Recognize Financial Entities - Live Demos & Notebooks
Named Entity Recognition on Financial Annual Reports
This demo showcases how you can apply NER models to extract financial entities from annual reports, as Expenses, Loses, Profit declines or increases, etc. (...)
Extract 139 financial entities from 10-Q
This demo shows how to extract 139 financial entities on US Security Exchange Commission 10-Q filings. (...)
Extract public companies key data from 10-K filings
This demo uses Name Entity Recognition to extract information like Company Name, Trading symbols, Stock markets, Addresses, Phones, Stock types and values, IRS, CFN, etc. from the first page of 10-K filings. (...)
Extract People, Roles, Dates and Organisations
This model extracts People and their Roles, Organizations and Dates from financial documents. (...)
Extract Trading Symbols / Tickers
This demo shows how to extract ticker alias from financial texts. (...)
Extract Roles, Job Positions and Titles
This demo shows how to extract Roles, Job Positions in Resumes and People’s Titles from documents. (...)
Extract Organizations and Products
This model uses Name Entity Recognition to extract ORG (Organization names) and PRODUCT (Product names). (...)
Identify Companies and their aliases in financial texts
This model uses Entity Recognition to identify ORG (Companies), their ALIAS (other names the company uses in financial reports) and company PRODUCTS. (...)
Extract economic and social entities in Russian
This model extracts entities such as ECO (economics), SOC (social) for economic and social entities, institutions of events, and also quantifiers (QUA), metrics (MET), etc. from Government documents in Russian. (...)
Name Entity Recognition on financial texts
This demo shows how you can extract the standard four entities (ORG, PER, LOC, MISC) from financial documents. (...)
Financial Zero-Shot Named Entity Recognition
This demo shows how you can use prompts in the form of questions, to carry our Named Entity Recognition without any pretrained dataset. You will find a table with the example questions (prompts) used for the different labels on the side menu. (...)
Capital Calls NER
This demo shows how to extract financial and contact entities from Capital Call Notices. (...)
Detect financial entities in Chinese text
This demo uses Name Entity Recognition to extract information like company names, holding shares, trading prices, dates, etc. from Chinese texts. (...)
Extract Entities from Responsibility and ESG Reports
This demo shows how to extract up to 20 quantifiable entities, including KPI, from the Responsibility and ESG Reports of companies. (...)
Name Entity Recognition on Broker Reports
This demo showcases how you can apply NER models to extract financial entities from broker reports, as Currency, Amount, Revenue, Rating, Target Price or Ticker, etc. (...)
Extract Financial Entities from Suspicious Activity Reports
This demo shows how we can extract entities from suspicious activity reports that are filed by financial institutions, and those associated with their business, with the Financial Crimes Enforcement Network. (...)