coypu

Knowledge Extraction module for Coypu project

Requirement

• python>=3.7.0
• Jave
• stanford_openie(https://github.com/philipperemy/stanford-openie-python)

Overview

This repository is a simple implementation for relation extraction and entity linking on twitter text. The workflow is as folllows: Tweet —-> extracted triples —–> link entity to wikidata through wikidata api.

How to run an example?

pip install stanford_openie
python ie.py

Replace the text by the twitter you want to work on: extractor.AnnoText(‘Fire breaks out in Hawaii’, save=True) —> extractor.AnnoText(‘Your own text’, True)

The code will return you the triples from that text in json form.

{
    "subject": "Fire",
    "relation": "breaks out in",
    "object": "Hawaii",
    "sublink":
        {
            "pid": "P910",
            "property": "topic's main category",
            "eid": "Q4992738",
            "entity": "Category:Fires"
        },
    "oblink":
        {
            "pid": "P6",
            "property": "head of government",
            "eid": "Q469689",
            "entity": "Neil Abercrombie"
        }
}

This result will be saved to triple.json file under the same directory since we give True to save argument.

Pipeline

The pipeline of this module is based on following parts:

1. A txt2graph class, which extract the triples in a given text. (Based on openie)
2. A entLink class, which links the found entities using the wikidata entity search API.

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