This thread has been quiet for a while, but I came across a pointer
to a blog with answers to questions about Watson. All the answers
were written by members of the Watson team: (01)
http://blog.reddit.com/2011/02/ibm-watson-research-team-answers-your.html (02)
They answered 14 questions on various issues. At the end of this
note is question #3 and the answer, which shows the steps to process
a typical question. Watson does a lot more than matching words. (03)
The answer to question #6 included the following point: (04)
"Watson was written in mostly Java but also significant chunks of
code are written in C++ and Prolog, all components are deployed and
integrated using UIMA." (05)
Note that the excerpts below use a variant of Prolog notation.
Marking variables with a capital letter, such as X, is a typical
Prolog convention. But the person who answered the question
probably removed the obligatory quotes around phrases like
"Stevenson's Treasure Island". (06)
John
___________________________________________________________________ (07)
3. Can you walk us through the logic Watson would go through to answer
a question such as, "The antagonist of Stevenson's Treasure Island."
(Who is Long John Silver?) (08)
Step One: Parses sentence to get some logical structure describing
the answer. X is the answer. (09)
antagonist(X).
antagonist_of(X, Stevenson's Treasure Island).
modifies_possesive(Stevenson, Treasure Island).
modifies(Treasure, Island) (010)
Step Two: Generates Semantic Assumptions (011)
island(Treasure Island)
location(Treasure Island)
resort(Treasure Island)
book(Treasure Island)
movie(Treasure Island) (012)
person(Stevenson)
organization(Stevenson)
company(Stevenson)
author(Stevenson)
director(Stevenson) (013)
person(antagonist)
person(X) (014)
Step Three: Builds different semantic queries based on phrases, keywords
and semantic assumptions. (015)
Step Four: Generates 100s of answers based on passage, documents
and facts returned from 3. Hopefully Long-John Silver is one of them. (016)
Step Five: For each answer formulates new searches to find evidence in
support or refutation of answer -- score the evidence. (017)
Positive Examples:
Long-John Silver the main character in Treasure Island.....
The antagonist in Treasure Island is Long-John Silver
Treasure Island, by Stevenson was a great book.
One of the great antagonists of all time was Long-John Silver
Richard Lewis Stevenson's book, Treasure Island features many great
characters, the greatest of which was Long-John Silver. (018)
Step Six: Generate, get evidence and score new assumptions (019)
Positive Examples: (negative examples would support other characters,
people, books, etc associated with any Stevenson, Treasure or Island)
Stevenson = Richard Lewis Stevenson
"by Stevenson" --> Stevenson's
main character --> antagonist (020)
Step Seven: Combine all the evidence and their scores Based on analysis
of evidence for all possible answer compute a final confidence and link
back to the evidence. (021)
Watson's correctness will depend on evidence collection, analysis and
scoring algorithms and the machine learning used to weight and combine
the scores. (022)
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