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@CODE
DisplayKB(G("icd_hier"),1);
SaveKB("icd_hierarchy.kbb",G("icd_hier"),2);
@@CODE |
@NODES _ROOT
@RULES
_item <-
_itemOpen ### (1)
_xWILD [fails=(_itemClose)] ### (2)
_itemClose ### (3)
@@ |
@NODES _LINE
@PRE
<1,1> cap();
<3,3> cap();
<5,5> cap();
@RULES
# Ex: American\_Sign\_Language
_naturalLanguages [layer=(_Caps )] <- American [s] _xWHITE [star s] Sign [s] _xWHITE [star s] Language [s] @@
@PRE
<1,1> cap();
@RULES
# Ex: ASL
_naturalLanguages [layer=(_Caps )] <- ASL [s] @@
# Ex: Afrikaans
_naturalLanguages [layer=(_Caps )] <- Afrikaans [s] @@
# Ex: Albanian
_naturalLanguages [layer=(_Caps )] <- Albanian [s] @@
# Ex: Amharic
_naturalLanguages [layer=(_Caps )] <- Amharic [s] @@
# Ex: Arabic
_naturalLanguages [layer=(_Caps )] <- Arabic [s] @@
# Ex: Armenian
_naturalLanguages [layer=(_Caps )] <- Armenian [s] @@
# Ex: Azerbaijani
_naturalLanguages [layer=(_Caps )] <- Azerbaijani [s] @@
# Ex: Aztec
_naturalLanguages [layer=(_Caps )] <- Aztec [s] @@
# Ex: Basque
_naturalLanguages [layer=(_Caps )] <- Basque [s] @@
# Ex: Bengali
_naturalLanguages [layer=(_Caps )] <- Bengali [s] @@
# Ex: Bosnian
_naturalLanguages [layer=(_Caps )] <- Bosnian [s] @@
# Ex: Breton
_naturalLanguages [layer=(_Caps )] <- Breton [s] @@
# Ex: Bulgarian
_naturalLanguages [layer=(_Caps )] <- Bulgarian [s] @@
# Ex: Burmese
_naturalLanguages [layer=(_Caps )] <- Burmese [s] @@
# Ex: Cambodian
_naturalLanguages [layer=(_Caps )] <- Cambodian [s] @@
# Ex: Cantonese
_naturalLanguages [layer=(_Caps )] <- Cantonese [s] @@
# Ex: Catalan
_naturalLanguages [layer=(_Caps )] <- Catalan [s] @@
# Ex: Cebuano
_naturalLanguages [layer=(_Caps )] <- Cebuano [s] @@
# Ex: Chamorro
_naturalLanguages [layer=(_Caps )] <- Chamorro [s] @@
# Ex: Chechen
_naturalLanguages [layer=(_Caps )] <- Chechen [s] @@
# Ex: Chinese
_naturalLanguages [layer=(_Caps )] <- Chinese [s] @@
# Ex: Cornish
_naturalLanguages [layer=(_Caps )] <- Cornish [s] @@
# Ex: Corsican
_naturalLanguages [layer=(_Caps )] <- Corsican [s] @@
# Ex: Croatian
_naturalLanguages [layer=(_Caps )] <- Croatian [s] @@
# Ex: Czech
_naturalLanguages [layer=(_Caps )] <- Czech [s] @@
# Ex: Danish
_naturalLanguages [layer=(_Caps )] <- Danish [s] @@
# Ex: Dutch
_naturalLanguages [layer=(_Caps )] <- Dutch [s] @@
# Ex: English
_naturalLanguages [layer=(_Caps )] <- English [s] @@
# Ex: Eskimo
_naturalLanguages [layer=(_Caps )] <- Eskimo [s] @@
# Ex: Esperanto
_naturalLanguages [layer=(_Caps )] <- Esperanto [s] @@
# Ex: Estonian
_naturalLanguages [layer=(_Caps )] <- Estonian [s] @@
# Ex: Faroese
_naturalLanguages [layer=(_Caps )] <- Faroese [s] @@
# Ex: Farsi
_naturalLanguages [layer=(_Caps )] <- Farsi [s] @@
# Ex: Fijian
_naturalLanguages [layer=(_Caps )] <- Fijian [s] @@
# Ex: Filipino
_naturalLanguages [layer=(_Caps )] <- Filipino [s] @@
# Ex: Finnish
_naturalLanguages [layer=(_Caps )] <- Finnish [s] @@
# Ex: Flemish
_naturalLanguages [layer=(_Caps )] <- Flemish [s] @@
# Ex: French
_naturalLanguages [layer=(_Caps )] <- French [s] @@
# Ex: Frisian
_naturalLanguages [layer=(_Caps )] <- Frisian [s] @@
# Ex: Fulani
_naturalLanguages [layer=(_Caps )] <- Fulani [s] @@
# Ex: Galician
_naturalLanguages [layer=(_Caps )] <- Galician [s] @@
# Ex: Georgian
_naturalLanguages [layer=(_Caps )] <- Georgian [s] @@
# Ex: German
_naturalLanguages [layer=(_Caps )] <- German [s] @@
# Ex: Greek
_naturalLanguages [layer=(_Caps )] <- Greek [s] @@
# Ex: Greenlandic
_naturalLanguages [layer=(_Caps )] <- Greenlandic [s] @@
# Ex: Gujarati
_naturalLanguages [layer=(_Caps )] <- Gujarati [s] @@
# Ex: Hausa
_naturalLanguages [layer=(_Caps )] <- Hausa [s] @@
# Ex: Hawaiian
_naturalLanguages [layer=(_Caps )] <- Hawaiian [s] @@
# Ex: Hebrew
_naturalLanguages [layer=(_Caps )] <- Hebrew [s] @@
# Ex: Hellenic
_naturalLanguages [layer=(_Caps )] <- Hellenic [s] @@
# Ex: Hindi
_naturalLanguages [layer=(_Caps )] <- Hindi [s] @@
# Ex: Hmong
_naturalLanguages [layer=(_Caps )] <- Hmong [s] @@
# Ex: Hokkien
_naturalLanguages [layer=(_Caps )] <- Hokkien [s] @@
# Ex: Hungarian
_naturalLanguages [layer=(_Caps )] <- Hungarian [s] @@
# Ex: Icelandic
_naturalLanguages [layer=(_Caps )] <- Icelandic [s] @@
# Ex: Ilokano
_naturalLanguages [layer=(_Caps )] <- Ilokano [s] @@
# Ex: Indonesian
_naturalLanguages [layer=(_Caps )] <- Indonesian [s] @@
# Ex: Irish
_naturalLanguages [layer=(_Caps )] <- Irish [s] @@
# Ex: Italian
_naturalLanguages [layer=(_Caps )] <- Italian [s] @@
# Ex: Japanese
_naturalLanguages [layer=(_Caps )] <- Japanese [s] @@
# Ex: Khmer
_naturalLanguages [layer=(_Caps )] <- Khmer [s] @@
# Ex: Korean
_naturalLanguages [layer=(_Caps )] <- Korean [s] @@
# Ex: Kuna
_naturalLanguages [layer=(_Caps )] <- Kuna [s] @@
# Ex: Kurdish
_naturalLanguages [layer=(_Caps )] <- Kurdish [s] @@
# Ex: Lao
_naturalLanguages [layer=(_Caps )] <- Lao [s] @@
# Ex: Latin
_naturalLanguages [layer=(_Caps )] <- Latin [s] @@
# Ex: Latvian
_naturalLanguages [layer=(_Caps )] <- Latvian [s] @@
# Ex: Lithuanian
_naturalLanguages [layer=(_Caps )] <- Lithuanian [s] @@
# Ex: Macedonian
_naturalLanguages [layer=(_Caps )] <- Macedonian [s] @@
# Ex: Magyar
_naturalLanguages [layer=(_Caps )] <- Magyar [s] @@
# Ex: Malagasy
_naturalLanguages [layer=(_Caps )] <- Malagasy [s] @@
# Ex: Malay
_naturalLanguages [layer=(_Caps )] <- Malay [s] @@
# Ex: Maltese
_naturalLanguages [layer=(_Caps )] <- Maltese [s] @@
# Ex: Mandarin
_naturalLanguages [layer=(_Caps )] <- Mandarin [s] @@
# Ex: Mayan
_naturalLanguages [layer=(_Caps )] <- Mayan [s] @@
# Ex: Mongolian
_naturalLanguages [layer=(_Caps )] <- Mongolian [s] @@
# Ex: Norwegian
_naturalLanguages [layer=(_Caps )] <- Norwegian [s] @@
# Ex: Pashto
_naturalLanguages [layer=(_Caps )] <- Pashto [s] @@
# Ex: Persian
_naturalLanguages [layer=(_Caps )] <- Persian [s] @@
# Ex: Polish
_naturalLanguages [layer=(_Caps )] <- Polish [s] @@
# Ex: Portuguese
_naturalLanguages [layer=(_Caps )] <- Portuguese [s] @@
# Ex: Quechua
_naturalLanguages [layer=(_Caps )] <- Quechua [s] @@
# Ex: Romanian
_naturalLanguages [layer=(_Caps )] <- Romanian [s] @@
# Ex: Russian
_naturalLanguages [layer=(_Caps )] <- Russian [s] @@
# Ex: Serbian
_naturalLanguages [layer=(_Caps )] <- Serbian [s] @@
# Ex: Sinhalese
_naturalLanguages [layer=(_Caps )] <- Sinhalese [s] @@
# Ex: Slovak
_naturalLanguages [layer=(_Caps )] <- Slovak [s] @@
# Ex: Slovenian
_naturalLanguages [layer=(_Caps )] <- Slovenian [s] @@
# Ex: Spanish
_naturalLanguages [layer=(_Caps )] <- Spanish [s] @@
# Ex: Sundanese
_naturalLanguages [layer=(_Caps )] <- Sundanese [s] @@
# Ex: Swahili
_naturalLanguages [layer=(_Caps )] <- Swahili [s] @@
# Ex: Swedish
_naturalLanguages [layer=(_Caps )] <- Swedish [s] @@
# Ex: Tagalog
_naturalLanguages [layer=(_Caps )] <- Tagalog [s] @@
# Ex: Tahitian
_naturalLanguages [layer=(_Caps )] <- Tahitian [s] @@
# Ex: Tajik
_naturalLanguages [layer=(_Caps )] <- Tajik [s] @@
# Ex: Tamil
_naturalLanguages [layer=(_Caps )] <- Tamil [s] @@
# Ex: Telegu
_naturalLanguages [layer=(_Caps )] <- Telegu [s] @@
# Ex: Thai
_naturalLanguages [layer=(_Caps )] <- Thai [s] @@
# Ex: Tibetan
_naturalLanguages [layer=(_Caps )] <- Tibetan [s] @@
# Ex: Turkish
_naturalLanguages [layer=(_Caps )] <- Turkish [s] @@
# Ex: Ukrainian
_naturalLanguages [layer=(_Caps )] <- Ukrainian [s] @@
# Ex: Urdu
_naturalLanguages [layer=(_Caps )] <- Urdu [s] @@
# Ex: Uyghur
_naturalLanguages [layer=(_Caps )] <- Uyghur [s] @@
# Ex: Uzbek
_naturalLanguages [layer=(_Caps )] <- Uzbek [s] @@
# Ex: Vietnamese
_naturalLanguages [layer=(_Caps )] <- Vietnamese [s] @@
# Ex: Welsh
_naturalLanguages [layer=(_Caps )] <- Welsh [s] @@
# Ex: Xhosa
_naturalLanguages [layer=(_Caps )] <- Xhosa [s] @@
# Ex: Yao
_naturalLanguages [layer=(_Caps )] <- Yao [s] @@
# Ex: Yiddish
_naturalLanguages [layer=(_Caps )] <- Yiddish [s] @@
# Ex: Yoruba
_naturalLanguages [layer=(_Caps )] <- Yoruba [s] @@
# Ex: Zapotec
_naturalLanguages [layer=(_Caps )] <- Zapotec [s] @@
# Ex: Zulu
_naturalLanguages [layer=(_Caps )] <- Zulu [s] @@
|
@CODE
fileout("dump.txt");
prlit("dump.txt","\n");
prlit("dump.txt","ALP NUM PUN WHT BLOBS INDENT WALP WCAP WALL\n");
prlit("dump.txt","-------------------------------------------\n");
@@CODE
@NODES _ROOT
# Print out the total count of vars in each line.
@POST
"dump.txt" << rightjustifynum(N("nalpha",1), 3) << " ";
"dump.txt" << rightjustifynum(N("nnum",1), 3) << " ";
"dump.txt" << rightjustifynum(N("npunct",1), 3) << " ";
"dump.txt" << rightjustifynum(N("nwhite",1), 3) << " ";
"dump.txt" << rightjustifynum(N("nblobs",1), 3) << " ";
"dump.txt" << rightjustifynum(N("nindent",1),3) << " ";
"dump.txt" << rightjustifynum(N("walpha",1), 3) << " ";
"dump.txt" << rightjustifynum(N("wcap",1), 3) << " ";
"dump.txt" << rightjustifynum(N("wallcaps",1),3) << "\n";
# noop();
@RULES
_xNIL <- _LINE @@
@POST
prlit("dump.txt", "blank line\n");
@RULES
_xNIL <- _BLANKLINE @@
|
@PATH _ROOT _textZone _LINE
@POST
excise(1,1);
noop();
@RULES
_xNIL <-
_xWHITE [s] ### (1)
@@
@POST
X("up",3) = 1;
"found.txt" << "this\n";
@RULES
_xNIL <-
_language [s] ### (1)
@@
|
@NODES _FOOTER
@POST
"zap.txt" << N("$text") << " - 2\n";
excise(1,1);
@RULES
_xNIL <-
_xWILD [one match=(_beginEnum _endEnum _itemMarker _COMMENT _spacing)] ### (1)
@@
|
@CODE
L("hello") = 0;
@@CODE
#@PATH _ROOT _TEXTZONE _sent _seg
@NODES _seg
# Assume we're here because this is an np.
@CHECK
if (!N(2) && !N(3) && !N(4))
fail(); # Handle the raw alpha alpha elsewhere.
if (!N("noun",6)) # 01/12/05 AM.
fail();
@POST
if (N("verb",6))
X("last verb") = 1; # Last is possibly a verb.
if (numbersagree(N(2),N(6)) )
X("noun agree") = 1;
X("vconj") = vconj(N(6));
xrename("_np");
pncopyvars(N(6),X());
clearpos(X(),1,1); # Zero out token info.
# Heur: assign pos to alphas.
L("tmp6") = N(6);
group(6,6,"_noun");
pncopyvars(L("tmp6"),N(6));
L("tmp5") = N(5);
if (N("adj",5))
{
group(5,5,"_adj");
pncopyvars(L("tmp5"),N(5));
if (N(4))
L("firstj") = N(4);
else
L("firstj") = N(5);
L("lastj") = N(5);
fixadjs(L("firstj"),L("lastj"));
fixnoun(N(6));
}
else if (N("noun",5))
{
group(5,5,"_noun");
pncopyvars(L("tmp5"),N(5));
fixnouns(N(5),N(6));
if (N(4))
fixadjs(N(4),N(4));
}
else if (N("verb",5))
{
group(5,5,"_adj");
pncopyvars(L("tmp5"),N(5));
if (N(4))
L("firstj") = N(4);
else
L("firstj") = N(5);
fixadjs(L("firstj"),N(5));
}
else # don't know; don't care anyway...
pncopyvars(L("tmp5"),N(5));
X("id") = "qseq100 dqa alph-alph";
@RULES
_xNIL <-
_xSTART
_xWILD [star match=(_det _pro)]
_xWILD [star match=(_quan _num _xNUM)]
_adj [star]
_xALPHA
_xALPHA
_xEND
@@
@CHECK
if (!N(2) && !N(3) && !N(4) && !N(5))
fail(); # Handle the raw alpha elsewhere.
if (!N("noun",6))
fail();
if (N("verb",6))
fail();
@POST
if (N("verb",6))
X("last verb") = 1; # Last is possibly a verb.
# if (numbersagree(N(2),N(6)) )
# X("noun agree") = 1;
X("vconj") = vconj(N(6));
L("tmp6") = N(6);
group(6,6,"_noun");
pncopyvars(L("tmp6"),N(6));
xrename("_np");
pncopyvars(N(6),X());
clearpos(X(),1,1); # Zero out token info.
@RULES
_xNIL <-
_xSTART
_xWILD [star match=(_det _pro)]
_xWILD [star match=(_quan _num _xNUM)]
_adj [star]
_noun [star]
_xALPHA
_xEND
@@
@CHECK
if (X("seg type") != "np")
fail();
@POST
L("tmp3") = N(3);
fixnpnonhead(2);
group(3,3,"_noun");
pncopyvars(L("tmp3"),N(3));
fixnoun(N(3));
xrename("_np");
pncopyvars(L("tmp3"),X());
clearpos(X(),1,1); # Zero out token info.
@RULES
_xNIL <-
_xSTART
_xALPHA
_xALPHA
_xEND
@@
|
@NODES _ROOT
@POST
if (N("code", 1)) {
GetWordCodeMappings(N(1));
}
@RULES
_xNIL <-
_term ### (2)
@@
|
@PATH _ROOT
@POST
excise(1,1);
noop();
@RULES
_xNIL <-
_xWHITE [s] ### (1)
@@
|
@NODES _ROOT
@POST
S("language") = N("$text",2);
"lang.txt" << N("$text",2) << "\n";
single();
@RULES
_language <-
_langStart ### (1)
_xWILD [plus fails=(_langEnd)] ### (2)
_langEnd ### (3)
@@
@RULES
_conjugation <-
_startConju ### (1)
_xWILD [plus fails=(\})] ### (2)
\} ### (3)
\} ### (4)
@@
|
@CODE
if (G("pretagged"))
exitpass();
@@CODE
@NODES _TEXTZONE
@POST
S("neg") = 1;
S("mypos") = "VBP";
single();
@RULES
_modal <- won \' t @@
_modal <- can \' t @@
_modal <- cannot @@
_modal <- mayn \' t @@
_modal <- mightn \' t @@
_modal <- shan \' t @@
_modal <- oughtn \' t @@
_modal <- mustn \' t @@
_modal <- don \' t @@
_modal <- doesn \' t @@
_have [layer=(_verb)] <- haven \' t @@
_have [layer=(_verb)] <- hasn \' t @@
_be [layer=(_verb)] <- aren \' t @@
_be [layer=(_verb)] <- isn \' t @@
@POST
S("neg") = 1;
S("mypos") = "VBD";
single();
@RULES
_modal <- couldn \' t @@
_modal <- didn \' t @@
_modal <- shouldn \' t @@
_modal <- wouldn \' t @@
_have [layer=(_verb)] <- hadn \' t @@
_be [layer=(_verb)] <- wasn \' t @@
_be [layer=(_verb)] <- weren \' t @@
_be [layer=(_verb)] <- aren \' t @@
_be [layer=(_verb)] <- isn \' t @@
@POST
group(1,1, "_proSubj");
group(1,1, "_pro");
group(2,3, "am"); # Retokenize.
@RULES
_xNIL <-
I [s]
\' [s]
m [s]
@@
# you're
@POST
group(2,3,"_be");
group(2,2,"_verb");
N("sem",2) = N("stem",2) = "be";
N("number",2) = "any";
chpos(N(2),"VBP");
L("tmp1") = N(1);
group(1,1,"_proSubj");
group(1,1,"_pro");
pncopyvars(L("tmp1"),N(1));
@RULES
_xNIL <-
you
\'
re
@@
# you're
@POST
group(2,3,"_be");
group(2,2,"_verb");
N("sem",2) = N("stem",2) = "be";
N("number",2) = "plural";
chpos(N(2),"VBP");
L("tmp1") = N(1);
group(1,1,"_proSubj");
group(1,1,"_pro");
pncopyvars(L("tmp1"),N(1));
@RULES
_xNIL <-
we
\'
re
@@
# you're
@POST
group(2,3,"_be");
group(2,2,"_verb");
N("sem",2) = N("stem",2) = "be";
N("number",2) = "plural";
chpos(N(2),"VBP");
L("tmp1") = N(1);
group(1,1,"_proSubj");
group(1,1,"_pro");
pncopyvars(L("tmp1"),N(1));
@RULES
_xNIL <-
they
\'
re
@@
@RULES
_num <-
_xNUM
\' [s]
s [s]
@@
#@RULES
#_aposS <-
# \' [s]
# s [s]
# @@
# alpha '
@POST
N("apostrophe",1) = 1;
excise(2,2); # Trash the apostrophe.
