# Abbreviation Extractor
Abbreviation Extractor is a high-performance Rust library with Python bindings for extracting abbreviation-definition pairs from text, particularly focused on biomedical text. It implements an improved version of the [Schwartz-Hearst algorithm](https://psb.stanford.edu/psb-online/proceedings/psb03/schwartz.pdf), offering enhanced accuracy and speed. It's based the original [python implementation](https://github.com/philgooch/abbreviation-extraction).
[Speed Comparison With Other Abbreviation Extraction Libraries](#performance-comparison-of-abbreviation-extractor-against-other-libraries)
[Extraction Accuracy Comparison With Other Abbreviation Extraction Libraries](#performance-comparison-of-abbreviation-extractor-against-other-libraries)
## Features
- Fast and accurate extraction of abbreviation-definition pairs with tokenization.
- Support for both single-threaded and parallel processing
- Python bindings for easy integration with Python projects
- Customizable extraction parameters like selecting the most common or first definition for each abbreviation
## Installation
### Rust
Add this to your `Cargo.toml`:
```toml
abbreviation-extractor = "0.1.3"
```
### Python
pip install abbreviation-extractor-rs
## Basic Usage
### Rust
```rust
use abbreviation_extractor::{extract_abbreviation_definition_pairs, AbbreviationOptions};
let text = "The World Health Organization (WHO) is a specialized agency.";
let options = AbbreviationOptions::default();
let result = extract_abbreviation_definition_pairs(text, options);
for pair in result {
println!("Abbreviation: {}, Definition: {}", pair.abbreviation, pair.definition);
}
```
### Python
```python
from abbreviation_extractor import extract_abbreviation_definition_pairs
text = "The World Health Organization (WHO) is a specialized agency."
result = extract_abbreviation_definition_pairs(text)
for pair in result:
print(f"Abbreviation: {pair.abbreviation}, Definition: {pair.definition}")
```
### Customizing Extraction
#### Python
```python
from abbreviation_extractor import extract_abbreviation_definition_pairs
text = "The World Health Organization (WHO) is a specialized agency. The World Heritage Organization (WHO) is different."
# Get only the most common definition for each abbreviation
result = extract_abbreviation_definition_pairs(text, most_common_definition=True)
# Get only the first definition for each abbreviation
result = extract_abbreviation_definition_pairs(text, first_definition=True)
# Disable tokenization (if the input is already tokenized)
result = extract_abbreviation_definition_pairs(text, tokenize=False)
# Combine options
result = extract_abbreviation_definition_pairs(text, most_common_definition=True, tokenize=True)
for pair in result:
print(f"Abbreviation: {pair.abbreviation}, Definition: {pair.definition}")
```
#### Rust
```rust
use abbreviation_extractor::{extract_abbreviation_definition_pairs, AbbreviationOptions};
let text = "The World Health Organization (WHO) is a specialized agency. The World Heritage Organization (WHO) is different.";
// Get only the most common definition for each abbreviation
let options = AbbreviationOptions::new(true, false, true);
let result = extract_abbreviation_definition_pairs(text, options);
// Get only the first definition for each abbreviation
let options = AbbreviationOptions::new(false, true, true);
let result = extract_abbreviation_definition_pairs(text, options);
// Disable tokenization (if the input is already tokenized)
let options = AbbreviationOptions::new(false, false, false);
let result = extract_abbreviation_definition_pairs(text, options);
for pair in result {
println!("Abbreviation: {}, Definition: {}", pair.abbreviation, pair.definition);
}
```
## Parallel Processing
For processing multiple texts in parallel, you can use the `extract_abbreviation_definition_pairs_parallel` function:
### Rust
```rust
use abbreviation_extractor::{extract_abbreviation_definition_pairs_parallel, AbbreviationOptions};
let texts = vec![
"The World Health Organization (WHO) is a specialized agency.",
"The United Nations (UN) works closely with WHO.",
"The European Union (EU) is a political and economic union.",
];
let options = AbbreviationOptions::default();
let result = extract_abbreviation_definition_pairs_parallel(texts, options);
for extraction in result.extractions {
println!("Abbreviation: {}, Definition: {}", extraction.abbreviation, extraction.definition);
}
```
### Python
```python
from abbreviation_extractor import extract_abbreviation_definition_pairs_parallel
