Ontologically-based
Searching for Jobs in
Linguistics
Deryle Lonsdale
lonz@byu.edu
Funded by:
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The BYU Data Extraction Group
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Group of faculty (5) and students (15)
from CS, Linguistics, SOAIS
Goal: ontology-based data extraction
NSF funding: CISE/IIS/IDM TIDIE
Website: www.deg.byu.edu/
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Papers, presentations
Tools
Demos
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The BYU Data Extraction Group
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Overview
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Ontology-based extraction
Building knowledge sources
Jobs in linguistics (Sproat)
Putting it all together
Some sample results
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Ontologies and IE
Source
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Target
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Document-based IE
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Conceptual modeling (OSM)
Year
Price
1..*
1..*
Make
1..*
has
has
has
0..1 0..1
0..1 0..1
Car
0..1
has
Model 1..*
1..* Mileage
has
has
0..* 0..1
is for
1..*
Feature
1..* PhoneNr
0..1
has
1..*
Extension
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Recognition and Extraction
Car
0001
0002
0003
Year
1989
1998
1994
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Make Model
Mileage Price PhoneNr
Subaru SW
$1900 (336)835-8597
Elantra
(336)526-5444
HONDA ACCORD EX 100K
(336)526-1081
Car
0001
0001
0002
0002
0002
0002
0002
0002
0002
0002
0002
0002
0003
0003
0003
Feature
Auto
AC
Black
4 door
tinted windows
Auto
pb
ps
cruise
am/fm
cassette stereo
a/c
Auto
jade green
gold
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Car-Ads Ontology (textual)
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Car [->object];
Car [0..1] has Year [1..*];
Car [0..1] has Make [1..*];
Car [0...1] has Model [1..*];
Car [0..1] has Mileage [1..*];
Car [0..*] has Feature [1..*];
Car [0..1] has Price [1..*];
PhoneNr [1..*] is for Car [0..*];
PhoneNr [0..1] has Extension [1..*];
Year matches [4]
constant {extract “\d{2}”;
context "([^\$\d]|^)[4-9]\d[^\d]";
substitute "^" -> "19"; },
…
…
End;
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The data-frame library
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Low-level patterns implemented as
regular expressions
Match items such as email addresses,
phone numbers, names, etc.
Mileage matches [8]
constant { extract "\b[1-9]\d{0,2}k"; substitute "[kK]" -> "000"; },
{ extract "[1-9]\d{0,2}?,\d{3}";
context "[^\$\d][1-9]\d{0,2}?,\d{3}[^\d]"; substitute "," -> "";},
{ extract "[1-9]\d{0,2}?,\d{3}";
context "(mileage\:\s*)[^\$\d][1-9]\d{0,2}?,\d{3}[^\d]"; substitute
"," -> "";},
{ extract "[1-9]\d{3,6}";
context "[^\$\d][1-9]\d{3,6}\s*mi(\.|\b\les\b)";},
{ extract "[1-9]\d{3,6}";
context "(mileage\:\s*)[^\$\d][1-9]\d{3,6}\b";};
keyword "\bmiles\b", "\bmi\.", "\bmi\b", "\bmileage\b";
end;
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Lexicons
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Repositories of enumerable classes of
lexical information
FirstNames, LastNames, USstates,
ProvoOremApts, CarMakes, Drugs,
CampGroundFeats, etc.
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Accessing the output
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Extracted information is stored in a
relational database
Results can be queried using SQL
Wide range of views is possible
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Finding jobs in linguistics
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Linguistlist.org, LSA
Email distribution lists (corpora,
langage naturelle, CAAL/ACLA, etc.)
Usual commercial sites (monster.com,
flipdog.com, dice.com)
Word-of-mouth sources
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Sproat’s analysis
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Random sample (224/2250) of LinguistList
postings, 1994-2001
Development vs. research, academic vs.
industrial
Linguists are most often (approx. 80% of
the time) offered development jobs
Linguists hired more for specific tasks (e.g.
grammar, lexicon development) rather than
for more general research-oriented tasks
(e.g. creating new technological approaches.)
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The banner years
Year Academia Industry % Industry
1994
27
2
7%
1995
45
5
10%
1996
52
3
5%
1997
48
3
6%
1998
57
3
5%
1999
56
14
20%
2000
55
43
39%
2001 (mid) 22
10
31%
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Dramatic rise in 1999, 2000
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Steep drop-off since 2001
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Rising demand for technical, computational skills
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Linguistic jobs ontology
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Why?
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user-specifiable constraints
Somewhat closely follows existing
ontologies (e.g. jobs, software)
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Data frames and lexicons
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Language names
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(sub)fields of linguistics
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ethnologue
Linguistlist.org
Tools, toolkits
Software components, programming languages
Linguistics-related job titles
Activities
Responsibilities
Country names
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The corpus
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3237 postings (LinguistList, Corpora, LN,
WoM):
1998
1999
2000
2001
2002
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541
575
871
952
788
Some noise (non-English, factored,
program descriptions, attachments, etc.)
Semi-automatic edits (boilerplate,
publicity blurbs about institutions, etc.)
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Sample output
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Here
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Observations
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270 don’t have linguist* (!)
Demand for knowledge of English
equals that for all other languages
combined (G, F, S, J, C)
Computer/computational background
required for almost 1/3 (1116)
Noticeable amount of headhunting,
particularly in Seattle, DC areas
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Programming languages
700
600
500
400
300
200
100
0
C/C++
Java/Jscript
Prolog
VB
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CGI
Lisp/Python
SQL
XML/XSLT
HTML/SGML
Perl
Tcl
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Popular subfields
700
600
500
400
300
200
100
0
IE/IR
Phonology
Semantics
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Morpho
Pragmatics
MT
NLP
Speech
TESOL/EFL
Phonetics
Syntax
Translation
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Subfields (another perspective)
800
600
400
200
0
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Psycho
Typological
Socioling
Philosophy
Neuro
Acquisition
Lexicography
Anthropo
Historical
Cognition
Philology
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An engineering discipline?
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160 linguistics jobs ending in “engineer”
Software development cycle
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Specific subfields
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research e., software design e.
development e., software e.
software quality e., linguistic test e., linguistic quality e.
linguistic support e., user experience e.
presales e., technical sales e.
web site e.
speech e., voice recognition e., speech recognition application e., speech
e., ASR tuning e., audio e.
dialog e.
tools e.
AI e., NLP e.
knowledge e.
linguist e., natural language e.
staff e.
human factors e., user interface e.
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Paradigms
300
250
200
150
100
50
0
Machine learning
Statistical
Math
Field Methods
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Finite-state
Stoch/Prob
Generative
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Other observations
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Often a job title is not even listed (!)
More in18 of data frames (e.g. email, ph. #)
Great need for (preferably hierarchical)
lexical repositories related to linguistics
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job titles
theoretical frameworks, subfields
typical linguist job activities
linguistic research/development venues
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