This software provides code for two components:
About | Downloads | Usage | Release history
Input: seed sets (that is, dictionaries) of entities for some classes and unlabeled text.
Ouput: More entities belonging to the classes extracted from the text.
Algorithm: bootstrapped pattern-based learning.
The pattern learning system is described in:
Improved Pattern Learning for Bootstrapped Entity Extraction. Sonal Gupta and Christopher D. Manning. In Proceedings of the Eighteenth Conference on Computational Natural Language Learning (CoNLL). 2014.[pdf; Supplementary; bib]
Please refer to the license for Stanford CoreNLP.
The main class is
edu.stanford.nlp.patterns.GetPatternsFromDataMultiClass. An example properties file is
patterns/example.properties and the example data is in the same directory. (If you are using version < 3.5.1, use
See the example properties file
patterns/example.properties from the code distribution as
a basis. Change the HOME variable. The *** symbol in the properties file tells you which settings should be adjusted to fit your system; other ones can likely be left alone. For more details on the parameters and more parameters, see the javadoc.
The input consists of a file or directory of text and files with seed sets of entities for each label. For an example, see the data in projects/core/data/edu/stanford/nlp/patterns/surface/ -- in this example, we try to learn names of U.S. presidents and vice-presidents, names of their family members, and places they are related to from the text copied from the White House website.
The output files are the following, where $v means the value of the variable v in the properties file:
Inside $outDir/$identifier/$for-each-label , files
learnedwords.txt : learned words, iterations are separated by newlines
learnedpatterns.txt : learned patterns, iterations are separated by newlines
patterns.json : output json file for visualization
words.json : output json file for viusalization
tokensmatchedpatterns.json : output json file for visualization
java -cp classpath edu.stanford.nlp.patterns.GetPatternsFromDataMultiClass -props yourproperties.properties
java -cp stanford-corenlp-3.5.1.jar:stanford-corenlp-3.5.1-models.jar:javax.json.jar edu.stanford.nlp.patterns.surface.GetPatternsFromDataMultiClass -props patterns/example.properties
An earlier version of the visual interface is described in:
Sonal Gupta and Christopher D. Manning. 2014. SPIED: Stanford Pattern-based Information Extraction and Diagnostics. In Proceedings of the ACL 2014 Workshop on Interactive Language Learning, Visualization, and Interfaces (ACL-ILLVI). [pdf, bib]
SPIED-viz, the visualization part of SPIED, is licensed under the full GPL, which allows its use for research purposes, free software projects, software services, etc., but not in distributed proprietary software.
Download the code from GitHub.
See GitHub ReadMe file.
Other questions Please email Sonal Gupta if you have other questions. The distribution is still in beta and likely in need of more testing so feel free to ask.
|Version 1.0||July 1, 2014||Initial release|
Site design by Bill MacCartney