Language Log

The Health Promotion Board (Bǎojiàn cùjìn jú 保健促进局) of Singapore has launched a campaign to promote awareness of falling.  Here's the poster they circulated in conjunction with the launch:

(Source)

Today's xkcd:

Mouseover title: "President Andrew Johnson once said, 'If I am to be shot at, I want Gnome Ann to be in the way of the bullet.'"

In media reporting on current events in China, two of the most conspicuous terms one encounters are "clamp down" (qǔdì 取缔, qiābā 掐巴, qiánzhì 钳制, etc.) and "crack down" (yánlì dǎjí 严厉打击 / 嚴厲打擊 [to show how different simplified and traditional forms of the characters can be]).  There are also numerous other similar terms with related meanings in common use, such as those for "ban; forbid; outlaw; suppress; repress".  These clamp/crack downs and bans can be directed toward Islam, Christianity, feminism, human rights advocates / lawyers, any form of dissent, and so forth.  Yet no other clamp down has occasioned so much spontaneous and widespread opposition from those representing a broad spectrum of a large segment of the general population as the recent announcement of the new rules governing online video games.

"Mobile game devs are very pissed about China’s new censorship rules", by C. Custer, Tech in Asia (7/6/16)

I was just reading along in the NYT today but had to pause at this sentence:

Mr. Trump has used bankruptcy laws to shield him from personal losses while his investors suffer.

I found myself puzzling over whether "him" was all right there or whether I wanted "himself", and even more puzzled that I was having trouble deciding. I would try out one, then the other, and the sentence kept shape-shifting on me. I didn't "feel" any particular ambiguity, and yet either choice would sound bad to me one second and good the next. Puzzled.

An ad that's been popping up for me on the web recently:

I expect that others have used asterisks in this particular way before, but web search engines seem generally to treat "**UK" as plain "UK" — perhaps someone else will have better luck finding precedents. (Of course, general taboo-avoidance via asterisks is common and has been discussed here many times.)

Earlier this year, Language Log readers contributed to the elucidation of "South Asian wrestling terms" (3/1/16).

Roger Lustig sends in this trending-on-facebook headline:

Police Find Jaguars Running Back Asleep Inside Car Sinking Into a Pond, Reports Say

Roger traces the first few steps down the garden path:

–Police find jaguars
–Police find jaguars running
–Police find jaguars running back (from where?)
–Police find jaguars running back asleep (talk about "second nature"!)

For me, "running back" is tightly enough bound as a compound word that I wouldn't have noticed the other possibilities without Roger's guidance. But it's special when the intended meaning is almost as weird as the crash blossom.

Mike Miller writes:

I recently stayed in a hotel in a smaller city in Shandong and was surprised to see what they are calling a hair dryer these days.

Here's a photograph that Mike sent along:

Paul Ryan's July 4 statement (emphasis added):

On this year’s Fourth, we can celebrate the historic document that was signed—and the self-evident truths it declared. We can celebrate the historic battles that were fought so that those truths would embrace all of our people. We can remember the extraordinary men and women, so dedicated to those truths, who died on this day—and the millions of others whose names we’ll never know. Or we can remember—and give thanks—that we live in a country where all these things are possible. We still believe in those self-evident truths. We still struggle to live up to them. And really, what that struggle represents is the pursuit of happiness. So today, with great gratitude, we celebrate our independence.

Could Speaker Ryan (or the intern who wrote this statement) have meant "on this day" to modify "We can remember"? Or are invited to remember the people who died in historic battles specifically on July 4? Puzzling.

Update — Jenny Chu points out that Adams, Jefferson and Monroe died on July 4. I was led away from that interpretation by the previous discussion of "historic battles" and the reference to "extraordinary men and women" who died on that day, as well as the following "millions of others".  And now I also wonder what we're meant to understand by "all these things" — the document? the truths? the battles? the deaths? All of them?

Perhaps this message is a lightly-adapted version of  an all-purpose patriotic-holiday exhortation.

[h/t Adam Rosenthal]

That's what practically everybody else calls her too.

There's a great article by Qian Jinghua in Sixth Tone (Fresh voices from today's China) titled "Call Me Angelababy, Maybe:  Ban on foreign names in Chinese-language press reveals fear of cultural fragility." (6/30/16)

It's about a phenomenally popular 27-year-old actress, model, and singer whose Chinese name is 楊穎, which is read as Yáng Yǐng in Modern Standard Mandarin (MSM) and Joeng4 Wing6 (conventional spelling Yeung Wing) in Cantonese.  Her father, from Hong Kong, is half Chinese and half German, her mother is Shanghainese.  Yang Ying's stage name, "Angelababy", by which virtually everyone knows her (most people are uncertain about her Chinese name or don't know it at all), comes from a combination of her English name "Angela" and her nickname "Baby".

So what's all the fuss over her name?

The many Americans in the University of Edinburgh's community of language and information scientists had to celebrate the glorious 4th on the 3rd this year, because the 4th is an ordinary working Monday. I attended a Sunday-afternoon gathering kindly hosted by the Head of the School of Informatics, Johanna Moore. We barbecued steadfastly in the drizzle despite classic Scottish indecisive summer weather: it was cloudy, well under 60°F. Twice we all had to flee inside indoors when the rain became heavier. No matter: we chatted together and enjoyed ourselves. (I swore in 2007 that one thing I was not going to do was spend my time in this bracing intellectual environment grumbling about how the weather in Santa Cruz had been better. I'm here for the linguistic science, not the weather.) So it was a happy Fourth of July for me. Until this morning, the actual 4th, when people started emailing me (thanks, you sadistic bastards) to note that Robert McCrum had chosen America's independence day to make his choice for the 23rd in a series called "The 100 Best Nonfiction Books of All Time," in the British newspaper The Observer. He chooses The Elements of Style by William Strunk and E. B. White. For crying out loud!

The last installment of this series, "Spelling with Chinese character(istic)s, pt. 3" (6/30/16), contains links to many other Language Log posts relevant to this subject.

It is often difficult to fathom which English word is intended when it is transcribed in Chinese characters.  John Kieschnick called my attention to an especially challenging one:  ěrlílìjǐng 爾釐利景.  Before going on to the next page and before googling it, try to figure out what it is meant to "spell".  Scout's honor!  No peeking!

"Heavy Metal and Natural Language Processing – Part 1", Degenerate State 4/20/2016:

Natural language is ubiquitous. It is all around us, and the rate at which it is produced in written, stored form is only increasing. It is also quite unlike any sort of data I have worked with before.

Natural language is made up of sequences of discrete characters arranged into hierarchical groupings: words, sentences and documents, each with both syntactic structure and semantic meaning.

Not only is the space of possible strings huge, but the interpretation of a small sections of a document can take on vastly different meanings depending on what context surround it.

These variations and versatility of natural language are the reason that it is so powerful as a way to communicate and share ideas.

In the face of this complexity, it is not surprising that understanding natural language, in the same way humans do, with computers is still a unsolved problem. That said, there are an increasing number of techniques that have been developed to provide some insight into natural language. They tend to start by making simplifying assumptions about the data, and then using these assumptions convert the raw text into a more quantitative structure, like vectors or graphs. Once in this form, statistical or machine learning approaches can be leveraged to solve a whole range of problems.

I haven't had much experience playing with natural language, so I decided to try out a few techniques on a dataset I scrapped from the internet: a set of heavy metal lyrics (and associated genres).

[h/t Chris Callison-Burch]