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From "Nicolas Hernandez (JIRA)" <...@uima.apache.org>
Subject [jira] [Updated] (UIMA-2106) Handling tokens not present in the language model (and also with no suffix present in the model) causes a null pointer exception in the tagger process
Date Fri, 01 Apr 2011 09:48:06 GMT

     [ https://issues.apache.org/jira/browse/UIMA-2106?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel

Nicolas Hernandez updated UIMA-2106:

    Attachment: TaggerHandlingTokensNotPresentInTheLanguageModel.patch

As a default probability value for unkwnon token, the algorithm used the probability of an
assumed known token which is "(".
Unfortunately the latter can be absent from the language model too.
We propose to keep this default value when its token exists in the model and to set it to
set it to Double.MIN_VALUE if not. Actually, it is not the value which is set but the couple
token and its value. A question arises anyway: would it be better for the algorithm to take
as default value an absent token from the training data but present in the testing data or
an unprobable token both in the training and testing data ?
The current solution aims at fitting the most the previous results.

> Handling tokens not present in the language model (and also with no suffix present in
the model) causes a null pointer exception in the tagger process
> ------------------------------------------------------------------------------------------------------------------------------------------------------
>                 Key: UIMA-2106
>                 URL: https://issues.apache.org/jira/browse/UIMA-2106
>             Project: UIMA
>          Issue Type: Bug
>          Components: Sandbox-Tagger
>    Affects Versions: 2.3
>         Environment: OS
> Linux version 2.6.32-30-generic (buildd@vernadsky) (gcc version 4.4.3 (Ubuntu 4.4.3-4ubuntu5)
) #59-Ubuntu SMP Tue Mar 1 21:30:21 UTC 2011
> java version "1.6.0_17"
> Java(TM) SE Runtime Environment (build 1.6.0_17-b04)
> Java HotSpot(TM) Server VM (build 14.3-b01, mixed mode)
>            Reporter: Nicolas Hernandez
>            Priority: Minor
>             Fix For: 2.3
>         Attachments: TaggerHandlingTokensNotPresentInTheLanguageModel.patch
>   Original Estimate: 5m
>  Remaining Estimate: 5m
> The HMMTagger Analysis Engine class uses the org.apache.uima.examples.tagger.Viterbi.java
implementation to determine the pos tag list of a given sentence.
> In practice this implementation is partially dependant on the part of speech tagging
(likewise the remaining HMMTagger classes actually).
> For exemple it makes strong assumptions on the kind of tokens it can take as input. It
assumes no restriction about the token covertext values.
> It results in using some covertext probabilities for initialization or default value
when the tagger processes an unknown token...
> As a consequence if the coveredText used for setting the default value is not present
in the training model an error occurs. Roughly speaking, the process looks first for probability
associated to the current token coverText, if the coverText is not present in the model, it
looks in the model for the probability of its longest suffix, and finally if it does not found
a match, the process assigns to the unknown coverText the probability of the arbitrary coverText
: "("  
> The problem is that if the probability of this coverText is not available in the model,
the probability of the unknown token is not defined and a null pointer exception occurs latter
when the variable is called.
> Why the probability of the "(" text would not be available in the model ? In a large
training corpus if we consider all the tokens, there is little chance not to find at least
one occurrence of "(". 
> Nevertheless if we use the HMM training  AE to build a model for predicting noun gender
and number, or verb tense and person, or "being a part of" named entity... these tokens won
t have the "(" coverText... and consequently an error will occurs when the tagging will be

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