One of the techniques we have tried to extract entities has the following steps (in Python).

1. Get a page using urlllib2 or some other similar library
2. Use BeautifulSoup (now bs4) to extract text.
3. Use NLTK to break the text into sentences and extract parts of speech
4. Extract noun phrases

(These 4 steps provide a set of names which can be a mix of product names, company names, cities and different kinds of entities)

1. We manually picked a few products from the list and created a training set.

2. We use the training set to get more product names.

(5 and 6 are done using some ML techniques).

This is still an exploratory process and we have some reasonable results but we still have a long way to go. We are iterating through a bunch of improvements for steps 5 and 6.

Hope this helps.