So, you want a real job?

My guest post about the job market for linguistics outside academia at Zoltan Varju's blog is available here.

no one is scared of Johnny Depp (a film review)

I just saw The Rum Diary starring Johnny Depp. I enjoyed this film a lot. It is well paced, fun, beautiful, caustic, and funny ...yet... Depp just never seemed right as Thompson (thinly veiled as Paul Kemp, Puerto Rico journalist in the early 1960s).

Before critiquing Depp, let me run through a few non-Depp related points:

I can recommend this film without hesitation as unquestionably worth your time and money. Go see this film. This film is better than 95% of the films that have come out in the last 20 years. I'm not joking, Go see this film.

Brilliant dialogue: Kudos to writer/direct Bruce Robinson for allowing Thompson's witty yet brutally incisive social critiques to highlight the dialogue. This is a beautifully rendered script. It was an honor to listen to characters say interesting things again after decades of trite piffle littering our movie screens. This is the best screenplay since 2009's An Education.

Giovanni Ribisi is fantastic as the weird, drunk, Hitler-loving Moburg. His performance alone is worth the price of admission.

Amber Heard is visually stunning, but she is rarely given more than 6 words to say at a time (same is true for her performance in Pineapple Express). With so few lines, it's not clear if she is a bad actor or if no one will give her the chance to act. I couldn't help but be reminded of Scarlett Johansson, who is truly beautiful, but is an utterly cringe-worthy actor (only Sofia Coppola has managed to wring a competent performance out of her).

That said...

I am a Johnny Depp fan. I like most of his films. I have known Depp to be a Thompson devotee for some time, but only this week learned he actually lived with Thompson for a couple years in the early 1990s (if I read this correctly).

But! Depp has something of the vaudevillian in him. A knowing performer, deft at character, but always with a nod to the audience about the façade, the game, a wink to their suspension of disbelief. Enjoy the show folks, glad you could spare some time for my little charade. It is precisely this man-behind-the-curtain nod that troubled me throughout the film. I had a similar response to Depp's turn as Thompson in the 1998 film, but I couldn't quite put it to words.

I grew up in a family of Hunter Thompson fans. My three older brothers lived Thompson-esque lives (complete with hilarious, madcap drug addled stories, but also to horrible ends in one case). I read Fear and Loathing in Las Vegas when I was 12 and loved it. I read everything Thompson I could find. My dad once found about 30 old Rolling Stone magazines at a yard sell for like $2 and bought the lot and they were filled with Thompson articles. I read them all. I read Hell Angels, The Great Shark Hunt. Hell, I even read The Curse of Lono. Like all Thompson fans, I knew of the existence of The Rum Diary, his first novel written in the 1960s but not published until the late 1990s, and I yearned for the chance to read the unpublished manuscript. When it finally did get published, I jumped at it. Some of you line up for Harry Potter movies, I lined up for The Rum Diaries.

So, I respect Johnny Depp's talent and sincerity and I defer to the fact that he actually knew the man quite well (and I didn't); nonetheless, Hunter S. Thompson played a remarkably important role in my formative years and I feel that entitles me to a certain level of critique (I could be wrong about that...entitlements are typically bullshit ... but this is my bullshit).

And my critique is this: Johnny Depp lacks authenticity. I cannot buy him as Thompson. At least, I cannot buy him as the embodiment of my conception of Thompson. Depp is fun, quirky, smarmy, but always superficial. Thompson is dangerously loose, and frighteningly deep. Depp is never dangerous because his knowing smirk lets us know it's just a game. Thompson never lets us off the hook this way. You may question the truth of Thompson's claims secretly, in your heart, but Thompson never lets you question him to his face, you wouldn't dare. You'd be too scared. But no one is scared of Johnny Depp. He's a kid playing dress up.

This is not a losing battle. Bill Murray's 1980 performance as Thompson in Where the Buffalo Roam is dead on. Murray nails Thompson's duality of hilarious and dangerous, fun and scary, fake and real. Johnny Depp nails the hilarious, fun, fake parts, but fails at the dangerous, scary, real parts. No duality. Perhaps my early, formative exposure to that 1980 film has poisoned me to all others. Maybe.

Regardless, I end with my opening plea: Go see this film. You will be happy you did.

Stanford professors and grammatical illusions

I started reading The Origins of Political Order by Stanford professor Francis Fukuyama when I stumbled across this sentence:

• But it is clear that the political job of finding the right regulatory mechanisms to tame capitalism's volatility have not yet been found.

I read it a second time. Then a third. It just didn't seem right. The verb "have" is wrong, right? It should be "has", I think. But it was difficult to see why until I broke the sentence down to its essential elements. The linguistic dependencies are obscured by multiple embedded PPs, in this case, making it difficult to get the agreement right.

