What computational linguists actually do all day: The read-between-the-lines edition

Watch a movie like Arrival and you’ll get the impression that linguists spend their professional lives sitting around speculating about Sanskrit etymologies and the nature of the relationship between language and reality.  I’m not saying that we never do such things, but, no: that’s not what we do with our typical workdays.  I’m a computational linguist, which among other things means that what I do involves computers, which among other things means that I spend a certain amount of my time sitting around writing computer programs that do things with language.  Often, those programs are doing things that do not look very…exciting.  Not to the untrained eye, at any rate.

For other glimpses into the daily life of computational linguists, click here.

Case in point: yesterday I wanted to see how the statistical characteristics of language are affected by different decisions about what you consider a “word.”  You would think that the word “word” would be easy to define–in fact, not only do linguists not agree on what a word is, but you would have a hard time getting all linguists to agree that words even exist.  (One of the French-language linguistics books that I have my nose stuck in the most is Maurice Pergnier’s Le mot, “The Word.”  The first 50 pages (literally) are devoted to theoretical controversies around the question of whether words actually exist–or not. Want a good English-language discussion of the issues?  See Elisabetta Jezek’s The lexicon: An introduction.)

So, yesterday I got to thinking about one of the questionable cases in English: contracted negatives of modal verbs.  Here’s what that means.

In English, there is a small number of frequently-occurring verbs that can (and do) get negated not by a separate word like no, but by adding a special ending, spelled -n’t:

  • is/isn’t
  • did/didn’t
  • have/haven’t
  • could/couldn’t
  • would/wouldn’t
  • does/doesn’t

Note that British English has another form:

I’ve not

…which means I haven’t.

Now, if you care about statistics, you care about counting things.  Think about how you would count the numbers of words in these examples:

  1. I want to go.
  2. I do want to go.
  3. I do not want to go.
  4. I don’t want to go.

(3) and (4) are both perfectly acceptable ways of negating (1) and (2).  How would they affect a program that counts the number of words?  It depends.  Here are the straightforward cases: if (1) has four words (I, want, to, and go), then (2) has five (add do to the previous four), and (3) has 6 (add not to the previous five).

The questionable case is (4).  You could make a reasonable argument that don’t is a single word.  You also could make a reasonable argument that don’t should be counted as two words.  But, which two words?  A reasonable person could propose do and n’t–just split the “stem” do from the negative n’t.  

Fine.  But, let’s look at a little more data:

  1. I will go.
  2. I will not go.
  3. I won’t go.
  4. I can go.
  5. I cannot go.
  6. I can’t go.

Clearly (1) has three words–I, will, and go.  …  (2) adds one more, with not.  What about (3), though?  Is it inconsistent to count will not as two words, but won’t as one?  Maybe.  If you’re going to split it into two “words,” what are they?  Presumably wo and n’t?  But, what the hell is wo?  Is it the same “word” as will?  Notice that we’ve now had to start putting “word” in “scare quotes,” which should tell you that knowing what, exactly, a “word” is isn’t quite as simple as it might appear at first glance.  Think about this: in science you need to know what it is, exactly, the thing that you’re studying, which implies that you can recognize the boundary between one of those things and another.

What’s the right answer?  Hell, I don’t know.  I do know this, though: if you’re interested in the statistics of language (wait–what’s you’re?  Hell, what’s what’s?), then you have to be able to count things, so you have to make some decisions about where the boundaries between them are.  My issue du moment is actually not choosing between the options, but rather seeing what the consequences of those specific decisions would be for the resulting statistical measures, so I need to be able to test the effects of different ways of splitting things up (or not), so I need to write some code…

What you see below is me using a computational tool called a “regular expression” to find words that have a negative thing attached at the end (e.g. n’t) and separate the negative thing from the rest of the word.  So, given an input like didn’t, I want my program to (1) recognize that it has a negative thing at the end, and (2) split it into two parts: did, and n’t.  Grok (see the English notes for what grok means) the code (code means “instructions in a programming language”–here I’m using one called Perl), and then scroll down past it for an explanation of how it illustrates a piece of advice that I often give to students…

# this assumes input from a pipe...
while (my $line = <>) {

print "Input: $line";

