The motion that the wing has is remarkable.
But the result of embedding the motion that the wing has phrase inside the rapidity that the motion has phrase is surprisingly hard to understand:
The rapidity that the motion that the wing has has is remarkable.
Embedding a third phrase, like the wing that the hummingbird has, creating a triply embedded onion sentence, results in complete unintelligibility:
The rapidity that the motion that the wing that the hummingbird has has has is remarkable
When the human parser encounters the three successive has’s, it thrashes ineffectively, not knowing what to do with them. But the problem is not that the phrases have to be held in memory too long; even short sentences are uninterpretable if they have multiple embeddings:
The dog the stick the fire burned beat bit the cat.
The malt that the rat that the cat killed ate lay in the house.
If if if it rains it pours I get depressed I should get help.
That that that he left is apparent is clear is obvious.
Why does human sentence understanding undergo such complete collapse when interpreting sentences that are like onions or Russian dolls? This is one of the most challenging puzzles about the design of the mental parser and the mental grammar. At first one might wonder whether the sentences are even grammatical. Perhaps we got the rules wrong, and the real rules do not even provide a way for these words to fit together. Could the maligned word-chain device of Chapter 4, which has no memory for dangling phrases, be the right model of humans after all? No way; the sentences check out perfectly. A noun phrase can contain a modifying clause; if you can say the rat, you can say the rat that S, where S is a sentence missing an object that modifies the rat. And a sentence like the cat killed X can contain a noun phrase, such as its subject, the cat. So when you say The rat that the cat killed, you have modified a noun phrase with something that in turn contains a noun phrase. With just these two abilities, onion sentences become possible: just modify the noun phrase inside a clause with a modifying clause of its own. The only way to prevent onion sentences would be to claim that the mental grammar defines two different kinds of noun phrase, a kind that can be modified and a kind that can go inside a modifier. But that can’t be right: both kinds of noun phrase would have to be allowed to contain the same twenty thousand nouns, both would have to allow articles and adjectives and possessors in identical positions, and so on. Entities should not be multiplied unnecessarily, and that is what such tinkering would do. Positing different kinds of phrases in the mental grammar just to explain why onion sentences are unintelligible would make the grammar exponentially more complicated and would give the child an exponentially larger number of rules to record when learning the language. The problem must lie elsewhere.
Onion sentences show that a grammar and a parser are different things. A person can implicitly “know” constructions that he or she can never understand, in the same way that Alice knew addition despite the Red Queen’s judgment:
“Can you do addition?” the White Queen asked. “What’s one and one and one and one and one and one and one and one and one and one?”
“I don’t know,” said Alice. “I lost count.”
“She can’t do Addition,” the Red Queen interrupted.
Why does the human parser seem to lose count? Is there not enough room in short-term memory to hold more than one or two dangling phrases at a time? The problem must be more subtle. Some three-layer onion sentences are a little hard because of the memory load but are not nearly as opaque as the has has has sentence:
The cheese that some rats I saw were trying to eat turned out to be rancid.
The policies that the students I know object to most strenuously are those pertaining to smoking.
The guy who is sitting between the table that I like and the empty chair just winked.
The woman who the janitor we just hired hit on is very pretty.
What boggles the human parser is not the amount of memory needed but the kind of memory: keeping a particular kind of phrase in memory, intending to get back to it, at the same time as it is analyzing another example of that very same kind of phrase. Examples of these “recursive” structures include a relative clause in the middle of the same kind of relative clause, or an if…then sentence inside another if…then sentence. It is as if the human sentence parser keeps track of where it is in a sentence not by writing down a list of currently incomplete phrases in the order in which they must be completed, but by writing a number in a slot next to each phrase type on a master checklist. When a type of phrase has to be remembered more than once—so that both it (the cat that…) and the identical type of phrase it is inside of (the rat that…) can be completed in order—there is not enough room on the checklist for both numbers to fit, and the phrases cannot be completed properly.
Unlike memory, which people are bad at and computers are good at, decision-making is something that people are good at and computers are bad at. I contrived the toy grammar and the baby sentence we have just walked through so that every word had a single dictionary entry (that is, was at the right-hand side of only one rule). But all you have to do is open up a dictionary, and you will see that many nouns have a secondary entry as a verb, and vice versa. For example, dog is listed a second time—as a verb, for sentences like Scandals dogged the administration all year. Similarly, in real life hot dog is not only a noun but a verb, meaning “to show off.” And each of the verbs in the toy grammar should also be listed as nouns, because English speakers can talk of cheap eats, his likes and dislikes, and taking a few bites. Even the determiner one, as in one dog, can have a second life as a noun, as in Nixon’s the one.
These local ambiguities present a parser with a bewildering number of forks at every step along the road. When it comes across, say, the word one at the beginning of a sentence, it cannot simply build
but must also keep in mind
Similarly, it has to jot down two rival branches when it comes across dog, one in case it is a noun, the other in case it is a verb. To handle one dog, it would need to check four possibilities: determiner-noun, determiner-verb, noun-noun, and noun-verb. Of course determiner-verb can be eliminated because no rule of grammar allows it, but it still must be checked.
