Commit 796d8a43 authored by Nandeesh Patel Gowdru Prabushanker's avatar Nandeesh Patel Gowdru Prabushanker
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Updating the documentation

parent 90d17385
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mvn clean package tomcat:run
For more information, go to our <a href="">Wiki</a>.
### Usage for "Entity Linking using Neural Networks" thesis
1. Download the gerbil datasets from
2. Extract the contents and change the parentPath value in GetCandidates class Main function
3. Run ```mvn clean & mvn install & mvn exec:java -Dexec.mainClass="org.aksw.agdistis.webapp.GetCandidates``` to generate the training files needed for the model
4. Run ```mvn exec:java -Dexec.mainClass="org.aksw.agdistis.webapp.RunApp``` to start the server
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## DBpedia entity embeddings
This repo has APIs the can be used to access embeddings for all the DBpedia entities. The embeddings are indexed on Elasticsearch server.
This repo contains source code for the thesis "Entity Linking using Neural Networks".
### List of APIs
Using the repo to link entities in a text
1. Use AGDISTIS to create training files as explained in the documentation
2. Install all dependencies from requirements.txt
3. Run ```python``` to train and save entity linking models
4. Run the Flask app using ```python```
### List of APIs available
#### 1. Get entity embeddings
This API takes a list of entities as input and returns the embeddings of the given entities in response. It returns embeddings of first 10 unique entities and ignores the rest.
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Request Body: NIF content
These APIs can be accessed from on UPB network for now.
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Currently file trains and saves all models used for evaluation. You can modify the code as explained in the comments of the file to use a single model.
The APIs can be accessed from http://localhost:5000/
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