# this doesn't work--why?
#$line =~ s/\b(wo|ca|did|could|should|might)(n't)\b$/\$1 $\2)/gi;
# works...
#$line =~ s/(a)(n)/a n/gi;
# this does what I want...
#$line =~ s/(a)(n)/$1 $2/gi;
# works...
#$line =~ s/(ca)(n't)/$1 $2/gi;
# works...
#$line =~ s/(ca|wo)(n't)/$1 $2/gi;
# works...
#$line =~ s/\b(ca|wo)(n't)\b/$1 $2/gi;
# works...
#$line =~ s/\b(ca|wo|did)(n't)\b/$1 $2/gi;
# works...
#$line =~ s/\b(ca|wo|did|could)(n't)\b/$1 $2/gi;
# works...
#$line =~ s/\b(ca|wo|did|could|should|might)(n't)\b/$1 $2/gi;
# works...
#$line =~ s/\b(ca|wo|did|had|could|should|might)(n't)\b/$1 $2/gi;
# works...
#$line =~ s/\b(ca|wo|did|had|have|could|should|might)(n't)\b/$1 $2/gi;
# works...
#$line =~ s/\b(ca|wo|do|did|has|had|have|could|should|might)(n't)\b/$1 $2/gi;
# and finally: this pretty much looks like what I started with, but
# what I started with most definitely does NOT work...  what the fuck??

$line =~ s/\b(ca|wo|do|did|has|had|have|would|could|should|might)(n't)\b/$1 $2/gi;

       print $line;

} # close while-loop through input

The “regular expressions” in this code are the things that look like this:

s/\b(wo|ca|did|could|should|might)(n't)\b$/\$1 $\2)/gi

…or, in the case of a much shorter one, like this:

s/(a)(n)/a n/gi

(Note to other linguists: yes, I know that technically, the regular expression is just the part between the first two slashes, i.e. the underlined part s/(a)(n)/a n/gi in the second example.  Don’t hate on me–I’m trying to make this at least somewhat clear.) The lines that start with # are my notes to myself—the “reading between the lines” that you have to do to see how irritating it can be to troubleshoot this kind of thing.

regular expression is a way of describing a set of things.  What makes it “regular”–a mathematical term–is that those things can only occur in a very limited number of relationships.  In particular, that limited number of relationships do not include some phenomena that are very important in language, such as agreement between subjects and verbs–think of Les trois soeurs de ma grand-mère m’ont toujours aimé, “my grandmother’s three sisters have always loved me.”  The issue here is that regular expressions can only describe sequences of things that you might think of as “next to” each other; les trois soeurs is separated from the verb avoir, which must be in the third person plural form ont, by ma grand-mère, which would require the third person singular form a.  (Linguists: I know.)

Regular expressions, and the “regular languages” that they can describe, became of importance in linguistics when B.F. Skinner (yes, the famous psychologist) wrote a book about the psychology of language in which he suggested that they can describe human languages from a mathematical perspective.  This claim caught the attention of one Noam Chomsky, who wrote a book review pointing out the inadequacy of the idea of regular expressions as a description of human language.  The review brought him a lot of notice, and he went on to develop the ideas in that review into the most widespread and influential linguistic theory since the Tower of Babel.  Today, if you’ve only heard of one linguist, it was almost certainly Chomsky.

Chomsky’s critique of “regular languages” included the observation that there are perfectly natural things that can be said in any human language that can’t be described by a regular language.  For example:

Me, my brother, and my sister went to William and Mary, Indiana University, and Virginia Tech, respectively.

The problem that this illustrates for regular languages is that they don’t have a mechanism for accounting for the fact that you can have sentences where you have a list of things in an early part of the sentence, and then must have a list of things of the same length in a later part of the sentence.  Don’t believe me? Go read a book on “formal languages,” and then try it.

Linguistic geekery

Regular expressions are pretty natural tools for people who work with textual data, and they’re especially natural for linguists.  This is a surprise to a lot of computer scientists, some of whom are masters of regular expressions, but some of whom find them irritatingly bewildering.  It turns out that if you take a course on the “formal foundations” of linguistics, i.e. its groundings in logic and set theory, you will run across regular languages, which fact makes regular expressions pretty easy to learn.  And, for textual data, they are really useful even despite their limits–so much so that a programming language (named Perl) was created expressly for the purpose of making it easy to use regular expressions to “parse” textual data.  So, when I found myself wanting to be able to rip through a bunch of textual data and find the negative things like n’t, Perl and its regular expressions were a logical choice.


I love a good monosyllable III: Fleam

Fleam: An instrument for opening veins in bloodletting.

