This repository hosts the code for "Inferring Temporal Knowledge for Near-Periodic Recurrent Events, IJCAI 2018"
The paper has three components: schedule extractor, instance extractor and a temporal inference engine (PGM). The extractors are stand-alone, while the PGM module requires the output of the extractors.
Refer to the comments in extractor.py
.
The following programs have to be run in order:
- Run
edu.iitd.nlp.ee.freebase.FreebaseEventExtractor
to get a list of events from FreeBase - Run the programs in the
edu.iitd.nlp.ee.corpus
package to create an index of paragraphs that contain recurrent events. Choose the program based on the corpus (ClueWeb or NYT Corpus). - Run
edu.iitd.nlp.ee.core.InstanceCandidateOccurrenceDatePairExtractor
to extract instance, candidate-occurrence-date pairs - To train a occurrence date classifier use
edu.iitd.nlp.ee.classify.LingpipeClassifier
The instructions are compiled as a Jupyter Notebook (TRINE_tutorial.ipynb
)
Inferring Temporal Knowledge for Near-Periodic Recurrent Events. Dinesh Raghu, Surag Nair, Mausam. 2018. IJCAI.