texts = [
"The World Health Organization (WHO) is a specialized agency.",
"The United Nations (UN) works closely with WHO.",
"The European Union (EU) is a political and economic union.",
]
result = extract_abbreviation_definition_pairs_parallel(texts)
for extraction in result.extractions:
print(f"Abbreviation: {extraction.abbreviation}, Definition: {extraction.definition}")
```
## Processing Large Files
For extracting abbreviations from large files, you can use the `extract_abbreviations_from_file` function:
### Rust
```rust
use abbreviation_extractor::{extract_abbreviations_from_file, AbbreviationOptions, FileExtractionOptions};
let file_path = "path/to/your/large/file.txt";
let abbreviation_options = AbbreviationOptions::default();
let file_options = FileExtractionOptions::default();
let result = extract_abbreviations_from_file(file_path, abbreviation_options, file_options);
for extraction in result.extractions {
println!("Abbreviation: {}, Definition: {}", extraction.abbreviation, extraction.definition);
}
```
### Python
```python
from abbreviation_extractor import extract_abbreviations_from_file
file_path = "path/to/your/large/file.txt"
result = extract_abbreviations_from_file(file_path)
for extraction in result.extractions:
print(f"Abbreviation: {extraction.abbreviation}, Definition: {extraction.definition}")
```
You can customize the file extraction process by specifying additional parameters:
```python
result = extract_abbreviations_from_file(
file_path,
most_common_definition=True,
first_definition=False,
tokenize=True,
num_threads=4,
show_progress=True,
chunk_size=2048 * 1024 # 2MB chunks
)
```
# Benchmark
Below is a comparison of how the abbreviation extractor performs in comparison to other libraries, namely Schwartz-Hearst and ScispaCy in terms of accuracy and speed.
## Performance Comparison of Abbreviation Extractor Against Other Libraries
| Abbrv | Ground Truth | abbreviation-extractor (This Library) | abbreviation-extraction | ScispaCy |
|-----------|------------------------------------------------------------------------------|-----------------------------------------------|---------------------------------|------------|
| '3-meAde' | '3-methyl-adenine' | '3-methyl-adenine' | '3-methyl-adenine' | 'N/A' |
| '5'UTR' | '5' untranslated region' | '5' untranslated region' | 'N/A' | 'N/A' |
| '5LO' | '5-lipoxygenase' | '5-lipoxygenase' | '5-lipoxygenase' | 'N/A' |
| 'AAV' | 'adeno-associated virus' | 'adeno-associated virus' | 'associated virus' | 'adeno-associated virus' |
| 'ACP' | 'Enoyl-acyl carrier protein' | 'Enoyl-acyl carrier protein' | 'acyl carrier protein' | 'Enoyl-acyl carrier protein' |
| 'ADIOL' | '5-androstene-3beta, 17beta-diol' | '5-androstene-3beta, 17beta-diol' | 'androstene-3beta, 17beta-diol' | '5-androstene-3beta, 17beta-diol' |
| cAMP | 'cyclic AMP' | 'cyclic AMP' | 'N/A' | |
| 'ALAD' | '5-aminolaevulinic acid dehydratase' | '5-aminolaevulinic acid dehydratase' | 'N/A' | '5-aminolaevulinic acid dehydratase' |
| 'AMPK' | 'AMP-activated protein kinase' | 'AMP-activated protein kinase' | 'N/A' | 'AMP-activated protein kinase' |
| 'AP' | 'apurinic/apyrimidinic site' | 'apurinic/apyrimidinic site' | 'apyrimidinic site' | 'apurinic/apyrimidinic site' |
| 'AcCoA' | 'acetyl coenzyme A' | 'acetyl coenzyme A' | 'N/A' | 'acetyl coenzyme A' |
| 'Ahr' | 'aryl hydrocarbon receptor' | 'aryl hydrocarbon receptor' | 'N/A' | 'aryl hydrocarbon receptor' |
| 'BD' | 'binding domain' | 'binding domain' | 'N/A' | 'binding domain' |
| '8-OxoG' | '7,8-dihydro-8-oxoguanine' | '7,8-dihydro-8-oxoguanine' | '8-oxoguanine' | 'N/A' |
| dsRNA | double-stranded RNA | double-stranded RNA | double-stranded RNA | 'N/A' |
| 'BERI' | 'Biomolecular Engineering Research Institute' | 'Biomolecular Engineering Research Institute' | 'N/A' | 'Biomolecular Engineering Research Institute' |
| 'CTLs | 'cytotoxic T lymphocytes' | 'cytotoxic T lymphocytes' | 'N/A' | 'N/A' |
| 'C-RBD' | 'C-terminal RNA binding domain' | 'C-terminal RNA binding domain' | 'N/A' | 'C-terminal RNA binding domain' |
| 'CAP' | 'cyclase-associated protein' | 'cyclase-associated protein' | 'N/A' | 'cyclase-associated protein' |
## Speed Comparison with Other Abbreviation Extraction Libraries
<img src="https://github.com/praise2112/abbreviation-extractor/raw/main/benches/abbreviation_extraction_benchmark.png" alt="Abbreviation Extraction Benchmark" width="1100"/>
## API Reference
For detailed API documentation, please refer to the [Rust docs](https://docs.rs/abbreviation_extractor) or the Python module docstrings.
## Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
## License
This project is licensed under the [MIT License](LICENSE).
## Acknowledgements
This library is based on the Schwartz-Hearst algorithm:
[A. Schwartz and M. Hearst (2003) A Simple Algorithm for Identifying Abbreviations Definitions in Biomedical Text. Biocomputing, 451-462.](https://psb.stanford.edu/psb-online/proceedings/psb03/schwartz.pdf)
The implementation is inspired by the original Python variant by Phil Gooch: [abbreviation-extractor](https://github.com/philgooch/abbreviation-extraction)
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"description": "\n# Abbreviation Extractor\n\nAbbreviation Extractor is a high-performance Rust library with Python bindings for extracting abbreviation-definition pairs from text, particularly focused on biomedical text. It implements an improved version of the [Schwartz-Hearst algorithm](https://psb.stanford.edu/psb-online/proceedings/psb03/schwartz.pdf), offering enhanced accuracy and speed. It's based the original [python implementation](https://github.com/philgooch/abbreviation-extraction).\n\n[Speed Comparison With Other Abbreviation Extraction Libraries](#performance-comparison-of-abbreviation-extractor-against-other-libraries)\n\n[Extraction Accuracy Comparison With Other Abbreviation Extraction Libraries](#performance-comparison-of-abbreviation-extractor-against-other-libraries)\n\n## Features\n\n- Fast and accurate extraction of abbreviation-definition pairs with tokenization.\n- Support for both single-threaded and parallel processing\n- Python bindings for easy integration with Python projects\n- Customizable extraction parameters like selecting the most common or first definition for each abbreviation\n\n## Installation\n\n### Rust\n\nAdd this to your `Cargo.toml`:\n\n```toml\nabbreviation-extractor = \"0.1.3\"\n```\n\n### Python\n\npip install abbreviation-extractor-rs\n\n## Basic Usage\n\n### Rust\n\n```rust\nuse abbreviation_extractor::{extract_abbreviation_definition_pairs, AbbreviationOptions};\n\nlet text = \"The World Health Organization (WHO) is a specialized agency.\";\nlet options = AbbreviationOptions::default();\nlet result = extract_abbreviation_definition_pairs(text, options);\n\nfor pair in result {\n println!(\"Abbreviation: {}, Definition: {}\", pair.abbreviation, pair.definition);\n}\n```\n\n### Python\n\n```python\nfrom abbreviation_extractor import extract_abbreviation_definition_pairs\n\ntext = \"The World Health Organization (WHO) is a specialized agency.\"\nresult = extract_abbreviation_definition_pairs(text)\n\nfor pair in result:\n print(f\"Abbreviation: {pair.abbreviation}, Definition: {pair.definition}\")\n```\n\n### Customizing Extraction\n\n#### Python\n\n```python\nfrom abbreviation_extractor import extract_abbreviation_definition_pairs\n\ntext = \"The World Health Organization (WHO) is a specialized agency. The World Heritage Organization (WHO) is different.\"\n\n# Get only the most common definition for each abbreviation\nresult = extract_abbreviation_definition_pairs(text, most_common_definition=True)\n\n# Get only the first definition for each abbreviation\nresult = extract_abbreviation_definition_pairs(text, first_definition=True)\n\n# Disable tokenization (if the input is already tokenized)\nresult = extract_abbreviation_definition_pairs(text, tokenize=False)\n\n# Combine options\nresult = extract_abbreviation_definition_pairs(text, most_common_definition=True, tokenize=True)\n\nfor pair in result:\n print(f\"Abbreviation: {pair.abbreviation}, Definition: {pair.definition}\")\n```\n\n#### Rust\n\n```rust\nuse abbreviation_extractor::{extract_abbreviation_definition_pairs, AbbreviationOptions};\n\nlet text = \"The World Health Organization (WHO) is a specialized agency. The World Heritage Organization (WHO) is different.