One of the oddities of the lexicon–that is, the set of words that you know–is that you keep learning it for pretty much your entire life.  This is quite different from anything else that you know about your native language: you know almost everything that you will ever know about the phonology and syntax of your language quite early in your childhood.  In contrast, learning new words can continue to your dying day.

Of course, the rate of learning new words changes over the course of the lifespan.  Young toddlers may learn fewer than 5 words a month; between the ages of 2 and 6 years, they’re probably learning more like 30 words a month.  When you enter school, the range of semantic classes that the child is learning shifts in the direction of abstract words, from the concrete ones that formed most of their vocabulary acquisition up to that point.  If you go to college (la fac in French), you will probably see another spurt in your learning of new words; by the time you finish it, the typical person will know most of the vocabulary that they’re going to have.  Certainly not all of it, though.  If you were to graph the number of words that you know over time, it would look something like this–fast growth early in life, followed by slow growth later in life, but no end to the growth.  (Note that the numbers for vocabulary size are not realistic. Total vocabulary size by age 22 will be much larger than I have indicated, probably on the order of 30,000 words.)

Figure source: me. I generated it using a programming language called R. NOTA BENE: the vocabulary size figures are completely unrealistically low–the total vocabulary size should be something like 30,000 words, assuming a college-educated native speaker.

So: I’m 58 years old, and I spent a really long time in college and graduate school, but I am still learning new words in my native language.  Some recent ones:

  • morganitic: relating to marriage between an aristocrat and a non-aristocrat, such that the issue of the marriage do not inherit ranks, titles, and the like.
  • aramid: a group of synthetic materials used to make textiles and plastics.
  • mephitic: nasty-smelling.
  • irredentism: political policy of claiming territories occupied by members of your ethnic group (think Hitler in the Sudetenland), or that were historically part of your political group (think what Hungary would like to do with Transylvania).

What doesn’t happen very often, though: I don’t learn a new monosyllable in my native language very often.  Thus, when I run across one, it tickles me.  So, when a recent trip to New Orleans found me in a pharmacy museum, I was delighted to come across this exhibit:

Where the fuck does this come from?  Let’s go look. Merriam-Webster does not have an entry for fleam, although it does have one for fleam tooth:

A sawtooth shaped like an isosceles triangle

The Online Etymological Dictionary gives me this:

“sharp instrument for opening veins in bloodletting,” late Old English, from Old French flieme (Modern French flamme), from Medieval Latin fletoma, from Late Latin flebotomus, from Greek phlebotomos “a lancet”

So: I never would have guessed it, but it turns out to be historically related to our word phlebotomy, and in fact precedes it in English by centuries.  And thus the pathetic life of a fat, bald old man is made happy by learning a new one-syllable word…

Geeky linguist notes

  1. I’ve given 30,000 words as the size of a typical college-educated adult’s vocabulary.  Take that with a grain of salt–counting the size of someone’s vocabulary is really hard, for a lot of reasons.  You can find a good discussion of them in Elisabetta Jezek’s book The lexicon: An introduction.
  2. I calculated cumulative vocabulary size to age 22 (i.e. approximately the completion of an American college education) using the rate of growth that I gave in the post for the 2:6 age range, because that was the only age range for which I could find numbers.  This results in a drastic underestimate of total vocabulary size–by age 22, it gives just a bit over 7,600 words.  With slow growth after leaving college, there is no fucking way to hit 30,000 in a human lifetime.


What’s making me happy today: élucubrations

You have to grab happiness where you can find it. What’s making me happy today: élucubrations.

You have to grab happiness wherever you can find it, right? I mean, I would love to be feeling happy today because I knew that the Constitution of the United States of America slept as safely last night as I did, or because I was confident that tomorrow’s foreign policy will not further weaken America and strengthen Russia. But, such is not my lot this morning–Trump is still in the White House, and not even his own cabinet knows what he talked with Putin about for two hours in Finland. That doesn’t mean that there’s nothing to feel good about, though.

Today my heart is gladdened by the existence of the word élucubration. I ran across it while reading the French-language translation of the magisterial World War Z, Max Brooks’s allegorical reflection on American culture in the early 20th century. Brooks on conspiracy theorists:

Le secret, ça fonctionne comme un trou sans fond ; et il y a toujours des paranoïaques pour essayer de le combler avec leurs élucubrations.

