Posted 5 CommentsPosted in Team solutions

Although the data given to us has several snippets corresponding to each parent-subsidy pair, only some of the snippets reveal actual parent-subsidiary relationship. Therefore we felt that concatenating the snippets corresponding to each pair  into one single article and then training can give the model more information about which text snippet actually reveals the parent-subsidy relationship. A Bidirectional GRU models each sentence into a sentence vector and then two attention networks try to figure out the important words in each sentence and important sentences in each document. In addition to returning the probability of company 2 being a subsidiary of company 1 the model as returns important sentences which triggered its prediction. For instance when it says Orcale Corp is the parent of Microsys it can also return that
Orcale Corp’s Microsys customer support portal was seen communicating with a server known to be used by the carbanak gang, is the sentence which triggered its prediction.

Ontotext case – Team _A

Posted 13 CommentsPosted in Learn, NLP, Team solutions

The objective of our task is extract parent-subsidiary relationship in text. For example, a news from techcruch says this, ‘Remember those rumors a few weeks ago that Google was looking to acquire the plug-and-play security camera company, Dropcam? Yep. It just happened.’. Now from this sentence we can infer that Dropcam is a subsidiary of Google. But there are million of companies and several million articles talking about them. A Human being can be tired of doing even 10! Trust me 😉 We have developed some cool Machine learning models spanning from classical algorithms to Deep Neural network do this for you. There is a bonus! We just do not give you probabilities. We also give out that sentences that triggered the algorithm to make the inference!  For instance when it says Orcale Corp is the parent of  Microsys it can also return that the sentence in its corpus ‘Oracle Corp’s  Microsys customer support portal was seen communicating with a server’, triggered its prediction.