@RULES
_xNIL <-
_xALPHA [s]
\' [trigger]
@@
# Some mumbles.
@PRE
<1,1> varz("NOSP");
<2,2> var("NOSP");
@POST
++X("nmumbles");
single();
@RULES
_mumble <-
_xWILD [one match=(_xALPHA _xNUM \_ )]
_xWILD [plus match=(_xALPHA _xNUM \_ )]
@@
# Some mumbles.
@POST
++X("nmumbles");
single();
@RULES
_mumble <-
_xALPHA
_xNUM
@@
_noun <-
_noun
\/
_noun
@@
@RULES
_dbldash <- \- \- \- @@ # Triple!
_dbldash <- \- \- @@
@POST
group(2,2,"_dbldash");
@RULES
_xNIL <-
_xWHITE [s plus]
\-
_xWHITE [s plus]
@@
|
# Fetch the first word-concept in the KB dictionary hierarchy.
L("return_con") = dictfirst(L("")); |
# show how we can create a concept like noun and assign it as the value of a word's attribute. We create the concepts named words and noun as children to the root of the KB (concept), and then make the concept book a child of words
G("words") = makeconcept(findroot(), "words");
G("noun") = makeconcept(findroot(),"noun");
G("noun_book") = makeconcept(G("words"),"book"); |
@PATH _ROOT _pronunciations _headerZone _LINE
@POST
addstrval(X("pronunciation",2),"phonetic",N("$text",1));
"debug.txt" << N("$text",1) << "\n";
@RULES
_xNIL <-
_phonetic ### (1)
@@
|
###############################################
# FILE: XML OverallSchema.pat #
# SUBJ: Put together the last pieces of an XML#
# document #
# AUTH: Paul Deane #
# CREATED: 14/Jan/01
# DATE OF THIS VERSION: 31/Aug/01 #
# Copyright
###############################################
###############################
# CONTENTS #
# In code section: sorting #
# algorithm that organizes #
# the data from DTD info #
# #
# In main rule: overall #
# structure of an XML file #
###############################
@CODE
if (G("Organize DTD")==1) {
#At this point the DTD knowledge base is complete.
#So the next task is to sort the element list under
#the gram tab so that the information is ordered in
#the order we want to make generation of passes as
#natural as possible.
G("CurrentConcept") = down(G("Elements")) ;
G("CurrentConceptName") = conceptname(G("CurrentConcept")) ;
G("Continue") = 1 ;
G("CurrentChildConcept") = down(G("CurrentConcept")) ;
G("CurrentChildConceptName") = conceptname(G("CurrentChildConcept")) ;
G("ReferenceIDforConcept") = findconcept(G("Elements"),G("CurrentChildConceptName")) ;
G("NextConcept") = next(G("ReferenceIDforConcept")) ;
#This is a sorting algorithm that puts the elements of
#the DTD data we've been creating into alphabetic order
G("attrName") = "sortedYet" ;
while ( G("Continue") != 0 ) {
if (G("CurrentConcept") == 0 ) {
G("Continue") = 0 ;
}
else if ( G("CurrentChildConcept") == 0 &&
numval(G("CurrentConcept"),G("attrName")) == 0
) {
replaceval(G("CurrentConcept"),G("attrName"),1) ;
G("CurrentConcept") = down(G("Elements")) ;
G("CurrentConceptName") = conceptname(G("CurrentConcept")) ;
G("CurrentChildConcept") = down(G("CurrentConcept")) ;
if (G("CurrentChildConcept")!=0) {
G("CurrentChildConceptName") = conceptname(G("CurrentChildConcept")) ;
G("ReferenceIDforConcept") = findconcept(G("Elements"),G("CurrentChildConceptName")) ;
G("NextConcept") = next(G("ReferenceIDforConcept")) ;
}
else {
G("CurrentChildConceptName") = " " ;
G("ReferenceIDforConcept") = 0 ;
G("NextConcept") = 0 ;
}
}
else if (G("CurrentChildConcept") == 0 ) {
G("CurrentConcept") = next(G("CurrentConcept")) ;
G("CurrentConceptName") = conceptname(G("CurrentConcept")) ;
G("CurrentChildConcept") = down(G("CurrentConcept")) ;
if (G("CurrentChildConcept")!=0) {
G("CurrentChildConceptName") = conceptname(G("CurrentChildConcept")) ;
G("ReferenceIDforConcept") = findconcept(G("Elements"),G("CurrentChildConceptName")) ;
G("NextConcept") = next(G("ReferenceIDforConcept")) ;
}
else {
G("CurrentChildConceptName") = " " ;
G("ReferenceIDforConcept") = 0 ;
G("NextConcept") = 0 ;
}
}
else if (
G("CurrentChildConcept") != 0 &&
G("ReferenceIDforConcept") != 0 &&
G("CurrentChildConceptName") != " " &&
numval(G("ReferenceIDforConcept"),G("attrName")) == 0 &&
!strequal(G("CurrentConceptName"),G("CurrentChildConceptName"))
) {
movecleft(G("ReferenceIDforConcept")) ;
G("NextConcept") = next(G("ReferenceIDforConcept")) ;
if ( G("NextConcept") == G("CurrentConcept") ) {
G("CurrentChildConcept") = next(G("CurrentChildConcept")) ;
if (G("CurrentChildConcept") != 0 ) {
G("CurrentChildConceptName") = conceptname(G("CurrentChildConcept")) ;
G("ReferenceIDforConcept") = findconcept(G("Elements"),G("CurrentChildConceptName")) ;
G("NextConcept") = next(G("ReferenceIDforConcept")) ;
}
else { replaceval(G("CurrentConcept"),G("attrName"),1) ;
G("CurrentConcept") = down(G("Elements")) ;
G("CurrentConceptName") = conceptname(G("CurrentConcept")) ;
G("CurrentChildConcept") = down(G("CurrentConcept")) ;
if (G("CurrentChildConcept")!=0) {
G("CurrentChildConceptName") = conceptname(G("CurrentChildConcept")) ;
G("ReferenceIDforConcept") = findconcept(G("Elements"),G("CurrentChildConceptName")) ;
G("NextConcept") = next(G("ReferenceIDforConcept")) ;
}
else {
G("CurrentChildConceptName") = " " ;
G("ReferenceIDforConcept") = 0 ;
G("NextConcept") = 0 ;
}
}
}
}
else if ( G("CurrentConcept") != 0 &&
G("CurrentChildConcept") != 0
) {
G("CurrentChildConcept") = next(G("CurrentChildConcept")) ;
G("CurrentConceptName") = conceptname(G("CurrentConcept")) ;
if (G("CurrentChildConcept")!=0) {
G("CurrentChildConceptName") = conceptname(G("CurrentChildConcept")) ;
G("ReferenceIDforConcept") = findconcept(G("Elements"),G("CurrentChildConceptName")) ;
G("NextConcept") = next(G("ReferenceIDforConcept")) ;
}
else {
G("CurrentChildConceptName") = " " ;
G("ReferenceIDforConcept") = 0 ;
G("NextConcept") = 0 ;
}
}
else {
G("Continue") = 0 ;
}
}
G("Attr") = "sortedYet" ;
G("CurrentConcept") = down(G("Entities")) ;
while ( G("CurrentConcept") != 0 ) {
"hierDtd.log" << conceptpath(G("CurrentConcept")) << "\n" ;
G("nextC") = next(G("CurrentConcept")) ;
G("CurrentConcept") = G("nextC") ;
}
G("CurrentConcept") = down(G("Elements")) ;
while ( G("CurrentConcept") != 0 ) {
rmattr(G("CurrentConcept"),"sortedYet") ;
"hierDtd.log" << conceptpath(G("CurrentConcept")) << "\n" ;
G("CurrentChildConcept") = down(G("CurrentConcept")) ;
while (G("CurrentChildConcept") != 0 ) {
rmattr(G("CurrentChildConcept"),"sortedYet") ;
"hierDtd.log" << conceptpath(G("CurrentChildConcept")) << "\n" ;
G("nextC") = next(G("CurrentChildConcept")) ;
G("CurrentChildConcept") = G("nextC") ;
}
G("nextC") = next(G("CurrentConcept")) ;
G("CurrentConcept") = G("nextC") ;
}
}
@@CODE
@NODES _ROOT
@RULES
_XMLDocument [unsealed] <-
_Prolog [one] ### (1)
_Element [one] ### (2)
_Misc [star] ### (3)
@@
|
@CODE
DisplayKB(G("icd_codes"),1);
SaveToKB(G("icd_codes"), "icd_mapping.kbb");
@@CODE |
@PATH _ROOT _headerZone _Experience _headerZone _LINE
@RULES
_dateRange <-
_xNUM ### (1)
to ### (2)
_xWILD [match=(_xNUM present)] ### (3)
@@
|
@CODE
L("hello") = 0;
@@CODE
@NODES _sent
# np lists...
@POST
if (pnname(N(7)) != "_np")
{
nountonp(7,1);
}
group(2,7,"_np");
N("list-np",2) = 1;
# listadd(7,2,"true");
@RULES
_xNIL <-
\,
_xWILD [one match=(_noun _np)]
\,
_xWILD [one match=(_noun _np)]
\, [opt]
_conj
_xWILD [one match=(_noun _np)]
_xWILD [one lookahead fail=(_noun _xALPHA)]
@@
# Extend list backwards.
@CHECK
if (!N("list-np",4))
fail();
@POST
listadd(4,2,"true");
@RULES
_xNIL <-
_xWILD [one fail=(_det _quan _num _xNUM _adj _noun)]
_xWILD [one match=(_noun _np)]
\,
_np
@@
_xNIL <-
_xSTART
_xWILD [one match=(_noun _np)]
\,
_np
@@
@POST
nountonp(2,1);
@RULES
_xNIL <-
_xSTART
_noun
_xWILD [one lookahead fail=(_noun _xALPHA)]
@@
# cap's adj
# cap's noun
# Note: "John's green" could mean "John IS green...".
#@CHECK
# if (!N("apos-s",1))
# fail();
#@POST
# L("tmp") = N(1);
# group(1,1,"_adj");
# pncopyvars(L("tmp"),N(1));
#@RULES
#_xNIL <-
# _caps
# _xWILD [one lookahead match=(_noun _adj)]
# @@
# noun alpha adj
@CHECK
if (!N("verb",2))
fail();
if (!vconjq(N(2),"-en"))
fail();
@POST
L("tmp2") = N(2);
group(2,2,"_verb");
pncopyvars(L("tmp2"),N(2));
L("v") = N(2);
group(2,2,"_vg");
mhbv(N(2),L("neg"),0,0,0,0,L("v"));
pncopyvars(L("tmp2"),N(2));
# N("voice",2) = "passive";
N("verb node",2) = L("v");
clearpos(N(2),1,0); # Zero out token info.
@RULES
_xNIL <-
_noun
_xALPHA
_xWILD [one lookahead fail=(_noun _np)]
@@
# noun alpha vg
# Too broad. Too old. #
#@CHECK
# if (!N("noun",2))
# fail();
# if (N("adv",2))
# fail(); # Too ambiguous...
#@POST
# L("tmp2") = N(2);
# group(2,2,"_noun");
# pncopyvars(L("tmp2"),N(2));
#@RULES
#_xNIL <-
# _noun
# _xALPHA
# _xWILD [one lookahead match=(_verb _vg)]
# @@
# vg adj alpha alpha
@CHECK
if (!N("noun",3) && !N("adj",3))
fail();
if (!N("noun",4) && !N("adj",4))
fail();
@POST
L("tmp3") = N(3);
L("tmp4") = N(4);
if (N("adj",3))
{
group(3,3,"_adj");
pncopyvars(L("tmp3"),N(3));
fixadj(N(3));
}
else
{
group(3,3,"_noun");
pncopyvars(L("tmp3"),N(3));
}
if (N("noun",4))
group(4,4,"_noun");
else
group(4,4,"_adj");
pncopyvars(L("tmp4"),N(4));
if (pnname(N(4)) == "_adj")
fixadj(N(4));
group(2,4,"_np");
pncopyvars(L("tmp4"),N(2));
clearpos(N(2),1,1); # Zero out token info.
@RULES
_xNIL <-
_vg
_xWILD [plus match=(_det _quan _num _xNUM _adj)]
_xALPHA
_xALPHA
_xWILD [plus lookahead match=(_prep _conj _qEOS _fnword _xEND)]
@@
# apos-s alpha
#@CHECK
# if (!N("apos-s",1))
# fail();
#@POST
# L("tmp2") = N(2);
# if (N("noun",2))
# group(2,2,"_noun");
# else if (N("adj",2))
# group(2,2,"_adj");
# else if (N("adv",2))
# group(2,2,"_adv");
# pncopyvars(L("tmp2"),N(2));
#@RULES
#_xNIL <-
# _adj
# _xALPHA
# _xWILD [one lookahead match=(_prep _conj _qEOS _fnword _xEND)]
# @@
# there vg np
@CHECK
if (N("there-vg",2))
fail();
@POST
N("there-vg",2) = 1;
fixvg(N(2),"active","VBP");
@RULES
_xNIL <-
there [s]
_vg [lookahead]
_np
@@
# det alpha noun
@POST
L("tmp2") = N(2);
if (N("adj",2))
{
group(2,2,"_adj");
fixadj(N(2));
}
else if (N("noun",2))
group(2,2,"_noun");
else if (N("adv",2))
group(2,2,"_adv");
else
group(2,2,"_noun"); # Loop guard. # 06/19/05
pncopyvars(L("tmp2"),N(2));
@RULES
_xNIL <-
_xWILD [plus match=(_det _quan _num _xNUM _adj)]
_xALPHA
_noun
@@
# vg _adj _noun _fnword
@POST
pncopyvars(3);
sclearpos(1,0); # Zero out token info.
singler(2,3);
@RULES
_np <-
_vg
_adj
_noun
_xWILD [one lookahead fail=(_noun _xALPHA)]
@@
# det adj noun noun
@CHECK
L("last") = lasteltnode(3);
if (N(1))
L("first") = N(1);
else if (N(2))
L("first") = N(2);
else
L("first") = N(3);
if (!numbersagree(L("first"),L("last")))
S("disagree") = 1;
@POST
# if (S("disagree"))
# {
# # Check multiple nouns...
# group(1,2,"_np");
# }
# else
# {
L("tmp") = lasteltnode(3);
group(1,3,"_np");
pncopyvars(L("tmp"),N(1));
clearpos(N(1),1,1); # Zero out token info.
# }
@RULES
_xNIL <-
_xWILD [plus match=(_det _quan _num _xNUM)]
_adj [star]
_noun [plus]
_xWILD [one lookahead fail=(_xALPHA _aposS)]
@@
# det quan adj alpha
# Todo: agreement checks here.
@CHECK
if (N("pos200 a-v",3))
fail(); # Loop guard.
@POST
N("pos200 a-v",3) = 1; # Loop guard.
L("last") = lasteltnode(2);
L("tmp3") = N(3);
if (!N("noun",3))
{
# etc.
}
else
{
if (numbersagree(N(2),N(3))) # Agreement of range of nodes.
{
if (G("error"))
"err.txt" << "Agreement " << L("need") << "\n";
}
else if (N("verb",3))
{
group(3,3,"_verb");
pncopyvars(L("tmp3"),N(3));
clearpos(N(3),1,0); # Zero out token info.
}
}
@RULES
_xNIL <-
_xSTART
_xWILD [plus match=(_det _quan _num _xNUM _adj)]
_xALPHA
_xWILD [one lookahead match=(_adv _advl _prep)]
@@
@CHECK
if (!N("noun",2))
fail();
@POST
L("tmp2") = N(2);
group(2,2,"_noun");
pncopyvars(L("tmp2"),N(2));
@RULES
_xNIL <-
_xWILD [plus match=(_det _quan _num _xNUM _adj)]
_xALPHA
_xWILD [one lookahead match=(_vg _verb)]
@@
# prep alpha
@CHECK
if (!N("noun",2) && !N("adj",2) && !N("unknown",2))
fail();
@POST
L("tmp2") = N(2);
if (N("noun",2) || N("unknown",2))
{
group(2,2,"_noun");
pncopyvars(L("tmp2"),N(2));
if (number(N(2)) == "plural")
chpos(N(2),"NNS");
else if (N("unknown",2) && strendswith(N("$text",2),"s"))
chpos(N(2),"NNS");
}
else
{
group(2,2,"_adj");
pncopyvars(L("tmp2"),N(2));
fixadj(N(2));
}
nountonp(2,1);
@RULES
_xNIL <-
_xWILD [one match=(_prep) except=(to)]
_xALPHA
_xWILD [lookahead one match=(_prep _conj \, _fnword _xEND)]
@@
# vg , noun vg
@POST
nountonp(3,1);
@RULES
_xNIL <-
_xWILD [one match=(_vg)]
\, [opt]
_noun
\, [opt lookahead]
_xWILD [one match=(_vg)]
@@
# noun alpha noun
@CHECK
if (!N("verb",2))
fail();
if (N("noun",2))
fail();
@POST
L("tmp2") = N(2);
group(2,2,"_verb");
L("v") = N(2);
pncopyvars(L("tmp2"),N(2));
group(2,2,"_vg");
mhbv(N(2),L("neg"),0,0,0,0,L("v"));
pncopyvars(L("tmp2"),N(2));
N("voice",2) = "active";
clearpos(N(2),1,0); # Zero out token info.
@RULES
_xNIL <-
_noun
_xALPHA
_noun
@@
# vg noun aposS
# prep noun aposS
@POST
chpos(N(2),"POS"); # Assumed.
L("tmp2") = lasteltnode(2);
group(2,3,"_adj");
pncopyvars(L("tmp2"),N(2));
clearpos(N(2),1,0);
N("possessive",2) = 1;
if (pnname(N(1)) == "_vg")
if (!N("voice",1))
N("voice",1) = "active";
@RULES
_xNIL <-
_xWILD [one match=(_vg _verb _prep _conj \,)]
_noun [plus]
_aposS
@@
# adj alpha fnword
@CHECK
if (!N("noun",2))
fail();
@POST
L("tmp2") = N(2);
group(2,2,"_noun");
pncopyvars(L("tmp2"),N(2));
@RULES
_xNIL <-
_adj
_xALPHA
_xWILD [lookahead one match=(_fnword)]
@@
# fnword noun vg
@POST
dqaninfo(0,0,0,2); # Cleanup. # 05/25/07 AM.
groupnp();
@RULES
_xNIL <-
_xWILD [one match=(_fnword)]
_noun [plus]
_xWILD [one lookahead match=(_vg)]
@@
# apposition, appositive.
# vg np , noun , prep
@POST
# Todo: compose...
L("tmp2") = N(2);
L("tmp4") = N(4);
if (pnname(N(4)) == "_noun")
{
nountonp(4,1);
}
group(2,5,"_np");
pncopyvars(L("tmp2"),N(2));
pncopyvars(L("tmp4"),N(2));
clearpos(N(2),1,0); # Zero out token info.
@RULES
_xNIL <-
_xWILD [one match=(_verb _vg _fnword _prep _conj _clause)]
_np
_xWILD [one match=( \, _dbldash)]
_xWILD [one match=(_noun _np)]
_xWILD [one match=( \, _dbldash)]
_xWILD [one lookahead match=(_prep _vg)]
@@
# vg np , noun , prep
@POST
# Todo: compose...
L("tmp2") = N(2);
L("tmp4") = N(4);
if (pnname(N(4)) == "_noun")
{
nountonp(4,1);
}
group(2,4,"_np");
pncopyvars(L("tmp2"),N(2));
pncopyvars(L("tmp4"),N(2));
clearpos(N(2),1,0); # Zero out token info.
N("ne",2) = 0;
@RULES
_xNIL <-
_xWILD [one match=(_verb _vg _fnword _prep)]
_np
\,
_xWILD [one match=(_noun _np)]
_xWILD [one lookahead match=(_qEOS _xEND)]
@@
# noun alpha vg
# assume spell correct hasn't found verb.
@CHECK
if (!N("unknown",2))
fail();
@POST
L("tmp2") = N(2);
group(2,2,"_noun");
pncopyvars(L("tmp2"),N(2));
@RULES
_xNIL <-
_xWILD [one match=(_noun _np)]
_xALPHA
_xWILD [one lookahead match=(_verb _vg)]
@@
# neither noun nor
@POST
if (nonliteral(N(1)))
pnrename(N(1),"_det");
else
group(1,1,"_det");
chpos(N(1),"CC");
chpos(N(3),"CC");
@RULES
_xNIL <-
_xWILD [s one match=(neither) except=(_det)] # Loop guard.