Distilling a complex sentence down to its essential elements is a technique I taught to students for years because it helps us see what the sentence "means" in a basic sense, and all we need is our intuition. No linguistic theory or technical terms are required. One way to do begin is to simply replace noun phrases with variables like X and Y:

• But it is clear that the X of finding the right Y to tame Z have not yet been found.

Already we see that "have" sounds more clearly wrong. Next we can delete the introductory phrase "But..."

• The X of finding the right Y to tame Z have not yet been found.

Now we have distilled the sentence to its basic elements. To figure out why "have" sounds wrong, we can delete all prepositional phrases, as they are not essential to the basic meaning of the sentence:

• The X have not yet been found.

Finally, we need only put the original X phrase back in:

• The political job have not yet been found.

Using just our intuition, two things should be obvious:

1. The subject "political job" is singular and requires the verb to be "has" (syntax).
2. It is odd to speak about finding a political job (when it clearly does not mean job in the sense of getting paid to do something). Rather, this is referring to political will (semantics).

A little analysis of the original and we can guess that Fukuyama was probably trying to construct a linguistic dependency between "have" and "regulatory mechanisms." But this dependency is ungrammatical in the strict sense that "regulatory mechanisms" is not the subject of the sentence. Yet the sentence is not obviously ungrammatical (like "Bob feet have."). I taught 18 year old public school freshmen about this, but we can see that this kind of thing gets the best of even highly educated, accomplished Stanford professors. It is a function of how our brains construct and parse sentences.

This sentence presents what Colin Phillips has called a grammatical illusion. He explains them thusly:

Research on the online implementation of grammatical constraints reveals a strikingly uneven profile. The parser shows impressive accuracy in the application of some rather complex constraints, but makes many errors in the implementation of some relatively simple constraints.

His plenary talk at LSA 2010 provided a variety of examples (many involving "have", curiously enough). Here's a pre-print PDF of his work on the topic:

Grammatical illusions and selective fallibility in real-time language comprehension. Colin Phillips, Matt Wagers, & Ellen Lau. 26pp. June 2009. To appear in Language and Linguistics Compass.

"the definition of “metaphoricity” is problematic in itself"

One of the metaphor recognition papers I read this week had an interesting finding wrt inter-annotator agreement and metaphor: The Automatic Identification of Conceptual Metaphors in Hungarian Texts: A Corpus-based Analysis (Babarczy et a., LREC 2010 Workshop).

The purpose of the paper was to run a sort-of bake-off between three methods of creating source/target word lists (to be used by selection preference metaphor recognition system): Three different methods of compiling the word lists were tested: a) word association experiment, b) dictionary of synonyms, and c) reference corpus.

Ultimately they found that their corpus based method was most successful as measured by recall/precision, but there was a more striking result rather buried in the paper that I feel deserves more analysis. They created a gold standard by hand-tagging a 30,000 word "baseline" corpus. Here's what they found:

At the first attempt, inter-annotator agreement was only 17%. After refining the annotation instructions, we made a second attempt, which resulted in an agreement level of 48%, which is still a strikingly low value. These results indicate that the definition of “metaphoricity” is problematic in itself [emphasis added].

They reported three general sources of inter-annotator DISagreement:

• Direct vs. Indirect Reference: For example, in the case of the conceptual metaphors ANGER IS HEAT or CONFLICT IS FIRE, the source domain should be an expression referring to a sort of “heated thing”. However, in some cases, one or the other annotator included words indirectly suggesting the presence of heat, such as kiolt ('extinguish'), kihől ( 'get cold') etc.

• Lexical Ambiguity: For example, the expression eljutottam a mai napig ('I've gotten to this day') may or may not represent a CHANGE IS MOTION metaphor depending on whether the Hungarian verb jut (literally: get somewhere, reach a place by moving the entire body) is taken only to denote physical movement or to be ambiguous.

• Discrepancies in Classification: ...it is difficult to make an informed decision on whether the following example contains a CHANGE IS MOTION or a PROGRESS IS MOTION FORWARD metaphor, neither of which appear to be an intuitively correct choice: a járvány végigsöpört szülıvárosukon ('the epidemic swept through their hometown').

Of the four or five articles I've reviewed on automatic metaphor identification, this is the only one which reported on the results of human-tagging a corpus for metaphor. This strikes me as the sort of thing that should be a first step for anyone seriously interested in this program (certainly anyone interested in the IARPA Metaphor Program).I don't doubt that others have done this, but it seems to be under-reported, suggesting it is not be treated as a core part of the problem.

I've complained in my previous posts that there is an overly restricted definition of metaphor underlying contemporary approaches to auto identification, but even within a highly restricted definition like those used by Babarczy et al. and others, there appears to be problems at the heart of identification for humans. So what exactly is being identified?


