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Gene Smirnov

A Day in the Life of a Dictionary Editor

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Gene Smirnov

As told to Jen Doll

As a lexicographer for Merriam-Webster, Kory Stamper defines new words (a personal favorite? mosh) and updates old ones. She explains what it takes to become a word, why angry letters are also inspiring, and how a day in the life of a dictionary editor includes both death threats and marriage proposals. 

1. Becoming a lexicographer was completely an accident.
It’s not a job your high school guidance counselor has a folder on. I stumbled across a want ad for an editorial assistant. I got called for the interview and found out it was for Merriam-Webster. I thought, Oh, I was a nerdy kid, sure, I could do that. Within a couple of months, I realized this was exactly what I needed to do.

2. My job is to define new words and update old ones.
Part of that means constantly collecting evidence of how words are used in print and online and adding that to a big database, which we call the citations file. From there, I can analyze whether each meaning we’ve collected for a word—say, green—is already covered by an existing definition, if that existing definition needs to be broadened or narrowed, or if we need to write a new definition. It’s a giant matching game.

3. People think there’s a celebration for every new word ...
... but some days I might draft seven new entries.

4. When I first started, I thought I’d keep a list of words I wrote new entries for.
I gave up after a year and a 50-page-long list. At this point, when people ask how many words I’ve entered, I can’t tell them. I have probably looked at every single entry in all of our dictionaries.

5. I do have a handful of words I give people when they ask “What words have you defined that you’re proud of?”
I totally revised the entry for God in the Unabridged. It had been written in the mid-’50s. There was no sense that covered Greek or Roman gods of mythology, or any of the incidental uses of God, like OMG, or God help you.

6. To be a new entry, a word must meet three criteria.
First, widespread use. If it only appears in Wine Spectator, it’s not a great candidate. Second, it has to have sustained usage over a certain period of time (usually years). People think of the dictionary as being either the gatekeeper or the bleeding edge, but it’s neither. By the time a word is in a dictionary, most people have at least seen it. Third, it has to have a meaning. There are words without a formal meaning that get used a lot, like antidisestablishmentarianism. It’s used as an example of a long word, but it doesn’t have a lexical definition.

7. The gatekeepers are the editors.
Maybe I’m going to let an ugh come through, but not an ew, for example.

8. Most words don’t enter the language in a smooth, upward motion.
You’ll get spikes—words will drop out, then spike again. There’s a jagged upward trend for most words. AIDS, I think, we entered within a year of its first use. It was clear it was not going away anytime soon.

9. Some words take forever to fully enter the language.
The first written use of the word korma, for the Indian dish, was in the 1830s or so. It didn’t enter the language until the late 1990s. Now it shows up on Indian menus. It’s sort of at the halfway point.

10. I’ve been at this job for almost 17 years.
That’s kind of crazy in this day and age, but it doesn’t get boring. You must have a threshold for the same work over and over again, but you can find things that are new and fresh and interesting.

11. I’ve gotten marriage proposals, and also death threats.
Because language is universal, people feel very strongly about it. They have no problem going from “I don’t like this word or what it represents” to “I don’t like the dictionary” to “I don’t like the editor.” One year, Stephen Colbert noticed we had entered a sense of marriage that covered same-sex marriage. The hate mail came in fast and furious.

12. Even when people get angry, it’s inspiring.
They’re engaging with language, and I can help them do that.

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iStock // Ekaterina Minaeva
Man Buys Two Metric Tons of LEGO Bricks; Sorts Them Via Machine Learning
May 21, 2017
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iStock // Ekaterina Minaeva

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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Nick Briggs/Comic Relief
What Happened to Jamie and Aurelia From Love Actually?
May 26, 2017
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Nick Briggs/Comic Relief

Fans of the romantic-comedy Love Actually recently got a bonus reunion in the form of Red Nose Day Actually, a short charity special that gave audiences a peek at where their favorite characters ended up almost 15 years later.

One of the most improbable pairings from the original film was between Jamie (Colin Firth) and Aurelia (Lúcia Moniz), who fell in love despite almost no shared vocabulary. Jamie is English, and Aurelia is Portuguese, and they know just enough of each other’s native tongues for Jamie to propose and Aurelia to accept.

A decade and a half on, they have both improved their knowledge of each other’s languages—if not perfectly, in Jamie’s case. But apparently, their love is much stronger than his grasp on Portuguese grammar, because they’ve got three bilingual kids and another on the way. (And still enjoy having important romantic moments in the car.)

In 2015, Love Actually script editor Emma Freud revealed via Twitter what happened between Karen and Harry (Emma Thompson and Alan Rickman, who passed away last year). Most of the other couples get happy endings in the short—even if Hugh Grant's character hasn't gotten any better at dancing.

[h/t TV Guide]