\";\n\n// Get only the most common definition for each abbreviation\nlet options = AbbreviationOptions::new(true, false, true);\nlet result = extract_abbreviation_definition_pairs(text, options);\n\n// Get only the first definition for each abbreviation\nlet options = AbbreviationOptions::new(false, true, true);\nlet result = extract_abbreviation_definition_pairs(text, options);\n\n// Disable tokenization (if the input is already tokenized)\nlet options = AbbreviationOptions::new(false, false, false);\nlet result = extract_abbreviation_definition_pairs(text, options);\n\nfor pair in result {\n println!(\"Abbreviation: {}, Definition: {}\", pair.abbreviation, pair.definition);\n}\n```\n\n\n## Parallel Processing\n\nFor processing multiple texts in parallel, you can use the `extract_abbreviation_definition_pairs_parallel` function:\n\n### Rust\n\n```rust\nuse abbreviation_extractor::{extract_abbreviation_definition_pairs_parallel, AbbreviationOptions};\n\nlet texts = vec![\n \"The World Health Organization (WHO) is a specialized agency.\",\n \"The United Nations (UN) works closely with WHO.\",\n \"The European Union (EU) is a political and economic union.\",\n];\n\nlet options = AbbreviationOptions::default();\nlet result = extract_abbreviation_definition_pairs_parallel(texts, options);\n\nfor extraction in result.extractions {\n println!(\"Abbreviation: {}, Definition: {}\", extraction.abbreviation, extraction.definition);\n}\n```\n\n### Python\n\n```python\nfrom abbreviation_extractor import extract_abbreviation_definition_pairs_parallel\n\ntexts = [\n \"The World Health Organization (WHO) is a specialized agency.\",\n \"The United Nations (UN) works closely with WHO.\",\n \"The European Union (EU) is a political and economic union.\",\n]\n\nresult = extract_abbreviation_definition_pairs_parallel(texts)\n\nfor extraction in result.extractions:\n print(f\"Abbreviation: {extraction.abbreviation}, Definition: {extraction.definition}\")\n```\n\n## Processing Large Files\n\nFor extracting abbreviations from large files, you can use the `extract_abbreviations_from_file` function:\n\n### Rust\n\n```rust\nuse abbreviation_extractor::{extract_abbreviations_from_file, AbbreviationOptions, FileExtractionOptions};\n\nlet file_path = \"path/to/your/large/file.txt\";\nlet abbreviation_options = AbbreviationOptions::default();\nlet file_options = FileExtractionOptions::default();\n\nlet result = extract_abbreviations_from_file(file_path, abbreviation_options, file_options);\n\nfor extraction in result.extractions {\n println!(\"Abbreviation: {}, Definition: {}\", extraction.abbreviation, extraction.definition);\n}\n```\n\n### Python\n\n```python\nfrom abbreviation_extractor import extract_abbreviations_from_file\n\nfile_path = \"path/to/your/large/file.txt\"\nresult = extract_abbreviations_from_file(file_path)\n\nfor extraction in result.extractions:\n print(f\"Abbreviation: {extraction.abbreviation}, Definition: {extraction.definition}\")\n```\n\nYou can customize the file extraction process by specifying additional parameters:\n\n```python\nresult = extract_abbreviations_from_file(\n file_path,\n most_common_definition=True,\n first_definition=False,\n tokenize=True,\n num_threads=4,\n show_progress=True,\n chunk_size=2048 * 1024 # 2MB chunks\n)\n```\n\n# Benchmark\n\nBelow is a comparison of how the abbreviation extractor performs in comparison to other libraries, namely Schwartz-Hearst and ScispaCy in terms of accuracy and speed.