_xWILD [one lookahead match=(_noun _np)]
nor [s]
@@
# Some clausal pattern...
# vg np prep np vg
# Looking for a 2nd vg to be passive.
@CHECK
if (N("fixed",5))
fail();
@POST
L("vb") = N("verb node",5);
fixverb(L("vb"),"passive","VBP");
N("fixed",5) = 1; # To avoid infinite recursion.
@RULES
_xNIL <-
_vg
_np
_prep
_np
_vg
@@
# noun noun
# dqan
@POST
L("tmp2") = lasteltnode(2);
nountonp(2,1);
N("ne",2) = 0;
if (pnname(N(3)) == "_vg")
if (!N("voice",3))
N("voice",3) = "active";
@RULES
_xNIL <-
_xWILD [one match=(_xSTART _qEOS _np)]
_noun [plus]
_xWILD [one lookahead match=(_verb _vg _adv _advl _np \,)]
@@
# vg to vg
# used to make
#@POST
# # Assign infinitive.
# L("n") = pndown(N(3));
# if (pnname(L("n")) == "_verb")
# pnreplaceval(L("n"),"inf",1);
# L("v") = N("verb node",3);
# if (L("v"))
# chpos(L("v"),"VB"); # infinitive.
# L("v") = N("verb node",1);
# if (L("v"))
# fixverb(L("v"),"active",0);
#
# L("tmp3") = N(3);
# group(1,3,"_vg");
# pncopyvars(L("tmp3"),N(1));
# # N("voice") ?
#@RULES
#_xNIL <-
# _vg
# to [s]
# _vg
# @@
# prep np and np
# check agreement?
@PRE
<2,2> varne("glom","left");
<4,4> varne("glom","right");
@POST
if (pnname(N(4)) == "_noun")
{
group(4,4,"_np");
N("bracket",4) = 1;
}
if (pnname(N(2)) == "_noun")
{
nountonp(2,1);
}
group(2,4,"_np");
N("compound-np",2) = 1;
clearpos(N(2),1,0);
@RULES
_xNIL <-
_xWILD [one match=(_prep)]
_xWILD [one match=(_np _noun)]
_conj
_xWILD [one match=(_np _noun)]
_xWILD [one lookahead match=(_verb _vg _prep)]
@@
# np , alpha conj alpha np
@CHECK
if (!N("noun",3))
fail();
if (!N("adv",6))
fail();
@POST
L("tmp6") = N(6);
L("tmp3") = N(3);
group(6,6,"_adv");
pncopyvars(L("tmp6"),N(6));
group(3,3,"_noun");
pncopyvars(L("tmp3"),N(3));
fixnoun(N(3));
@RULES
_xNIL <-
_xWILD [one match=(_np _noun)]
\,
_xALPHA
\, [opt]
_conj
_xALPHA
_xWILD [one lookahead match=(_np)]
@@
# verb alpha prep
@CHECK
if (N("pos num",2) != 2)
fail();
if (!N("noun",2))
fail();
@POST
L("tmp2") = N(2);
group(2,2,"_noun");
pncopyvars(L("tmp2"),N(2));
fixnoun(N(2));
nountonp(2,1);
@RULES
_xNIL <-
_xWILD [one match=(_verb _vg)]
_xALPHA
_xWILD [one lookahead match=(_prep)]
@@
# verb dqan alpha
@CHECK
if (!N("noun",6))
fail();
# Check noun agreement...
@POST
L("tmp6") = N(6);
group(6,6,"_noun");
pncopyvars(L("tmp6"),N(6));
fixnoun(N(6));
dqaninfo(2,3,4,5);
S("olast") = 6;
S("last") = S("lastn") = S("lastan") = N(6);
groupnp();
@RULES
_xNIL <-
_xWILD [one match=(_verb _vg)]
_det [opt]
_xWILD [star match=(_xNUM _quan _num)]
_adj [star]
_noun [plus]
_xALPHA
_xWILD [one lookahead match=(_qEOS _fnword _xEND)]
@@
# np vg prep dqan alpha alpha
@CHECK
# Check tenses.
if (!N("noun",8) || !N("noun",9))
fail();
@POST
L("tmp8") = N(8);
L("tmp9") = N(9);
group(9,9,"_noun");
pncopyvars(L("tmp9"),N(9));
group(8,8,"_noun");
pncopyvars(L("tmp8"),N(8));
@RULES
_xNIL <-
_np
_vg
_prep
_det [star]
_xWILD [star match=(_quan _num _xNUM)]
_adj [star]
_noun [star]
_xALPHA
_xALPHA
_xWILD [one lookahead match=(_prep _fnword _clausesep)]
@@
# of dqan and noun
@POST
group(2,4,"_np");
N("bracket",2) = 1;
@RULES
_xNIL <-
of [s]
_noun [plus]
_conj
_noun
_xWILD [one lookahead match=(_vg _verb _prep _qEOS _xEND)]
@@
|
@NODES _LINE
@RULES
# Taking out the big list of cities. #
_CityName <- _xWILD [s one match=( _cityPhrase _cityWord)] @@
|
@PATH _ROOT _paragraph _sentence
@POST
S("comment") = makeconcept(N("object",1),"comment");
addstrval(S("comment"),"position",N("$text",9));
addstrval(S("comment"),"commentor",N("$text",10));
single();
@RULES
_event <-
_eventAnaphora [s] ### (1)
_prep [s] ### (2)
_det [s] ### (3)
_xWILD [s plus except=(_companyMarker)] ### (4)
_companyMarker [s] ### (5)
for [s] ### (6)
_money [s] ### (7)
_be [s] ### (8)
_position [s] ### (9)
_commentor [s] ### (10)
@@
@POST
S("comment") = makeconcept(N("object",1),"comment");
addstrval(S("comment"),"position",N("$text",6));
addstrval(S("comment"),"degree",N("$text",5));
addstrval(S("comment"),"field",N("$text",11));
single();
@RULES
_event <-
_eventAnaphora [s] ### (1)
_conj [s optional] ### (2)
_company [s] ### (3)
_have [s] ### (4)
_adv [s] ### (5)
strengthened [s] ### (6)
_company [s] ### (7)
hold [s] ### (8)
on [s] ### (9)
_det [s] ### (10)
_xWILD [s plus except=(_field)] ### (11)
_field [s] ### (12)
@@ |
@PATH _ROOT _LINE
# Should be a header from caps, not one from kb. Need to flag.
@POST
N("hi hdr conf") = 0;
N("hi hdr class") = "NULL";
if (N("end education hdr"))
N("hi hdr class") = "edu";
else if (N("end skills hdr"))
N("hi hdr class") = "skills";
else if (N("end experience hdr"))
N("hi hdr class") = "exp";
else if (N("education hdrs"))
N("hi hdr class") = "edu";
else if (N("skills hdrs"))
N("hi hdr class") = "skills";
else if (N("experience hdrs"))
N("hi hdr class") = "exp";
@RULES
_xNIL <- _header @@
|
@NODES _LINE
@PRE
<1,1> cap();
<1,1> length(9);
@RULES
# Ex: Objective
_ObjectiveHeaderWord [layer=(_headerWord )] <- _xWILD [min=1 max=1 s match=("Objective")] @@
|
# Compute a stem for nouns and verbs
@CODE
G("stem") = stem("lounging");
@@CODE |
@PATH _ROOT _paragraph _sentence
###############################################
# Ronald DiPietro (a Certified Public Accountant)
###############################################
@POST
S("con") = AddPerson(N(1),0);
AddUniqueStr(S("con"),"title",N("title",2));
single();
@RULES
_person <-
_person ### (1)
_titleParen ### (2)
@@
###############################################
# U.S. District Magistrate Judges Amanda M. Knapp of and Moose Manhold
###############################################
@PRE
<1,1> var("plural");
@POST
AddPeople(N(2),"title",N("$text",1));
single();
@RULES
_titleConj <-
_title ### (1) ### (2)
_xWILD [plus match=(_titleCaps _person \, and all the _residentOf)] ### (2) ### (3)
@@
###############################################
# U.S. District Magistrate Judge Amanda M. Knapp of the Northern District of Ohio
###############################################
@POST
if (N(3)) {
S("con") = AddPerson(N(2),N(3));
} else {
S("con") = AddPerson(N(2),0);
}
if (N("title",1))
AddUniqueStr(S("con"),"title",N("title",1));
else
AddUniqueStr(S("con"),"title",N("$text",1));
if (N("agency",1))
AddUniqueStr(S("con"),"agency",N("agency",1));
single();
@RULES
_person <-
_title ### (1)
_person ### (3)
_ofRegion [opt] ### (4)
@@
|
@NODES _ROOT
@RULES
_choiceElement [unsealed] <-
_whiteSpace [opt] ### (1)
\| ### (2)
_whiteSpace [opt] ### (3)
_cp ### (4)
_xWILD [opt matches=("*" "+" "?")] ### (5)
@@
_seqElement [unsealed] <-
_whiteSpace [opt] ### (1)
\, [one] ### (2)
_whiteSpace [opt] ### (3)
_cp [one] ### (4)
_xWILD [opt matches=("*" "+" "?")] ### (5)
@@
|
# Convert a relative URL to an absolute URL
@CODE
"output.txt"
<< resolveurl("http://www.abcd.edu/x/y/z.html", "../gif/img1.gif")
<<
"\n";
prints out:
http://www.abcd.edu/x/gif/img1.gif |
@CODE
L("hello") = 0;
@@CODE
@NODES _TEXTZONE
@POST
excise(1,1);
@RULES
_xNIL <-
_xWHITE [plus]
@@
|
@NODES _LINE
@PRE
<2,2> length(1);
@POST
L("text") = N("$text");
if (L("text") != "(") {
L("bullet") = getconcept(G("format"),"bullet");
L("con") = AddUniqueCon(L("bullet"),L("text"));
X("bullet") = 1;
IncrementCount(L("con"),"count");
single();
}
@RULES
_bullet <-
_xSTART ### (1)
_xWILD [one match=(_xCTRL _xPUNCT) fail=(\()] ### (2)
@@
|
@PATH _ROOT _doctypedecl
@POST
G("CurrentElementName") = str(N("ElementName",1)) ;
noop() ;
@@POST
@RULES
_xNIL <-
_ElementDeclStart [one] ### (1)
@@
@@RULES
@POST
G("CurrentElementName") = 0 ;
noop() ;
@@POST
@RULES
_xNIL <-
_EndTag [one] ### (1)
@@
@@RULES
@RULES
_Mixed <-
_PCDataStart [one] ### (1)
_xWILD [plus fail=("\) ")] ### (2)
_whiteSpace [opt] ### (3)
\) [one] ### (4)
\* [one] ### (5)
@@
_Mixed <-
_PCDataStart [one] ### (1)
_whiteSpace [opt] ### (2)
\) [one] ### (3)
@@
@@RULES
@CHECK
if (strequal(str(N("$text",1)),"EMPTY") ||
strequal(str(N("$text",1)),"ANY")) {
fail() ;
}
@@CHECK
@POST
S("buffer1") = str(N("$text",1)) ;
S("buffer2") = str(N("$text",2)) ;
if (N("$text",1) && N("$text",2)) {
S("ChildElementName") = S("buffer1") + S("buffer2") ;
}
else if ( N("$text",1)) {
S("ChildElementName") = S("buffer1") ;
}
else if ( N("$text",2)) {
S("ChildElementName") = S("buffer2") ;
}
G("CurrentConcept") = findconcept(G("Elements"),G("CurrentElementName")) ;
G("CurrentChildConcept") = findconcept(G("CurrentConcept"),S("ChildElementName")) ;
if (G("CurrentChildConcept") == 0 ) {
G("CurrentChildConcept") = makeconcept(G("CurrentConcept"),S("ChildElementName")) ;
G("ReferenceIDforConcept") = findconcept(G("Elements"),S("ChildElementName")) ;
if (G("ReferenceIDforConcept")==0) {
makeconcept(G("Elements"),S("ChildElementName")) ;
}
}
single() ;
@@POST
@RULES
_cp <-
_xWILD [s one matches=("_xALPHA" "_" ":")] ### (1)
_xWILD [s star matches=("_xALPHA" "_xNUM" "." "-" "_" ":")] ### (2)
_xWILD [s opt matches=("?" "*" "+")] ### (3)
@@
@@RULES
@RULES
_cp <-
\( [one] ### (1)
_PEReference [one] ### (2)
\) [one] ### (3)
_xWILD [opt match=("?" "+" "*")] ### (4)
@@
@@RULES
|
@CODE
DispKB();
@@CODE |
@NODES _split
@POST
"test.log" << X("split") << ": " << N("$text", 1) << "\n";
L("code") = N("$text", 1);
L("alt_code_format1") = "0"+N("$text", 1);
L("alt_code_format2") = "00"+N("$text", 1);
L("code_con") = findconcept(G("icd9_codes"), N("$text", 1));
L("alt_code_con1") = findconcept(G("icd9_codes"), L("alt_code_format1"));
L("alt_code_con2") = findconcept(G("icd9_codes"), L("alt_code_format2"));
if (L("code_con")) {
# addstrval(L("code_con"), "split", X("split"));
L("split_con") = findconcept(G("mimic_splits"), X("split"));
makeconcept(L("split_con"), L("code"));
}
else if (L("alt_code_con1")) {
# addstrval(L("alt_code_con1"), "split", X("split"));
L("split_con") = findconcept(G("mimic_splits"), X("split"));
makeconcept(L("split_con"), L("alt_code_format1"));
}
else if (L("alt_code_con2")) {
# addstrval(L("alt_code_con2"), "split", X("split"));
L("split_con") = findconcept(G("mimic_splits"), X("split"));
makeconcept(L("split_con"), L("alt_code_format2"));
}
else {
"test.log" << X("split") << ": " << N("$text", 1) << " has no match in icd9 kbb.\n";
}
@RULES
_xNIL <-
_LINE ### (1)
@@
|
# Find first named node in phrase.
L("return_con") = findnode(L("phrase"), L("name")); |
@NODES _LINE
@RULES
_year <- _xWILD [one s match=(
1950 1951 1952 1953 1954 1955 1956 1957 1958 1959
1960 1961 1962 1963 1964 1965 1966 1967 1968 1969
1970 1971 1972 1973 1974 1975 1976 1977 1978 1979
1980 1981 1982 1983 1984 1985 1986 1987 1988 1989
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
2010 )]
@@
_year <- _xWILD [opt s match=(\')]
_xWILD [one s match=(
50 51 52 53 54 55 56 57 58 59
60 61 62 63 64 65 66 67 68 69
70 71 72 73 74 75 76 77 78 79
80 81 82 83 84 85 86 87 88 89
90 91 92 93 94 95 96 97 98 99
00
)]
@@
_season <- _xWILD [one s match=(
winter spring summer fall ) ] @@
_present <- _xWILD [one s match=(
current present now ) ] @@
|
# Convert the strings in multi-string valued global variable to lower case
@CODE
G("strs") = "abc";
G("strs")[1] = "def";
gtolower("strs");
"output.txt" << G("strs") << "\n"; |
@NODES _split
@RULES
_BLANKLINE <-
_xWILD [min=0 max=0 matches=(\ \t \r)] ### (1)
\n ### (2)
@@
_LINE <-
_xWILD [min=0 max=0 fails=(\r \n)] ### (1)
_xWILD [one match=(\n _xEND)] ### (2)
@@
|
@CODE
closefile(G("file"));
@@CODE |
@CODE
### ICD Keywords ##############################################
G("words") = findconcept(findroot(),"words");
if (!G("words")) G("words") = makeconcept(findroot(),"words");
rmchildren(G("words"));
G("procedure_words") = AddUniqueCon(G("words"), "procedure");
rmchildren(G("procedure_words"));
G("diagnosis_words") = AddUniqueCon(G("words"), "diagnosis");
rmchildren(G("diagnosis_words"));
### ICD Terms/Attributes #######################################
G("codes") = findconcept(findroot(),"codes");
if (!G("codes")) G("codes") = makeconcept(findroot(),"codes");
rmchildren(G("codes"));
G("procedure_codes") = AddUniqueCon(G("codes"), "procedure");
rmchildren(G("procedure_codes"));
G("diagnosis_codes") = AddUniqueCon(G("codes"), "diagnosis");
rmchildren(G("diagnosis_codes"));
@@CODE |
@PATH _ROOT _Mixed
@RULES
_childItem <-
_whiteSpace [opt] ### (1)
\| [one] ### (2)
_whiteSpace [opt] ### (3)
_xWILD [s one matches=("_xALPHA" "_" ":")] ### (4)
_xWILD [s star matches=("_xALPHA" "_xNUM" "." "-" "_" ":")] ### (5)
@@
_childItem <-
_whiteSpace [opt] ### (1)
\| [one] ### (2)
_whiteSpace [opt] ### (3)
_PEReference [one] ### (4)
@@
@@RULES
@POST
noop() ;
@@POST
@RULES
_xNIL <-
_whiteSpace [one] ### (1)
@@
@@RULES
@POST
"output.txt" << "Error: stray characters in PCDATA section\n";
noop() ;
@@POST
@RULES
_xNIL <-
_xWILD
@@
@@RULES
|
# TODO: PUT YOUR CONTEXT IN HERE.
@NODES _TEXTZONE
# TODO: SET UP USER ACTIONS HERE.
@POST
pncopyvars(1); # 06/05/06 AM.
S("ne text") = phrasetext();
S("ne type") = "location";
S("ne type conf") = 95;
S("ne") = 1;
S("sem") = "location";
S("sem location") = "country";
S("mypos") = "NP";
S("country") = S("stem") = phrasetext();
if (G("verbose"))
"country.txt" << phrasetext() << "\n";
single();
@RULES
_country [layer=(_noun)] <-
Bangladesh
@@
_country [layer=(_noun)] <-
Burma
@@
_country [layer=(_noun)] <-
Cambodia
@@
_country [layer=(_noun)] <-
China
@@
_country [layer=(_noun)] <-
India
@@
_country [layer=(_noun)] <-
Indonesia
@@
_country [layer=(_noun)] <-
Laos
@@
_country [layer=(_noun)] <-
Malaysia
@@
_country [layer=(_noun)] <-
Myanmar
@@
_country [layer=(_noun)] <-
Singapore
@@
_country [layer=(_noun)] <-
Sri
_xWHITE
Lanka
@@
_country [layer=(_noun)] <-
Thailand
@@
_country [layer=(_noun)] <-
Vietnam
@@
|
@PATH _ROOT _header
@POST
excise(1,1);
noop();
@RULES
_xNIL <-
_xWHITE [s] ### (1)
@@
|
@CODE
L("hello") = 0;
@@CODE
#@PATH _ROOT _TEXTZONE _sent
@NODES _sent
# det alpha
# NIBBLE.
@CHECK
if (N("unknown",3))
succeed();
if (N("number",1) == "singular" && plural(N(3)))
fail();
if (!N("verb",3))
fail();
if (N("pos num",3) < 2)
fail();
@POST
N("pos25 det-a-a") = 1;
if (N("unknown",3))
alphatonoun(3);
else
{
if (vconjq(N(3),"-en") && !N("noun",3) && !N("adj",3))
L("pos") = "VBN";
N("verb",3) = 0; # verb = 0
--N("pos num",3);
if (N("noun",3) && N("pos num",3) == 1)
alphatonoun(3); # 04/21/07 AM.
if (L("pos"))
N("mypos",3) = L("pos");
}
@RULES
_xNIL <-
_det
_adv [star]
_xALPHA
@@
# det alpha , alpha
@PRE
<2,2> var("adj");
<4,4> var("adj");
@POST
fixnpnonhead(2);
@RULES
_xNIL <-
_det
_xALPHA
\, [lookahead]
_xALPHA
@@
# ^ num alpha
@CHECK
if (N("noun",3))
{
if (numbersagree(N(2),N(3)))
{
S("pos") = "noun";
succeed();
}
else if (N("verb",3))
{
S("pos") = "verb";
succeed();
}
}
else if (N("verb",3))
{
S("pos") = "verb";
succeed();
}
fail();
@POST
if (S("pos") == "noun")
fixnphead(3);
else if (S("pos") == "verb")
alphatovg(3,0,0);
@RULES
_xNIL <-
_xSTART
_num
_xALPHA
_xWILD [one fail=(_xALPHA _adj _noun)]
@@
# prep alpha conj alpha
# Note: Do an intersection of pos!
@PRE
<2,2> varz("pos10 p-a-x-a");
<2,2> varne("stem","to");
@CHECK
# Looking for non-verb agreement.
if (N("noun",3) && N("noun",5))
S("noun") = 1;
if (N("adj",3) && N("adj",5))
S("adj") = 1;
if (S("adj") && S("noun"))
fail(); # Ambig.