Word Reference defines élucubrations as “flights of fancy, hare-brained ideas.” (A hare is a kind of rabbit–lièvre, maybe?) French definitions emphasize the amount of work that goes into them:

Discours, pensée issus de recherches laborieuses mais dépourvus de bon sens (Maxipoche 2014, Larousse 2013)

Coming across the word in a translation as I did, it seemed too adorable to be true: surely such a lovely and useful word could not really exist in normal language? Wroooong again, Zipf.

In 1966, the singer Antoine released the song Les Élucubrations d’Antoine. According to Wikipedia, it differentiated itself from the typical yéyé (hippie) music of the time by its militancy, proposing that The Pill be sold in supermarkets and insulting music legend Johnny Halliday. The song sold like crazy and made his career. So…apparently I am the last person in the world to learn the world élucubration, and once again we see the awesome power of Zipf’s Law: most words are very rare–but, they do occur. Enjoy!

Combinatorics and pod hostels

Go to the shitty part of any decent-sized American city–usually on the edges of the old downtown area–in the early evening, and you will find a line of battered-looking men standing in line outside of a building–usually run-down.  The building is a homeless shelter.  A typical one will give you two nights a month for free, and more if you can pay a small amount.  Dinner is a baloney sandwich or something similar, almost always preceded by a non-optional and decidedly denominational church service. A couple of guys will walk up to the front and accept Jesus Christ as their personal lord and savior.  The Christ will accept them with enthusiasm; the shelter staff, not so much, having seen it aaaaaaaall before.  Crusty old bums who may want to blow you, fuck you, get blown by you, or get fucked by you. (That’s 24 possible combinations of 1 or more sexual acts involving a crusty old bum and you, which equals 16; most of the time, nobody asks, and if they do, you politely say “no”–I am not judgmental, and I am not easily shocked–and that’s generally the end of it. So, a total of 17 possible outcomes, exactly one of which does not involve sexual contact between a crusty old bum and you.)  Breakfast is most likely to be a cup of coffee and a piece of toast (butter, unlike the church service, is optional), and then it’s out the door and on the street, regardless of the weather–no loitering during the day.  That’s fine, since you need to get to the day labor office really early if you want to find work, and if that part of your morning is unsuccessful, you need to haul ass to the plasma donation center as quickly as possible–otherwise your protein drops too low and they won’t let you donate, which means that you’re out round-trip bus fare and still have to figure out where you’re going to sleep that night.  The worst one that I’ve ever stayed in was a dank and dark one in Columbus, Ohio, next to a White Castle.  The best one that I’ve ever stayed in was a Veterans of America one outside of Sacramento, California–clean, sunny, and they offered some social-service-type stuff.  God bless the Veterans of America.  Hell, God bless anyone who will feed and house the homeless.

Then you join the Navy.  Boot camp is 80 guys in a large room; big, clean showers in the morning; 15 minutes three times a day to consume all of the food you can inhale (I actually gained weight in boot camp), and then it’s off to do interesting and/or fun things like make emergency flotation devices out of your clothing, learn what to do in case of nerve gas attack (gas mask on, syrette of atropine jammed hard into your thigh if you think you got exposed), and fight fires (pretty involved on a ship, since all of that water has to go somewhere outside of the vessel, or your ass is going to sink).  When you get to your ship, it’s three bunks deep in a compartment that smells of sweat, farts, and depression.  Plus, you learn to sleep with a 5-inch artillery piece firing directly over your head.  (I did, anyway.)  But, it’s warm, they feed you well, the food is quite good, and cigarettes are $1 a pack once you get out of American territorial waters.

Out of the Navy, you head to a super-nice college where everybody but you and the 12 kids in the theater department is polite; smart; attractive, even (possibly especially–who knows how the Upper East Side mates) in LL Bean boots; from New York, New Jersey, or Northern Virginia; and 18-22 years old.  But, you’re married and have a kid, and you’re paying your way via the GI Bill and weekends spent drawing arterial blood samples and adjusting the occasional ventilator at the local hospital, so you live in one of those apartment complexes.  That means (1) at night, entering the kitchen with your eyes closed, stomping like a motherfucker to kill as many cockroaches as possible, and then turning on the lights; and (2) during the day, hunting for their egg cases, ’cause every one that you crush and dump gleefully down the garbage disposal is 15 little cockroaches preemptively and preventatively obliterated.

…all of this to make it clear to my friends who have expressed concern about the fact that I’m living in a pod hostel at the moment that it is totally fine.  Warm, clean, and so far no bums have suggested blowing me, fucking me, me blowing them, or me fucking them.  Not that anyone makes a man of my age that kind of offer very often–I still politely say “no,” but being an old fat bald guy…at this point, I take it as a compliment.

