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4 More Unofficial Rules Native English Speakers Don't Realize They Know

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The BBC’s Matthew Anderson tweeted about a rule that “English speakers know, but don’t know we know.” It was a screen grab of a passage from Mark Forsyth’s The Elements of Eloquence explaining that the reason “great green dragons” sounds better than “green great dragons” is that we unconsciously follow a rule that stipulates that the order of adjectives in English goes opinion-size-age-shape-color-origin-material-purpose. Size comes before color, so no “green great dragons.”

People reacted to the tweet with amazement, astonishment, and thousands of retweets. It can be shocking to realize that we are able to follow rules that no one ever taught us explicitly. But that’s what most of language is: Not the little things that textbooks tell us we’re getting wrong, but the solid ones we always get right. Non-native speakers, however, might get them wrong, and that gives us a good opportunity to get a peek at the rules we don’t otherwise notice.

1. WHY “MY BROTHER’S CAR” AND NOT “THE CAR OF MY BROTHER”

There are two main ways to express possession in English, one with possession marked on the possessor (my brother’s car) and one with an “of” phrase (the car of my brother). Teachers and usage guides don’t usually give rules telling you why “the car of my brother” sounds bad but “the door of my house” sounds fine, because no one thinks to say “the car of my brother” in the first place. But why not? After all, languages like Spanish and French use this kind of construction (el coche de mi hermano, la voiture de mon frère). Why does “my brother’s car” sound so much better than “the car of my brother,” but “my house’s door” sounds the same or worse than “the door of my house”?

We don’t know it, but we make these phrases with reference to something called the animacy hierarchy. The hierarchy in this case is basically a scale in decreasing order of humanness going from human to animal to inanimate objects. The higher in animacy the possessor is, the worse the “of” phrase type of construction sounds. So,

"my brother's car" sounds better than "the car of my brother"

"my parakeet's cage" sounds a bit better than "the cage of my parakeet"

"my house's door" sounds the same or worse than "the door of my house"

Of course, there are considerations like conversational context and rhetorical effect that result in exceptions to this rule, but it does account for a lot of the difference in the relative acceptability of these two syntactic choices. For example, “city hall” can be conceived of as an inanimate building ("the steps of city hall") or a collection of people ("city hall’s announcement").

2. WHY ABSO-FREAKIN’-LUTELY AND NOT ABSOLUTE-FREAKIN’-LY

There’s a way to emphasize a word in English that involves inserting an expletive into the middle of the word—but not just anywhere in the middle. While abso-freakin’-lutely sounds right, ab-freakin’-solutely and absolute-freakin’-ly sound terrible. There is a rule at work here, having to do with the syllable structure of the word. Essentially, you find the syllable with the most emphasis inside the word and put the swear word before it. Kalama-freakin’-ZOO. Im-bloody-PORtant, la-freakin’-SAgna.

Things get tricky when the only stress is on the first syllable (YESter-freakin’-day? Ele-bloody-phant?) or when there are other, more separable boundaries in the word like un- or re- (un-freakin’-beLIEVable and re-freakin’-poSSESSED, are better than unbe-freakin’-LIEVable and repo-freakin’-SSESSED), but these exceptions can be categorized and explained. The important thing is that there’s a rule, and we already know how to apply it, even if we can’t state it.

3. WHY “WHAT DID YOU SAY THAT HE ATE?” AND NOT “WHAT DID YOU MUMBLE THAT HE ATE?”

In English, when we ask a who/what/where/when/why question, there is usually a slot in the sentence where the answer would fit if it were not a question. For “What did you eat?” the corresponding sentence is “I ate __ [potatoes/an apple/my breakfast…].” For “Where did they go?” the corresponding sentence is “They went __ [to the beach/to lunch/downstairs…].”

Linguists talk about these types of questions in terms of movement; it’s as if the 'wh' word has moved from the non-question sentence slot to the beginning of the sentence. Wh-movement can also happen out of phrases a long way from the beginning of the sentence. “What did you say that the beginning of the movie reminded you of?” corresponds to “You said that the beginning of the movie reminded you of __ [moving day/the weather report/ancient Greece…].”

But there are many cases where you can’t do this kind of movement. For example, for these complex, long distance cases, the main verb of the sentence must belong to a specific class of verbs linguists call bridge verbs. Say is a bridge verb (“What did you say that he ate _____?”) but verbs that include the manner in which something was said (mumble, shout, whisper, sob) are not. So “What did you mumble that he ate ___?” sounds terrible. We don’t make those kinds of sentences because we know the rule, even if we don’t know there is a rule.

4. WHY “I CHEERED UP MY FRIEND” AND NOT “I CHEERED UP HER”

English has a group of verbs known as phrasal verbs that give language learners a major headache. These are verbs made of multiple words that together give a different meaning than you would expect by simple combination. For example blow up is a phrasal verb because it means “explode” not “blow in an upward direction.” You just have to learn what these mean. They are verbs like call off (cancel), go over (review), and put down (insult). There are hundreds of them.

Phrasal verbs do not all work according to the same rules. Some do not allow an object to come between the parts of the verb: You can say “Don't pick on your sister” but not “Don't pick your sister on.” But other phrasal verbs can be separated: You can say “Let’s call off the meeting” or “Let’s call the meeting off.” Native speakers know which ones are separable and which are not without ever looking at a rule book. Non-native speakers have to learn the difference through painstaking experience.