@POST
N("pos10 p-a-x-a",2) = 1;
if (S("noun"))
{
alphatonoun(5);
alphatonoun(3);
}
else if (S("adj"))
{
alphatoadj(5);
alphatoadj(3);
}
@RULES
_xNIL <-
_xWILD [one match=(_noun _np)]
_prep
_xALPHA
_conj
_xALPHA
@@
#######################3
# NOUN LISTING #
@PRE
<1,1> var("prenoun");
@POST
if (literal(N(2)))
alphatonoun(2);
if (pnname(N(2)) != "_np")
group(2,2,"_np");
++N("noun-list",2);
@RULES
_xNIL <-
_prep
_xWILD [one match=(_xALPHA _noun)]
_xWILD [one lookahead match=( \, and _and)]
@@
# NOUN LISTING #
@PRE
<1,1> var("prenoun");
<4,4> var("noun");
@POST
if (literal(N(4)))
alphatonoun(4);
if (pnname(N(4)) != "_np")
group(4,4,"_np");
N("noun-list",2) = 1;
listadd(2,4,"true");
@RULES
_xNIL <-
_prep ### (1)
_xWILD [one match=(_np)] ### (2)
_xWILD [plus match=( \, and _and _conj)] ### (3)
_xWILD [one match=(_xALPHA _noun)] ### (4)
_xWILD [one lookahead match=( \, and _and _conj _qEOS _xEND)] ### (5)
@@
|
@NODES _ROOT
@RULES
_subgroup <-
_subgroupHeader ### (1)
_xWILD [fail=(_subgroupHeader _groupHeader)] ### (2)
@@
|
@NODES _LINE
@POST
noop();
@RULES
_xNIL <-
_xWILD [fail=(\t) group="_column"] ### (1)
\t ### (2)
_xWILD [fail=(\t) group="_column"] ### (3)
\t ### (4)
_xWILD [fail=(\t) group="_column"] ### (5)
\t ### (6)
_xWILD [fail=(\t) group="_column"] ### (7)
\t ### (8)
_xWILD [fail=(\t) group="_column"] ### (9)
\t ### (8)
_xWILD [fail=(\t) group="_column"] ### (9)
@@ |
# Remove node from concept's phrase.
rmnode(L("con")); |
@CODE
GetTitles(G("top"));
GetTitles(G("rare"));
DisplayKB(G("mimic_splits"), 1);
SaveToKB(G("mimic_splits"),"mimic_splits");
@@CODE |
@NODES _enum
@RULES
_itemMarker <-
\\ [s] ### (1)
item [s] ### (2)
@@
|
# See if analyzer is operating in an interactive environment
@CODE
# In VisualText, send output to a file, but outside of VisualText, direct outputs to a user-supplied buffer.
if (interactive())
G("out") = "buf.txt";
else
G("out") = cbuf();
G("out") << "Hello output!" << "\n";
@@CODE |
@NODES _ROOT
@POST
if (num(N("words")) && num(N("words")) == num(N("caps"))) {
N("level") = 1;
N("possible") = 1;
single();
}
# else if (num(N("words")) && num(N("words")) == num(N("upper")) && N("words") == 1) {
# N("level") = 2;
# single();
# }
@RULES
_header <-
_LINE ### (1)
@@
|
# Fetch entire path of given concept as a string.
L("return_str") = conceptpath(L("con")); |
# Remove dictionary concept from KB.
rmword(L("str")); |
@PATH _ROOT _bodyZone _trZone _tdZone
@POST
X("value") = N("$text",3);
@RULES
_xNIL <-
_td ### (1)
_strong [opt] ### (2)
_xWILD [fail=(_tdClose _strongClose)] ### (3)
_strongClose [opt] ### (4)
_tdClose ### (5)
@@
|
@NODES _LINE
@RULES
_GPA <-
Grade [s]
_xWHITE [s star]
Point [s]
_xWHITE [s star]
Average[s]
@@
_GPA <- GPA [s] @@
_GPA <-
G [s]
\. [s opt]
_xWHITE [s star]
P [s]
\. [s opt]
_xWHITE [s star]
A [s]
@@
# Changing this to exploit NLP++. #
@POST
if ((num(N("integer")) >= 2 || num(N("integer")) <= 6)
&& (num(N("decimal")) >= 0 && num(N("decimal")) <= 99))
N("GPAValue") = "true"; # Good candidate for GPA.
# noop()
@RULES
_xNIL <- _numDecimal @@
#@PRE
#<1,1> numrange(3, 4)
#<3,3> numrange(0, 99)
#@RULES
#_GPAValue [] <-
# _xNUM [s]
# \. [s]
# _xNUM [s] @@
|
@PATH _ROOT _LINE _brackets
@PRE
<3,3> lowercase();
@POST
if (!X("word",2)) {
X("word",2) = N("$text",3);
"words.txt" << N("$text",3) << "\n";
}
@RULES
_xNIL <-
_xSTART ### (1)
\[ ### (2)
_xWILD [plus match=(_xALPHA \_ \-)] ### (3)
@@
|
@NODES _ROOT
@RULES
_xNIL <-
_xNIL ### (1)
@@
|
@NODES _ROOT
@POST
S("label") = makeconcept(G("labels"), N("$text", 1));
single();
@RULES
_labelEntry <-
_xWILD [fails=(\n \r)] ### (1)
_xWILD [one match=(\n \r _xEND)] ### (2)
@@ |
@NODES _LINE
@POST
setbase(1,"false");
@RULES
_xNIL <- _Caps @@
|
@NODES _ROOT
@POST
excise(1,1);
noop();
@RULES
_xNIL <-
_xWHITE ### (1)
@@
|
# Fetch the concept that node is a proxy for.
L("return_con") = nodeconcept(L("node")); |
@CODE
DisplayKB(G("root"), 0);
@@CODE
|
@PATH _ROOT _headerZone _iOpen
@POST
X("attr") = N("$text",1);
X("value") = N("$text",4);
@RULES
_xNIL <-
_xALPHA ### (1)
\= ### (2)
\" ### (3)
_xWILD [fail=(\")] ### (4)
\" ### (5)
@@
|
@DECL
########
# FUNC: REGISTERX
# SUBJ: Add string to a node's variable.
# EX: register(X(4),"temporal","
# Adds a date string to "temporal" var of node
# in context.
# NOTE: For adding multiple values to a variable.
# Should rename this to something else.
# Lowercase register() conflicts with C++ reserved word,
# when analyzer is compiled.
########
registerx(
L("node"), # Parse tree node we are adding info to.
L("field"),
L("str")
)
{
if (!L("node") || !L("field") || !L("str"))
return;
L("vals") = pnvar(L("node"),L("field"));
if (!L("vals"))
L("len") = 0;
else
L("len") = arraylength(L("vals"));
# Can't directly append a new value onto node.
# Need something like pnaddval(L("node"),L("field"),L("str")).
L("vals")[L("len")] = L("str");
pnreplaceval(L("node"),L("field"),L("vals"));
}
domadvl(L("n"),L("sent"))
{
}
domcopyattrs(L("ref"),L("con"))
{
}
domcopynodetocon(L("n"),L("con"))
{
}
dommergeevent(L("ref"),L("cand"))
{
}
domnewevent(L("ref"),L("con"))
{
}
domnp(L("n"),L("sent"))
{
}
########
# FUNC: DOMNPOFNP
# SUBJ: Try to categorize named entity.
########
domnpofnp(
L("n"), # Reduced np.
L("np1"), # First np.
L("np2")) # of-np.
{
if (!pnvar(L("np2"),"ne") || pnvar(L("np2"),"ne type"))
return;
if (pnvar(L("np1"),"ne") || !pnvar(L("np1"),"sem"))
return;
L("sem1") = pnvar(L("np1"),"sem");
if (L("sem1") == "city")
pnreplaceval(L("np2"),"ne type","location");
}
########
# FUNC: DOMOBJECTREGISTER
# SUBJ: Domain- and task-specific register of object.
# NOTE: Domain functions calling generic functions.
# The reverse of previous implementations in Parse_EN-US.
# This lets us do domain and task stuff as we like.
# (One could go domain-to-generic or generic-to-domain, etc.)
########
domobjectregister(
L("n"), # Object's pnode. eg, an _np node.
L("cnode") # Object's clause pnode.
)
{
# Generic register of object reference in kb.
L("obj") = objectregister(L("n"),L("cnode"));
if (!L("obj"))
return 0;
# Generic resolve of object reference against list of objects
# in the kb.
L("object") = resolveobject(L("obj"),G("objects"));
# Entities.
# If the object has an array of entities, use that.
# nenoderange(
L("arr") = pnvar(L("n"),"ne arr");
if (L("arr"))
{
L("ii") = 0;
while (L("arr")[L("ii")])
{
L("x") = L("arr")[L("ii")];
L("ent") = entregister(L("x"),L("n"));
L("entity") = resolveentity(L("ent"),G("entities"));
++L("ii");
}
return L("obj");
}
# Else if the object itself is a named entity, use that.
L("ent") = entregister(L("n"),L("n"));
L("entity") = resolveentity(L("ent"),G("entities"));
return L("obj");
}
########
# FUNC: DOMENTITYREGISTER
# SUBJ: Domain- and task-specific register of entity.
########
domentityregister(
L("n"), # Object's pnode. eg, an _np node.
L("cnode") # Object's clause pnode.
)
{
if (!L("n"))
return 0;
# Entities.
# If the object has an array of entities, use that.
# nenoderange(
L("arr") = pnvar(L("n"),"ne arr");
if (L("arr"))
{
L("ii") = 0;
while (L("arr")[L("ii")])
{
L("x") = L("arr")[L("ii")];
L("ent") = entregister(L("x"),L("n"));
L("entity") = resolveentity(L("ent"),G("entities"));
++L("ii");
}
return L("entity"); # What if an array? ...
}
# Else if the object itself is a named entity, use that.
L("ent") = entregister(L("n"),L("n"));
L("entity") = resolveentity(L("ent"),G("entities"));
return L("entity");
}
@CODE
L("hello") = 0;
@@CODE
|
@MULTI _ROOT _LINE _split
@POST
excise(1,1);
@RULES
_xNIL <-
_xWILD [one matches=(\n \r _BLANKLINE)] ### (1)
@@
|
@NODES _LINE
@RULES
# Ex: interdisciplinary
_fieldNames <- _xWILD [min=1 max=1 s match=(interdisciplinary accounting acoustics adapted administration adult advertising aeronautical aeronautics aerospace aesthetics affairs african africology afro agribusiness agricultural agronomy air american analysis anatomy animal anthropology apparel applied aquatic archaeology architectural architecture army art arts asian assistance astronautics astronomy astrophysics athletic atmospheric audiology automotive aviation banking bilingual biochemistry bioengineering biological biology biomedical biophysics botany brain building business care cell ceramic chemical chemistry childhood chinese city civil classics climatology clinch clinical coastal cognitive communication communications communicative community comparative computer computing conservation construction consumer continuing control cooperative counseling counselor creative criminal criticism cs curriculum dairy decision demography dental dentistry dermatology design development developmental dietetics disorders drama early earth east eastern ecology econometrics economics education educational ee eecs electric electrical electronics elementary energy enforcement engineering english entomology environmental epidemiology estate ethics ethnic european evaluation exercise family fashion film finance fine fisheries fitness food force foreign forest forestry foundations french gas general genetics geochemistry geography geology geophysics geosciences german germanic gerontological gerontology government grain greek health hebrew history horticultural horticulture hospitality hotel human humanistic humanities husbandry immunology individual industrial information institutional instruction instructional insurance accountancy interior international italian japanese jewish journalism justice kinesiology labor laboratory landscape language languages latin law leadership learning legal leisure liberal library linguistics literary literature literatures lithuanian logistics management manufacturing marketing mass materials math mathematics mechanical mechanics media medical medicinal medicine metals meteorology microbiology middle military mineral mineralogy mining modern molecular motor music natural navy nematology neuroscience nuclear nutrition occupational ocean oceanographic oceanography office operations optics optometry oral organization park pathobiology pathology pedagogy pediatrics performance personnel pest petroleum pharmaceutical pharmaceutics pharmacology pharmacy philosophy physical physics physiology planetary planning plant police policy political pollution polymer portuguese poultry power processing program programs promotion psychology public quality quantitative radiologic radiological reading real recreation regional rehabilitation relations religion religious research resource resources respiratory restaurant romance rotc rural russian school science sciences service services slavic social sociology software soil solid spanish special speech sport sports state statistics structural student studies systems taxation teacher teaching technology telecommunications telemedicine tesl textile textiles theater theatre theology theory therapeutics therapist therapy thought tourism training transportation urban valley veterinary video visual voice water wildlife women work workforce writing zoology)] @@
|
# Perform a reduction on the range of rule elements from node1 to node2 and name the group node labelString. node1 and node2 should be a well-formed range in the current rule match. For example from N(1) to N(3)
@POST
L("n") = group(N(1),N(2),"_np");
"output.txt" << pnname(L("n")) << "\n";
@RULES
_xNIL <- _det _noun _xWILD [s lookahead fail=(_noun)] @@
output.txt then gets an output like:
_np |
@NODES _LINE
@POST
ResolvePronoun(X("con"),N("con"));
@RULES
_xNIL <-
_pro ### (1)
@@
|
@NODES _ROOT
@CODE
G("people") = 0;
@@CODE |
@NODES _ROOT
@POST
S("code") = N("$text", 1);
S("term") = N("$text", 3);
excise(4,4);
excise(1,2);
single();
@RULES
_entry<-
_xWILD [fails=(\t _icdRoot)] ### (1)
\t ### (2)
_xWILD [fails=(\n \r)] ### (3)
_xWILD [one matches=(\n \r)] ### (4)
@@ |
@NODES _ROOT
@RULES
_trStart <- \< tr \> @@
_trEnd <- \< \/ tr \> @@
_tdStart <- \< td \> @@
_tdEnd <- \< \/ td \> @@
_thStart <- \< th \> @@
_thEnd <- \< \/ th \> @@
_aStart <- \< a _xWILD [fail=(\>)] \> @@
_aEnd <- \< \/ a \> @@
|
@CODE
L("debugpath") = G("$kbpath") + "debug.txt";
G("debug") = openfile(L("debugpath"),"app");
G("words") = findconcept(findroot(),"words");
if (!G("words")) G("words") = makeconcept(findroot(),"words");
#rmchildren(G("words"));
G("stats") = findconcept(findroot(),"stats");
if (!G("stats")) G("stats") = makeconcept(findroot(),"stats");
#rmchildren(G("stats"));
G("conjugations") = findconcept(findroot(),"conjugations");
if (!G("conjugations")) G("conjugations") = makeconcept(findroot(),"conjugations");
#rmchildren(G("conjugations"));
@@CODE |
@PATH _ROOT _LINE
# If there's a "The" before a cap phrase, add it in.
# Reassess some things accordingly.
# Need a function to find a good runner-up.
# If it's humanname or job title, should trash those assignments.
@PRE
<1,1> cap();
@POST
if (N("hi class",3) == "humanname"
|| N("hi class",3) == "job title")
{
# Todo: find runner up confidence here.
N("hi class",3) = "NULL";
N("hi conf",3) = 0;
}
listadd(3,1,"true");
@RULES
_xNIL <- The [s] _xWHITE [s star] _Caps [s] @@
|
@CODE
if (G("pretagged"))
exitpass();
if (!G("hilite")) # 10/25/10 AM.
exitpass(); # 10/25/10 AM.
G("hello") = 0;
@@CODE
# Traverse the whole tree.
@MULTI _ROOT
@POST
if (G("verbose"))
"np.txt" << N("$text") << "\n";
noop(); # Merely matching the rule will set text to green.
