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Words with Multiple Meanings Pose a Special Challenge To Algorithms (theatlantic.com)
Sample this: Me: So that's the marshmallow but you're going to eat it with this graham cracker and chocolate.
[My son looks at me like I am the dumbest person alive.]
Sebastian: No, I'm going to eat it with my MOUTH.
[End of play.] That's from "S'MORES. A Real-Life One-Act Play", a conversation between Hamilton impresario Lin-Manuel Miranda which his young son Sebastian. In that brief interaction, young Sebastian Miranda inadvertently hit upon a kind of ambiguity that reveals a great deal about how people learn and process language -- and how we might teach computers to do the same.
The misinterpretation on which the s'mores story hinges is hiding in the humble preposition with. Imagine the many ways one could finish this sentence: I'm going to eat this marshmallow with ... If you're in the mood for s'mores, then "graham cracker and chocolate" is an appropriate object of the preposition with. But if you want to split the marshmallow with a friend, you could say you're going to eat it "with my buddy Charlie." The Atlantic elaborates: Somehow speakers of English master these many possible uses of the word with without anyone specifically spelling it out for them. At least that's the case for native speakers -- in a class for English as a foreign language, the teacher likely would tease apart these nuances. But what if you wanted to provide the same linguistic education to a machine?
As it happens, just days after Miranda sent his tweet, computational linguists presented a conference paper exploring exactly why such ambiguous language is challenging for a computer-based system to figure out. The researchers did so using an online game that serves as a handy introduction to some intriguing work currently being done in the field of natural language processing (NLP). The game, called Madly Ambiguous , was developed by the linguist Michael White and his colleagues at Ohio State University. In it, you are given a challenge: to stump a bot named Mr. Computer Head by filling the blank in the sentence Jane ate spaghetti with ____________. Then the computer tries to determine which kind of with you intended. Playful images drive the point home. [Editor's note: check the article for corresponding images.]
In the sentence Jane ate spaghetti with a fork, Mr. Computer Head should be able to figure out that the fork is a utensil, and not something that is eaten in addition to the spaghetti. Likewise, if the sentence is Jane ate spaghetti with meatballs, it should be obvious that meatballs are part of the dish, not an instrument for eating spaghetti.
[My son looks at me like I am the dumbest person alive.]
Sebastian: No, I'm going to eat it with my MOUTH.
[End of play.] That's from "S'MORES. A Real-Life One-Act Play", a conversation between Hamilton impresario Lin-Manuel Miranda which his young son Sebastian. In that brief interaction, young Sebastian Miranda inadvertently hit upon a kind of ambiguity that reveals a great deal about how people learn and process language -- and how we might teach computers to do the same.
The misinterpretation on which the s'mores story hinges is hiding in the humble preposition with. Imagine the many ways one could finish this sentence: I'm going to eat this marshmallow with ... If you're in the mood for s'mores, then "graham cracker and chocolate" is an appropriate object of the preposition with. But if you want to split the marshmallow with a friend, you could say you're going to eat it "with my buddy Charlie." The Atlantic elaborates: Somehow speakers of English master these many possible uses of the word with without anyone specifically spelling it out for them. At least that's the case for native speakers -- in a class for English as a foreign language, the teacher likely would tease apart these nuances. But what if you wanted to provide the same linguistic education to a machine?
As it happens, just days after Miranda sent his tweet, computational linguists presented a conference paper exploring exactly why such ambiguous language is challenging for a computer-based system to figure out. The researchers did so using an online game that serves as a handy introduction to some intriguing work currently being done in the field of natural language processing (NLP). The game, called Madly Ambiguous , was developed by the linguist Michael White and his colleagues at Ohio State University. In it, you are given a challenge: to stump a bot named Mr. Computer Head by filling the blank in the sentence Jane ate spaghetti with ____________. Then the computer tries to determine which kind of with you intended. Playful images drive the point home. [Editor's note: check the article for corresponding images.]
In the sentence Jane ate spaghetti with a fork, Mr. Computer Head should be able to figure out that the fork is a utensil, and not something that is eaten in addition to the spaghetti. Likewise, if the sentence is Jane ate spaghetti with meatballs, it should be obvious that meatballs are part of the dish, not an instrument for eating spaghetti.