But that’s not all. Even the separable verbs have a restriction on them that native speakers never explicitly learn about. Cheer up is separable. You can say “I cheered my friend up” or “I cheered up my friend.”  But if you want to substitute my friend with a pronoun, it must be placed between the parts of the verb. You cannot say “I cheered up her” only “I cheered her up.” For the inseparable verbs, pronouns are no problem: "Don't pick on her."

In the rest of English grammar you can substitute a pronoun anywhere you have a noun phrase. Not in this case. But you already knew that, even if you didn't know you knew that.

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Man Buys Two Metric Tons of LEGO Bricks; Sorts Them Via Machine Learning
May 21, 2017
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Jacques Mattheij made a small, but awesome, mistake. He went on eBay one evening and bid on a bunch of bulk LEGO brick auctions, then went to sleep. Upon waking, he discovered that he was the high bidder on many, and was now the proud owner of two tons of LEGO bricks. (This is about 4400 pounds.) He wrote, "[L]esson 1: if you win almost all bids you are bidding too high."

Mattheij had noticed that bulk, unsorted bricks sell for something like €10/kilogram, whereas sets are roughly €40/kg and rare parts go for up to €100/kg. Much of the value of the bricks is in their sorting. If he could reduce the entropy of these bins of unsorted bricks, he could make a tidy profit. While many people do this work by hand, the problem is enormous—just the kind of challenge for a computer. Mattheij writes:

There are 38000+ shapes and there are 100+ possible shades of color (you can roughly tell how old someone is by asking them what lego colors they remember from their youth).

In the following months, Mattheij built a proof-of-concept sorting system using, of course, LEGO. He broke the problem down into a series of sub-problems (including "feeding LEGO reliably from a hopper is surprisingly hard," one of those facts of nature that will stymie even the best system design). After tinkering with the prototype at length, he expanded the system to a surprisingly complex system of conveyer belts (powered by a home treadmill), various pieces of cabinetry, and "copious quantities of crazy glue."

Here's a video showing the current system running at low speed:

The key part of the system was running the bricks past a camera paired with a computer running a neural net-based image classifier. That allows the computer (when sufficiently trained on brick images) to recognize bricks and thus categorize them by color, shape, or other parameters. Remember that as bricks pass by, they can be in any orientation, can be dirty, can even be stuck to other pieces. So having a flexible software system is key to recognizing—in a fraction of a second—what a given brick is, in order to sort it out. When a match is found, a jet of compressed air pops the piece off the conveyer belt and into a waiting bin.

After much experimentation, Mattheij rewrote the software (several times in fact) to accomplish a variety of basic tasks. At its core, the system takes images from a webcam and feeds them to a neural network to do the classification. Of course, the neural net needs to be "trained" by showing it lots of images, and telling it what those images represent. Mattheij's breakthrough was allowing the machine to effectively train itself, with guidance: Running pieces through allows the system to take its own photos, make a guess, and build on that guess. As long as Mattheij corrects the incorrect guesses, he ends up with a decent (and self-reinforcing) corpus of training data. As the machine continues running, it can rack up more training, allowing it to recognize a broad variety of pieces on the fly.

Here's another video, focusing on how the pieces move on conveyer belts (running at slow speed so puny humans can follow). You can also see the air jets in action:

In an email interview, Mattheij told Mental Floss that the system currently sorts LEGO bricks into more than 50 categories. It can also be run in a color-sorting mode to bin the parts across 12 color groups. (Thus at present you'd likely do a two-pass sort on the bricks: once for shape, then a separate pass for color.) He continues to refine the system, with a focus on making its recognition abilities faster. At some point down the line, he plans to make the software portion open source. You're on your own as far as building conveyer belts, bins, and so forth.

Check out Mattheij's writeup in two parts for more information. It starts with an overview of the story, followed up with a deep dive on the software. He's also tweeting about the project (among other things). And if you look around a bit, you'll find bulk LEGO brick auctions online—it's definitely a thing!

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Scientists Think They Know How Whales Got So Big
May 24, 2017
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It can be difficult to understand how enormous the blue whale—the largest animal to ever exist—really is. The mammal can measure up to 105 feet long, have a tongue that can weigh as much as an elephant, and have a massive, golf cart–sized heart powering a 200-ton frame. But while the blue whale might currently be the Andre the Giant of the sea, it wasn’t always so imposing.

For the majority of the 30 million years that baleen whales (the blue whale is one) have occupied the Earth, the mammals usually topped off at roughly 30 feet in length. It wasn’t until about 3 million years ago that the clade of whales experienced an evolutionary growth spurt, tripling in size. And scientists haven’t had any concrete idea why, Wired reports.

A study published in the journal Proceedings of the Royal Society B might help change that. Researchers examined fossil records and studied phylogenetic models (evolutionary relationships) among baleen whales, and found some evidence that climate change may have been the catalyst for turning the large animals into behemoths.

As the ice ages wore on and oceans were receiving nutrient-rich runoff, the whales encountered an increasing number of krill—the small, shrimp-like creatures that provided a food source—resulting from upwelling waters. The more they ate, the more they grew, and their bodies adapted over time. Their mouths grew larger and their fat stores increased, helping them to fuel longer migrations to additional food-enriched areas. Today blue whales eat up to four tons of krill every day.

If climate change set the ancestors of the blue whale on the path to its enormous size today, the study invites the question of what it might do to them in the future. Changes in ocean currents or temperature could alter the amount of available nutrients to whales, cutting off their food supply. With demand for whale oil in the 1900s having already dented their numbers, scientists are hoping that further shifts in their oceanic ecosystem won’t relegate them to history.

[h/t Wired]

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