@RULES
_xNIL <- _xWILD [one match=(
_np _nps
)] @@
|
@NODES _term
@POST
X("code") = N("$text", 2);
@RULES
_xNIL <-
_xSTART ### (1)
_xNUM ### (2)
\, ### (3)
_xWILD
@@
|
@NODES _ROOT
@PRE
<2,2> vargt("prose",2);
@POST
listadd(1,2,"false");
@RULES
_xNIL <-
_prose
_LINE
@@
@PRE
<1,1> vargt("prose",2);
<2,2> vargt("prose",2);
@RULES
_prose <-
_LINE
_LINE
@@
|
@DECL
###############################################
# General functions
###############################################
AddUniqueCon(L("concept"),L("name")) {
L("con") = findconcept(L("concept"),L("name"));
if (!L("con")) L("con") = makeconcept(L("concept"),L("name"));
return L("con");
}
AddUniqueStr(L("concept"),L("attr"),L("value")) {
if (L("value") && strval(L("concept"),L("attr")) != L("value"))
addstrval(L("concept"),L("attr"),L("value"));
}
AddUniqueNum(L("concept"),L("attr"),L("value")) {
"unique.txt" << L("attr") << " " << str(L("value")) << " " << conceptpath(L("concept")) << "\n";
L("val") = AttrValues(L("concept"),L("attr"));
while (L("val")) {
L("num") = getnumval(L("val"));
"unique.txt" << " value: " << str(L("num")) << "\n";
if (L("num") == L("value"))
return 0;
L("val") = nextval(L("val"));
}
addnumval(L("concept"),L("attr"),L("value"));
return 1;
}
AddUniqueConVal(L("concept"),L("attr"),L("value")) {
"unique.txt" << L("attr") << " " << conceptpath(L("concept")) << " ==> " << L("attr") << " -- " << conceptpath(L("value")) << "\n";
L("val") = AttrValues(L("concept"),L("attr"));
while (L("val")) {
L("con") = getconval(L("val"));
"unique.txt" << conceptname(L("con")) << "\n";
if (conceptpath(L("con")) == conceptpath(L("value")))
return 0;
L("val") = nextval(L("val"));
}
addconval(L("concept"),L("attr"),L("value"));
return 1;
}
CopyAttr(L("from"),L("to"),L("attr")) {
L("from value") = strval(L("from"),L("attr"));
if (L("from value")) {
L("to value") = strval(L("to"),L("attr"));
if (L("from value") && !L("to value"))
addstrval(L("to"),L("attr"),L("from value"));
}
}
CopyAttrNew(L("from"),L("to"),L("attr from"),L("attr to")) {
L("from value") = strval(L("from"),L("attr from"));
if (L("from value")) {
L("to value") = strval(L("to"),L("attr to"));
if (L("from value") && !L("to value"))
addstrval(L("to"),L("attr to"),L("from value"));
}
}
CopyConAttr(L("from"),L("to"),L("attr")) {
L("from value") = conval(L("from"),L("attr"));
if (L("from value")) {
L("to value") = conval(L("to"),L("attr"));
if (L("from value") && !L("to value"))
addconval(L("to"),L("attr"),L("from value"));
}
}
AttrValues(L("con"),L("attr")) {
L("at") = findattr(L("con"),L("attr"));
if (L("at"))
return attrvals(L("at"));
return 0;
}
LastChild(L("parent")) {
L("child") = down(L("parent"));
while (L("child")) {
L("last") = L("child");
L("child") = next(L("child"));
}
return L("last");
}
MakeCountCon(L("con"),L("count name")) {
L("count name") = CountName(L("con"),L("count name"));
return makeconcept(L("con"),L("count name"));
}
IncrementCount(L("con"),L("countname")) {
L("count") = numval(L("con"),L("countname"));
if (L("count")) {
L("count") = L("count") + 1;
replaceval(L("con"),L("countname"),L("count"));
} else {
addnumval(L("con"),L("countname"),1);
L("count") = 1;
}
return L("count");
}
CountName(L("con"),L("root")) {
L("count") = IncrementCount(L("con"),L("root"));
return L("root") + str(L("count"));
}
StripEndDigits(L("name")) {
if (strisdigit(L("name"))) return 0;
L("len") = strlength(L("name")) - 1;
L("i") = L("len") - 1;
L("str") = strpiece(L("name"),L("i"),L("len"));
while (strisdigit(L("str")) && L("i")) {
L("i")--;
L("str") = strpiece(L("name"),L("i"),L("len"));
}
return strpiece(L("name"),0,L("i"));
}
###############################################
# KB Dump Functins
###############################################
DumpKB(L("con"),L("file")) {
L("dir") = G("$apppath") + "/kb/";
L("filename") = L("dir") + L("file") + ".kb";
if (!kbdumptree(L("con"),L("filename"))) {
"kb.txt" << "FAILED dump: " << L("filename") << "\n";
} else {
"kb.txt" << "DUMPED: " << L("filename") << "\n";
}
}
TakeKB(L("filename")) {
L("path") = G("$apppath") + "kb\\" + L("filename") + ".kb";
"kb.txt" << "Taking: " << L("path") << "\n";
if (take(L("path"))) {
"kb.txt" << " Taken successfully: " << L("path") << "\n";
} else {
"kb.txt" << " Taken FAILED: " << L("path") << "\n";
}
}
ChildCount(L("con")) {
L("count") = 0;
L("child") = down(L("con"));
while (L("child")) {
L("count")++;
L("child") = next(L("child"));
}
return L("count");
}
###############################################
# KBB DISPLAY FUNCTIONS
###############################################
DisplayKB(L("top con"),L("full")) {
L("file") = DisplayFileName();
DisplayKBRecurse(L("file"),L("top con"),0,L("full"));
L("file") << "\n";
return L("top con");
}
KBHeader(L("text")) {
L("file") = DisplayFileName();
L("file") << "#######################\n";
L("file") << "# " << L("text") << "\n";
L("file") << "#######################\n\n";
}
DisplayFileName() {
if (num(G("$passnum")) < 10) {
L("file") = "ana00" + str(G("$passnum"));
}else if (num(G("$passnum")) < 100) {
L("file") = "ana0" + str(G("$passnum"));
} else {
L("file") = "ana" + str(G("$passnum"));
}
L("file") = L("file") + ".kbb";
return L("file");
}
DisplayKBRecurse(L("file"),L("con"),L("level"),L("full")) {
while (L("con")) {
L("file") << SpacesStr(L("level")+1) << conceptname(L("con"));
DisplayAttributes(L("file"),L("con"),L("full"),L("level"));
L("file") << "\n";
if (down(L("con"))) {
L("lev") = 1;
DisplayKBRecurse(L("file"),down(L("con")),L("level")+L("lev"),L("full"));
}
if (L("level") == 0)
return 0;
L("con") = next(L("con"));
}
}
DisplayAttributes(L("file"),L("con"),L("full"),L("level")) {
L("attrs") = findattrs(L("con"));
if (L("attrs")) L("file") << ": ";
if (L("full") && L("attrs")) L("file") << "\n";
L("first attr") = 1;
while (L("attrs")) {
L("vals") = attrvals(L("attrs"));
if (!L("full") && !L("first attr")) {
L("file") << ", ";
}
if (L("full")) {
if (!L("first attr")) L("file") << "\n";
L("file") << SpacesStr(L("level")+2);
}
L("file") << attrname(L("attrs")) << "=[";
L("first") = 1;
while (L("vals")) {
if (!L("first"))
L("file") << ",";
L("val") = getstrval(L("vals"));
L("num") = getnumval(L("vals"));
L("con") = getconval(L("vals"));
if (L("con")) {
L("file") << conceptpath(L("con"));
} else if (!L("full") && strlength(L("val")) > 20) {
L("shorty") = strpiece(L("val"),0,20);
L("file") << L("shorty");
L("file") << "...";
if (strendswith(L("val"),"\""))
L("file") << "\"";
} else if (L("num") > -1) {
L("file") << str(L("num"));
} else {
L("file") << L("val");
}
L("first") = 0;
L("vals") = nextval(L("vals"));
}
L("file") << "]";
L("first attr") = 0;
L("attrs") = nextattr(L("attrs"));
}
}
# Because NLP++ doesn't allow for empty strings,
# this function can only be called with "num" >= 1
SpacesStr(L("num")) {
L("n") = 1;
L("spaces") = " ";
while (L("n") < L("num")) {
L("spaces") = L("spaces") + " ";
L("n")++;
}
return L("spaces");
}
###############################################
# DICTIONARY FUNCTIONS
###############################################
DictionaryClear() {
G("dictionary path") = G("$apppath") + "\\kb\\user\\dictionary.kb";
G("dictionary") = openfile(G("dictionary path"));
}
DictionaryWord(L("word"),L("attrName"),L("value"),L("attrType")) {
L("file") = G("dictionary");
if (!dictfindword(L("word")))
L("file") << "add word \"" + L("word") + "\"\n";
L("file") << "ind attr\n" << findwordpath(L("word")) << "\n0\n";
L("file") << findwordpath(L("attrName")) << "\n";
if (L("attrType") == "str")
L("file") << "pst\n" << L("value");
else if (L("attrType") == "num")
L("file") << "pnum\n" << str(L("value"));
else if (L("attrType") == "con")
L("file") << "pcon\n" << conceptpath(L("value"));
L("file") << "\nend ind\n\n";
}
DictionaryEnd() {
G("dictionary") << "\nquit\n\n";
closefile(G("dictionary"));
}
@@DECL
|
@NODES _areaCodes
@POST
L("areacodes") = getconcept(G("state"),"areacodes");
makeconcept(L("areacodes"),N("$text"));
@RULES
_xNIL <-
_xNUM ### (1)
@@
|
@NODES _LINE
@POST
X("start") = 1;
single();
@RULES
_start <-
ind ### (1)
attr ### (2)
@@
@POST
X("end") = 1;
single();
@RULES
_end <-
end ### (1)
ind ### (2)
@@
|
@NODES _ROOT
##################################################
# Lookup of character codes in &ALPHABETIC; format
# (but not whitespace chars -- these are handled
# in the rule block for whitespace
##################################################
@POST
G("root") = findroot() ;
G("character_codes") = findconcept(G("root"),"character_codes") ;
if (G("character_codes")) {
G("current code") = findconcept(G("character_codes"),N("$text",2)) ;
}
else G("current code") = 0;
if (G("current code")) {
G("new text") = strval(G("current code"),"textValue") ;
if (G("new text")) {
S("textValue") = G("new text") ;
}
}
single();
@@POST
@RULES
_specialCharacter <-
\& [trig one] ### (1)
_xALPHA [one] ### (2)
\; [one] ### (3)
@@
@@RULES
##################################################
# Lookup of character codes in &#NUMERIC; format
# (but not whitespace chars -- these are handled
# in the rule block for whitespace
##################################################
@POST
G("root") = findroot() ;
G("character_codes") = findconcept(G("root"),"character_codes") ;
G("current code") = findconcept(G("character_codes"),N("$text",3)) ;
if (G("current code")) {
G("new text") = strval(G("current code"),"textValue") ;
if (G("new text")) {
S("textValue") = G("new text") ;
}
}
single();
@@POST
@RULES
_specialCharacter <-
\& [one] ### (1)
\# [trig one] ### (2)
_xNUM [one] ### (3)
\; [one] ### (4)
@@
@@RULES
##################################################
# Lookup of character codes in &#xHEX; format
# (but not whitespace chars -- these are handled
# in the rule block for whitespace
##################################################
@POST
G("root") = findroot() ;
G("character_codes") = findconcept(G("root"),"character_codes") ;
G("current code") = findconcept(G("character_codes"),N("$text",4)) ;
if (G("current code")) {
G("new text") = strval(G("current code"),"textValue") ;
if (G("new text")) {
S("textValue") = G("new text") ;
}
}
single();
@@POST
@RULES
_specialCharacter <-
\& [one] ### (1)
\# [one] ### (2)
x [trig one] ### (3)
_xWILD [min=1 max=4 matches=("0" "1" "2" "3" "4" "5" "6" "7" "8" "9" "A" "B" "C" "D" "E" "F" "a" "b" "c" "d" "e" "f")] ### (4)
\; [one] ### (5)
@@
@@RULES
|
@PATH _ROOT _paragraph _sentence
@POST S("type") = "total"; single();
@RULES _operator <- a total of @@
@POST S("type") = ">"; single();
@RULES _operator <- more than @@
|
@NODES _LINE
@RULES
# Ex: afro\_\\-\_american\_and\_african\_studies
_field [layer=(_Caps )] <- afro [s] _xWHITE [star s] \\ [s] \- [s] _xWHITE [star s] american [s] _xWHITE [star s] and [s] _xWHITE [star s] african [s] _xWHITE [star s] studies [s] @@
# Ex: finance\_\\,\_insurance\_and\_real
_field [layer=(_Caps )] <- finance [s] _xWHITE [star s] \\ [s] \, [s] _xWHITE [star s] insurance [s] _xWHITE [star s] and [s] _xWHITE [star s] real [s] @@
# Ex: exercise\_physiology\_\\/\_adult\_fitness
_field [layer=(_Caps )] <- exercise [s] _xWHITE [star s] physiology [s] _xWHITE [star s] \\ [s] \/ [s] _xWHITE [star s] adult [s] _xWHITE [star s] fitness [s] @@
# Ex: atmospheric\_\\,\_and\_planetary\_sciences
_field [layer=(_Caps )] <- atmospheric [s] _xWHITE [star s] \\ [s] \, [s] _xWHITE [star s] and [s] _xWHITE [star s] planetary [s] _xWHITE [star s] sciences [s] @@
# Ex: writing\_and\_humanistic\_studies
_field [layer=(_Caps )] <- writing [s] _xWHITE [star s] and [s] _xWHITE [star s] humanistic [s] _xWHITE [star s] studies [s] @@
# Ex: women\_\\'\_s\_studies
_field [layer=(_Caps )] <- women [s] _xWHITE [star s] \\ [s] \' [s] _xWHITE [star s] s [s] _xWHITE [star s] studies [s] @@
# Ex: wildlife\_and\_fisheries\_science
_field [layer=(_Caps )] <- wildlife [s] _xWHITE [star s] and [s] _xWHITE [star s] fisheries [s] _xWHITE [star s] science [s] @@
# Ex: voice\_performance\_and\_pedagogy
_field [layer=(_Caps )] <- voice [s] _xWHITE [star s] performance [s] _xWHITE [star s] and [s] _xWHITE [star s] pedagogy [s] @@
# Ex: urban\_studies\_and\_planning
_field [layer=(_Caps )] <- urban [s] _xWHITE [star s] studies [s] _xWHITE [star s] and [s] _xWHITE [star s] planning [s] @@
# Ex: urban\_and\_regional\_planning
_field [layer=(_Caps )] <- urban [s] _xWHITE [star s] and [s] _xWHITE [star s] regional [s] _xWHITE [star s] planning [s] @@
# Ex: urban\_and\_environmental\_planning
_field [layer=(_Caps )] <- urban [s] _xWHITE [star s] and [s] _xWHITE [star s] environmental [s] _xWHITE [star s] planning [s] @@
# Ex: transportation\_systems\_and\_management
_field [layer=(_Caps )] <- transportation [s] _xWHITE [star s] systems [s] _xWHITE [star s] and [s] _xWHITE [star s] management [s] @@
# Ex: student\_counseling\_and\_personnel
_field [layer=(_Caps )] <- student [s] _xWHITE [star s] counseling [s] _xWHITE [star s] and [s] _xWHITE [star s] personnel [s] @@
# Ex: soil\_and\_water\_science
_field [layer=(_Caps )] <- soil [s] _xWHITE [star s] and [s] _xWHITE [star s] water [s] _xWHITE [star s] science [s] @@
# Ex: slavic\_languages\_and\_literatures
_field [layer=(_Caps )] <- slavic [s] _xWHITE [star s] languages [s] _xWHITE [star s] and [s] _xWHITE [star s] literatures [s] @@
# Ex: romance\_languages\_and\_literatures
_field [layer=(_Caps )] <- romance [s] _xWHITE [star s] languages [s] _xWHITE [star s] and [s] _xWHITE [star s] literatures [s] @@
# Ex: recreation\_and\_park\_management
_field [layer=(_Caps )] <- recreation [s] _xWHITE [star s] and [s] _xWHITE [star s] park [s] _xWHITE [star s] management [s] @@
# Ex: quality\_and\_manufacturing\_management
_field [layer=(_Caps )] <- quality [s] _xWHITE [star s] and [s] _xWHITE [star s] manufacturing [s] _xWHITE [star s] management [s] @@
# Ex: political\_and\_social\_thought
_field [layer=(_Caps )] <- political [s] _xWHITE [star s] and [s] _xWHITE [star s] social [s] _xWHITE [star s] thought [s] @@
# Ex: petroleum\_and\_natural\_gas
_field [layer=(_Caps )] <- petroleum [s] _xWHITE [star s] and [s] _xWHITE [star s] natural [s] _xWHITE [star s] gas [s] @@
# Ex: nuclear\_and\_radiological\_engineering
_field [layer=(_Caps )] <- nuclear [s] _xWHITE [star s] and [s] _xWHITE [star s] radiological [s] _xWHITE [star s] engineering [s] @@
# Ex: microbiology\_and\_cell\_science
_field [layer=(_Caps )] <- microbiology [s] _xWHITE [star s] and [s] _xWHITE [star s] cell [s] _xWHITE [star s] science [s] @@
# Ex: library\_and\_information\_science
_field [layer=(_Caps )] <- library [s] _xWHITE [star s] and [s] _xWHITE [star s] information [s] _xWHITE [star s] science [s] @@
# Ex: insurance\_and\_real\_estate
_field [layer=(_Caps )] <- insurance [s] _xWHITE [star s] and [s] _xWHITE [star s] real [s] _xWHITE [star s] estate [s] @@
# Ex: instructional\_technology\_and\_telecommunications
_field [layer=(_Caps )] <- instructional [s] _xWHITE [star s] technology [s] _xWHITE [star s] and [s] _xWHITE [star s] telecommunications [s] @@
# Ex: industrial\_and\_systems\_engineering
_field [layer=(_Caps )] <- industrial [s] _xWHITE [star s] and [s] _xWHITE [star s] systems [s] _xWHITE [star s] engineering [s] @@
# Ex: industrial\_and\_manufacturing\_systems
_field [layer=(_Caps )] <- industrial [s] _xWHITE [star s] and [s] _xWHITE [star s] manufacturing [s] _xWHITE [star s] systems [s] @@
# Ex: industrial\_and\_manufacturing\_engineering
_field [layer=(_Caps )] <- industrial [s] _xWHITE [star s] and [s] _xWHITE [star s] manufacturing [s] _xWHITE [star s] engineering [s] @@
# Ex: health\_education\_and\_promotion
_field [layer=(_Caps )] <- health [s] _xWHITE [star s] education [s] _xWHITE [star s] and [s] _xWHITE [star s] promotion [s] @@
# Ex: foreign\_languages\_and\_literatures
_field [layer=(_Caps )] <- foreign [s] _xWHITE [star s] languages [s] _xWHITE [star s] and [s] _xWHITE [star s] literatures [s] @@
# Ex: fisheries\_and\_aquatic\_sciences
_field [layer=(_Caps )] <- fisheries [s] _xWHITE [star s] and [s] _xWHITE [star s] aquatic [s] _xWHITE [star s] sciences [s] @@
# Ex: film\_and\_media\_studies
_field [layer=(_Caps )] <- film [s] _xWHITE [star s] and [s] _xWHITE [star s] media [s] _xWHITE [star s] studies [s] @@
# Ex: family\_and\_consumer\_sciences
_field [layer=(_Caps )] <- family [s] _xWHITE [star s] and [s] _xWHITE [star s] consumer [s] _xWHITE [star s] sciences [s] @@
# Ex: exercise\_and\_sport\_sciences
_field [layer=(_Caps )] <- exercise [s] _xWHITE [star s] and [s] _xWHITE [star s] sport [s] _xWHITE [star s] sciences [s] @@
# Ex: environmental\_planning\_and\_management
_field [layer=(_Caps )] <- environmental [s] _xWHITE [star s] planning [s] _xWHITE [star s] and [s] _xWHITE [star s] management [s] @@
# Ex: engineering\_and\_applied\_science
_field [layer=(_Caps )] <- engineering [s] _xWHITE [star s] and [s] _xWHITE [star s] applied [s] _xWHITE [star s] science [s] @@
