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 127 (Graph Colouring) — Constraint detection
When
used
without
any
qualification
,
a
coloring
of
a
graph
is
almost
always
a
proper
vertex
coloring
,
namely
a
labelling
of
the
graph
's
vertices
with
colors
such
that
no
two
vertices
sharing
the
same
edge
have
the
same
color
.
Since
a
vertex
with
a
loop
-LRB-
i.e.
a
connection
directly
back
to
itself
-RRB-
could
never
be
properly
colored
,
it
is
understood
that
graphs
in
this
context
are
loopless
.
Problem 127 (Graph Colouring) — Detection of the decisions and objects to be modeled
When
used
without
any
qualification
,
a
coloring
of
a
graph
is
almost
always
a
proper
vertex
coloring
,
namely
a
labelling
of
the
graph
's
vertices
with
colors
such
that
no
two
vertices
sharing
the
same
edge
have
the
same
color
.
Since
a
vertex
with
a
loop
-LRB-
i.e.
a
connection
directly
back
to
itself
-RRB-
could
never
be
properly
colored
,
it
is
understood
that
graphs
in
this
context
are
loopless
.
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