuture Framework. Your task is to generate two things:\n1. A list of key skills for the job (the positive).\n2. A list of unrelated skills (the easy negative).\n\nAn **easy negative** is a set of keywords that is completely unrelated to the job description and its industry. It should be easy for the model to distinguish and serves to give the model a clear sense of what is definitively irrelevant.\n\nExample:\nJob Role: \"Network Engineer\"\nPositive Keywords: \"Network administration, Cisco, firewall management, VPN\"\nEasy Negative Keywords: \"Retail inventory management, customer service, cash handling, visual merchandising\"\n\n\n## Anchor\n\nThe Audit Associate/Audit Assistant Associate undertakes specific stages of audit work under supervision. He/She begins to appreciate the underlying principles behind the tasks assigned to him as part of the audit plan. He is also able to make adjustments to the application of skills to improve the work tasks or solve non-complex issues. The Audit Associate/Audit Assistant Associate operates in a structured work environment. He is able to build relationships, work in a team and identify ethical issues with reference to the code of professional conduct and ethics. He is able to select and apply from a range of known solutions to familiar problems and takes responsibility for his own learning and performance. He is a trustworthy and meticulous individual.\n",
"role": "user"
}
],
"raw_output_hard_keywords": "## Positive\nAudit procedures, financial reporting, risk assessment, ethical compliance, teamwork, problem-solving, professional conduct, attention to detail, supervised audit tasks, performance improvement\n\n## Negative\nGraphic design, social media marketing, culinary arts, event planning, fashion styling, interior decorating, photography, creative writing, music production, sports coaching",
"statistics_hard_keywords": {
"input_tokens": 415,
"output_tokens": 66
}
},
"model_name": "gpt-4.1-mini",
"negative": "Graphic design, social media marketing, culinary arts, event planning, fashion styling, interior decorating, photography, creative writing, music production, sports coaching",
"positive": "Audit procedures, financial reporting, risk assessment, ethical compliance, teamwork, problem-solving, professional conduct, attention to detail, supervised audit tasks, performance improvement"
}
```
This subset can be loaded as:
```python
from datasets import load_dataset
ds = load_dataset("Fatin757/ssf-dataset-v8", "hard_keywords")
```
</details>
<details><summary> Configuration: easy_triplets </summary><hr>
```json
{
"Job Role": "Audit Associate / Audit Assistant Associate",
"Performance Expectation": "In accordance with: Singapore Standards on Auditing, Ethics Pronouncements in Singapore, Singapore Companies Act, and Singapore Financial Reporting Standards",
"Sector": "Accountancy",
"Track": "Assurance",
"anchor": "The Audit Associate/Audit Assistant Associate undertakes specific stages of audit work under supervision. He/She begins to appreciate the underlying principles behind the tasks assigned to him as part of the audit plan. He is also able to make adjustments to the application of skills to improve the work tasks or solve non-complex issues. The Audit Associate/Audit Assistant Associate operates in a structured work environment. He is able to build relationships, work in a team and identify ethical issues with reference to the code of professional conduct and ethics. He is able to select and apply from a range of known solutions to familiar problems and takes responsibility for his own learning and performance. He is a trustworthy and meticulous individual.",
"distilabel_metadata": {
"raw_input_easy_triplets": [
{
"content": "Your task is to generate a positive and a negative sentence given an anchor sentence. Take into account the context given. The positive sentence has to paraphrase the anchor sentence, while the negative sentence can use similar words but must not be related to the anchor sentence. You must output only two new sections: `## Positive` and `## Negative`.",
"role": "system"
},
{
"content": "## Context\n\n\n\n\n## Task Overview\nYou are tasked with generating realistic job descriptions based on Singapore SkillsFuture Framework job descriptions. Your goal is to create both positive and a few negative examples for training a retrieval model.\n\n## Input Format\nYou will receive a job description from the Singapore SkillsFuture Framework containing:\n- Job title (e.g., Audit Associate/Audit Assistant Associate)\n- Role responsibilities and duties\n- Work environment and supervision structure\n- Required skills and attributes\n- Professional conduct expectations\n\nThe text is a job description from the Singapore SkillsFuture Framework. Your task is to generate a realistic positive variation and a few easy negative variation.\n\nEasy negative is a job description and title that is completely irrelevant to the original job\u0027s industry, domain, or skills. It should be easy for the model to distinguish from the positive document.