Year: 2013
Type: article
Abstract: I am deeply honored to receive the ACL's Lifetime Achievement Award. I'm especially honored when I look back at the list of previous winners—Chuck Fillmore, Eugene Charniak, Eva Hajičová, Fred Jelinek, Martin Kay, Aravind Joshi, and the others—they're all my heroes.I was of course delighted to learn of this award. The most we can hope for in life is to take part in the conversation, and an award like this means that you've taken part in the conversation.It seems to be a tradition to begin with a few formative anecdotes from childhood. For me, it all begins before I was born. My grandfather, a crusty old country lawyer in southern Indiana, told my father not to bother trying to go to law school. “You don't know English grammar,” he said. “You'll flunk out.” My dad accepted the challenge, bought a book entitled English Grammar, by Smith, Magee, and Seward (1928), and mastered it. He went on to become a very successful lawyer.Fast-forward to when I was in junior high school. My dad was distressed that my English classes looked to him more like social studies, and barely touched on grammar. So he persuaded me—actually, he probably bribed me, but I can't remember what with—to master that same book, English Grammar by Smith, Magee, and Seward. This was a concession, because I was a math nerd, reading only textbooks on trigonometry and calculus, as my way of avoiding the humiliation of playing baseball. But I read the book, and I was amazed. English grammar was just like math! It had the same sorts of rules, the same kinds of abstractions, the same types of puzzles. It was actually fun!In my junior or senior year of high school we had to take something called the Kuder Preference Test, which would help us decide what career to choose. I scored high in math and in language. So my high school counselor told me I should write math books. In fact, she got it exactly backwards. It wasn't that I should do language about math. It was that I should do math about language.I've met any number of computational linguists with a similar story. They grew up not knowing whether they wanted to be a physicist or a poet. They just knew both sounded fascinating. Then they discovered our field.My last near miss happened the week I was drafted into the Army. They gave us a battery of aptitude tests to see what specialties we'd be best for. One of the tests was to see if we should be sent to the Monterey Language School. Looking back on it, I realize now it was testing how well you could understand formal language theory. They'd give you a bunch of rules for an artificial language, and you'd have to say whether different strings were in or not in the language. I'd never seen anything like it, but it was really fun to do. Later I met with a personnel specialist who went over my test scores. I got a 46 out of 50. He ignored that until I pointed it out to him. Then he said, “That's a mistake. Nobody ever gets more than 6 or 7 points on that test.”I said, “No, I think it might be correct.”He said, “It doesn't matter. You're not going to the Monterey Language School. You're going to South Vietnam.”Actually, I didn't go to the Monterey Language School or to South Vietnam. I spent two years in South Carolina, and was glad to be there. How I managed that is a story for another occasion.So I didn't really discover computational linguistics until my third year in graduate school at New York University. In October I passed my oral exam in topics like algebraic topology and complex analysis, by one generous yes and two abstensions. In the subsequent months I discovered more and more facts about myself—for example, that I was never going to figure out a faster way of multiplying matrices, and that fascinating though recursion theory might be, I was never going to prove a theorem that Hartley Rogers would be compelled to include in his next edition. As I surveyed vaguely plausible fields, I realized I had no idea what the next problem to solve would be or even what makes a problem interesting.Then in April, when I had nearly resigned myself to becoming a taxi driver, I discovered New York University's best-kept secret: Naomi Sager's Linguistic String Project. I think it is also computational linguistics' best kept secret as well. She was motivated by the science, not by the performance, and her very impressive work is nowhere near as well-known as it should be. I think her Linguistic String Grammar (Sager 1981) ranks, as a computational specification of English syntax, with Pollard and Sag's Head-driven Phrase Structure Grammar (1994), for thoroughness, insight, and elegance. So, for example, in 1992 when we developed the FASTUS system for information extraction using cascaded finite-state transducers (Hobbs et al. 1997), it was straightforward to copy the rules for Noun Groups straight from her grammar. It's no accident that in the late 1980s during the Strategic Computing Initiative and in the early 1990s in the Message Understanding Conferences, three of the most important efforts were led by Linguistic String Project alumni—Ralph Grishman's group at New York University, Lynette Hirschman's at Unisys, and my group at SRI International. I think the most important lesson I learned from Naomi Sager was to look closely at the data and to take it seriously.My other thesis advisor was Jack Schwartz. He was a polymath, so to speak. I took a course in logic from him. I knew about his book on compilers and the classic Dunford and Schwartz on functional analysis. But when I saw his book on mathematical economics and his book on the theory of relativity, I did some research to see if there was more than one Jack Schwartz. Among his writings was an unpublished Chapter 9 of his compilers book, on parsing natural language, which I of course read.My thesis was on Earley's algorithm applied to natural language. It quickly became apparent that the constraints on phrase structure rules had to be expressed and that one could do that with fairly simple operations on vectors of features, where among the features were what I called the “cores” of the constituents, since they bundled many of the relevant features. My “core” was what linguists came to call “head.” Years later, I ran across Chapter 9 again and reread it, and realized that all the ideas in my thesis were there. So when in 1987 Schwartz told someone that I had anticipated head-driven phrase structure grammar, that was his way of saying he had anticipated head-driven phrase structure grammar.My first job was at Yale University as a very temporary instructor—I think the position is now called “post-doc.” Over the course of the year I became convinced that syntax was a solved problem—something I still believe. But that left me adrift for problems to work on. 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Source: Computational Linguistics
DOI: 10.1162/coli_a_00171
Author: Jerry Hobbs
Institution: University of Southern California
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W2094895311