BASEBALL (QA) System
A Baseball QA System is a Chatterbot Question Answering System that answered questions about the US baseball league developed by Green Jr et al., (1961).
- AKA: BASEBALL System, BASEBALL Program.
- Context:
- …
- Example(s):
- Q: "Where did each team play on July 7?".
- …
- Counter-Example(s):
- IBM's Watson QA System,
- LUNAR System,
- ELIZA System,
- EAGLi System,
- DOCTOR System,
- SHRDLU System,
- LILOG System,
- TRIPSYS System,
- SFU's SQuASH System.
- AnswerBus http://www.answerbus.com/index.shtml
- UMich's NSIR http://tangra.si.umich.edu/clair/NSIR/html/nsir.cgi
- MIT's START http://start.csail.mit.edu/
- CMU's JAVELIN.
- a Question-Answering Character such as:
- See: Help System, QA Service, Chatterbot, Turing Test, Expert System, SQL, SPARQL, Prolog, FunQL, DCS Tree.
References
2018
- (Wikipedia, 2018) ⇒ https://en.wikipedia.org/wiki/Question_answering#History Retrieved:2018-12-23.
- Two early QA systems were BASEBALL and LUNAR. BASEBALL answered questions about the US baseball league over a period of one year. LUNAR, in turn, answered questions about the geological analysis of rocks returned by the Apollo moon missions. Both QA systems were very effective in their chosen domains. In fact, LUNAR was demonstrated at a lunar science convention in 1971 and it was able to answer 90% of the questions in its domain posed by people untrained on the system. Further restricted-domain QA systems were developed in the following years. The common feature of all these systems is that they had a core database or knowledge system that was hand-written by experts of the chosen domain. The language abilities of BASEBALL and LUNAR used techniques similar to ELIZA and DOCTOR, the first chatterbot programs.
SHRDLU was a highly successful question-answering program developed by Terry Winograd in the late 60s and early 70s. It simulated the operation of a robot in a toy world (the "blocks world"), and it offered the possibility of asking the robot questions about the state of the world. Again, the strength of this system was the choice of a very specific domain and a very simple world with rules of physics that were easy to encode in a computer program.
In the 1970s, knowledge bases were developed that targeted narrower domains of knowledge. The QA systems developed to interface with these expert systems produced more repeatable and valid responses to questions within an area of knowledge. These expert systems closely resembled modern QA systems except in their internal architecture. Expert systems rely heavily on expert-constructed and organized knowledge bases, whereas many modern QA systems rely on statistical processing of a large, unstructured, natural language text corpus.
The 1970s and 1980s saw the development of comprehensive theories in computational linguistics, which led to the development of ambitious projects in text comprehension and question answering. One example of such a system was the Unix Consultant (UC), developed by Robert Wilensky at U.C. Berkeley in the late 1980s. The system answered questions pertaining to the Unix operating system. It had a comprehensive hand-crafted knowledge base of its domain, and it aimed at phrasing the answer to accommodate various types of users. Another project was LILOG, a text-understanding system that operated on the domain of tourism information in a German city. The systems developed in the UC and LILOG projects never went past the stage of simple demonstrations, but they helped the development of theories on computational linguistics and reasoning.
Recently, specialized natural language QA systems have been developed, such as EAGLi for health and life scientists.
- Two early QA systems were BASEBALL and LUNAR. BASEBALL answered questions about the US baseball league over a period of one year. LUNAR, in turn, answered questions about the geological analysis of rocks returned by the Apollo moon missions. Both QA systems were very effective in their chosen domains. In fact, LUNAR was demonstrated at a lunar science convention in 1971 and it was able to answer 90% of the questions in its domain posed by people untrained on the system. Further restricted-domain QA systems were developed in the following years. The common feature of all these systems is that they had a core database or knowledge system that was hand-written by experts of the chosen domain. The language abilities of BASEBALL and LUNAR used techniques similar to ELIZA and DOCTOR, the first chatterbot programs.
1961
- (Green Jr et al., 1961) ⇒ Bert F. Green Jr, Alice K. Wolf, Carol Chomsky, and Kenneth Laughery. (1961). "Baseball: An Automatic Question-answerer". In: Proceedings of western joint IRE-AIEE-ACM computer conference. IRE-AIEE-ACM '61 (Western) Papers. AFIPS Joint Computer Conferences. doi:10.1145/1460690.1460714
- ASBTRACT: Baseball is a computer program that answers questions phrased in ordinary English about stored data. The program reads the question from punched cards. After the words and idioms are looked up in a dictionary, the phrase structure and other syntactic facts are determined for a content analysis, which lists attribute-value pairs specifying the information given and the information requested. The requested information is then extracted from the data matching the specifications, and any necessary processing is done. Finally, the answer is printed. The program's present context is baseball games; it answers such questions as " Where did each team play on July 7? "----