# Ex: electrical\_and\_computer\_engineering
_field [layer=(_Caps )] <- electrical [s] _xWHITE [star s] and [s] _xWHITE [star s] computer [s] _xWHITE [star s] engineering [s] @@
# Ex: decision\_and\_information\_sciences
_field [layer=(_Caps )] <- decision [s] _xWHITE [star s] and [s] _xWHITE [star s] information [s] _xWHITE [star s] sciences [s] @@
# Ex: dairy\_and\_poultry\_sciences
_field [layer=(_Caps )] <- dairy [s] _xWHITE [star s] and [s] _xWHITE [star s] poultry [s] _xWHITE [star s] sciences [s] @@
# Ex: computing\_and\_information\_sciences
_field [layer=(_Caps )] <- computing [s] _xWHITE [star s] and [s] _xWHITE [star s] information [s] _xWHITE [star s] sciences [s] @@
# Ex: computer\_science\_and\_engineering
_field [layer=(_Caps )] <- computer [s] _xWHITE [star s] science [s] _xWHITE [star s] and [s] _xWHITE [star s] engineering [s] @@
# Ex: computer\_and\_information\_science
_field [layer=(_Caps )] <- computer [s] _xWHITE [star s] and [s] _xWHITE [star s] information [s] _xWHITE [star s] science [s] @@
# Ex: coastal\_and\_oceanographic\_engineering
_field [layer=(_Caps )] <- coastal [s] _xWHITE [star s] and [s] _xWHITE [star s] oceanographic [s] _xWHITE [star s] engineering [s] @@
# Ex: clinical\_and\_school\_psychology
_field [layer=(_Caps )] <- clinical [s] _xWHITE [star s] and [s] _xWHITE [star s] school [s] _xWHITE [star s] psychology [s] @@
# Ex: clinical\_and\_health\_psychology
_field [layer=(_Caps )] <- clinical [s] _xWHITE [star s] and [s] _xWHITE [star s] health [s] _xWHITE [star s] psychology [s] @@
# Ex: civil\_and\_environmental\_engineering
_field [layer=(_Caps )] <- civil [s] _xWHITE [star s] and [s] _xWHITE [star s] environmental [s] _xWHITE [star s] engineering [s] @@
# Ex: brain\_and\_cognitive\_sciences
_field [layer=(_Caps )] <- brain [s] _xWHITE [star s] and [s] _xWHITE [star s] cognitive [s] _xWHITE [star s] sciences [s] @@
# Ex: biological\_and\_agricultural\_engineering
_field [layer=(_Caps )] <- biological [s] _xWHITE [star s] and [s] _xWHITE [star s] agricultural [s] _xWHITE [star s] engineering [s] @@
# Ex: agricultural\_and\_biological\_engineering
_field [layer=(_Caps )] <- agricultural [s] _xWHITE [star s] and [s] _xWHITE [star s] biological [s] _xWHITE [star s] engineering [s] @@
# Ex: afro\_\\-\_american\_studies
_field [layer=(_Caps )] <- afro [s] _xWHITE [star s] \\ [s] \- [s] _xWHITE [star s] american [s] _xWHITE [star s] studies [s] @@
# Ex: veterinary\_medical\_sciences
_field [layer=(_Caps )] <- veterinary [s] _xWHITE [star s] medical [s] _xWHITE [star s] sciences [s] @@
# Ex: training\_and\_development
_field [layer=(_Caps )] <- training [s] _xWHITE [star s] and [s] _xWHITE [star s] development [s] @@
# Ex: solid\_state\_science
_field [layer=(_Caps )] <- solid [s] _xWHITE [star s] state [s] _xWHITE [star s] science [s] @@
# Ex: social\_studies\_education
_field [layer=(_Caps )] <- social [s] _xWHITE [star s] studies [s] _xWHITE [star s] education [s] @@
# Ex: physical\_therapist\_assistance
_field [layer=(_Caps )] <- physical [s] _xWHITE [star s] therapist [s] _xWHITE [star s] assistance [s] @@
# Ex: pharmacology\_and\_therapeutics
_field [layer=(_Caps )] <- pharmacology [s] _xWHITE [star s] and [s] _xWHITE [star s] therapeutics [s] @@
# Ex: natural\_resources\_conservation
_field [layer=(_Caps )] <- natural [s] _xWHITE [star s] resources [s] _xWHITE [star s] conservation [s] @@
# Ex: natural\_resource\_conservation
_field [layer=(_Caps )] <- natural [s] _xWHITE [star s] resource [s] _xWHITE [star s] conservation [s] @@
# Ex: mineral\_engineering\_management
_field [layer=(_Caps )] <- mineral [s] _xWHITE [star s] engineering [s] _xWHITE [star s] management [s] @@
# Ex: middle\_eastern\_languages
_field [layer=(_Caps )] <- middle [s] _xWHITE [star s] eastern [s] _xWHITE [star s] languages [s] @@
# Ex: middle\_east\_studies
_field [layer=(_Caps )] <- middle [s] _xWHITE [star s] east [s] _xWHITE [star s] studies [s] @@
# Ex: manufacturing\_engineering\_technology
_field [layer=(_Caps )] <- manufacturing [s] _xWHITE [star s] engineering [s] _xWHITE [star s] technology [s] @@
# Ex: management\_information\_systems
_field [layer=(_Caps )] <- management [s] _xWHITE [star s] information [s] _xWHITE [star s] systems [s] @@
# Ex: management\_and\_organization
_field [layer=(_Caps )] <- management [s] _xWHITE [star s] and [s] _xWHITE [star s] organization [s] @@
# Ex: law\_and\_justice
_field [layer=(_Caps )] <- law [s] _xWHITE [star s] and [s] _xWHITE [star s] justice [s] @@
# Ex: latin\_american\_studies
_field [layer=(_Caps )] <- latin [s] _xWHITE [star s] american [s] _xWHITE [star s] studies [s] @@
# Ex: laboratory\_animal\_medicine
_field [layer=(_Caps )] <- laboratory [s] _xWHITE [star s] animal [s] _xWHITE [star s] medicine [s] @@
# Ex: instruction\_and\_curriculum
_field [layer=(_Caps )] <- instruction [s] _xWHITE [star s] and [s] _xWHITE [star s] curriculum [s] @@
# Ex: human\_resources\_management
_field [layer=(_Caps )] <- human [s] _xWHITE [star s] resources [s] _xWHITE [star s] management [s] @@
# Ex: human\_resource\_management
_field [layer=(_Caps )] <- human [s] _xWHITE [star s] resource [s] _xWHITE [star s] management [s] @@
# Ex: human\_resource\_development
_field [layer=(_Caps )] <- human [s] _xWHITE [star s] resource [s] _xWHITE [star s] development [s] @@
# Ex: health\_services\_administration
_field [layer=(_Caps )] <- health [s] _xWHITE [star s] services [s] _xWHITE [star s] administration [s] @@
# Ex: health\_science\_education
_field [layer=(_Caps )] <- health [s] _xWHITE [star s] science [s] _xWHITE [star s] education [s] @@
# Ex: health\_information\_technology
_field [layer=(_Caps )] <- health [s] _xWHITE [star s] information [s] _xWHITE [star s] technology [s] @@
# Ex: health\_information\_administration
_field [layer=(_Caps )] <- health [s] _xWHITE [star s] information [s] _xWHITE [star s] administration [s] @@
# Ex: health\_evaluation\_sciences
_field [layer=(_Caps )] <- health [s] _xWHITE [star s] evaluation [s] _xWHITE [star s] sciences [s] @@
# Ex: health\_care\_management
_field [layer=(_Caps )] <- health [s] _xWHITE [star s] care [s] _xWHITE [star s] management [s] @@
# Ex: foundations\_of\_education
_field [layer=(_Caps )] <- foundations [s] _xWHITE [star s] of [s] _xWHITE [star s] education [s] @@
# Ex: foreign\_language\_education
_field [layer=(_Caps )] <- foreign [s] _xWHITE [star s] language [s] _xWHITE [star s] education [s] @@
# Ex: food\_service\_management
_field [layer=(_Caps )] <- food [s] _xWHITE [star s] service [s] _xWHITE [star s] management [s] @@
# Ex: film\_and\_video
_field [layer=(_Caps )] <- film [s] _xWHITE [star s] and [s] _xWHITE [star s] video [s] @@
# Ex: environmental\_pollution\_control
_field [layer=(_Caps )] <- environmental [s] _xWHITE [star s] pollution [s] _xWHITE [star s] control [s] @@
# Ex: environmental\_engineering\_sciences
_field [layer=(_Caps )] <- environmental [s] _xWHITE [star s] engineering [s] _xWHITE [star s] sciences [s] @@
# Ex: electric\_power\_engineering
_field [layer=(_Caps )] <- electric [s] _xWHITE [star s] power [s] _xWHITE [star s] engineering [s] @@
# Ex: early\_childhood\_education
_field [layer=(_Caps )] <- early [s] _xWHITE [star s] childhood [s] _xWHITE [star s] education [s] @@
# Ex: curriculum\_and\_instruction
_field [layer=(_Caps )] <- curriculum [s] _xWHITE [star s] and [s] _xWHITE [star s] instruction [s] @@
# Ex: cooperative\_education\_program
_field [layer=(_Caps )] <- cooperative [s] _xWHITE [star s] education [s] _xWHITE [star s] program [s] @@
# Ex: clinical\_laboratory\_sciences
_field [layer=(_Caps )] <- clinical [s] _xWHITE [star s] laboratory [s] _xWHITE [star s] sciences [s] @@
# Ex: clinical\_laboratory\_science
_field [layer=(_Caps )] <- clinical [s] _xWHITE [star s] laboratory [s] _xWHITE [star s] science [s] @@
# Ex: banking\_and\_finance
_field [layer=(_Caps )] <- banking [s] _xWHITE [star s] and [s] _xWHITE [star s] finance [s] @@
# Ex: astronomy\_and\_astrophysics
_field [layer=(_Caps )] <- astronomy [s] _xWHITE [star s] and [s] _xWHITE [star s] astrophysics [s] @@
# Ex: applied\_information\_technology
_field [layer=(_Caps )] <- applied [s] _xWHITE [star s] information [s] _xWHITE [star s] technology [s] @@
# Ex: american\_ethnic\_studies
_field [layer=(_Caps )] <- american [s] _xWHITE [star s] ethnic [s] _xWHITE [star s] studies [s] @@
# Ex: air\_force\_rotc
_field [layer=(_Caps )] <- air [s] _xWHITE [star s] force [s] _xWHITE [star s] rotc [s] @@
# Ex: agricultural\_technology\_management
_field [layer=(_Caps )] <- agricultural [s] _xWHITE [star s] technology [s] _xWHITE [star s] management [s] @@
# Ex: agricultural\_operations\_management
_field [layer=(_Caps )] <- agricultural [s] _xWHITE [star s] operations [s] _xWHITE [star s] management [s] @@
# Ex: aeronautics\_and\_astronautics
_field [layer=(_Caps )] <- aeronautics [s] _xWHITE [star s] and [s] _xWHITE [star s] astronautics [s] @@
# Ex: adapted\_physical\_education
_field [layer=(_Caps )] <- adapted [s] _xWHITE [star s] physical [s] _xWHITE [star s] education [s] @@
# Ex: workforce\_education
_field [layer=(_Caps )] <- workforce [s] _xWHITE [star s] education [s] @@
# Ex: wildlife\_science
_field [layer=(_Caps )] <- wildlife [s] _xWHITE [star s] science [s] @@
# Ex: wildlife\_ecology
_field [layer=(_Caps )] <- wildlife [s] _xWHITE [star s] ecology [s] @@
# Ex: voice\_performance
_field [layer=(_Caps )] <- voice [s] _xWHITE [star s] performance [s] @@
# Ex: visual\_arts
_field [layer=(_Caps )] <- visual [s] _xWHITE [star s] arts [s] @@
# Ex: veterinary\_science
_field [layer=(_Caps )] <- veterinary [s] _xWHITE [star s] science [s] @@
# Ex: veterinary\_medicine
_field [layer=(_Caps )] <- veterinary [s] _xWHITE [star s] medicine [s] @@
# Ex: urban\_studies
_field [layer=(_Caps )] <- urban [s] _xWHITE [star s] studies [s] @@
# Ex: urban\_planning
_field [layer=(_Caps )] <- urban [s] _xWHITE [star s] planning [s] @@
# Ex: urban\_development
_field [layer=(_Caps )] <- urban [s] _xWHITE [star s] development [s] @@
# Ex: transportation\_systems
_field [layer=(_Caps )] <- transportation [s] _xWHITE [star s] systems [s] @@
# Ex: tourism\_administration
_field [layer=(_Caps )] <- tourism [s] _xWHITE [star s] administration [s] @@
# Ex: theatre\_arts
_field [layer=(_Caps )] <- theatre [s] _xWHITE [star s] arts [s] @@
# Ex: textile\_design
_field [layer=(_Caps )] <- textile [s] _xWHITE [star s] design [s] @@
# Ex: telecommunications\_studies
_field [layer=(_Caps )] <- telecommunications [s] _xWHITE [star s] studies [s] @@
# Ex: teacher\_education
_field [layer=(_Caps )] <- teacher [s] _xWHITE [star s] education [s] @@
# Ex: systems\_engineering
_field [layer=(_Caps )] <- systems [s] _xWHITE [star s] engineering [s] @@
# Ex: student\_counseling
_field [layer=(_Caps )] <- student [s] _xWHITE [star s] counseling [s] @@
# Ex: structural\_mechanics
_field [layer=(_Caps )] <- structural [s] _xWHITE [star s] mechanics [s] @@
# Ex: sports\_medicine
_field [layer=(_Caps )] <- sports [s] _xWHITE [star s] medicine [s] @@
# Ex: sport\_psychology
_field [layer=(_Caps )] <- sport [s] _xWHITE [star s] psychology [s] @@
# Ex: speech\_pathology
_field [layer=(_Caps )] <- speech [s] _xWHITE [star s] pathology [s] @@
# Ex: speech\_communication
_field [layer=(_Caps )] <- speech [s] _xWHITE [star s] communication [s] @@
# Ex: special\_education
_field [layer=(_Caps )] <- special [s] _xWHITE [star s] education [s] @@
# Ex: solid\_state
_field [layer=(_Caps )] <- solid [s] _xWHITE [star s] state [s] @@
# Ex: soil\_science
_field [layer=(_Caps )] <- soil [s] _xWHITE [star s] science [s] @@
# Ex: software\_engineering
_field [layer=(_Caps )] <- software [s] _xWHITE [star s] engineering [s] @@
# Ex: social\_work
_field [layer=(_Caps )] <- social [s] _xWHITE [star s] work [s] @@
# Ex: social\_studies
_field [layer=(_Caps )] <- social [s] _xWHITE [star s] studies [s] @@
# Ex: slavic\_languages
_field [layer=(_Caps )] <- slavic [s] _xWHITE [star s] languages [s] @@
# Ex: science\_education
_field [layer=(_Caps )] <- science [s] _xWHITE [star s] education [s] @@
# Ex: school\_psychology
_field [layer=(_Caps )] <- school [s] _xWHITE [star s] psychology [s] @@
# Ex: russian\_studies
_field [layer=(_Caps )] <- russian [s] _xWHITE [star s] studies [s] @@
# Ex: rural\_sociology
_field [layer=(_Caps )] <- rural [s] _xWHITE [star s] sociology [s] @@
# Ex: rotc\_programs
_field [layer=(_Caps )] <- rotc [s] _xWHITE [star s] programs [s] @@
# Ex: romance\_languages
_field [layer=(_Caps )] <- romance [s] _xWHITE [star s] languages [s] @@
# Ex: restaurant\_management
_field [layer=(_Caps )] <- restaurant [s] _xWHITE [star s] management [s] @@
# Ex: respiratory\_technology
_field [layer=(_Caps )] <- respiratory [s] _xWHITE [star s] technology [s] @@
# Ex: religious\_studies
_field [layer=(_Caps )] <- religious [s] _xWHITE [star s] studies [s] @@
# Ex: rehabilitation\_science
_field [layer=(_Caps )] <- rehabilitation [s] _xWHITE [star s] science [s] @@
# Ex: rehabilitation\_counseling
_field [layer=(_Caps )] <- rehabilitation [s] _xWHITE [star s] counseling [s] @@
# Ex: recreation\_resources
_field [layer=(_Caps )] <- recreation [s] _xWHITE [star s] resources [s] @@
# Ex: recreation\_management
_field [layer=(_Caps )] <- recreation [s] _xWHITE [star s] management [s] @@
# Ex: real\_estate
_field [layer=(_Caps )] <- real [s] _xWHITE [star s] estate [s] @@
# Ex: reading\_education
_field [layer=(_Caps )] <- reading [s] _xWHITE [star s] education [s] @@
# Ex: radiological\_engineering
_field [layer=(_Caps )] <- radiological [s] _xWHITE [star s] engineering [s] @@
# Ex: radiologic\_technology
_field [layer=(_Caps )] <- radiologic [s] _xWHITE [star s] technology [s] @@
# Ex: quantitative\_analysis
_field [layer=(_Caps )] <- quantitative [s] _xWHITE [star s] analysis [s] @@
# Ex: public\_relations
_field [layer=(_Caps )] <- public [s] _xWHITE [star s] relations [s] @@
# Ex: public\_policy
_field [layer=(_Caps )] <- public [s] _xWHITE [star s] policy [s] @@
# Ex: public\_health
_field [layer=(_Caps )] <- public [s] _xWHITE [star s] health [s] @@
# Ex: public\_administration
_field [layer=(_Caps )] <- public [s] _xWHITE [star s] administration [s] @@
# Ex: polymer\_science
_field [layer=(_Caps )] <- polymer [s] _xWHITE [star s] science [s] @@
# Ex: political\_science
_field [layer=(_Caps )] <- political [s] _xWHITE [star s] science [s] @@
# Ex: police\_science
_field [layer=(_Caps )] <- police [s] _xWHITE [star s] science [s] @@
# Ex: plant\_sciences
_field [layer=(_Caps )] <- plant [s] _xWHITE [star s] sciences [s] @@
# Ex: plant\_physiology
_field [layer=(_Caps )] <- plant [s] _xWHITE [star s] physiology [s] @@
# Ex: plant\_pathology
_field [layer=(_Caps )] <- plant [s] _xWHITE [star s] pathology [s] @@
# Ex: planetary\_sciences
_field [layer=(_Caps )] <- planetary [s] _xWHITE [star s] sciences [s] @@
# Ex: physical\_therapy
_field [layer=(_Caps )] <- physical [s] _xWHITE [star s] therapy [s] @@
# Ex: physical\_therapist
_field [layer=(_Caps )] <- physical [s] _xWHITE [star s] therapist [s] @@
# Ex: physical\_education
_field [layer=(_Caps )] <- physical [s] _xWHITE [star s] education [s] @@
# Ex: pharmacy\_health
_field [layer=(_Caps )] <- pharmacy [s] _xWHITE [star s] health [s] @@
# Ex: pharmaceutical\_sciences
_field [layer=(_Caps )] <- pharmaceutical [s] _xWHITE [star s] sciences [s] @@
# Ex: pest\_management
_field [layer=(_Caps )] <- pest [s] _xWHITE [star s] management [s] @@
# Ex: park\_management
_field [layer=(_Caps )] <- park [s] _xWHITE [star s] management [s] @@
# Ex: oral\_biology
_field [layer=(_Caps )] <- oral [s] _xWHITE [star s] biology [s] @@
# Ex: operations\_research
_field [layer=(_Caps )] <- operations [s] _xWHITE [star s] research [s] @@
# Ex: operations\_management
_field [layer=(_Caps )] <- operations [s] _xWHITE [star s] management [s] @@
# Ex: office\_technology
_field [layer=(_Caps )] <- office [s] _xWHITE [star s] technology [s] @@
# Ex: ocean\_engineering
_field [layer=(_Caps )] <- ocean [s] _xWHITE [star s] engineering [s] @@
# Ex: occupational\_therapy
_field [layer=(_Caps )] <- occupational [s] _xWHITE [star s] therapy [s] @@
# Ex: occupational\_development
_field [layer=(_Caps )] <- occupational [s] _xWHITE [star s] development [s] @@
# Ex: nuclear\_engineering
_field [layer=(_Caps )] <- nuclear [s] _xWHITE [star s] engineering [s] @@
# Ex: navy\_rotc
_field [layer=(_Caps )] <- navy [s] _xWHITE [star s] rotc [s] @@
# Ex: motor\_learning
_field [layer=(_Caps )] <- motor [s] _xWHITE [star s] learning [s] @@
# Ex: molecular\_genetics
_field [layer=(_Caps )] <- molecular [s] _xWHITE [star s] genetics [s] @@
# Ex: molecular\_biology
_field [layer=(_Caps )] <- molecular [s] _xWHITE [star s] biology [s] @@
