To answer questions, you need to know what they mean. For example, to answer the question "Where did the battle of New Orleans start?" you need to know that "battle of New Orleans" represents a specifc event, "start" represents a more specific event (a specific time during the battle) and "where" represents the location of the event. Kparser is a tool that gets this information out of the text, and it models it as a graph. Each "object" is a node and each relation between objects is a connection between nodes, otherwise called an edge. Here is how the graph of the question above would look:
You can use Kparser too: just go to http://kparser.org and put in a question and see what it gives you. It's not perfect yet; some things don't parse correctly, but really there's no perfect semantic parser yet.
The research I'm doing is motivated by Percy Liang's research into the same idea, answering questions using a semantic parser and Freebase. You can find his main paper on the topic here. At the bottom of this paper in the section "Error analysis" he notes that the semantic parser that he used has difficulty on certain phrases and he notes the example I showed above as one. Kparser handles this sentence just fine, as it does other sentences that did not work with the style of semantic parse Liang used, and this is why Kparser might be better suited for this task, the motivation of my research.
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