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arg-tech / bert-te

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Default BART Textual Entailment Service

This service, part of the Argument Mining Framework (AMF), classifies argument relations between propositions into support, attack, and none. It leverages a pre-trained LLM fine-tuned on the NLI dataset. As a lightweight solution not specifically fine-tuned on an argumentation dataset, it is considered the default AMF argument relation identifier, providing faster classification of argument structures. It can be integrated into the argument mining pipeline alongside other AMF components for further analysis and processing.

Table of Contents

Brief Overview of the Architecture/Method

This application leverages a pruned and quantized BART model, fine-tuned on the MNLI dataset, to perform textual entailment in text-classification task settings. By pruning and quantizing the model, we achieve faster inference times without significantly compromising accuracy. The system maps entailment relations to support relations and contradiction relations to conflicts, for constructing argument structures. This approach ensures the model remains lightweight and suitable for real-time applications within AMF.

Endpoints

/bert-te

Details

GET Method

POST Method

Input and Output Formats

Input Format

Output Format

The inferred argument structure is returned in the xAIF format, including the argument relation nodes and their connecting edges, while preserving other information in a monotonic fashion. As demonstrated in the following example, the service identifies 1 "RA" node (nodeID 9) between "I" node 3 and 7.

{
  "AIF": {
    "descriptorfulfillments": null,
    "edges": [
      {
        "edgeID": 0,
        "fromID": 0,
        "toID": 4
      },
      {
        "edgeID": 1,
        "fromID": 4,
        "toID": 3
      },
      {
        "edgeID": 2,
        "fromID": 1,
        "toID": 6
      },
      {
        "edgeID": 3,
        "fromID": 6,
        "toID": 5
      },
      {
        "edgeID": 4,
        "fromID": 2,
        "toID": 8
      },
      {
        "edgeID": 5,
        "fromID": 8,
        "toID": 7
      },
      {
        "edgeID": 6,
        "fromID": 3,
        "toID": 9
      },
      {
        "edgeID": 7,
        "fromID": 9,
        "toID": 7
      }
    ],
    "locutions": [
      {
        "nodeID": 0,
        "personID": 0
      },
      {
        "nodeID": 1,
        "personID": 1
      },
      {
        "nodeID": 2,
        "personID": 2
      }
    ],
    "nodes": [
      {
        "nodeID": 0,
        "text": "disagreements between party members are entirely to be expected.",
        "type": "L"
      },
      {
        "nodeID": 1,
        "text": "the SNP has disagreements.",
        "type": "L"
      },
      {
        "nodeID": 2,
        "text": "it's not uncommon for there to be disagreements between party members.",
        "type": "L"
      },
      {
        "nodeID": 3,
        "text": "disagreements between party members are entirely to be expected.",
        "type": "I"
      },
      {
        "nodeID": 4,
        "text": "Default Illocuting",
        "type": "YA"
      },
      {
        "nodeID": 5,
        "text": "the SNP has disagreements.",
        "type": "I"
      },
      {
        "nodeID": 6,
        "text": "Default Illocuting",
        "type": "YA"
      },
      {
        "nodeID": 7,
        "text": "it's not uncommon for there to be disagreements between party members.",
        "type": "I"
      },
      {
        "nodeID": 8,
        "text": "Default Illocuting",
        "type": "YA"
      },
      {
        "nodeID": 9,
        "text": "Default Inference",
        "type": "RA"
      }
    ],
    "participants": [
      {
        "firstname": "Speaker",
        "participantID": 0,
        "surname": "1"
      },
      {
        "firstname": "Speaker",
        "participantID": 1,
        "surname": "2"
      }
    ],
    "schemefulfillments": null
  },
  "dialog": true,
  "ova": [],
  "text": {
    "txt": " Speaker 1 <span class=\"highlighted\" id=\"0\">disagreements between party members are entirely to be expected.</span>.<br><br> Speaker 2 <span class=\"highlighted\" id=\"1\">the SNP has disagreements.</span>.<br><br> Speaker 1 <span class=\"highlighted\" id=\"2\">it's not uncommon for there to be disagreements between party members. </span>.<br><br>"
  }
}

Installation

Requirements for Installation

Installation Setup

Using Docker Container

  1. Clone the Repository:

    git clone https://github.com/arg-tech/bert-te.git

  2. Navigate to the Project Root Directory:

    cd bert-te

  3. Make Required Changes:

    • Edit the Dockerfile, main.py, and docker-compose.yml files to specify the container name, port number, and other settings as needed.

  4. Build and Run the Docker Container:

    docker-compose up

From Source Without Docker

If you prefer to install without Docker:

  1. Install Dependencies:

    • Ensure Python and necessary libraries are installed.

  2. Configure and Run:

    • Configure the environment variables and settings in main.py.
    • Run the application using Python: 
      python main.py

Usage

Using Programming Interface

Example Python Code Snippet

import requests
import json

url = 'http://your-server-url/bert-te'
input_file_path = 'example_xAIF.json'

with open(input_file_path, 'r', encoding='utf-8') as file:

    files = {'file': (input_file_path, file, 'application/json')}

response = requests.post(url, files=files)

if response.status_code == 200:

    output_file_path = 'output_xAIF.json'

    with open(output_file_path, 'w', encoding='utf-8') as output_file:

        json.dump(response.json(), output_file, ensure_ascii=False, indent=4)

    print(f'Response saved to {output_file_path}')

else:

    print(f'Failed to make a POST request. Status code: {response.status_code}')

    print(response.text)

Using cURL

curl -X POST \
  -F "file=@example_xAIF.json" \
  http://your-server-url/bert-te

Using Web Interface

The service can also be used to create a pipeline on our n8n interface. The service can also be used to create a pipeline on our n8n interface.

  1. Create an HTTP node
  2. Configure the node
    • Specify the URL of the service
    • Include the parameter (file)
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