THis really isn't that complicated. It's not that words have two meaning but there are different cases. In many languages there is a dative suffix for words taking a supporting roll. I threw the ball out the window. case endings can cleanly separate subject (I), direct object (ball) and participating clause object (window). IN english we lack a dative suffix on most words. So we have helper words and word orders to tell us which are the dative.
In the case of all the examples give, "with" here is just saying the object named participated. "fork, meatball, Buddy". It doesn't say how it participated. That is completely not the content of the sentence.
the point I'm making is that the sentence scans identically. It's not ambiguous. It's exact. It's entirely possible that I ground up my buddy to make meatballs out of him and that I actually like eating small forks. That information is not intended to be present. It would come from external context. The senstence is not ambiguous.
Some drink at the fountain of knowledge. Others just gargle.
Want a context-free language, easily parseable, with plenty of computer-driven tooling, without this irritating English ambiguity?
Sure, but I also want to be able to converse with people on the street. Since statistically nobody speaks lojban there is no sense in learning it. If I were going to spend effort learning another language, it would be one people actually use.
"You're right," Fisheye says. "I should have set it on 'whip' or 'chop.'"
Me: Your new magazine you got from your grandmother for your birthday came in the mail. Do you want to read it tonight for bedtime?
4yo: [Confused] Magazines aren't for reading.
Me: What are they for?
4yo: [Stated with an tone of obviousness] Magazines are for cutting.
[End scene]
Time flies like an arrow
Fruit flies like a banana.
Computer scientists focus on this because it highlights a really interesting difference between how our brains represent information and how computers do. The reality is human minds have no problem holding onto a word or phrase in a state of semantic superposition. For instance, if someone tells you to "turn left at the bronze rooster", you will keep an eye out for a business with that name, or an actual bronze statue of a rooster. Computers don't have this ability, to declare
Int x = 54 or 75 or 23;
Intuitively, and the ability to do so seems to give our minds a lot of unique powers.
-The art of programming is the pursuit of absolute simplicity.
Children are very highly specialized in reducing an argument to absurdity. This is a very important tool in logic and, in my opinion, it is no better exemplified elsewhere other than in Lewis Carroll's books, which I think is why Miranda's kid interpreted his father's statement as absurd. As a mathematician, Carroll was quite aware of how easily logical errors come about. I like citing when Humpty Dumpty explains what an un-birthday is to Alice: “I mean, what is an un-birthday present?" A present given when it isn't your birthday, of course." Alice considered a little. "I like birthday presents best," she said at last. You don't know what you're talking about!" cried Humpty Dumpty. "How many days are there in a year?" Three hundred and sixty-five," said Alice. And how many birthdays have you?" One.” I suppose Miranda could have been more explicit and said "along with", rather than just using "with" alone. As another example of this, we say "a glass of water", despite the glass not being made of water. Yet we don't say "a glass with water". And we certainly don't drink the glass, but rather its contents. I find all this fascinating. Brits have trouble understanding some American phrases as well for pretty much the same reason. Same thing goes for European Spanish and Latin American Spanish. Maybe feeding an AI with several samples of such phrases, as said and interpreted by multiple cultures would better train it to deal with such "inconsistencies"?
Geez, what's with other languages having words/nouns "male" and "female" for things....with no rhyme or reason.
I've tried to figure that out for decades and it makes no fucking sense.
Now that today, somehow we have > 2 genders [rolls eyes], are those languages changing that, or making a telephone gender neutral?
Light travels faster than sound. This is why some people appear bright until you hear them speak.........
Ambiguity exists in all natural languages, and in many forms.
The problem (as I see it) is one of context. Each answer is possible, but given "context", one answer will be more likely than another. It's this notion of context that's the difficult part to grok, and must be accounted for in any system intended for "intelligent" processing.
One thing I notice is that our brains don't seem to rely on this type of *explicit* enumeration. Assume it is a statue, and imagine the trillions and trillions of possible permutations, each a different size, pose, or with one different feather from the last, that you would still recognize as a rooster. We don't hold all those in our brain at once. The only thing I've seen in CS like it is with quantum computers, where you've prepared a state with a million different outcomes, from an original uncorrelated state with a billion different outcomes, using a small amount of info. Somehow concepts in our brain are like that: A concept simple enough to share and communicate (e.g. shoe) applies simultaneously to trillions and trillions of possible things, while excluding even more, without us having a mental list of every possible shoe. It's a magic that's hard for me to visualize as code!
-The art of programming is the pursuit of absolute simplicity.