Update flex files to use Math.toIntExact to downgrade from long to int

Author: AngledLuffa

src/edu/stanford/nlp/international/arabic/process/ArabicLexer.flex

@@ -289,14 +289,14 @@ import edu.stanford.nlp.util.PropertiesUtils;
     if (invertible) {
       String str = prevWordAfter.toString();
       prevWordAfter.setLength(0);
-      CoreLabel word = (CoreLabel) tokenFactory.makeToken(txt, yychar, yylength());
+      CoreLabel word = (CoreLabel) tokenFactory.makeToken(txt, Math.toIntExact(yychar), yylength());
       word.set(CoreAnnotations.OriginalTextAnnotation.class, originalText);
       word.set(CoreAnnotations.BeforeAnnotation.class, str);
       prevWord.set(CoreAnnotations.AfterAnnotation.class, str);
       prevWord = word;
       return word;
     } else {
-      return tokenFactory.makeToken(txt, yychar, yylength());
+      return tokenFactory.makeToken(txt, Math.toIntExact(yychar), yylength());
     }
   }
 

src/edu/stanford/nlp/international/french/process/FrenchLexer.flex

@@ -253,7 +253,7 @@ import edu.stanford.nlp.util.logging.Redwood;
 
   private Object getNext(String txt, String originalText, String annotation) {
     txt = LexerUtils.removeSoftHyphens(txt);
-    Label w = (Label) tokenFactory.makeToken(txt, yychar, yylength());
+    Label w = (Label) tokenFactory.makeToken(txt, Math.toIntExact(yychar), yylength());
     if (invertible || annotation != null) {
       CoreLabel word = (CoreLabel) w;
       if (invertible) {

src/edu/stanford/nlp/international/spanish/process/SpanishLexer.flex

@@ -269,7 +269,7 @@ import edu.stanford.nlp.util.logging.Redwood;
 
   private Object getNext(String txt, String originalText, String annotation) {
     txt = LexerUtils.removeSoftHyphens(txt);
-    Label w = (Label) tokenFactory.makeToken(txt, yychar, yylength());
+    Label w = (Label) tokenFactory.makeToken(txt, Math.toIntExact(yychar), yylength());
     if (invertible || annotation != null) {
       CoreLabel word = (CoreLabel) w;
       if (invertible) {

src/edu/stanford/nlp/process/PTBLexer.flex

@@ -489,14 +489,14 @@ import edu.stanford.nlp.util.logging.Redwood;
     if (invertible) {
       String str = prevWordAfter.toString();
       prevWordAfter.setLength(0);
-      CoreLabel word = (CoreLabel) tokenFactory.makeToken(txt, yychar, yylength());
+      CoreLabel word = (CoreLabel) tokenFactory.makeToken(txt, Math.toIntExact(yychar), yylength());
       word.set(CoreAnnotations.OriginalTextAnnotation.class, originalText);
       word.set(CoreAnnotations.BeforeAnnotation.class, str);
       prevWord.set(CoreAnnotations.AfterAnnotation.class, str);
       prevWord = word;
       return word;
     } else {
-      Object word = tokenFactory.makeToken(txt, yychar, yylength());
+      Object word = tokenFactory.makeToken(txt, Math.toIntExact(yychar), yylength());
       if (word instanceof CoreLabel) {
         prevWord = (CoreLabel) word;
       }

src/edu/stanford/nlp/process/WhitespaceLexer.flex

@@ -53,8 +53,8 @@ TEXT = [^ \t\u1680\u2000-\u2006\u2008-\u200A\u205F\u3000\r\n\u0085\u2028\u2029\u
 
 %%
 
-{CR}     { return tokenFactory.makeToken(NEWLINE, yychar, yylength()); }
-{OTHERSEP} { return tokenFactory.makeToken(NEWLINE, yychar, yylength()); }
+{CR}     { return tokenFactory.makeToken(NEWLINE, Math.toIntExact(yychar), yylength()); }
+{OTHERSEP} { return tokenFactory.makeToken(NEWLINE, Math.toIntExact(yychar), yylength()); }
 {SPACES} { }
-{TEXT}   { return tokenFactory.makeToken(yytext(), yychar, yylength()); }
+{TEXT}   { return tokenFactory.makeToken(yytext(), Math.toIntExact(yychar), yylength()); }
 <<EOF>>  { return null; }