Python implementation on extracting triplet, which consists of subject, predicate and object from a sentence. Currently, there are two models being implemented.
The first model is based on [1], which extracts the first noun subject, last verb as predicate, and the first noun or adjective as subject to form the triplet of a sentence.
The second model is based on [2], which can be considered as an improvement of the first model because it extracts all the subjects, predicates. With this, the model can determine more relations in the sentence.
- Python 3.6
- Stanford CoreNLP which can be downloaded from here
- A sentence is parsed using Stanford CoreNLP Parser as part of the preprocessing stage.
- Extract all the subjects, predicates and objects from the sentence.
- Determine relations with the triplets obtained based on the different models.
[1] Delia Rusu, Lorand Dali, Blaz Fortuna, Marko Grobelnik, DunjaMladenic, “Triplet extraction from sentences” in Artificial Intelligence Laboratory, Jožef Stefan Institute, Slovenia, Nov. 7, 2008. http://ailab.ijs.si/dunja/SiKDD2007/Papers/Rusu_Trippels.pdf
[2] The Multi-Liaison algorithm by Ms. Anjali Ganesh Jivani, Ms.AmishaHetalShingala, Dr. Paresh. V. Virparia published in International Journal of Advanced Computer Science and Applications Vol. 2, No. 5, 2011. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.625.507&rep=rep1&type=pdf