Anna Babarczy, Ildikó Bencze M., István Fekete, & Eszter Simon (2010). The Automatic Identification of Conceptual Metaphors in Hungarian Texts: A Corpus-Based Analysis LREC 2010 Workshop. Proceedings

more on auto metaphor recognition methods

A quick follow-up to my previous post on automatic metaphor recognition wrt the IARPA Metaphor Program. The paper Automatic Metaphor Recognition Based on Semantic Relation Patterns by Tang et al. challenges the dominant selectional preferences method by substituing their own Semantic Relations Patterns. They point out the problems with Selection Preferences (unfortunately I don't think they solved the problems with their own method, more on that in a bit).

Again I'll give the Ling 101, computational linguistics for dummies version (as I understand it ...): Selection Preferences assumes that words frequently co-occur with other words that are literally associated with the same semantic domain. For example,

1. That ship has sailed the mighty ocean.
2. That boat has sailed across lake Erie.
3. That captain has sailed many seas.

In these three sentences, the verb sailed occurs with three different subjects (ship, boat, captain) and three different objects (ocean, lake, seas), but all of them evoke the SAILING domain. So a computer could use this info to create a model of the verb sail that would match up the semantics of its expected subjects and objects, then compare them to a new sentence. If the computer encountered the new sentence

    4. That student sailed through final exams.

It could automatically use the model created from sentences 1-3 above to recognize that the verb sailed occurs with a subject and object not from the SAILING domain, but rather from the STUDENT domain. Then it could use a metaphor mapping component to recognize that HUMANS as MACHINES is an acceptable mapping and thus recognize that #4 might be coherent under a metaphorical interpretation.

Tang et al. rightly point out that matching frequency-based selectional preferences is not the same thing as literal meaning. First, they note that some times, a metaphorical pairing is actually MORE FREQUENT than a litertal pairing. They use some Chinese examples, but I think the English translation makes the point. Take the following two uses of close:

• The plane is close to the tower.
• Opinion are close.

In their corpus, Chinese uses like 'opinions are close' were more frequent, even though this is a non-literal use of close. Frequency would lead the Selectional Preference method to believe that the opinions-type use is literal simply because it is more frequent. This outcome is predicted by Lakoff & Johnson, btw, because one of the core tenants of their seminal work on metaphors was that metaphors are NOT special uses of language, but rather quite common and normal.

Tang et al.'s solution is a new method they call Semantic Relation Patterns. Their explanation is brief and highly technical, making it a slog to get through, but it hinges on incorporating an existing semantic relations knowledge base, HowNet, and adding a probabalistic model. Note, I had trouble getting the HowNet website to load, but here is a PDF explanation.

How Net is an on-line common-sense knowledge base unveiling inter-conceptual relations and inter-attribute relations of concepts as connoting in Chinese and English bilingual lexicons.

In my quick read the two methods differed only minimally in the crucial ways (namely, they are both lexalist and local). Semantic Relation patterns are still based on lexical semantics and still derived entirely locally. I don't see how SRP would handle this metaphor from my earlier post any better than SP:

Imagine a situation in a biology class where two students, Alger and Miriam, were originally going to be partners for a lab assignment. Then they got into an argument. A third student, Annette, asks Miriam:

• Annette: Are you still going to be lab partners with Alger?
• Miriam: No. That ship has sailed.

In this scenario, the sentence "That ship has sailed" is entirely coherent and literal from a selectional preferences perspective (i.e., ships really do sail). Yet it is clearly being used metaphorically (there is literally no ship). Here, the metaphor is only detectable if we link two sentences together via co-reference. The phrase "the ship" does not co-refer to a real ship in the discourse. Rather, it refers to the possible event of be-lab-partners-with-Alger. Unless we can link phrases between sentences and between types (i.e., allowing an NP to co-refer to an event), then we are not going to get a computer to recognize these types of metaphors (which I suspect are quite common).

I appreciate Tang et al.'s critique of the SP method and their attempt to get beyond it, but I think their methodology fails to make the critical improvements to automatic metaphor recognition that will be crucial to creating a full scale tool that handles real world metaphor.



Xuri Tang, Weiguang Qu, Xiaohe Chen, & Shiwen Yu (2010). Automatic Metaphor Recognition Based on Semantic Relation Patterns International Conference on Asian Language Processing

the big picture: automatic metaphor identification

The recently popularized IARPA Metaphor Program piqued my curiosity, so I've been reviewing a variety of articles on contemporary approaches to automatic metaphor identification. I've read three articles so far and one thing is somewhat dissapointing: they all severely restrict the notion of metaphor to mean local metaphors within single sentences.

