Tag: Information Extraction
In the previous article, I showed how we can use ATNs for extracting key information from natural language text. I also pointed out in that article that Definite Clause Grammars (DCG) are a more compact formalism for doing this. That will be the focus of today’s article. For a nice introduction to DCG, read this. […]
After Wood’s paper [1], Augmented Transition Networks (ATN) became popular in the 1970s, for parsing text. An ATN is a generalized transition network with two major enhancements: Support for recursive transitions, including jumping to other ATNs Performing arbitrary actions when edges are traversed Remembering state through the use of registers See the “Further Reading” section at […]
This is the third part in the series on information extraction from unstructured text. In the first part, we saw how MeaningCloud allows us to specify complex rules to identify custom categories through their Deep Categorization API. The second part covered spaCy’s pattern matcher. Today, I would like to discuss how we can use TextRazor’s “Prolog Engine” to perform […]
In the previous article, I explored the Deep Categorization capabilities of MeaningCloud. We saw how a powerful rule-based pattern matching language allowed us to map fragments of unstructured text to custom categories. In today’s post, I want to go through spaCy’s pattern matching capabilities. The version I am using is 2.0.13. Some newer features are available […]
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