W14-4705 |
along with preprocessing steps (
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database generation
|
) . 2 . The kind of distributional
|
H92-1095 |
the extracted information for
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database generation
|
. This approach is described
|
H90-1092 |
evaluated on performance on the
|
database generation
|
task in a blind test . Measures
|
P06-2035 |
paper deals with multilingual
|
database generation
|
from parallel corpora . The idea
|
C96-2190 |
plications in text understanding ,
|
database generation
|
fi'om text and computer-based
|
P06-2035 |
. <title> Multilingual Lexical
|
Database Generation
|
from parallel texts in 20 European
|
P05-1061 |
question answer - ing , automatic
|
database generation
|
, and intelligent document searching
|
H90-1070 |
applying the system to much broader
|
database generation
|
projects than those of SCISOR
|
H90-1070 |
engineering required , although current
|
database generation
|
tasks are still too small for
|
H90-1070 |
to semantic interpretation and
|
database generation
|
. In database generation , the
|
W13-4309 |
tremendous relevance in lexical
|
database generation
|
, morphological processing ,
|
H90-1070 |
interpretation and database generation . In
|
database generation
|
, the new knowledge base has
|
J92-1001 |
including information re - trieval ,
|
database generation
|
from text , and machine translation
|
M93-1012 |
include information extraction and
|
database generation
|
tasks suc h as MUC-5 , message
|
W13-4309 |
relevance in cross-lingual lexical
|
database generation
|
, morphological processing ,
|
C90-3077 |
same capabilities , including
|
database generation
|
, question answering , and automatic
|
H90-1070 |
processing-including information retrieval ,
|
database generation
|
, and machine translation --
|