him1411/edgar10q-dataset
EDGAR10-Q Dataset and implementation of the paper Context NER
This project provides a dataset built from publicly available Quarterly and Yearly Reports (10-Q/K documents) of listed companies on the SEC. It takes raw text sentences from these financial reports and extracts specific numerical or temporal entities (like '4,66,62,179' or 'nine years'), along with their corresponding financial context (e.g., 'Shares Outstanding' or 'Intangible assets'). Financial analysts, quantitative researchers, and compliance officers can use this to train or evaluate models for automated information extraction from financial disclosures.
No commits in the last 6 months.
Use this if you need a large, pre-processed dataset of financial disclosures with key entities and their contexts labeled, specifically for training or evaluating natural language processing models.
Not ideal if you are looking for a tool to perform real-time financial analysis or extract data from custom documents without prior model training.
Stars
17
Forks
7
Language
Python
License
MIT
Category
Last pushed
Sep 29, 2023
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/nlp/him1411/edgar10q-dataset"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.