English notes

Decent-sizednot small, but not necessarily big, either.  How much cake do you want?  Gimme a decent-size piece, but not too big, ’cause I’m old, fat, and bald.  How I used it in the post: Go to the shitty part of any decent-sized American city–usually on the edges of the old downtown area–in the early evening, and you will find a line of battered-looking men standing in line outside of a building–usually run-down.

To be out (something of value): To have spent a quantity of money or rendered something of value without getting anything in return.  I bought a bus ticket, but then I got stopped and frisked and I missed the bus, so now I’m out $25.50 and I’m still stuck in this shithole.  How I used it in the post:  You’re out round-trip bus fare and still have to figure out where you’re going to sleep that night.   

Boot camp is the American military’s basic training.  Recent graduates are known as boot camps, or just boots–confusing, I know.  No less than in France, where said recent graduates are either pieds-bleus (did I pluralize that correctly??), or just bleus.

Combinatorics is a branch of mathematics that (in my very limited understanding) has to do with efficiently calculating the number of  possible combinations of things.  No hate mail on this, please—just correct me in the Comments section.  The formula that appears in this post appeared on Quora–if you can prove it (in the mathematical sense), that would be much appreciated.  Note that I did not do the subtraction of 1, because the formula is for proper subsets only, and experience has given me no reason to exclude the non-proper subset option.

Proper subsets: subsets that do not contain all of the members of a set.

Non-proper subsets: subsets that include the subset containing all of the members of a set.  So, for the set = {1, 2}, the set of proper subsets is {1} and {2} (and maybe {}, the “empty set”–I don’t remember from Linguist School).  The set of non-proper subsets is {1}, {2}, and {1,2}.


Mechanism of deanimation of zombies by burning: Academic writing and how not to start a paper

Since the earliest known zombie attacks (Max and Roberson 2010), researchers have been aware that penetrating head injury is universally successful in deanimating zombies.

Comment: Zipf, don’t begin a paper by talking about what researchers know.  Nobody gives a shit about researchers.

Since the earliest known zombie attacks (Max and Roberson 2010), it has been known that penetrating head injury is universally successful in deanimating zombies.

Comment: Zipf, there is a time–and there are excellent places–for the passive.  The first sentence of your paper is not it.

Max and Roberson (2010) describe a zombie attack dated to no later than 140,000 years before the Common Era. It is the earliest known outbreak of The Plague–and the first time that hominids are known to have deanimated them via penetrating head injury.

Comment: Zipf, this is a TERRIBLE context in which to use the passive.  You have hominids fighting for their lives against relentless protoanthropophages (unfortunate terminology–so ambiguous…). Keep that alive for the reader–with the active voice.

Max and Roberson (2010) describe a zombie attack dated to no later than 140,000 years before the Common Era. It is the earliest known outbreak of The Plague–and the first time that hominids deanimated them via penetrating head injury.

Comment: Zipf, this is a shitty context for anaphoric reference.  Why did you use it?

Well, it’s frame-licensed, right?  When there is a zombie attack, there are zombies, and what else could be the antecedent of “them” here?

Comment: (1) to your second point: a zombie attack only requires a single zombie, and in fact your text as given provides only the slightest support for the notion that there were more than one. (2) to your first point: “bridging anaphora” is a much more constrained analysis of this than “frame-licensed.” (3) Don’t be ambiguous.  Say “zombies,” not “them.”

What’s a bridging reference

Zipf, what did you find when you looked up “bridging reference” before asking me that question?

By the way: in work-related emails, punctuation is not optional.  These are not text messages, and I am not your friend.

[no response…]

[no reponse…]

[no response…]

Zipf, we need to talk about your continued funding in this graduate program.


Brooks, Max, and Ibraim Roberson. The Zombie Survival Guide: Recorded Attacks. Broadway Books, 2010.

Note to the reader: do not search Google Images for zombie penetrating head wound unless you have an even stronger stomach than I do.  For context: I brought home the bacon as a medic for many years, and I could not begin to count how many dead bodies I have seen.  Nonetheless: I hit the “back” button on that page as fast as I possibly could.

Picture source: https://open-shelf.ca/161001-phd/



Things I am grateful for today

Moral injury: distress related to having violated core moral boundaries.

