Stanford NLP enhance splitting a line to sentences

the example in the documents works fine
\stanford-corenlp-full-2015-04-20> java -cp stanford-corenlp-3.5.2.jar -Xmx2g edu.stanford.nlp.pipeline.StanfordCoreNLP -annotators tokenize,ssplit -file input.txt

I saw Dr. Spock yesterday, he was speaking with Mr. McCoy.  They were walking down Mullholand Dr. talking about  Dr. Spock returns!

Sentence #1 (13 tokens):
I saw Dr. Spock yesterday, he was speaking with Mr. McCoy.
Sentence #2 (10 tokens):
They were walking down Mullholand Dr. talking about
Sentence #3 (4 tokens):
Dr. Spock returns!

But if the input is:
The paper is 7 cm. length. What is you name? the size of the picture is 5 cm. x 8 cm.

the output is:
Sentence #1 (6 tokens):
The paper is 7 cm.
Sentence #2 (2 tokens):
Sentence #3 (5 tokens):
What is you name?
Sentence #4 (9 tokens):
the size of the picture is 5 cm.
Sentence #5 (4 tokens):
x 8 cm.

Can I put such a Regex constraint, somehow somewhere for a separator:

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Thanks, Aryeh.
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Bob LearnedCommented:
I am trying to figure out the benefit of annotators, like RegexNER:

Properties props = new Properties();
props.put("annotators", "tokenize, ssplit, pos, lemma, ner, regexner");
props.put("regexner.mapping", "org/foo/resources/jg-regexner.txt");
StanfordCoreNLP pipeline = new StanfordCoreNLP(props);
Bob LearnedCommented:
Another interesting discovery:

Stanford TokensRegex

 List<CoreMap> sentences = ...;
 CoreMapExpressionExtractor extractor = CoreMapExpressionExtractor.createExtractorFromFiles(TokenSequencePattern.getNewEnv(), file1, file2,...);
 for (CoreMap sentence:sentences) {
   List<MatchedExpression> matched = extractor.extractExpressions(sentence);

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Bob LearnedCommented:
Stanford CoreNLP FAQ

How do I add constraints to the parser in CoreNLP?
The parser can be instructed to keep certain sets of tokens together as a single constituent. If you do this, it will try to make a parse which contains a subtree where the exact set of tokens in that subtree are the ones specified in the constraint.

For any sentence where you want to add constraints, attach the ParserAnnotations.ConstraintAnnotation to that sentence. This annotation is a List<ParserConstraint>, where ParserConstraint specifies the start (inclusive) and end (exclusive) of the range and a pattern which the enclosing constituent must match. However, there is a bug in the way patterns are handled in the parser, so it is strongly recommended to use .* for the matching pattern.
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tuchfeldAuthor Commented:
I got a tip:
Need to:
1) edit PTBLexer.flex
2) recompile stanford-corenlp-full-2015-04-20 with ant and create the jar file.
3) run ikvmc.
4) replace the dll in the project
See snapshot.
p.s was not too trivial because need to take care about versions.
Paragraph splitted to sentences considering Measurements like Inch and Centimeter abbreviations

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Bob LearnedCommented:
There really should be an easier way than having to rebuild the Java code.  What changes did you have to make to the PTBLexer.flex file?
tuchfeldAuthor Commented:
ABMEASURE = In|Cm|mm /* <== */

/* ABRREV2 abbreviations are normally followed by an upper case word.
 *  We assume they aren't used sentence finally.
ABBREV4 = [A-Za-z]|{ABTITLE}|vs|Alex|Wm|Jos|Cie|a\.k\.a|cf|TREAS|{ACRO}|{ABCOMP2}|{ABMEASURE}

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tuchfeldAuthor Commented:
I think the Flex is very powerful
and might be useful in the future for additional splitting rules...
Also, I have created a batch file to do the whole process:
cd C:\JFLEX\bin
CMD /C jflex.bat PTBLexer.flex
copy /Y D:\Dev\NLP\stanford-corenlp\stanford-corenlp-full-2015-04-20\src\edu\stanford\nlp\process\
cd D:\Dev\NLP\stanford-corenlp\stanford-corenlp-full-2015-04-20
CMD /C ant
cd classes
CMD /C jar -cfm ../stanford-corenlp-aryeh_1.1.jar ..\src\META-INF\MANIFEST.MF edu
cd C:\ikvm-8.0.5449.1\bin
CMD /C ikvmc.exe -target:library D:\Dev\NLP\stanford-corenlp\stanford-corenlp-full-2015-04-20\stanford-corenlp-aryeh_1.1.jar
copy /Y stanford-corenlp-aryeh_1.1.dll D:\Dev\NLP\stanford-corenlp\Test_Stanford_NLP\bin\Debug\
echo the dll is ready

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Bob LearnedCommented:
Thanks for sharing!!
Bob LearnedCommented:
I wonder if this setting for the PTBTokenizer would have some affect:

Class PTBTokenizer<T extends HasWord>

strictTreebank3: PTBTokenizer deliberately deviates from strict PTB3 WSJ tokenization in two cases. Setting this improves compatibility for those cases. They are: (i) When an acronym is followed by a sentence end, such as "U.K." at the end of a sentence, the PTB3 has tokens of "Corp" and ".", while by default PTBTokenizer duplicates the period returning tokens of "Corp." and ".", and (ii) PTBTokenizer will return numbers with a whole number and a fractional part like "5 7/8" as a single token, with a non-breaking space in the middle, while the PTB3 separates them into two tokens "5" and "7/8". (Exception: for only "U.S." the treebank does have the two tokens "U.S." and "." like our default; strictTreebank3 now does that too.) The default is false.
tuchfeldAuthor Commented:
Eventually I found the solution myself.
I think it might be useful for others..
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Regular Expressions

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