This post duplicates my Quora answer. Feel free to vote and comment there.
Relation extraction is used to build knowledge bases. These can be used:
- to answer simple questions directly;
- to combine extracted pieces of knowledge to answer more complex questions;
- for answer typing.
For example, if you extract a ternary relation (frogs, eat, insects) from the sentence: "Adult frogs eat mainly small insects", you can answer a question "What do frog eat?". In the modern era of QA this approach was pioneered by the MIT system Start. See, e.g. a related publication: REXTOR a system for generating relations from natural language, 2000, Katz, Boris, and Jimmy Lin.
Furthermore, answers to more complex questions can be found by combining several ternary relations, however, this requires a complex (and often intractable) logical inference. Some approximate approaches are often applied here, see, e.g., the paper Relation extraction and scoring in DeepQA
Answer typing is a classic answer extraction/matching technology employed from the early days of QA in extractive QA systems (see a seminal paper by R. F. Simmons: Answering English questions by computer). For example, if the question is "What is the largest mammal?" (answer blue whale), a possible answer can only be an animal that feeds babies with its own milk.
To be able to deduce the correct answer blue whale, a QA system needs to know that the blue whale is a mammal. This information may come from human-crafted ontologies. However, human-created ontologies often have poor coverage. An alternative strategy to obtaining such knowledge is relation extraction. For more details, please, see the following IBM Watson paper: Automatic knowledge extraction from documents