It gets even worse when the words are grouped into phrases, because phrases can fit inside larger phrases in many different ways. Even in our toy grammar, a prepositional phrase (PP) can go inside either a noun phrase or a verb phrase—as in the ambiguous discuss sex with Dick Cavett, where the writer intended the PP with Dick Cavett to go inside the verb phrase (discuss it with him) but readers can interpret it as going inside the noun phrase (sex with him). These ambiguities are the rule, not the exception; there can be dozens or hundreds of possibilities to check at every point in a sentence. For example, after processing The plastic pencil marks…, the parser has to keep several options open: it can be a four-word noun phrase, as in The plastic pencil marks were ugly, or a three-word noun phrase plus a verb, as in The plastic pencil marks easily. In fact, even the first two words, The plastic…, are temporarily ambiguous: compare The plastic rose fell with The plastic rose and fell.
If it were just a matter of keeping track of all the possibilities at each point, a computer would have little trouble. It might churn away for minutes on a simple sentence, or use up so much short-term memory that the printout would spill halfway across the room, but eventually most of the possibilities at each decision point would be contradicted by later information in the sentence. If so, a single tree and its associated meaning should pop out at the end of the sentence, as in the toy example. When the local ambiguities fail to cancel each other out and two consistent trees are found for the same sentence, we should have a sentence that people find ambiguous, like
Ingres enjoyed painting his models nude.
My son has grown another foot.
Visiting relatives can be boring.
Vegetarians don’t kn
ow how good meat tastes.
I saw the man with the binoculars.
But here is the problem. Computer parsers are too meticulous for their own good. They find ambiguities that are quite legitimate, as far as English grammar is concerned, but that would never occur to a sane person. One of the first computer parsers, developed at Harvard in the 1960s, provides a famous example. The sentence Time flies like an arrow is surely unambiguous if there ever was an unambiguous sentence (ignoring the difference between literal and metaphorical meanings, which have nothing to do with syntax). But to the surprise of the programmers, the sharp-eyed computer found it to have five different trees!
Time proceeds as quickly as an arrow proceeds, (the intended reading)
Measure the speed of flies in the same way that you measure the speed of an arrow.
Measure the speed of flies in the same way that an arrow measures the speed of flies.
Measure the speed of flies that resemble an arrow.
Flies of a particular kind, time-flies, are fond of an arrow.
Among computer scientists the discovery has been summed up in the aphorism “Time flies like an arrow; fruit flies like a banana.” Or consider the song line Mary had a little lamb. Unambiguous? Imagine that the second line was: With mint sauce. Or: And the doctors were surprised. Or: The tramp! There is even structure in seemingly nonsensical lists of words. For example, this fiendish string devised by my student Annie Senghas is a grammatical sentence:
Buffalo buffalo Buffalo buffalo buffalo buffalo Buffalo buffalo.
American bison are called buffalo. A kind of bison that comes from Buffalo, New York, could be called a Buffalo buffalo. Recall that there is a verb to buffalo that means “to overwhelm, to intimidate.” Imagine that New York State bison intimidate one another: (The) Buffalo buffalo (that) Buffalo buffalo (often) buffalo (in turn) buffalo (other) Buffalo buffalo. The psycholinguist and philosopher Jerry Fodor has observed that a Yale University football cheer
Bulldogs Bulldogs Bulldogs Fight Fight Fight!
is a grammatical sentence, albeit a triply center-embedded one.
How do people home in on the sensible analysis of a sentence, without tarrying over all the grammatically legitimate but bizarre alternatives? There are two possibilities. One is that our brains are like computer parsers, computing dozens of doomed tree fragments in the background, and the unlikely ones are somehow filtered out before they reach consciousness. The other is that the human parser somehow gambles at each step about the alternative most likely to be true and then plows ahead with that single interpretation as far as possible. Computer scientists call these alternatives “breadth-first search” and “depth-first search.”
At the level of individual words, it looks as if the brain does a breadth-first search, entertaining, however briefly, several entries for an ambiguous word, even unlikely ones. In an ingenious experiment, the psycholinguist David Swinney had people listen over headphones to passages like the following:
Rumor had it that, for years, the government building had been plagued with problems. The man was not surprised when he found several spiders, roaches, and other bugs in the corner of his room.
