Information retrieval is about returning the information that is relevant for a specific query or field of interest. Note that this information could also be in the form of general documents, sure enough search engines are a notable example of such task.
I would say that the most important entities recognizable for information retrieval are the initial set of documents/information and the query that specify "what to search for".
On the other hand information extraction is more about extracting (or inferring) general knowledge (or relations) from a set of documents or information. Note that here all the content of the documents could be considered as a whole corpus of data from which extract the knowledge. Of course also for this case you can somehow specify what do you want to extract, but it is more about properties/relations than specific subjects/topics. Properties are more domain-specific, while generally relations cover more generic scenarios.
Again, with search engines you're asking to get the sites that are most likely to contain information about that specific subject. This is an example of information retrieval.
For information extraction you could instead, for example, ask to extract all the names of cities, or e-mail addresses, that appear in a corpus of documents. You could even go much more generic, asking simply to extract knowledge. As you can see this is really generic, but it can be accomplish, for example, by obtaining triplets of the form subject-action-object for each valid sentence of a text (this is best suited for natural language texts).
If you're interested these (and other) topics are explain in details in the Natural Language Processing chapter of the book Artificial Intelligence: A Modern