Any successful implementation of comprehension must progressively enhance the world model based on additional information. Furthermore it must understand some basic rules, such as, "Any subject, set of subjects, or actions can be represented multiple ways."
So if you said, "Mary's brother is Sam," or "Mary has a brother named Sam," or "Mary's brother is named Sam," the world model must collocate the meanings "Sam" and "brother" for Mary and be able to respond to queries about either.
Further, if you mention that John also has a brother named Sam, and then you mention Sam in an ambiguous context, the program should be smart enough to ask, "Which Sam? Mary's brother or John's?" Infocom games did this; you are building a more flexible world model builder, but the parser would operate similarly.
There is also the concept of recency. If I talk about "John's brother Sam", ignoring the fact that pronoun references to "he" should be contextually mapped correctly, and then mention Sam, the program should not need to ask which Sam I mean. It would be like talking to someone who wasn't paying attention.
Finally, there is also the concept of confidence. In the face of ambiguity that can't be resolved, a confidence rating should be assigned based on available information and future answers should be based on that confidence.
I suspect that if someone were to create a language parser that could create a mostly-accurate world model AND modify itself based on new rules it read (e.g., "When some says 'he' after referring to someone's name, they are almost certainly talking about the man they previously referred to"), you would be 90% of the way to creating a useful virtual intelligence. It would of course not be able to reason or have opinions of its own, but it would be extremely useful as a virtual assistant that could learn your preferences over time.
Not only this, the system would have to maintain multiple levels of world models and simulate them as well. Consider a sentence: "If he goes there, and then she does not reach in time, he will surely be disappointed."
There has to be a hierarchy of world models, and only the bottom-most layer would be the "real" one. Any kind of planning will require simulating hypothetical worlds.
> Finally, there is also the concept of confidence. In the face of ambiguity that can't be resolved, a confidence rating should be assigned based on available information and future answers should be based on that confidence.
That should probably be the first thing ;-) Every word has a probable meaning, and when all of them fit together into a coherent way including context, then the meaning is correct (probably). This also encompasses the use of pronouns, which you touch on. An inability to resolve ambiguity should also point to the appropriate question to ask for clarification, which you also mentioned. I think your points are all great, just wanted to point out that I think the notion of confidence should be more central.
I'd also go as far as saying part of the internal model of the world should also have a confidence. Any failure to understand a sentence may actually be a problem with its world view. But now I'm rambling.
I'd also go as far as saying part of the internal model of the world should also have a confidence. Any failure to understand a sentence may actually be a problem with its world view.
Yes, but that happens automatically by virtue of learning through natural language teaching. Put the VI through school.
In the blog comments someone raises proposes the sentence "Mary saw the jaguar". And points out that it wouldn't know if the jaguar was an animal or a car. Once again, confidence comes in but it would be based on context. Or perhaps it would become clear after more conversation.
Further, if you mention that John also has a brother named Sam, and then you mention Sam in an ambiguous context, the program should be smart enough to ask, "Which Sam? Mary's brother or John's?"
Option 3: The only Sam, since Mary and John are brothers :)
Comments
Some thoughts about creating a system like this:
Any successful implementation of comprehension must progressively enhance the world model based on additional information. Furthermore it must understand some basic rules, such as, "Any subject, set of subjects, or actions can be represented multiple ways."
So if you said, "Mary's brother is Sam," or "Mary has a brother named Sam," or "Mary's brother is named Sam," the world model must collocate the meanings "Sam" and "brother" for Mary and be able to respond to queries about either.
Further, if you mention that John also has a brother named Sam, and then you mention Sam in an ambiguous context, the program should be smart enough to ask, "Which Sam? Mary's brother or John's?" Infocom games did this; you are building a more flexible world model builder, but the parser would operate similarly.
There is also the concept of recency. If I talk about "John's brother Sam", ignoring the fact that pronoun references to "he" should be contextually mapped correctly, and then mention Sam, the program should not need to ask which Sam I mean. It would be like talking to someone who wasn't paying attention.
Finally, there is also the concept of confidence. In the face of ambiguity that can't be resolved, a confidence rating should be assigned based on available information and future answers should be based on that confidence.
I suspect that if someone were to create a language parser that could create a mostly-accurate world model AND modify itself based on new rules it read (e.g., "When some says 'he' after referring to someone's name, they are almost certainly talking about the man they previously referred to"), you would be 90% of the way to creating a useful virtual intelligence. It would of course not be able to reason or have opinions of its own, but it would be extremely useful as a virtual assistant that could learn your preferences over time.
Not only this, the system would have to maintain multiple levels of world models and simulate them as well. Consider a sentence: "If he goes there, and then she does not reach in time, he will surely be disappointed."
There has to be a hierarchy of world models, and only the bottom-most layer would be the "real" one. Any kind of planning will require simulating hypothetical worlds.
That should probably be the first thing ;-) Every word has a probable meaning, and when all of them fit together into a coherent way including context, then the meaning is correct (probably). This also encompasses the use of pronouns, which you touch on. An inability to resolve ambiguity should also point to the appropriate question to ask for clarification, which you also mentioned. I think your points are all great, just wanted to point out that I think the notion of confidence should be more central.
I'd also go as far as saying part of the internal model of the world should also have a confidence. Any failure to understand a sentence may actually be a problem with its world view. But now I'm rambling.
I'd also go as far as saying part of the internal model of the world should also have a confidence. Any failure to understand a sentence may actually be a problem with its world view.
Yes, but that happens automatically by virtue of learning through natural language teaching. Put the VI through school.
In the blog comments someone raises proposes the sentence "Mary saw the jaguar". And points out that it wouldn't know if the jaguar was an animal or a car. Once again, confidence comes in but it would be based on context. Or perhaps it would become clear after more conversation.
Option 3: The only Sam, since Mary and John are brothers :)
Back to the drawing board, you've failed this Turing test! (Mary is no one's brother.)