\n\nChoose from these strategies for easy negatives:\n1. Completely different industry (e.g., IT vs. Retail).\n2. Unrelated skills and responsibilities.\n3. Completely different job function (e.g., Software Engineering vs. Human Resources).\n\nExample:\nJob Role: \"Data Analyst\"\n\nPositive: \"As a Data Analyst, you will interpret data and analyze results using statistical techniques. You will work to develop and implement data collection systems and other strategies that optimize statistical efficiency and quality.\"\n\nEasy Negative : \"As a Retail Manager, you will be responsible for overseeing daily store operations, managing inventory, and training staff to provide excellent customer service.\"\n\n \"As a Human Resources Assistant, you will provide administrative support to the HR department, assist with recruitment and onboarding processes, and maintain employee records.\"\n\n \"As a Professional Chef, you will be responsible for managing kitchen staff, creating new menu items, and ensuring all dishes are prepared to the highest quality standards.\"\n\n\nMake sure, that there is a variety of easy negatives across the dataset, using different strategies as outlined above.\nMakesure to have a few negatives in one query like in the example given.\nThe query should always include the job role and start with \"The \u003cjob role\u003e\".\n\n\n## Anchor\n\nThe Audit Associate/Audit Assistant Associate undertakes specific stages of audit work under supervision. He/She begins to appreciate the underlying principles behind the tasks assigned to him as part of the audit plan. He is also able to make adjustments to the application of skills to improve the work tasks or solve non-complex issues. The Audit Associate/Audit Assistant Associate operates in a structured work environment. He is able to build relationships, work in a team and identify ethical issues with reference to the code of professional conduct and ethics. He is able to select and apply from a range of known solutions to familiar problems and takes responsibility for his own learning and performance. He is a trustworthy and meticulous individual.\n",
"role": "user"
}
],
"raw_output_easy_triplets": "## Positive\nThe Audit Assistant Associate performs designated audit tasks under guidance, gradually understanding the fundamental concepts behind the audit procedures. They adapt their skills to enhance task execution and resolve straightforward problems. Working within a well-organized environment, the Audit Assistant Associate collaborates effectively with team members, recognizes ethical considerations according to professional standards, and applies established solutions to routine issues. They take ownership of their development and maintain a high degree of reliability and attention to detail.\n\n## Negative\nThe Retail Store Supervisor manages daily store operations, oversees inventory control, and trains sales staff to deliver exceptional customer service. They work in a dynamic retail environment, focusing on meeting sales targets and ensuring customer satisfaction.\n\nThe Software Developer designs, develops, and tests software applications. They collaborate with cross-functional teams to create efficient, scalable code and troubleshoot technical issues, working primarily in an agile development setting.\n\nThe Human Resources Coordinator supports recruitment activities, assists with employee onboarding, and maintains personnel records. They ensure compliance with company policies and help facilitate employee engagement initiatives.",
"statistics_easy_triplets": {
"input_tokens": 630,
"output_tokens": 202
}
},
"model_name": "gpt-4.1-mini",
"negative": "The Retail Store Supervisor manages daily store operations, oversees inventory control, and trains sales staff to deliver exceptional customer service. They work in a dynamic retail environment, focusing on meeting sales targets and ensuring customer satisfaction.\n\nThe Software Developer designs, develops, and tests software applications. They collaborate with cross-functional teams to create efficient, scalable code and troubleshoot technical issues, working primarily in an agile development setting.\n\nThe Human Resources Coordinator supports recruitment activities, assists with employee onboarding, and maintains personnel records. They ensure compliance with company policies and help facilitate employee engagement initiatives.",
"positive": "The Audit Assistant Associate performs designated audit tasks under guidance, gradually understanding the fundamental concepts behind the audit procedures. They adapt their skills to enhance task execution and resolve straightforward problems. Working within a well-organized environment, the Audit Assistant Associate collaborates effectively with team members, recognizes ethical considerations according to professional standards, and applies established solutions to routine issues. They take ownership of their development and maintain a high degree of reliability and attention to detail."