\n\n## Performance Comparison of Abbreviation Extractor Against Other Libraries\n\n| Abbrv | Ground Truth | abbreviation-extractor (This Library) | abbreviation-extraction | ScispaCy |\n|-----------|------------------------------------------------------------------------------|-----------------------------------------------|---------------------------------|------------|\n| '3-meAde' | '3-methyl-adenine' | '3-methyl-adenine' | '3-methyl-adenine' | 'N/A' |\n| '5'UTR' | '5' untranslated region' | '5' untranslated region' | 'N/A' | 'N/A' |\n| '5LO' | '5-lipoxygenase' | '5-lipoxygenase' | '5-lipoxygenase' | 'N/A' |\n| 'AAV' | 'adeno-associated virus' | 'adeno-associated virus' | 'associated virus' | 'adeno-associated virus' |\n| 'ACP' | 'Enoyl-acyl carrier protein' | 'Enoyl-acyl carrier protein' | 'acyl carrier protein' | 'Enoyl-acyl carrier protein' |\n| 'ADIOL' | '5-androstene-3beta, 17beta-diol' | '5-androstene-3beta, 17beta-diol' | 'androstene-3beta, 17beta-diol' | '5-androstene-3beta, 17beta-diol' |\n| cAMP | 'cyclic AMP' | 'cyclic AMP' | 'N/A' | |\n| 'ALAD' | '5-aminolaevulinic acid dehydratase' | '5-aminolaevulinic acid dehydratase' | 'N/A' | '5-aminolaevulinic acid dehydratase' |\n| 'AMPK' | 'AMP-activated protein kinase' | 'AMP-activated protein kinase' | 'N/A' | 'AMP-activated protein kinase' |\n| 'AP' | 'apurinic/apyrimidinic site' | 'apurinic/apyrimidinic site' | 'apyrimidinic site' | 'apurinic/apyrimidinic site' |\n| 'AcCoA' | 'acetyl coenzyme A' | 'acetyl coenzyme A' | 'N/A' | 'acetyl coenzyme A' |\n| 'Ahr' | 'aryl hydrocarbon receptor' | 'aryl hydrocarbon receptor' | 'N/A' | 'aryl hydrocarbon receptor' |\n| 'BD' | 'binding domain' | 'binding domain' | 'N/A' | 'binding domain' |\n| '8-OxoG' | '7,8-dihydro-8-oxoguanine' | '7,8-dihydro-8-oxoguanine' | '8-oxoguanine' | 'N/A' |\n| dsRNA | double-stranded RNA | double-stranded RNA | double-stranded RNA | 'N/A' |\n| 'BERI' | 'Biomolecular Engineering Research Institute' | 'Biomolecular Engineering Research Institute' | 'N/A' | 'Biomolecular Engineering Research Institute' |\n| 'CTLs | 'cytotoxic T lymphocytes' | 'cytotoxic T lymphocytes' | 'N/A' | 'N/A' |\n| 'C-RBD' | 'C-terminal RNA binding domain' | 'C-terminal RNA binding domain' | 'N/A' | 'C-terminal RNA binding domain' |\n| 'CAP' | 'cyclase-associated protein' | 'cyclase-associated protein' | 'N/A' | 'cyclase-associated protein' |\n\n## Speed Comparison with Other Abbreviation Extraction Libraries\n\n<img src=\"https://github.com/praise2112/abbreviation-extractor/raw/main/benches/abbreviation_extraction_benchmark.png\" alt=\"Abbreviation Extraction Benchmark\" width=\"1100\"/>\n\n## API Reference\n\nFor detailed API documentation, please refer to the [Rust docs](https://docs.rs/abbreviation_extractor) or the Python module docstrings.\n\n## Contributing\n\nContributions are welcome! Please feel free to submit a Pull Request.\n\n## License\n\nThis project is licensed under the [MIT License](LICENSE).\n\n## Acknowledgements\n\nThis library is based on the Schwartz-Hearst algorithm:\n\n[A. Schwartz and M. Hearst (2003) A Simple Algorithm for Identifying Abbreviations Definitions in Biomedical Text. Biocomputing, 451-462.](https://psb.stanford.edu/psb-online/proceedings/psb03/schwartz.pdf)\n\nThe implementation is inspired by the original Python variant by Phil Gooch: [abbreviation-extractor](https://github.com/philgooch/abbreviation-extraction)\n\n",
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