Michael created OPENNLP-1309:
--------------------------------
Summary: NameFinderME - Unexpected result using unchanged training
data
Key: OPENNLP-1309
URL: https://issues.apache.org/jira/browse/OPENNLP-1309
Project: OpenNLP
Issue Type: Bug
Components: Name Finder
Affects Versions: 1.9.2
Reporter: Michael
Hello,
I based on
[NameFinderMETest.java|https://github.com/apache/opennlp/blob/master/opennlp-tools/src/test/java/opennlp/tools/namefind/NameFinderMETest.java]
/ function _testNameFinder()_, I have written a simple test code and changed
the [test
sentence|https://github.com/apache/opennlp/blob/master/opennlp-tools/src/test/java/opennlp/tools/namefind/NameFinderMETest.java#L79]
from *(1)*:
{code:java}
String[] sentence = {"Alisa",
"appreciated",
"the",
"hint",
"and",
"enjoyed",
"a",
"delicious",
"traditional",
"meal."};
{code}
to *(2)*:
{code:java}
String[] sentence = {"Alisa",
"and",
"Mike",
"appreciated",
"the",
"hint",
"and",
"enjoyed",
"a",
"delicious",
"traditional",
"meal."};
{code}
(Just added "and Mike") and expected to get 2 results (two names _Alisa_ and
_Mike_) because both names are annotated in the training data. I just get 1
result (Mike) for *(2)*. I used the training data file
[AnnotatedSentences.txt|https://github.com/apache/opennlp/blob/master/opennlp-tools/src/test/resources/opennlp/tools/namefind/AnnotatedSentences.txt]
(unchanged).
Can anyone tell me what's wrong? Thanks.
h3. +Test code:+
{code:java}
String trainingDatafilePath = "opennlp/tools/namefind/AnnotatedSentences.txt";
String encoding = "ISO-8859-1";
ObjectStream<NameSample> sampleStream = new NameSampleDataStream(new
PlainTextByLineStream(new MarkableFileInputStreamFactory(new
File(trainingDatafilePath+"AnnotatedSentences.txt")), encoding));
TrainingParameters params = new TrainingParameters();
params.put(TrainingParameters.ITERATIONS_PARAM, 70);
params.put(TrainingParameters.CUTOFF_PARAM, 1);
TokenNameFinderModel nameFinderModel = NameFinderME.train("eng", null,
sampleStream,
params, TokenNameFinderFactory.create(null, null, Collections.emptyMap(), new
BioCodec()));
TokenNameFinder nameFinder = new NameFinderME(nameFinderModel);
// now test if it can detect the sample sentences
String[] sentence = {"Alisa",
"and",
"Mike",
"appreciated",
"the",
"hint",
"and",
"enjoyed",
"a",
"delicious",
"traditional",
"meal."};
Span[] names = nameFinder.find(sentence);
if (names != null && names.length != 0) {
System.out.println(" > Found ["+names.length+"] results");
for(Span name : names){
String personName="";
for(int i=name.getStart(); i<name.getEnd(); i++){
personName+=sentence[i]+" ";
}
System.out.println(" > Result "+1+": Type: ["+name.getType()+"] : PersonName:
["+personName+"]\t [probability="+name.getProb()+"]");
}
} else {
System.out.println(" > No results found");
}
{code}
h3. +Result for (1):+
Indexing events with TwoPass using cutoff of 1
Computing event counts... done. 1392 events
Indexing... done.
Collecting events... Done indexing in 0.22 s.
Incorporating indexed data for training...
done.
Number of Event Tokens: 1392
Number of Outcomes: 3
Number of Predicates: 9164
Computing model parameters...
Performing 70 iterations.
1: . (1355/1392) 0.9734195402298851
2: . (1383/1392) 0.9935344827586207
3: . (1390/1392) 0.9985632183908046
4: . (1390/1392) 0.9985632183908046
5: . (1391/1392) 0.9992816091954023
6: . (1392/1392) 1.0
7: . (1392/1392) 1.0
8: . (1392/1392) 1.0
9: . (1392/1392) 1.0
Stopping: change in training set accuracy less than 1.0E-5
Stats: (1392/1392) 1.0
...done.
*Found [1] results*
*Result 1: Type: [default] : PersonName: [Alisa ]
[probability=0.5483001511243855]*
h3.
+Result for (2):+
Indexing events with TwoPass using cutoff of 1
Computing event counts... done. 1392 events
Indexing... done.
Collecting events... Done indexing in 0.22 s.
Incorporating indexed data for training...
done.
Number of Event Tokens: 1392
Number of Outcomes: 3
Number of Predicates: 9164
Computing model parameters...
Performing 70 iterations.
1: . (1355/1392) 0.9734195402298851
2: . (1383/1392) 0.9935344827586207
3: . (1390/1392) 0.9985632183908046
4: . (1390/1392) 0.9985632183908046
5: . (1391/1392) 0.9992816091954023
6: . (1392/1392) 1.0
7: . (1392/1392) 1.0
8: . (1392/1392) 1.0
9: . (1392/1392) 1.0
Stopping: change in training set accuracy less than 1.0E-5
Stats: (1392/1392) 1.0
...done.
*Found [1] results*
*Result 1: Type: [default] : PersonName: [Mike ]
[probability=0.460685209028902]*
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