}
```
This subset can be loaded as:
```python
from datasets import load_dataset
ds = load_dataset("Fatin757/ssf-dataset-v8", "easy_triplets")
```
</details>
<details><summary> Configuration: easy_keywords </summary><hr>
```json
{
"Job Role": "Audit Associate / Audit Assistant Associate",
"Performance Expectation": "In accordance with: Singapore Standards on Auditing, Ethics Pronouncements in Singapore, Singapore Companies Act, and Singapore Financial Reporting Standards",
"Sector": "Accountancy",
"Track": "Assurance",
"anchor": "The Audit Associate/Audit Assistant Associate undertakes specific stages of audit work under supervision. He/She begins to appreciate the underlying principles behind the tasks assigned to him as part of the audit plan. He is also able to make adjustments to the application of skills to improve the work tasks or solve non-complex issues. The Audit Associate/Audit Assistant Associate operates in a structured work environment. He is able to build relationships, work in a team and identify ethical issues with reference to the code of professional conduct and ethics. He is able to select and apply from a range of known solutions to familiar problems and takes responsibility for his own learning and performance. He is a trustworthy and meticulous individual.",
"distilabel_metadata": {
"raw_input_easy_keywords": [
{
"content": "Your task is to generate a positive and a negative sentence given an anchor sentence. Take into account the context given. The positive sentence has to be a query for the anchor sentence, while the negative sentence can use similar words but must not be related to the anchor sentence. You must output only two new sections: `## Positive` and `## Negative`.",
"role": "system"
},
{
"content": "## Context\n\n\nThe text below is a job description from the Singapore SkillsFuture Framework. Your task is to generate two things:\n1. A list of key skills for the job (the positive).\n2. A list of unrelated skills (the easy negative).\n\nAn **easy negative** is a set of keywords that is completely unrelated to the job description and its industry. It should be easy for the model to distinguish and serves to give the model a clear sense of what is definitively irrelevant.\n\nExample:\nJob Role: \"Network Engineer\"\nPositive Keywords: \"Network administration, Cisco, firewall management, VPN\"\nEasy Negative Keywords: \"Retail inventory management, customer service, cash handling, visual merchandising\"\n\n\n## Anchor\n\nThe Audit Associate/Audit Assistant Associate undertakes specific stages of audit work under supervision. He/She begins to appreciate the underlying principles behind the tasks assigned to him as part of the audit plan. He is also able to make adjustments to the application of skills to improve the work tasks or solve non-complex issues. The Audit Associate/Audit Assistant Associate operates in a structured work environment. He is able to build relationships, work in a team and identify ethical issues with reference to the code of professional conduct and ethics. He is able to select and apply from a range of known solutions to familiar problems and takes responsibility for his own learning and performance. He is a trustworthy and meticulous individual.\n",
"role": "user"
}
],
"raw_output_easy_keywords": "## Positive\nAudit procedures, financial reporting, risk assessment, ethical compliance, teamwork, problem solving, professional conduct, attention to detail, learning agility, audit planning\n\n## Negative\nGraphic design, culinary arts, landscape gardening, fashion merchandising, veterinary care, music production, automotive repair, event planning",
"statistics_easy_keywords": {
"input_tokens": 361,
"output_tokens": 59
}
},
"model_name": "gpt-4.1-mini",
"negative": "Graphic design, culinary arts, landscape gardening, fashion merchandising, veterinary care, music production, automotive repair, event planning",
"positive": "Audit procedures, financial reporting, risk assessment, ethical compliance, teamwork, problem solving, professional conduct, attention to detail, learning agility, audit planning"
}
```
This subset can be loaded as:
```python
from datasets import load_dataset
ds = load_dataset("Fatin757/ssf-dataset-v8", "easy_keywords")
```
</details>
<details><summary> Configuration: hard_triplets </summary><hr>
```json
{
"Job Role": "Audit Associate / Audit Assistant Associate",
"Performance Expectation": "In accordance with: Singapore Standards on Auditing, Ethics Pronouncements in Singapore, Singapore Companies Act, and Singapore Financial Reporting Standards",
"Sector": "Accountancy",
"Track": "Assurance",
"anchor": "The Audit Associate/Audit Assistant Associate undertakes specific stages of audit work under supervision. He/She begins to appreciate the underlying principles behind the tasks assigned to him as part of the audit plan. He is also able to make adjustments to the application of skills to improve the work tasks or solve non-complex issues. The Audit Associate/Audit Assistant Associate operates in a structured work environment. He is able to build relationships, work in a team and identify ethical issues with reference to the code of professional conduct and ethics. He is able to select and apply from a range of known solutions to familiar problems and takes responsibility for his own learning and performance. He is a trustworthy and meticulous individual.",
"distilabel_metadata": {
"raw_input_hard_triplets": [
{
"content": "Your task is to generate a positive and a negative sentence given an anchor sentence. Take into account the context given. The positive sentence has to paraphrase the anchor sentence, while the negative sentence is a \u0027hard negative\u0027 that meets the following criteria:\n- Uses similar keywords or phrases as the anchor sentence\n- Has a similar grammatical structure or syntax\n- Is not related to the anchor sentence, but could be mistaken for it\nTry to create a negative sentence that would be challenging for a model to distinguish from the positive sentence. You must output only two new sections: `## Positive` and `## Negative`.",
"role": "system"
},
{
