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Manual Reference Pages  -  TEXT::NSP (3)

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Text::NSP - Extract collocations and Ngrams from text



    Basic Usage

  use Text::NSP::Measures::2D::MI::ll;

  my $npp = 60; my $n1p = 20; my $np1 = 20;  my $n11 = 10;

  $ll_value = calculateStatistic( n11=>$n11,

  if( ($errorCode = getErrorCode()))
    print STDERR $errorCode." - ".getErrorMessage()."\n"";
    print getStatisticName."value for bigram is ".$ll_value."\n"";


The Ngram Statistics Package (NSP) is a collection of perl modules that aid in analyzing Ngrams in text files. We define an Ngram as a sequence of ’n’ tokens that occur within a window of at least ’n’ tokens in the text; what constitutes a token can be defined by the user. is a stub that doesn’t have any real functionality. It serves as a top level module in the hierarchy and allows us to group the Text::NSP::Count and Text::NSP::Measures modules.

The modules under Text::NSP::Measures implement measures of association that are used to evaluate whether the co-occurrence of the words in a Ngram is purely by chance or statistically significant. These measures compute a numerical score for Ngrams. This score can be used to decide whether or not there is enough evidence to reject the null hypothesis (that the Ngram is not statistically significant) for that Ngram.

To use one of the measures you can either use the program provided under the utils directory, or write your own driver program. Program takes as input a list of Ngrams with their frequencies (in the format output by and runs a user-selected statistical measure of association to compute the score for each Ngram. The Ngrams, along with their scores, are output in descending order of this score. For help on using utils/ please refer to its perldoc (perldoc utils/

If you are writing your own driver program, a basic usage example is provided above under SYNOPSIS. For further clarification please refer to the documentation of Text::NSP::Measures (perldoc Text::NSP::Measures).

    Error Codes

The following table describes the error codes use in the implementation,

Error codes common to all the association measures.

 100 - Trying to create an object of a abstract class.

 200 - one of the required values is missing.

 201 - one of the observed frequency comes out to be -ve.

 202 - one of the frequency values(n11) exceeds the total no of
       bigrams(npp) or a marginal total(n1p, np1).

 203 - one of the marginal totals(n1p, np1) exceeds the total bigram

 204 - one of the marginal totals is -ve.

Error Codes required by the mutual information measures

 211 - one of the expected values is zero.

 212 - one of the expected values is -ve.

Error codes required by the CHI measures.

 221 - one of the expected values is zero.



Ted Pedersen, University of Minnesota Duluth
<tpederse at>

Satanjeev Banerjee, Carnegie Mellon University

Amruta Purandare, University of Pittsburgh

Bridget Thomson-McInnes, University of Minnesota Twin Cities

Saiyam Kohli, University of Minnesota Duluth


Last updated: $Id:,v 1.44 2015/10/04 16:22:27 btmcinnes Exp $






Copyright (C) 2000-2008, Ted Pedersen, Satanjeev Banerjee, Amruta Purandare, Bridget Thomson-McInnes and Saiyam Kohli

This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along with this program; if not, write to

    The Free Software Foundation, Inc.,
    59 Temple Place - Suite 330,
    Boston, MA  02111-1307, USA.

Note: a copy of the GNU General Public License is available on the web at <> and is included in this distribution as GPL.txt.

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