probase-concept
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A fast and neat API for Conceptualization of Probase
Probase-Concept
Install
python setup.py install
Download the Probase Data
Please visit Probase website to download
Basic Usage
1. Load the data
from pbconcept import ProbaseConcept
pb_concept = ProbaseConcept("data/data-concept-instance-relations.txt")
2. Conceptualization
pb_concept.conceptualize("dog", score_method="likelihood")
which will produce
[('animal', 0.23049271472392638),
('pet', 0.10381518404907976),
('domestic animal', 0.049798696319018405),
('mammal', 0.043855444785276074),
('specie', 0.034700920245398774),
('domesticated animal', 0.026313266871165645),
('companion animal', 0.02142446319018405),
('household pet', 0.014666411042944786),
('predator', 0.013468174846625767),
('domestic pet', 0.012893021472392638),
...,
]
3. Instantiation
pb_concept.instantiate("dog")
Which will produce
[('german shepherd', 126),
('poodle', 106),
('rottweilers', 79),
('poodles', 78),
('rottweiler', 72),
('german shepherds', 72),
('chihuahua', 65),
('golden retriever', 63),
('labradors', 60),
('boxer', 60),
...,
]
4. Concept chain
pb_concept.get_concept_chain("dog")
which will produce
['dog', 'animal', 'organism', 'complex system', 'social complexity concept']
PS: Top 1 likelihood concept will be chosen when finding a chain