# Ex: modern\_languages
_field [layer=(_Caps )] <- modern [s] _xWHITE [star s] languages [s] @@
# Ex: mining\_engineering
_field [layer=(_Caps )] <- mining [s] _xWHITE [star s] engineering [s] @@
# Ex: mineral\_processing
_field [layer=(_Caps )] <- mineral [s] _xWHITE [star s] processing [s] @@
# Ex: mineral\_engineering
_field [layer=(_Caps )] <- mineral [s] _xWHITE [star s] engineering [s] @@
# Ex: mineral\_economics
_field [layer=(_Caps )] <- mineral [s] _xWHITE [star s] economics [s] @@
# Ex: military\_science
_field [layer=(_Caps )] <- military [s] _xWHITE [star s] science [s] @@
# Ex: metals\_science
_field [layer=(_Caps )] <- metals [s] _xWHITE [star s] science [s] @@
# Ex: medicinal\_chemistry
_field [layer=(_Caps )] <- medicinal [s] _xWHITE [star s] chemistry [s] @@
# Ex: medical\_sciences
_field [layer=(_Caps )] <- medical [s] _xWHITE [star s] sciences [s] @@
# Ex: medical\_school
_field [layer=(_Caps )] <- medical [s] _xWHITE [star s] school [s] @@
# Ex: medical\_assistance
_field [layer=(_Caps )] <- medical [s] _xWHITE [star s] assistance [s] @@
# Ex: media\_studies
_field [layer=(_Caps )] <- media [s] _xWHITE [star s] studies [s] @@
# Ex: media\_arts
_field [layer=(_Caps )] <- media [s] _xWHITE [star s] arts [s] @@
# Ex: mechanical\_engineering
_field [layer=(_Caps )] <- mechanical [s] _xWHITE [star s] engineering [s] @@
# Ex: mathematics\_education
_field [layer=(_Caps )] <- mathematics [s] _xWHITE [star s] education [s] @@
# Ex: materials\_science
_field [layer=(_Caps )] <- materials [s] _xWHITE [star s] science [s] @@
# Ex: materials\_engineering
_field [layer=(_Caps )] <- materials [s] _xWHITE [star s] engineering [s] @@
# Ex: mass\_communications
_field [layer=(_Caps )] <- mass [s] _xWHITE [star s] communications [s] @@
# Ex: mass\_communication
_field [layer=(_Caps )] <- mass [s] _xWHITE [star s] communication [s] @@
# Ex: manufacturing\_engineering
_field [layer=(_Caps )] <- manufacturing [s] _xWHITE [star s] engineering [s] @@
# Ex: management\_technology
_field [layer=(_Caps )] <- management [s] _xWHITE [star s] technology [s] @@
# Ex: management\_science
_field [layer=(_Caps )] <- management [s] _xWHITE [star s] science [s] @@
# Ex: management\_information
_field [layer=(_Caps )] <- management [s] _xWHITE [star s] information [s] @@
# Ex: literary\_theory
_field [layer=(_Caps )] <- literary [s] _xWHITE [star s] theory [s] @@
# Ex: literary\_criticism
_field [layer=(_Caps )] <- literary [s] _xWHITE [star s] criticism [s] @@
# Ex: liberal\_arts
_field [layer=(_Caps )] <- liberal [s] _xWHITE [star s] arts [s] @@
# Ex: leisure\_studies
_field [layer=(_Caps )] <- leisure [s] _xWHITE [star s] studies [s] @@
# Ex: legal\_assistance
_field [layer=(_Caps )] <- legal [s] _xWHITE [star s] assistance [s] @@
# Ex: law\_enforcement
_field [layer=(_Caps )] <- law [s] _xWHITE [star s] enforcement [s] @@
# Ex: landscape\_architecture
_field [layer=(_Caps )] <- landscape [s] _xWHITE [star s] architecture [s] @@
# Ex: labor\_studies
_field [layer=(_Caps )] <- labor [s] _xWHITE [star s] studies [s] @@
# Ex: labor\_relations
_field [layer=(_Caps )] <- labor [s] _xWHITE [star s] relations [s] @@
# Ex: jewish\_studies
_field [layer=(_Caps )] <- jewish [s] _xWHITE [star s] studies [s] @@
# Ex: international\_studies
_field [layer=(_Caps )] <- international [s] _xWHITE [star s] studies [s] @@
# Ex: international\_business
_field [layer=(_Caps )] <- international [s] _xWHITE [star s] business [s] @@
# Ex: interior\_design
_field [layer=(_Caps )] <- interior [s] _xWHITE [star s] design [s] @@
# Ex: interior\_architecture
_field [layer=(_Caps )] <- interior [s] _xWHITE [star s] architecture [s] @@
# Ex: interdisciplinary\_studies
_field [layer=(_Caps )] <- interdisciplinary [s] _xWHITE [star s] studies [s] @@
# Ex: instructional\_technology
_field [layer=(_Caps )] <- instructional [s] _xWHITE [star s] technology [s] @@
# Ex: institutional\_management
_field [layer=(_Caps )] <- institutional [s] _xWHITE [star s] management [s] @@
# Ex: information\_systems
_field [layer=(_Caps )] <- information [s] _xWHITE [star s] systems [s] @@
# Ex: information\_science
_field [layer=(_Caps )] <- information [s] _xWHITE [star s] science [s] @@
# Ex: information\_management
_field [layer=(_Caps )] <- information [s] _xWHITE [star s] management [s] @@
# Ex: industrial\_relations
_field [layer=(_Caps )] <- industrial [s] _xWHITE [star s] relations [s] @@
# Ex: industrial\_engineering
_field [layer=(_Caps )] <- industrial [s] _xWHITE [star s] engineering [s] @@
# Ex: individual\_studies
_field [layer=(_Caps )] <- individual [s] _xWHITE [star s] studies [s] @@
# Ex: human\_resources
_field [layer=(_Caps )] <- human [s] _xWHITE [star s] resources [s] @@
# Ex: human\_nutrition
_field [layer=(_Caps )] <- human [s] _xWHITE [star s] nutrition [s] @@
# Ex: human\_ecology
_field [layer=(_Caps )] <- human [s] _xWHITE [star s] ecology [s] @@
# Ex: human\_development
_field [layer=(_Caps )] <- human [s] _xWHITE [star s] development [s] @@
# Ex: hotel\_management
_field [layer=(_Caps )] <- hotel [s] _xWHITE [star s] management [s] @@
# Ex: hospitality\_management
_field [layer=(_Caps )] <- hospitality [s] _xWHITE [star s] management [s] @@
# Ex: horticultural\_sciences
_field [layer=(_Caps )] <- horticultural [s] _xWHITE [star s] sciences [s] @@
# Ex: horticultural\_science
_field [layer=(_Caps )] <- horticultural [s] _xWHITE [star s] science [s] @@
# Ex: hebrew\_studies
_field [layer=(_Caps )] <- hebrew [s] _xWHITE [star s] studies [s] @@
# Ex: health\_services
_field [layer=(_Caps )] <- health [s] _xWHITE [star s] services [s] @@
# Ex: health\_sciences
_field [layer=(_Caps )] <- health [s] _xWHITE [star s] sciences [s] @@
# Ex: health\_science
_field [layer=(_Caps )] <- health [s] _xWHITE [star s] science [s] @@
# Ex: health\_policy
_field [layer=(_Caps )] <- health [s] _xWHITE [star s] policy [s] @@
# Ex: health\_information
_field [layer=(_Caps )] <- health [s] _xWHITE [star s] information [s] @@
# Ex: health\_education
_field [layer=(_Caps )] <- health [s] _xWHITE [star s] education [s] @@
# Ex: health\_administration
_field [layer=(_Caps )] <- health [s] _xWHITE [star s] administration [s] @@
# Ex: grain\_science
_field [layer=(_Caps )] <- grain [s] _xWHITE [star s] science [s] @@
# Ex: gerontological\_studies
_field [layer=(_Caps )] <- gerontological [s] _xWHITE [star s] studies [s] @@
# Ex: germanic\_studies
_field [layer=(_Caps )] <- germanic [s] _xWHITE [star s] studies [s] @@
# Ex: general\_studies
_field [layer=(_Caps )] <- general [s] _xWHITE [star s] studies [s] @@
# Ex: forest\_resources
_field [layer=(_Caps )] <- forest [s] _xWHITE [star s] resources [s] @@
# Ex: foreign\_languages
_field [layer=(_Caps )] <- foreign [s] _xWHITE [star s] languages [s] @@
# Ex: foreign\_affairs
_field [layer=(_Caps )] <- foreign [s] _xWHITE [star s] affairs [s] @@
# Ex: food\_service
_field [layer=(_Caps )] <- food [s] _xWHITE [star s] service [s] @@
# Ex: food\_science
_field [layer=(_Caps )] <- food [s] _xWHITE [star s] science [s] @@
# Ex: fisheries\_science
_field [layer=(_Caps )] <- fisheries [s] _xWHITE [star s] science [s] @@
# Ex: fine\_arts
_field [layer=(_Caps )] <- fine [s] _xWHITE [star s] arts [s] @@
# Ex: film\_studies
_field [layer=(_Caps )] <- film [s] _xWHITE [star s] studies [s] @@
# Ex: fashion\_design
_field [layer=(_Caps )] <- fashion [s] _xWHITE [star s] design [s] @@
# Ex: family\_studies
_field [layer=(_Caps )] <- family [s] _xWHITE [star s] studies [s] @@
# Ex: exercise\_physiology
_field [layer=(_Caps )] <- exercise [s] _xWHITE [star s] physiology [s] @@
# Ex: european\_history
_field [layer=(_Caps )] <- european [s] _xWHITE [star s] history [s] @@
# Ex: ethnic\_studies
_field [layer=(_Caps )] <- ethnic [s] _xWHITE [star s] studies [s] @@
# Ex: environmental\_studies
_field [layer=(_Caps )] <- environmental [s] _xWHITE [star s] studies [s] @@
# Ex: environmental\_sciences
_field [layer=(_Caps )] <- environmental [s] _xWHITE [star s] sciences [s] @@
# Ex: environmental\_science
_field [layer=(_Caps )] <- environmental [s] _xWHITE [star s] science [s] @@
# Ex: environmental\_planning
_field [layer=(_Caps )] <- environmental [s] _xWHITE [star s] planning [s] @@
# Ex: environmental\_health
_field [layer=(_Caps )] <- environmental [s] _xWHITE [star s] health [s] @@
# Ex: environmental\_engineering
_field [layer=(_Caps )] <- environmental [s] _xWHITE [star s] engineering [s] @@
# Ex: english\_education
_field [layer=(_Caps )] <- english [s] _xWHITE [star s] education [s] @@
# Ex: engineering\_technology
_field [layer=(_Caps )] <- engineering [s] _xWHITE [star s] technology [s] @@
# Ex: engineering\_science
_field [layer=(_Caps )] <- engineering [s] _xWHITE [star s] science [s] @@
# Ex: engineering\_physics
_field [layer=(_Caps )] <- engineering [s] _xWHITE [star s] physics [s] @@
# Ex: engineering\_mechanics
_field [layer=(_Caps )] <- engineering [s] _xWHITE [star s] mechanics [s] @@
# Ex: engineering\_management
_field [layer=(_Caps )] <- engineering [s] _xWHITE [star s] management [s] @@
# Ex: energy\_engineering
_field [layer=(_Caps )] <- energy [s] _xWHITE [star s] engineering [s] @@
# Ex: elementary\_education
_field [layer=(_Caps )] <- elementary [s] _xWHITE [star s] education [s] @@
# Ex: electronics\_technology
_field [layer=(_Caps )] <- electronics [s] _xWHITE [star s] technology [s] @@
# Ex: electrical\_engineering
_field [layer=(_Caps )] <- electrical [s] _xWHITE [star s] engineering [s] @@
# Ex: educational\_research
_field [layer=(_Caps )] <- educational [s] _xWHITE [star s] research [s] @@
# Ex: educational\_psychology
_field [layer=(_Caps )] <- educational [s] _xWHITE [star s] psychology [s] @@
# Ex: educational\_policy
_field [layer=(_Caps )] <- educational [s] _xWHITE [star s] policy [s] @@
# Ex: educational\_leadership
_field [layer=(_Caps )] <- educational [s] _xWHITE [star s] leadership [s] @@
# Ex: educational\_evaluation
_field [layer=(_Caps )] <- educational [s] _xWHITE [star s] evaluation [s] @@
# Ex: educational\_administration
_field [layer=(_Caps )] <- educational [s] _xWHITE [star s] administration [s] @@
# Ex: earth\_sciences
_field [layer=(_Caps )] <- earth [s] _xWHITE [star s] sciences [s] @@
# Ex: developmental\_biology
_field [layer=(_Caps )] <- developmental [s] _xWHITE [star s] biology [s] @@
# Ex: dental\_sciences
_field [layer=(_Caps )] <- dental [s] _xWHITE [star s] sciences [s] @@
# Ex: criminal\_justice
_field [layer=(_Caps )] <- criminal [s] _xWHITE [star s] justice [s] @@
# Ex: creative\_writing
_field [layer=(_Caps )] <- creative [s] _xWHITE [star s] writing [s] @@
# Ex: counselor\_education
_field [layer=(_Caps )] <- counselor [s] _xWHITE [star s] education [s] @@
# Ex: cooperative\_education
_field [layer=(_Caps )] <- cooperative [s] _xWHITE [star s] education [s] @@
# Ex: continuing\_education
_field [layer=(_Caps )] <- continuing [s] _xWHITE [star s] education [s] @@
# Ex: computer\_programming
_field [layer=(_Caps )] <- computer [s] _xWHITE [star s] programming [s] @@
# Ex: computer\_technology
_field [layer=(_Caps )] <- computer [s] _xWHITE [star s] technology [s] @@
# Ex: computer\_science
_field [layer=(_Caps )] <- computer [s] _xWHITE [star s] science [s] @@
# Ex: computer\_engineering
_field [layer=(_Caps )] <- computer [s] _xWHITE [star s] engineering [s] @@
# Ex: comparative\_literature
_field [layer=(_Caps )] <- comparative [s] _xWHITE [star s] literature [s] @@
# Ex: comparative\_law
_field [layer=(_Caps )] <- comparative [s] _xWHITE [star s] law [s] @@
# Ex: community\_studies
_field [layer=(_Caps )] <- community [s] _xWHITE [star s] studies [s] @@
# Ex: community\_education
_field [layer=(_Caps )] <- community [s] _xWHITE [star s] education [s] @@
# Ex: communicative\_disorders
_field [layer=(_Caps )] <- communicative [s] _xWHITE [star s] disorders [s] @@
# Ex: communication\_sciences
_field [layer=(_Caps )] <- communication [s] _xWHITE [star s] sciences [s] @@
# Ex: communication\_disorders
_field [layer=(_Caps )] <- communication [s] _xWHITE [star s] disorders [s] @@
# Ex: cognitive\_sciences
_field [layer=(_Caps )] <- cognitive [s] _xWHITE [star s] sciences [s] @@
# Ex: cognitive\_science
_field [layer=(_Caps )] <- cognitive [s] _xWHITE [star s] science [s] @@
# Ex: clinical\_sciences
_field [layer=(_Caps )] <- clinical [s] _xWHITE [star s] sciences [s] @@
# Ex: clinical\_psychology
_field [layer=(_Caps )] <- clinical [s] _xWHITE [star s] psychology [s] @@
# Ex: clinical\_ethics
_field [layer=(_Caps )] <- clinical [s] _xWHITE [star s] ethics [s] @@
# Ex: clinch\_valley
_field [layer=(_Caps )] <- clinch [s] _xWHITE [star s] valley [s] @@
# Ex: civil\_engineering
_field [layer=(_Caps )] <- civil [s] _xWHITE [star s] engineering [s] @@
# Ex: city\_planning
_field [layer=(_Caps )] <- city [s] _xWHITE [star s] planning [s] @@
# Ex: chemical\_engineering
_field [layer=(_Caps )] <- chemical [s] _xWHITE [star s] engineering [s] @@
# Ex: ceramic\_science
_field [layer=(_Caps )] <- ceramic [s] _xWHITE [star s] science [s] @@
# Ex: business\_logistics
_field [layer=(_Caps )] <- business [s] _xWHITE [star s] logistics [s] @@
# Ex: business\_law
_field [layer=(_Caps )] <- business [s] _xWHITE [star s] law [s] @@
# Ex: business\_administration
_field [layer=(_Caps )] <- business [s] _xWHITE [star s] administration [s] @@
# Ex: building\_construction
_field [layer=(_Caps )] <- building [s] _xWHITE [star s] construction [s] @@
# Ex: biomedical\_engineering
_field [layer=(_Caps )] <- biomedical [s] _xWHITE [star s] engineering [s] @@
# Ex: biological\_sciences
_field [layer=(_Caps )] <- biological [s] _xWHITE [star s] sciences [s] @@
# Ex: biological\_chemistry
_field [layer=(_Caps )] <- biological [s] _xWHITE [star s] chemistry [s] @@
# Ex: bilingual\_education
_field [layer=(_Caps )] <- bilingual [s] _xWHITE [star s] education [s] @@
# Ex: aviation\_technology
_field [layer=(_Caps )] <- aviation [s] _xWHITE [star s] technology [s] @@
# Ex: automotive\_technology
_field [layer=(_Caps )] <- automotive [s] _xWHITE [star s] technology [s] @@
# Ex: atmospheric\_sciences
_field [layer=(_Caps )] <- atmospheric [s] _xWHITE [star s] sciences [s] @@
# Ex: athletic\_training
_field [layer=(_Caps )] <- athletic [s] _xWHITE [star s] training [s] @@
# Ex: asian\_studies
_field [layer=(_Caps )] <- asian [s] _xWHITE [star s] studies [s] @@
# Ex: asian\_languages
_field [layer=(_Caps )] <- asian [s] _xWHITE [star s] languages [s] @@
# Ex: asian\_history
_field [layer=(_Caps )] <- asian [s] _xWHITE [star s] history [s] @@
# Ex: art\_history
_field [layer=(_Caps )] <- art [s] _xWHITE [star s] history [s] @@
# Ex: art\_education
_field [layer=(_Caps )] <- art [s] _xWHITE [star s] education [s] @@
# Ex: army\_rotc
_field [layer=(_Caps )] <- army [s] _xWHITE [star s] rotc [s] @@
# Ex: architecture\_school
_field [layer=(_Caps )] <- architecture [s] _xWHITE [star s] school [s] @@
# Ex: architectural\_history
_field [layer=(_Caps )] <- architectural [s] _xWHITE [star s] history [s] @@
# Ex: architectural\_engineering
_field [layer=(_Caps )] <- architectural [s] _xWHITE [star s] engineering [s] @@
# Ex: applied\_mechanics
_field [layer=(_Caps )] <- applied [s] _xWHITE [star s] mechanics [s] @@
# Ex: applied\_mathematics
_field [layer=(_Caps )] <- applied [s] _xWHITE [star s] mathematics [s] @@
# Ex: apparel\_textiles
_field [layer=(_Caps )] <- apparel [s] _xWHITE [star s] textiles [s] @@
# Ex: apparel\_design
_field [layer=(_Caps )] <- apparel [s] _xWHITE [star s] design [s] @@
# Ex: animal\_sciences
_field [layer=(_Caps )] <- animal [s] _xWHITE [star s] sciences [s] @@
# Ex: animal\_science
_field [layer=(_Caps )] <- animal [s] _xWHITE [star s] science [s] @@
# Ex: animal\_nutrition
_field [layer=(_Caps )] <- animal [s] _xWHITE [star s] nutrition [s] @@
# Ex: animal\_medicine
_field [layer=(_Caps )] <- animal [s] _xWHITE [star s] medicine [s] @@
# Ex: animal\_husbandry
_field [layer=(_Caps )] <- animal [s] _xWHITE [star s] husbandry [s] @@
# Ex: american\_studies
_field [layer=(_Caps )] <- american [s] _xWHITE [star s] studies [s] @@
# Ex: american\_history
_field [layer=(_Caps )] <- american [s] _xWHITE [star s] history [s] @@
# Ex: american\_ethnic
_field [layer=(_Caps )] <- american [s] _xWHITE [star s] ethnic [s] @@
# Ex: agricultural\_technology
_field [layer=(_Caps )] <- agricultural [s] _xWHITE [star s] technology [s] @@
# Ex: agricultural\_operations
_field [layer=(_Caps )] <- agricultural [s] _xWHITE [star s] operations [s] @@
# Ex: agricultural\_engineering
_field [layer=(_Caps )] <- agricultural [s] _xWHITE [star s] engineering [s] @@
# Ex: agricultural\_education
_field [layer=(_Caps )] <- agricultural [s] _xWHITE [star s] education [s] @@
