NLP for CP
Addressing Constraint Programming with Natural Language Processing
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Correct
predictions are in
blue
. If we detect only a subset of a labelled sentence, we highlight the caught part as
blue
, the missing part
light blue.
False positives
are in
green
and
false negatives
are in
red
.
Problem 025 (Lam's problem) — Constraint detection
Consider
a
111
by
111
binary
matrix
.
The
goal
is
to
put
11
zeros
in
each
row
in
such
a
way
that
each
column
has
11
zeros
,
and
each
pair
of
rows
must
have
exactly
one
zero
in
the
same
column
.
This
problem
is
equivalent
to
finding
a
projective
plane
of
order
10
.
It
is
also
equivalent
to
the
<
111,111,11,11,1
>
BIBD
problem
-LRB-
prob028
-RRB-
.
Problem 025 (Lam's problem) — Detection of the decisions and objects to be modeled
Consider
a
111
by
111
binary
matrix
.
The
goal
is
to
put
11
zeros
in
each
row
in
such
a
way
that
each
column
has
11
zeros
,
and
each
pair
of
rows
must
have
exactly
one
zero
in
the
same
column
.
This
problem
is
equivalent
to
finding
a
projective
plane
of
order
10
.
It
is
also
equivalent
to
the
<
111,111,11,11,1
>
BIBD
problem
-LRB-
prob028
-RRB-
.
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