Requires:
Python 3.3+, Natural Language Toolkit for Python (NLTK), XLRD and openpyxl for Python (reads and writes Excel files)
Recommended for full functionality: Numpy for Python, Matplotlib for Python
Use:
Download the repo and install the recommended Python packages using PIP or an alternate installer
Run Python in a shell and import run.py
Bifrost will provide instructions and a list of commands on startup
Running a selected command will provide the user with instructions specific to that command and will execute when given valid input/s
A second branch is available that only includes the polysemy and mindepth related functions
Bifrost commands:
output - change type of output between shell text and external documentation
sort - sort the output based on a particular value
newc - add a new corpus
listc - lists all available corpora by registered name
swa - single word analysis
swac - single word analysis with a corpus
mwaw - multi-word analysis using word definitions and POS
mwax - multi-word analysis using excel and wordnet data
mwac - multi-word analysis with a corpus
dwsa - dual-word similarity analysis
polys - polysemy rating for a selection of words
mindep - mindepth of word/s (first result only, see dtree for alternate synsets)
pol_min - runs both polysemy and mindepth analysis of a selection of words
dtree - depth tree of a given word (working on making it neater)
xhyper - returns the highest order x (given number) hypernyms of a word or words
q - quit
Additional Independent Functions:
BSSA (binary synset similarity analysis): given a set of word pairs, compare the similarity of each pair using a set of metrics provided by WordNet.
Use:
Import BSSA.py in a Python shell to run. Instructions are printed at runtime.
BSSA Instructions:
Enter the file you would like to analyze, acceptable file types are '.txt' and '.xlsx'. The program will assume white-space based formatting for text files and 2 words, separated by column, per row for excel files. Once the words have been read into the program it will list them as pairs. If the pairs are incorrect you can reformat the input document and start over. If they are correct you can wait until the word definitions are compiled into a list and then for every word you entered the program will automatically display the known definitions for each word. If the word has no definitions it will be replaced by "None" and that pair will be skipped. If the word has exactly one definition it will be entered automatically. If there are multiple definitions you will be asked to pick one. After a definition has been chosen it will be printed back to you and the next word will be displayed. When all word definitions are chosen the program will display the final synsets and ask you to provide a name for a file to output the results to. The results are formatted such that each word pair is listed followed by the three similarity comparisons followed by the definitions used for the given words. Note that entering two word definitions with different parts of speech will fail.
Please cite as:
Krueger, N., & Lawrence, J., (2016). Bifrost: Bridging linguistic, cognitive and computer science resources (VersionMaster). Retrieved from https://github.com/Malthanatos/Bifrost
We extracted a total of 174,487 definitions. We tabulated these unique senses and meanings to establish two measures: in part of speech senses and meanings (IPOSSAM) and the across part of speech senses and meanings (APOSSAM). For example, the word phone has two entries, one with the part of speech of noun and the other with the part of speech of verb. Phone has three noun definitions and only one verb definition. The APOSSAM value for phone on both entries is 4 (3 + 1), and the IPOSSAM value for phone as a noun is 3 and as a verb is 1. We recoded two WordNet part-of-speech labels (adjective and satellite adjective) as adjectives.
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