# Ex: agricultural\_economics
_field [layer=(_Caps )] <- agricultural [s] _xWHITE [star s] economics [s] @@
# Ex: agricultural\_communications
_field [layer=(_Caps )] <- agricultural [s] _xWHITE [star s] communications [s] @@
# Ex: african\_studies
_field [layer=(_Caps )] <- african [s] _xWHITE [star s] studies [s] @@
# Ex: aerospace\_engineering
_field [layer=(_Caps )] <- aerospace [s] _xWHITE [star s] engineering [s] @@
# Ex: aeronautical\_engineering
_field [layer=(_Caps )] <- aeronautical [s] _xWHITE [star s] engineering [s] @@
# Ex: adult\_education
_field [layer=(_Caps )] <- adult [s] _xWHITE [star s] education [s] @@
# Ex: zoology
_field [layer=(_Caps )] <- zoology [s] @@
# Ex: writing
_field [layer=(_Caps )] <- writing [s] @@
# Ex: tourism
_field [layer=(_Caps )] <- tourism [s] @@
# Ex: theology
_field [layer=(_Caps )] <- theology [s] @@
# Ex: theatre
_field [layer=(_Caps )] <- theatre [s] @@
# Ex: theater
_field [layer=(_Caps )] <- theater [s] @@
# Ex: tesl
_field [layer=(_Caps )] <- tesl [s] @@
# Ex: telemedicine
_field [layer=(_Caps )] <- telemedicine [s] @@
# Ex: telecommunications
_field [layer=(_Caps )] <- telecommunications [s] @@
# Ex: teaching
_field [layer=(_Caps )] <- teaching [s] @@
# Ex: taxation
_field [layer=(_Caps )] <- taxation [s] @@
# Ex: statistics
_field [layer=(_Caps )] <- statistics [s] @@
# Ex: spanish
_field [layer=(_Caps )] <- spanish [s] @@
# Ex: sociology
_field [layer=(_Caps )] <- sociology [s] @@
# Ex: slavic
_field [layer=(_Caps )] <- slavic [s] @@
# Ex: science
_field [layer=(_Caps )] <- science [s] @@
# Ex: school
_field [layer=(_Caps )] <- school [s] @@
# Ex: russian
_field [layer=(_Caps )] <- russian [s] @@
# Ex: religion
_field [layer=(_Caps )] <- religion [s] @@
# Ex: rehabilitation
_field [layer=(_Caps )] <- rehabilitation [s] @@
# Ex: recreation
_field [layer=(_Caps )] <- recreation [s] @@
# Ex: psychology
_field [layer=(_Caps )] <- psychology [s] @@
# Ex: portuguese
_field [layer=(_Caps )] <- portuguese [s] @@
# Ex: physiology
_field [layer=(_Caps )] <- physiology [s] @@
# Ex: physics
_field [layer=(_Caps )] <- physics [s] @@
# Ex: philosophy
_field [layer=(_Caps )] <- philosophy [s] @@
# Ex: pharmacy
_field [layer=(_Caps )] <- pharmacy [s] @@
# Ex: pharmacology
_field [layer=(_Caps )] <- pharmacology [s] @@
# Ex: pharmaceutics
_field [layer=(_Caps )] <- pharmaceutics [s] @@
# Ex: pediatrics
_field [layer=(_Caps )] <- pediatrics [s] @@
# Ex: pedagogy
_field [layer=(_Caps )] <- pedagogy [s] @@
# Ex: pathology
_field [layer=(_Caps )] <- pathology [s] @@
# Ex: pathobiology
_field [layer=(_Caps )] <- pathobiology [s] @@
# Ex: optometry
_field [layer=(_Caps )] <- optometry [s] @@
# Ex: optics
_field [layer=(_Caps )] <- optics [s] @@
# Ex: operations
_field [layer=(_Caps )] <- operations [s] @@
# Ex: oceanography
_field [layer=(_Caps )] <- oceanography [s] @@
# Ex: nutrition
_field [layer=(_Caps )] <- nutrition [s] @@
# Ex: neuroscience
_field [layer=(_Caps )] <- neuroscience [s] @@
# Ex: nematology
_field [layer=(_Caps )] <- nematology [s] @@
# Ex: music
_field [layer=(_Caps )] <- music [s] @@
# Ex: mining
_field [layer=(_Caps )] <- mining [s] @@
# Ex: mineralogy
_field [layer=(_Caps )] <- mineralogy [s] @@
# Ex: microbiology
_field [layer=(_Caps )] <- microbiology [s] @@
# Ex: meteorology
_field [layer=(_Caps )] <- meteorology [s] @@
# Ex: metals
_field [layer=(_Caps )] <- metals [s] @@
# Ex: medicine
_field [layer=(_Caps )] <- medicine [s] @@
# Ex: media
_field [layer=(_Caps )] <- media [s] @@
# Ex: mechanics
_field [layer=(_Caps )] <- mechanics [s] @@
# Ex: mathematics
_field [layer=(_Caps )] <- mathematics [s] @@
# Ex: math
_field [layer=(_Caps )] <- math [s] @@
# Ex: marketing
_field [layer=(_Caps )] <- marketing [s] @@
# Ex: manufacturing
_field [layer=(_Caps )] <- manufacturing [s] @@
# Ex: management
_field [layer=(_Caps )] <- management [s] @@
# Ex: logistics
_field [layer=(_Caps )] <- logistics [s] @@
# Ex: lithuanian
_field [layer=(_Caps )] <- lithuanian [s] @@
# Ex: literature
_field [layer=(_Caps )] <- literature [s] @@
# Ex: linguistics
_field [layer=(_Caps )] <- linguistics [s] @@
# Ex: law
_field [layer=(_Caps )] <- law [s] @@
# Ex: latin
_field [layer=(_Caps )] <- latin [s] @@
# Ex: languages
_field [layer=(_Caps )] <- languages [s] @@
# Ex: kinesiology
_field [layer=(_Caps )] <- kinesiology [s] @@
# Ex: journalism
_field [layer=(_Caps )] <- journalism [s] @@
# Ex: japanese
_field [layer=(_Caps )] <- japanese [s] @@
# Ex: italian
_field [layer=(_Caps )] <- italian [s] @@
# Ex: insurance
_field [layer=(_Caps )] <- insurance [s] @@
# Ex: immunology
_field [layer=(_Caps )] <- immunology [s] @@
# Ex: humanities
_field [layer=(_Caps )] <- humanities [s] @@
# Ex: hospitality
_field [layer=(_Caps )] <- hospitality [s] @@
# Ex: horticulture
_field [layer=(_Caps )] <- horticulture [s] @@
# Ex: history
_field [layer=(_Caps )] <- history [s] @@
# Ex: hebrew
_field [layer=(_Caps )] <- hebrew [s] @@
# Ex: greek
_field [layer=(_Caps )] <- greek [s] @@
# Ex: government
_field [layer=(_Caps )] <- government [s] @@
# Ex: gerontology
_field [layer=(_Caps )] <- gerontology [s] @@
# Ex: german
_field [layer=(_Caps )] <- german [s] @@
# Ex: geosciences
_field [layer=(_Caps )] <- geosciences [s] @@
# Ex: geophysics
_field [layer=(_Caps )] <- geophysics [s] @@
# Ex: geology
_field [layer=(_Caps )] <- geology [s] @@
# Ex: geography
_field [layer=(_Caps )] <- geography [s] @@
# Ex: geochemistry
_field [layer=(_Caps )] <- geochemistry [s] @@
# Ex: genetics
_field [layer=(_Caps )] <- genetics [s] @@
# Ex: french
_field [layer=(_Caps )] <- french [s] @@
# Ex: forestry
_field [layer=(_Caps )] <- forestry [s] @@
# Ex: finance
_field [layer=(_Caps )] <- finance [s] @@
# Ex: film
_field [layer=(_Caps )] <- film [s] @@
# Ex: fashion
_field [layer=(_Caps )] <- fashion [s] @@
# Ex: ethics
_field [layer=(_Caps )] <- ethics [s] @@
# Ex: epidemiology
_field [layer=(_Caps )] <- epidemiology [s] @@
# Ex: entomology
_field [layer=(_Caps )] <- entomology [s] @@
# Ex: english
_field [layer=(_Caps )] <- english [s] @@
# Ex: engineering
_field [layer=(_Caps )] <- engineering [s] @@
# Ex: electronics
_field [layer=(_Caps )] <- electronics [s] @@
# Ex: eecs
_field [layer=(_Caps )] <- eecs [s] @@
# Ex: ee
_field [layer=(_Caps )] <- ee [s] @@
# Ex: economics
_field [layer=(_Caps )] <- economics [s] @@
# Ex: econometrics
_field [layer=(_Caps )] <- econometrics [s] @@
# Ex: ecology
_field [layer=(_Caps )] <- ecology [s] @@
# Ex: drama
_field [layer=(_Caps )] <- drama [s] @@
# Ex: dietetics
_field [layer=(_Caps )] <- dietetics [s] @@
# Ex: design
_field [layer=(_Caps )] <- design [s] @@
# Ex: dermatology
_field [layer=(_Caps )] <- dermatology [s] @@
# Ex: dentistry
_field [layer=(_Caps )] <- dentistry [s] @@
# Ex: demography
_field [layer=(_Caps )] <- demography [s] @@
# Ex: cs
_field [layer=(_Caps )] <- cs [s] @@
# Ex: counseling
_field [layer=(_Caps )] <- counseling [s] @@
# Ex: communications
_field [layer=(_Caps )] <- communications [s] @@
# Ex: climatology
_field [layer=(_Caps )] <- climatology [s] @@
# Ex: classics
_field [layer=(_Caps )] <- classics [s] @@
# Ex: chinese
_field [layer=(_Caps )] <- chinese [s] @@
# Ex: chemistry
_field [layer=(_Caps )] <- chemistry [s] @@
# Ex: business
_field [layer=(_Caps )] <- business [s] @@
# Ex: botany
_field [layer=(_Caps )] <- botany [s] @@
# Ex: biophysics
_field [layer=(_Caps )] <- biophysics [s] @@
# Ex: biology
_field [layer=(_Caps )] <- biology [s] @@
# Ex: bioengineering
_field [layer=(_Caps )] <- bioengineering [s] @@
# Ex: biochemistry
_field [layer=(_Caps )] <- biochemistry [s] @@
# Ex: banking
_field [layer=(_Caps )] <- banking [s] @@
# Ex: aviation
_field [layer=(_Caps )] <- aviation [s] @@
# Ex: audiology
_field [layer=(_Caps )] <- audiology [s] @@
# Ex: astrophysics
_field [layer=(_Caps )] <- astrophysics [s] @@
# Ex: astronomy
_field [layer=(_Caps )] <- astronomy [s] @@
# Ex: astronautics
_field [layer=(_Caps )] <- astronautics [s] @@
# Ex: art
_field [layer=(_Caps )] <- art [s] @@
# Ex: architecture
_field [layer=(_Caps )] <- architecture [s] @@
# Ex: archaeology
_field [layer=(_Caps )] <- archaeology [s] @@
# Ex: anthropology
_field [layer=(_Caps )] <- anthropology [s] @@
# Ex: anatomy
_field [layer=(_Caps )] <- anatomy [s] @@
# Ex: agronomy
_field [layer=(_Caps )] <- agronomy [s] @@
# Ex: agribusiness
_field [layer=(_Caps )] <- agribusiness [s] @@
# Ex: africology
_field [layer=(_Caps )] <- africology [s] @@
# Ex: aesthetics
_field [layer=(_Caps )] <- aesthetics [s] @@
# Ex: aeronautics
_field [layer=(_Caps )] <- aeronautics [s] @@
# Ex: advertising
_field [layer=(_Caps )] <- advertising [s] @@
# Ex: acoustics
_field [layer=(_Caps )] <- acoustics [s] @@
# Ex: accounting
_field [layer=(_Caps )] <- accounting [s] @@
# Ex: accountancy
_field [layer=(_Caps )] <- accountancy [s] @@
|
# Fetch concept's list of attributes.
L("return_attr") = findattrs(L("con")); |
@NODES _ROOT
@PRE
<1,1> var("header");
@POST
splice(1,1);
@RULES
_xNIL <-
_LINE ### (1)
@@
|
@POST
rfarecurse(2, 3, 5)
single()
@RULES
_RECURSE [base] <- _soRECURSE [s] _LIT _REGIONS [opt] _eoRECURSE [s] _LIT [opt] @@
|
@NODES _ROOT
@RULES
_headerClose <- \< \/ h 4 \> @@
_headerOpen <- \< h 4 \> @@
_bottom <- bottom \- horizontal @@
|
@NODES _split
@POST
L("code") = N("code", 1);
L("term") = N("term", 1);
if (strcontains(".", L("code"))) {
L("codes") = split(L("code"), ".");
if (strlength(L("codes")[1]) > 1) {
addEntryToHier(X("con"), L("code"), L("term"));
}
}
noop();
@RULES
_xNIL <-
_entry ### (1)
@@ |
@NODES _LINE
@RULES
_item <-
_xSTART ### (1)
_xWILD [plus match=(\# \*)] ### (2)
_xWILD [fail=(_xEND)] ### (3)
@@
|
@CODE
G("hello") = 0;
@@CODE
#@PATH _ROOT _TEXTZONE _noun _caps
@NODES _caps
# Want an _xFEAT match!
@CHECK
if (N("sem",3) != "person title")
fail();
if (N("ne",4) || N("ne",5))
fail();
@POST
L("tmp3") = N(3);
group(4,5,"_np");
N("ne",4) = 1;
N("ne type",4) = N("sem",4) = "person";
N("ne type conf",4) = 80;
N("stem",4) = N("$text",4);
registerpersnames(N("$text",4));
group(1,3,"_np");
pncopyvars(L("tmp3"),N(1));
L("x3") = pnparent(X()); # 07/10/12 AM.
pnreplaceval(L("x3"),"ne",0); # 07/10/12 AM.
X("ne") = 0;
# Need POS.
@RULES
_xNIL <-
_xWILD [one match=(_xCAP _noun)]
_xWILD [one match=(_xCAP _noun)]
_noun
_xWILD [one match=(_xCAP _noun)]
_xWILD [one match=(_xCAP _noun)]
@@
@POST
L("x3") = pnparent(X()); # 07/10/12 AM.
pnreplaceval(L("x3"),"ne",1); # 07/10/12 AM.
pnreplaceval(L("x3"),"ne type","organization"); # 07/10/12 AM.
pnreplaceval(L("x3"),"ne type conf",90); # 07/10/12 AM.
pnreplaceval(L("x3"),"sem","organization"); # 07/10/12 AM.
pnreplaceval(L("x3"),"stem",phrasetext()); # 07/10/12 AM.
@RULES
_xNIL <-
_xWILD [plus match=(_xCAP _noun)]
_xWILD [s one trigger match=(division department
administration
international
ministry affairs hospital bank
news tv
school college university
centre center)]
_xEND
@@
@CHECK
if (!N("ne type",3))
fail();
@POST
L("x3") = pnparent(X()); # 07/10/12 AM.
pnreplaceval(L("x3"),"ne",1); # 07/10/12 AM.
pnreplaceval(L("x3"),"ne type",N("ne type",3)); # 07/10/12 AM.
pnreplaceval(L("x3"),"ne type conf",N("ne type conf",3)); # 07/10/12 AM.
pnreplaceval(L("x3"),"sem",N("sem",3)); # 07/10/12 AM.
pnreplaceval(L("x3"),"stem",N("stem",3)); # 07/10/12 AM.
@RULES
_xNIL <-
_xSTART
_xWILD [plus match=(_xCAP)]
_noun
_xEND
@@
# Note: title name patterns.
@CHECK
if (!N("unknown",2) && !N("unknown",3))
fail();
@POST
L("tt") = N("$text",3) + " " + N("$text",4); # 07/10/12 AM.
L("x3") = pnparent(X()); # 07/10/12 AM.
pnreplaceval(L("x3"),"ne",1); # 07/10/12 AM.
pnreplaceval(L("x3"),"ne type","person"); # 07/10/12 AM.
pnreplaceval(L("x3"),"ne type conf",90); # 07/10/12 AM.
pnreplaceval(L("x3"),"sem","person"); # 07/10/12 AM.
pnreplaceval(L("x3"),"stem",L("tt")); # 07/10/12 AM.
# X("ne",3) = 1;
# X("ne type",3) = X("sem",3) = "person";
# X("ne type conf",3) = 90;
# X("stem",3) = N("$text",3) + " " + N("$text",4);
N("mypos",3) = "NP";
N("mypos",4) = "NP";
# Todo: Register first and last name.
@RULES
_xNIL <-
_xWILD [plus match=(_xCAP _noun)]
_xWILD [s trigger plus match=(_nounCountry
representative ceo coo cfo officer
president senator congressman)]
_xCAP
_xCAP
_xEND
@@
# title alpha
@POST
L("tt") = N("$text",3); # 07/10/12 AM.
L("x3") = pnparent(X()); # 07/10/12 AM.
pnreplaceval(L("x3"),"ne",1); # 07/10/12 AM.
pnreplaceval(L("x3"),"ne type","person"); # 07/10/12 AM.
pnreplaceval(L("x3"),"ne type conf",90); # 07/10/12 AM.
pnreplaceval(L("x3"),"sem","person"); # 07/10/12 AM.
pnreplaceval(L("x3"),"stem",L("tt")); # 07/10/12 AM.
# X("ne",3) = 1;
# X("ne type",3) = X("sem",3) = "person";
# X("ne type conf",3) = 90;
# X("stem",3) = N("$text",3);
N("mypos",3) = "NP";
# Todo: Register last name.
@RULES
_xNIL <-
_xSTART
_title [s]
_xALPHA
_xEND
@@
@CHECK
if (!N("unknown",2))
fail();
if (!N("unknown",3))
fail();
@POST
L("tt") = N("$text",2) + " " + N("$text",3); # 07/10/12 AM.
L("x3") = pnparent(X()); # 07/10/12 AM.
pnreplaceval(L("x3"),"ne",1); # 07/10/12 AM.
pnreplaceval(L("x3"),"ne type","person"); # 07/10/12 AM.
pnreplaceval(L("x3"),"ne type conf",90); # 07/10/12 AM.
pnreplaceval(L("x3"),"sem","person"); # 07/10/12 AM.
pnreplaceval(L("x3"),"stem",L("tt")); # 07/10/12 AM.
# X("ne",3) = 1;
# X("ne type",3) = X("sem",3) = "person";
# X("ne type conf",3) = 90;
# X("stem",3) = N("$text",2) + " " + N("$text",3);
N("mypos",2) = "NP";
N("mypos",3) = "NP";
# Todo: Register first and last name.
@RULES
_xNIL <-
_xSTART
_xCAP
_xCAP
_xEND
@@
|
@PATH _ROOT _LINE _column
@POST
excise(1,1);
noop();
@RULES
_xNIL <-
_xWHITE [s] ### (1)
@@
|
@NODES _doctypedecl
@RULES
_DeclSep <-
_PEReference [one]
@@
_DeclSep <-
_whiteSpace [one]
@@
@@RULES
|
# Remove attributes and values of concept con's attribute named str.
rmvals(L("con"), L("str")); |
@NODES _ROOT
@RULES
_companySuffix <-
_xWILD [one match=(inc llc)] ### (1)
\. ### (2)
@@
@RULES
_number <-
no ### (1)
\. ### (2)
@@
@RULES
_paragraphSeparator <-
\n [s min=2 max=0] ### (1)
@@
@POST
L("tmp") = N("$text",2) + "." + N("$text",4);
S("value") = flt(L("tmp"));
single();
@RULES
_money <-
_xWILD [s one matches=(\$)] ### (1)
_xNUM [s] ### (2)
_xWILD [s one matches=( \. \, )] ### (3)
_xNUM [s] ### (4)
@@
@POST
S("value") = num(N("$text"));
single();
@RULES
_money <-
_xWILD [s one matches=(\$)] ### (1)
_xNUM [s] ### (2)
@@
|
@PATH _ROOT _educationZone _educationInstance _LINE
# This one is for catching city turd to the right of school.
# Accepting short turds, even if known words, that haven't been reduced
# to anything.
@POST
if (!X("school",3))
X("school",3) = N("$text",1);
if (N("unknowns",5)
|| (N("unreduced",5) && N("caplen",5) <= 2) )
X("city",3) = N("$text",5);
@RULES
_xNIL <-
_school [s]
_xWHITE [s star]
_xWILD [s one match=( \, \- )]
_xWHITE [s star]
_Caps
@@
# This is for "late" schools. Ones formed after higher confidence
# stuff failed to find the school.
@CHECK
if (X("school",3)) fail(); # School not filled in yet.
@POST
X("school",3) = N("$text"); # Fill instance with school name.
# noop()
@RULES
_xNIL <- _school [s] @@
# If no degree in major constructs found, etc., use standalones.
@CHECK
if (X("degree",3)) fail(); # No degree yet.
@POST
X("degree",3) = N("$text");
@RULES
_xNIL <- _degree [s] @@
# Similarly for major.
@CHECK
if (X("major",3)) fail(); # No major yet.
@POST
X("major",3) = N("$text");
@RULES
_xNIL <- _major [s] @@
|
@NODES _ROOT
@RULES
_xNIL <-
_xNIL ### (1)
@@
|
@NODES _ROOT
@RULES
_enum <-
_beginEnum ### (1)
_xWILD ### (2)
_endEnum ### (3)
@@
|
@NODES _ROOT
@POST
singler(1,2);
@RULES
_emptyItem [base] <-
_enclosedBy ### (1)
_enclosedBy ### (2)
_xWILD [match=(_separator _lineTerminator _xEND)] ### (3)
@@
|
@NODES _ROOT
@POST
S("text") = N("$text",3);
single();
@RULES
_comment <-
\/ ### (1)
\/ ### (2)
_xWILD [fail=(\/ _pos)] ### (3)
@@
|
@CODE
G("filepath") = G("$apppath") + "\input\portverbs.txt";
"debug.txt" << G("filepath") << "\n";
if (G("$inputname") == "file001.txt") {
G("file") = openfile(G("filepath"));
}
else {
G("file") = openfile(G("filepath"),"app");
}
@@CODE |
@CODE
fileout("lines1.txt"); # 06/10/00 AM.
@@CODE
# No way right now to initialize var in the context node.
# Not in the current pass, anyway.
# "nlines" will keep line count in every experience zone.
@PATH _ROOT _experienceZone
# Give each line a line number.
@POST
++X("nlines");
N("lineno") = X("nlines");
# noop() # Implicit.
"lines1.txt" << "------------" << "\n";
ndump("lines1.txt",1);
@RULES
_xNIL <- _LINE [s] @@
|
@POST
rfanodes(2, nodes)
single()
@RULES
_NODES [base] <- _soNODES _NONLIT [star] _eoNODES [opt] @@
|
@DECL
NepaliNum(L("numString")){
if (L("numString") == "१")
return 1;
else if (L("numString") == "२")
return 2;
else if (L("numString") == "३")
return 3;
}
@@DECL
|
@NODES _LINE
@RULES
_indent <-
_xSTART
_xWILD [match=(_xWHITE)]
@@
|
Subsets and Splits