metadata
task_categories:
- text-generation
- question-answering
language:
- en
HTD Scraped Datasets
Cleaned text chunks from Home Team Department (HTD) agency websites, processed into a consistent 8-column format for downstream tasks (QA pairs annotation, fine-tuning, etc.)
Schema
| Column | Type | Description |
|---|---|---|
chunk_text |
str | Cleaned text chunk (40-650 words) |
source_url |
str | Original page URL |
page_title |
str | Page title |
section_headers |
str | Section heading path |
heading_path |
str | Hierarchical path from site structure |
content_type |
str | guide, press_release, faq, service_index, or event |
last_updated |
str | Article date or scrape date |
word_count |
int | Word count of chunk_text |
Datasets
| Agency | File | Rows | Source |
|---|---|---|---|
| HTX (Home Team Science & Technology Agency) | htx_dataset_cleaned.parquet |
59 | htx.gov.sg |
| MHA (Ministry of Home Affairs) | mha_dataset_cleaned.parquet |
6,149 | mha.gov.sg |
| SPF (Singapore Police Force) | spf_dataset_cleaned.parquet |
6,191 | police.gov.sg |
| CNB (Central Narcotics Bureau) | cnb_dataset_cleaned_060526.csv |
518 | cnb.gov.sg |
| ICA (Immigration & Checkpoints Authority) | ica_dataset_cleaned_060526.csv |
896 | ica.gov.sg |
| SPS (Singapore Prison Service) | sps_filtered_qa_utf8.csv |
766 | sps.gov.sg |
Usage
import pandas as pd
# Load a single dataset
df = pd.read_parquet("htx_dataset_cleaned.parquet")
print(df.head())
Or load via HuggingFace datasets:
from datasets import load_dataset
# Load a specific config
ds = load_dataset("ops-tuned-llm/unlabelled-data")