I am grateful for some things today.  I mean, I’m grateful for something every day–my kid has health insurance; I slept in a warm, dry, safe place last night; I had breakfast this morning.  Not everybody can say all three of those things, and a lot of people can’t say any of them.

Today, though, is a little special: instead of feeling grateful for what is, today I’m feeling grateful for what is not.  Three things in particular:

  1. I am not in a war.  A lot of folks are–Kurdish fighters who did most of the fighting against ISIS for us, and who we then abandoned; Ukrainian soldiers defending their country against their historic enemy, and ours since the end of the Second World War, and why the president of the United States of America would hate them so much, I can’t imagine, beyond the two hours that he spent in a room with Vladimir Putin and then wouldn’t even tell his own cabinet members about.
  2. I am not in the bowels of a guided missile cruiser wishing that I hadn’t dropped out of high school–a place that I have certainly been before, unlike the president of the United States, who participated actively in sports throughout college, and then got out of the draft on the grounds that he was not sufficiently physically fit.
  3.  I am not going to kill myself today.  In contrast, about 20 of my fellow US military veterans will do just that today.  Why?  There isn’t just one reason why anyone kills themselves. (See Thomas Joiner’s excellent book Why people die by suicide for details.  He knows what he’s talking about–an eminent suicidologist, and editor of the journal Suicide and Life-Threatening Behavior.)  And, veterans share the same risk factors as anyone else.  But, there’s a particular contributor to suicidality in veterans that is not often present in the general population.  It’s called “moral injury.”  Here’s a definition of it, from a paper by H.G. Koenig, N.A. Youssef, and M. Pierce:

Moral injury (MI) involves distress over having transgressed or violated core moral boundaries, accompanied by feelings of guilt, shame, self-condemnation, loss of trust, loss of meaning, and spiritual struggles.

Koenig, Harold G., Nagy A. Youssef, and Michelle Pearce. “Assessment of moral injury in veterans and active duty military personnel with PTSD: a review.” Frontiers in psychiatry 10 (2019).

What I find especially striking about the concept of moral injury is that it has nothing to do what I suspect most people would think was the big cause of guilt in veterans, which is to say: survivor guilt.  Nope–nothing about surviving going on in moral injury.  It’s not about your buddies getting killed–it’s about who you killed.  Moral injury is not about what you experienced– it’s about what you did.  Sociopaths like to kill–nobody else does.  And our military does a good job of screening out sociopaths.

Here’s the original caption of the picture that you see at the top of this post:

American Special Forces worked closely with Kurdish troops to fight the Islamic State in Manbij, Syria, last year. Credit: Mauricio Lima for The New York Times. Headline of the article: Pullback Leaves Green Berets Feeling ‘Ashamed,’ and Kurdish Allies Describing ‘Betrayal’

You certainly don’t have to pull the trigger on someone to suffer moral injury, though.  “Pullback leaves Green Berets feeling ‘ashamed’.”  Do you begin to get a sense for why Trump’s level of support in the military is so low?  The guy has done some deeply un-American stuff, but contributing to the rate of veteran suicide–feel free to tell me if you think I’m stretching too far with this, but it’s a new low, even for a guy so deeply in the gutter.

English notes

Things I am grateful for today is the title of this post.  Some observations about it:

  1. It contains what is known as a bare relative clause: “I am grateful for today.”  The “non-bare” version would be Things that I am grateful for today.  I try to use the non-bare versions, on the theory that I imagine them easier for non-native speakers to process, and I spend far more time speaking with non-native speakers than with native speakers.
  2. Another way to say it would be Things for which I am grateful today.  If that’s easy for anybody to process, I’m not aware of the evidence for it.
  3. Yet another possibility: Things which I am grateful for today.  I don’t know of any situation in which that would be preferred.  Which does not, of course, mean that there aren’t any.
  4. Explain to me again how “English is so much less complicated than other languages”???


Why the fuck would you…

So, I’m wandering around backstage in a theater trying to keep my cousins from making me help build props when I come across the following sign on a storage locker:

…and I wonder: why the fuck would you tell someone to spray a paint can?

I slowly digest the bright-red color of the cabinet. I slowly digest the “FLAMMABLE” signs. I slowly digest the fact that I am apparently becoming senile.

A paint can:

Picture source: https://www.google.com/imgres?imgurl=https://shop.thepurplepaintedlady.com

A can of spray paint:

The verb “to spray:”

An apparently senile computational linguist [PHOTO OMITTED TO PROTECT PUBLIC SENSIBILITIES]