A package providing text segmentation evaluation metrics and utilities
Project description
Text segmentation is the task of splitting up any amount of text into segments by placing boundaries between some atomic unit (e.g., morphemes, words, lines, sentences, paragraphs, sections, etc.). It’s a common pre-processing step in many Natural Language Processing (NLP) tasks.
This package is a collection of metrics and for comparing text segmentations and evaluating automatic text segmenters. Both new (Boundary Similarity, Segmentation Similarity) and traditional (WindowDiff, Pk) are included, as well as inter-coder agreement coefficients and confusion matrices based upon a boundary edit distance.
To see some examples of its usage, read the docs.
Feature Support
Included is a variety of segmentation comparison metrics, including:
Boundary Edit Distance (BED)
Boundary Similarity (B)
BED-based confusion matrices (and precision/recall/F1)
Segmentation Similarity (S)
WindowDiff
Pk
Additionally, B-based inter-coder agreement coefficients for segmentation that are suitable for 2 or more coders are provided, including:
Fleiss’ Pi (i.e., Siegel and Castellan’s K)
Fleiss’ Kappa
Installation
To install SegEval, simply run:
$ pip install segeval
Documentation
Documentation is available at http://segeval.readthedocs.org/.
Citing SegEval
If you’re using this software for research, please cite the ACL paper [PDF] and, if you need to go into details, the thesis [PDF] describing this work:
Chris Fournier. 2013. Evaluating Text Segmentation using Boundary Edit Distance. Proceedings of 51st Annual Meeting of the Association for Computational Linguistics. (ACL 2013), to appear. Association for Computational Linguistics, Stroudsburg, PA, USA.
Chris Fournier. 2013. Evaluating Text Segmentation. (Master’s thesis). University of Ottawa.
BibTeX:
@inproceedings{Fournier2013a,
author = {Fournier, Chris},
year = {2013},
title = {{Evaluating Text Segmentation using Boundary Edit Distance}},
booktitle = {Proceedings of 51st Annual Meeting of the Association for Computational Linguistics},
publisher = {Association for Computational Linguistics},
location = {Sophia, Bulgaria},
pages = {to appear},
address = {Stroudsburg, PA, USA}
}
@mastersthesis{Fournier2013b,
author = {Fournier, Chris},
title = {Evaluating Text Segmentation},
school = {University of Ottawa},
year = {2013}
}
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.