Information Extraction (IE) techniques enables us to distill knowledge from the abundantly available unstructured content. Some of the basic IE methods include the automatic extraction of relevant entities from text (e.g. places, dates, people, ...), understanding relations among them, building semantic resources (dictionaries, ontologies) to inform the extraction tasks, and connecting extraction results to standard classification resources. IE techniques cannot decouple from human input - at bare minimum, some of the data needs to be manually annotated by a human so that automatic methods can learn patterns to recognize certain types of information.
The human-in-the-loop paradigm applied to IE techniques focuses on how to better take advantage of human annotations (the recorded observations) and how much interaction with the human is needed for each specific extraction task.
This talk will explore different real world use cases of "Experts in the Loop", including building dictionaries, understanding data centers, and managing drug package inserts in the Pharmaceutical Domain.