They all pay considerable lip service to Lakoff & Johnson's seminal 1980 work Metaphors We Live By, taking as gospel the notion that metaphor is defined as a mapping from one conceptual domain to another. But their examples are all of a limited type. Here are three representative examples from the papers I've been reading:

• Achilles was a lion. (Babarczy et al.)
• The sky is sad. (Tang et al.)
• I attacked his arguments (Baumer)

What struck me is the methods used to identify metaphor are remarkably lexalist. The dominant strategy is Selectional Preferences whereby a list of source and target conceptual domains is created. Then from each, a list of words typically associated with that domain is culled from corpora or intuition or dictionaries. Then, each word is given a set of selectional preferences which constrain what kinds of subjects or predicates it typically occurs with.

Here is my Ling 101 version of this methodology: If I understand correctly (and I may not), for Tang et al.'s example "The sky is sad", we would have a concept like THE ENVIRONMENT IS HUMAN. We would have a list of words typically associated with the environment (e.g., "sky") and a list of words typically associated with being human (for example "sad"). A computer could then recognize the following:

1. The subject (the sky) is associated with the environment.
2. The predicate (sad) is associated with humans.
3. This subject (the sky) is not typical for this predicate (sad).
4. This sentence is incoherent on first analysis.
5. The concept THE ENVIRONMENT IS HUMAN links these non-typical phrases coherently.
6. This sentence is only coherent using conceptual mapping, therefore it is probably metaphorical.

This is a gross oversimplification, but I think it gets the big picture about right.

At first blush, I'm impressed with the simplicity and elegance of this solution. However, it seems to me that much metaphorical language is not local like this (local here = within a single sentence). For example, imagine a situation in a biology class where two students, Alger and Miriam, were originally going to be partners for a lab assignment. Then they got into an argument. A third student, Annette, asks Miriam:

• Annette: Are you still going to be lab partners with Alger?
• Miriam: No. That ship has sailed.

In this scenario, the sentence "That ship has sailed" is entirely coherent from a selectional preferences perspective (i.e., ships really do sail). Yet it is clearly being used metaphorically (there is literally no ship). Here, the metaphor is only detectable if we link two sentences together via co-reference. The phrase "the ship" does not co-refer to a real ship in the discourse. Rather, it refers to the possible event of be-lab-partners-with-Alger. Unless we can link phrases between sentences and between types (i.e., allowing an NP to co-refer to an event), then we are not going to get a computer to recognize these types of metaphors (which I suspect are quite common).



Xuri Tang, Weiguang Qu, Xiaohe Chen, & Shiwen Yu (2010). Automatic Metaphor Recognition Based on Semantic Relation Patterns International Conference on Asian Language Processing


Other citations:
The Automatic Identification of Conceptual Metaphors in Hungarian Texts: A
Corpus-Based Analysis. Anna Babarczy, Ildikó Bencze M.1, István Fekete1, Eszter Simon1

Computational Metaphor Identification to Foster Critical Thinking and Creativity. ERIC BAUMER (dissertation). 2009.

the largest whorfian study EVER! (and why it matters)

Let me take the ball Mark Liberman threw on Monday and run with it a bit. Liberman posted a thorough discussion of Fausey and Broditsky's neo-Whorfian English and Spanish speakers remember causal agents differently. Specifically, he invited readers to carefully examine the methodology of the experiments themselves, and not just focus on the conclusions. It turns out that a few years ago another set of neo-Whorfians, Jürgen Bohnemeyer and company, published a paper that addressed similar methodological concerns:

Ways to go: Methodological considerations in Whorfian studies on motion events. (With S. Eisenbeiss and B. Narasimhan) Colchester: University of Essex, Department of Language and Linguistics (Essex Research Reports in Linguistics 50: 1-19). 2006.

This paper addressed experiments involving motion events like rolling and falling whereas Fausey and Broditsky's work addressed agentivity like breaking and popping, but there's enough overlap to warrant some comparison, particularly since the Bohnemeyer et al. paper specifically addresses methodology wrt Whorfian experiments.

But before I get into the details, let me state clearly why I think this is important. In other posts, I have dismissed popular lingo-topics like language evolution as outside the mainstream of linguistics because they don't bear directly on what I consider to be the center of the linguistics universe: How the brain does language. But linguistic relativity (aka, The Whorfian hypothesis) is one of the great questions of linguistics and cognitive science precisely because it bears directly on the question of how the brain does language. And we're only just now developing the proper tools and methodologies to study the question with scientific rigor. It may turn out that language does not affect other cognitive processes or the effect is minor. I don't care. I just want to know one way or the other. And it's work like Bohnemeyer's and Broditsky's that will lead us to knowing, eventually.

Now the fun stuff.