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https://issues.apache.org/jira/browse/LUCENE-9112?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17006089#comment-17006089
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Markus Jelsma commented on LUCENE-9112:
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I now believe it is a problem in the Lucene code, namely it being fooled by a
punctuation mark and then something is mishandled with the internal buffer in
SegmentingTokenizerBase. The buffer is 1024 and the point where my term is
being split is exactly at the 1024th character in the String.
Simply increasing BUFFERMAX 'solves' the problem i have. But i don't know where
the underlying problem really is.
> OpenNLP tokenizer is fooled by text containing spurious punctuation
> -------------------------------------------------------------------
>
> Key: LUCENE-9112
> URL: https://issues.apache.org/jira/browse/LUCENE-9112
> Project: Lucene - Core
> Issue Type: Bug
> Components: modules/analysis
> Affects Versions: master (9.0)
> Reporter: Markus Jelsma
> Priority: Major
> Labels: opennlp
> Fix For: master (9.0)
>
> Attachments: LUCENE-9112-unittest.patch
>
>
> The OpenNLP tokenizer show weird behaviour when text contains spurious
> punctuation such as having triple dots trailing a sentence...
> # the first dot becomes part of the token, having 'sentence.' becomes the
> token
> # much further down the text, a seemingly unrelated token is then suddenly
> split up, in my example (see attached unit test) the name 'Baron' is split
> into 'Baro' and 'n', this is the real problem
> The problems never seem to occur when using small texts in unit tests but it
> certainly does in real world examples. Depending on how many 'spurious' dots,
> a completely different term can become split, or the same term in just a
> different location.
> I am not too sure if this is actually a problem in the Lucene code, but it is
> a problem and i have a Lucene unit test proving the problem.
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