relation extraction

[ines (Ines Montani)]

@mustafa

Is there any way to use real.manual on these models and then train the 'rel' model for identifying further relations? Or is there any alternative way to go about it.

You can definitely use rel.manual to create the data for this, and even feed in pre-labelled entity annotations. But there's currently no out-of-the-box component you can train in spaCy, so you'd have to use your own model implementation.

Also see the related threads here:

Named Entity Relations - beginner questions

I've created an NER model that seems to be working very well. Now I would like to do the relations between the entities. I'm curious on a few things that I'm ignorant on and can't seem to find an answer that suffices me. When I'm done annotating the relations can I train a model using "prodigy train parser my_rel_dataset....."? Or should that strictly be used for the dependency parsing? I trained one relation model doing this and it seemed to work quite well, however I'm questioning myself i…

Annotation scheme / workflow for entity relations

How do you recommend to use prodigy for these two examples? Training a custom parser for chat intent semantics Extracting entity relations I haven't worked out a good flow for a task like that yet. My tasks is really entity relations but I see option one as another way to solve it as well - correct me if I'm wrong.

Relationship between named entities

I'm having a lot of fun exploring prodigy for a text mining task. Training a NER model using annotations is extremely rewarding, and works surprisingly well with only a small amount of manual annotations. So far, I've been using prodigy train ner ... for assigning entities. Let's say I have two entity types, FIRM and TECH. Some data to illustrate my task: [IBM][FIRM] has identified [hybrid cloud][TECH] as the growth area it will focus on. In early March 2017, [Snapchat][FIRM] officially went…