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README.md
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license: apache-2.0
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---
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---
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license: apache-2.0
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datasets:
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- ACCORD-NLP/CODE-ACCORD-Relations
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language:
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- en
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---
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# ACCORD-NLP
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ACCORD-NLP is a Natural Language Processing (NLP) framework developed by the [ACCORD](https://accordproject.eu/) project to facilitate Automated Compliance Checking (ACC) within the Architecture, Engineering, and Construction (AEC) sector.
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It consists of several pre-trained/fine-tuned machine learning models to perform the following information extraction tasks from regulatory text.
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1. Entity Extraction/Classification (ner)
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2. Relation Extraction/Classification (re)
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**re-berta-large** is a BERT large model fine-tuned for relation classification using [CODE-ACCORD relations](https://huggingface.co/datasets/ACCORD-NLP/CODE-ACCORD-Relations) dataset.
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## Installation
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### From Source
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```
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git clone https://github.com/Accord-Project/accord-nlp.git
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cd accord-nlp
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pip install -r requirements.txt
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```
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### From pip
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```
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pip install accord-nlp
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```
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## Using Pre-trained Models
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### Entity Extraction/Classification (ner)
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```python
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from accord_nlp.text_classification.ner.ner_model import NERModel
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model = NERModel('roberta', 'ACCORD-NLP/ner-roberta-large')
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predictions, raw_outputs = model.predict(['The gradient of the passageway should not exceed five per cent.'])
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print(predictions)
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```
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### Relation Extraction/Classification (re)
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```python
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from accord_nlp.text_classification.relation_extraction.re_model import REModel
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model = REModel('roberta', 'ACCORD-NLP/re-roberta-large')
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predictions, raw_outputs = model.predict(['The <e1>gradient<\e1> of the passageway should not exceed <e2>five per cent</e2>.'])
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print(predictions)
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```
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For more details, please refer to the [ACCORD-NLP](https://github.com/Accord-Project/accord-nlp) GitHub repository.
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