"content": "## Context\n\n\n\n## Task Overview\nYou are tasked with generating realistic job descriptions based on Singapore SkillsFuture Framework job descriptions. Your goal is to create both positive and a few negative examples for training a retrieval model.\n\n## Input Format\nYou will receive a job description from the Singapore SkillsFuture Framework containing:\n- Job title (e.g., Audit Associate/Audit Assistant Associate)\n- Role responsibilities and duties\n- Work environment and supervision structure\n- Required skills and attributes\n- Professional conduct expectations\n\nThe text is a job description from the Singapore SkillsFuture Framework. Your task is to generate a realistic positive variation and a few hard negative variation.\n\n\nHard negative is a job description that is similar in some ways but is ultimately incorrect for the given job. It must not be a simple paraphrase of a different, unrelated job.\n\nChoose from these strategies for hard negatives:\n1. **Different seniority level:** (e.g., Senior vs. Junior)\n2. **Different function:** (e.g., Business Valuation vs. Risk Management)\n3. **Different technology stack:** (e.g., Python/AWS vs. Scala/Azure for a Data Engineer role)\n4. **Different job title, same responsibilities:** (e.g., \"Web Developer\" vs. \"Frontend Engineer\")\n5. **Different industry jargon:** (e.g., \"Project Manager\" in Tech vs. \"Project Manager\" in Construction)\n6. **Broad vs. specialized role:** (e.g., a \"Data Scientist\" role for a \"Machine Learning Engineer\" positive)\n\nExample:\nJob Role: \"Data Analyst\"\nPositive: \"As a Data Analyst, you will interpret data and analyze results using statistical techniques. You will work to develop and implement data collection systems and other strategies that optimize statistical efficiency and quality.\"\n\n\nNegative: \"As a Senior Data Analyst, you will lead a team of junior analysts, manage end-to-end data projects, and present insights to key stakeholders to drive business strategy.\"\n\n \"As a Financial Analyst, you will analyze financial data to provide insights into business performance and support strategic decision-making.\"\n\n \"As a Healthcare Data Analyst, you will manage electronic health records and assist in clinical research data analysis.\"\n\n\nMake sure to mix a few strategies in one negative query. you could also use different strategies that is not mentioned above as long as it is a hard negative.\nMakesure to have a few negatives in one query like in the example given and make a new line for each new query.\nThe Job description of the negatives should give the real job description to a real job title.\nThe query should always include the job role and start with \"The \u003cjob role\u003e\".\n\n\n## Anchor\n\nThe Audit Associate/Audit Assistant Associate undertakes specific stages of audit work under supervision. He/She begins to appreciate the underlying principles behind the tasks assigned to him as part of the audit plan. He is also able to make adjustments to the application of skills to improve the work tasks or solve non-complex issues. The Audit Associate/Audit Assistant Associate operates in a structured work environment. He is able to build relationships, work in a team and identify ethical issues with reference to the code of professional conduct and ethics. He is able to select and apply from a range of known solutions to familiar problems and takes responsibility for his own learning and performance. He is a trustworthy and meticulous individual.\n",
"role": "user"
}
],
"raw_output_hard_triplets": "## Positive\nThe Audit Associate/Audit Assistant Associate performs designated audit tasks under guidance, developing an understanding of the principles behind the audit procedures. They adapt their skills to enhance work quality and resolve straightforward issues. Working within a structured environment, they collaborate effectively with team members, recognize ethical considerations in line with professional standards, and apply established solutions to routine problems. They take ownership of their learning and work performance, demonstrating reliability and attention to detail.\n\n## Negative\nThe Senior Audit Associate leads audit engagements, manages complex audit issues, and mentors junior team members while ensuring compliance with advanced auditing standards. \nThe Risk Management Associate conducts risk assessments, develops mitigation strategies, and monitors organizational risk exposure across various departments. \nThe Audit Associate specializing in IT audits performs audit procedures focused on information systems, evaluates IT controls, and reports on cybersecurity compliance within a technology-driven environment. \nThe Audit Assistant in the financial advisory sector supports financial compliance reviews, prepares client portfolios for audit, and assists in regulatory reporting under minimal supervision.",
"statistics_hard_triplets": {
"input_tokens": 806,
"output_tokens": 199
}
},
"model_name": "gpt-4.1-mini",
"negative": "The Senior Audit Associate leads audit engagements, manages complex audit issues, and mentors junior team members while ensuring compliance with advanced auditing standards. \nThe Risk Management Associate conducts risk assessments, develops mitigation strategies, and monitors organizational risk exposure across various departments. \nThe Audit Associate specializing in IT audits performs audit procedures focused on information systems, evaluates IT controls, and reports on cybersecurity compliance within a technology-driven environment. \nThe Audit Assistant in the financial advisory sector supports financial compliance reviews, prepares client portfolios for audit, and assists in regulatory reporting under minimal supervision.",
"positive": "The Audit Associate/Audit Assistant Associate performs designated audit tasks under guidance, developing an understanding of the principles behind the audit procedures. They adapt their skills to enhance work quality and resolve straightforward issues. Working within a structured environment, they collaborate effectively with team members, recognize ethical considerations in line with professional standards, and apply established solutions to routine problems. They take ownership of their learning and work performance, demonstrating reliability and attention to detail."
}
```
This subset can be loaded as:
```python
from datasets import load_dataset
ds = load_dataset("Fatin757/ssf-dataset-v8", "hard_triplets")
```
</details>
|