Did you notice that the last sentence contains an ambiguous word, bug, which can mean either “insect” or “surveillance device”? Probably not; the second meaning is more obscure and makes no sense in context. But psycholinguists are interested in mental processes that last only milliseconds and need a more subtle technique than just asking people. As soon as the word bug had been read from the tape, a computer flashed a word on a screen, and the person had to press a button as soon as he or she had recognized it. (Another button was available for nonwords like blick.) It is well known that when a person hears one word, any word related to it is easier to recognize, as if the mental dictionary is organized like a thesaurus, so that when one word is found, others similar in meaning are more readily available. As expected, people pressed the button faster when recognizing ant, which is related to bug, than when recognizing sew, which is unrelated. Surprisingly, people were just as primed to recognize the word spy, which is, of course, related to bug, but only to the meaning that makes no sense in the context. It suggests that the brain knee-jerkingly activates both entries for bug, even though one of them could sensibly be ruled out beforehand. The irrelevant meaning is not around long: if the test word appeared on the screen three syllables after bugs instead of right after it, then only ant was recognized quickly; spy was no longer any faster than sew. Presumably that is why people deny that they even entertain the inappropriate meaning.
The psychologists Mark Seidenberg and Michael Tanenhaus showed the same effect for words that were ambiguous as to part-of-speech category, like tires, which we encountered in the ambiguous headline Stud Tires Out. Regardless of whether the word appeared in a noun position, like The tires…, or in a verb position, like He tires…, the word primed both wheels, which is related to the noun meaning, and fatigue, which is related to the verb meaning. Mental dictionary lookup, then, is quick and thorough but not very bright; it retrieves nonsensical entries that must be weeded out later.
At the level of the phrases and sentences that span many words, though, people clearly are not computing every possible tree for a sentence. We know this for two reasons. One is that many sensible ambiguities are simply never recognized. How else can we explain the ambiguous newspaper passages that escaped the notice of editors, no doubt to their horror later on? I cannot resist quoting some more:
The judge sentenced the killer to die in the electric chair for the second time.
Dr. Tackett Gives Talk on Moon
No one was injured in the blast, which was attributed to the buildup of gas by one town official.
The summary of information contains totals of the number of students broken down by sex, marital status, and age.
I once read a book jacket flap that said that the author lived with her husband, an architect and an amateur musician in Cheshire, Connecticut. For a moment I thought it was a ménage à quatre.
Not only do people fail to find some of the trees that are consistent with a sentence; sometimes they stubbornly fail to find the only tree that is consistent with a sentence. Take these sentences:
The horse raced past the barn fell.
The man who hunts ducks out on weekends.
The cotton clothing is usually made of grows in Mississippi.
The prime number few.
Fat people eat accumulates.
The tycoon sold the offshore oil tracts for a lot of money wanted to kill JR.
Most people proceed contendedly through the sentence up to a certain point, then hit a wall and frantically look back to earlier words to try to figure out where they went wrong. Often the attempt fails and people assume that the sentences have an extra word tacked onto the end or consist of two pieces of sentence stitched together. In fact, each one is a grammatical sentence:
The horse that was walked past the fence proceeded steadily, but the horse raced past the barn fell.
The man who fishes goes into work seven days a week, but the man who hunts ducks out on weekends.
The cotton that sheets are usually made of grows in Egypt, but the cotton clothing is usually made of grows in Mississippi.
The mediocre are numerous, but the prime number few.
Carbohydrates that people eat are quickly broken down, but fat people eat accumulates.
JR Ewing had swindled one tycoon too many into buying useless properties. The tycoon sold the offshore oil tracts for a lot of money wanted to kill JR.
These are called garden path sentences, because their first words lead the listener “up the garden path” to an incorrect analysis. Garden path sentences show that people, unlike computers, do not build all possible trees as they go along; if they did, the correct tree would be among them. Rather, people mainly use a depth-first strategy, picking an analysis that seems to be working and pursuing it as long as possible; if they come across words th
at cannot be fitted into the tree, they backtrack and start over with a different tree. (Sometimes people can hold a second tree in mind, especially people with good memories, but the vast majority of possible trees are never entertained.) The depth-first strategy gambles that a tree that has fit the words so far will continue to fit new ones, and thereby saves memory space by keeping only that tree in mind, at the cost of having to start over if it bet on the wrong horse raced past the barn.
Garden path sentences, by the way, are one of the hallmarks of bad writing. Sentences are not laid out with clear markers at every fork, allowing the reader to stride confidently through to the end. Instead the reader repeatedly runs up against dead ends and has to wend his way back. Here are some examples I have collected from newspapers and magazines:
Delays Dog Deaf-Mute Murder Trial
British Banks Soldier On
I thought that the Vietnam war would end for at least an appreciable chunk of time this kind of reflex anticommunist hysteria.
The musicians are master mimics of the formulas they dress up with irony.
The movie is Tom Wolfe’s dreary vision of a past that never was set against a comic view of the modern hype-bound world.
That Johnny Most didn’t need to apologize to Chick Kearn, Bill King, or anyone else when it came to describing the action [Johnny Most when he was in his prime].
Family Leave Law a Landmark Not Only for Newborn’s Parents
Condom Improving Sensation to be Sold
The Language Instinct: How the Mind Creates Language Page 23