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--- |
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license: apache-2.0 |
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task_categories: |
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- text-classification |
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- token-classification |
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language: |
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- en |
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tags: |
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- science |
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- glossary |
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- terms |
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- entity-recognition |
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- text-simplification |
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pretty_name: Science Terms and Phrases Glossary |
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size_categories: |
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- 10K<n<100K |
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--- |
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# Dataset Card for Science Terms and Phrases Glossary |
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## Dataset Details |
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This dataset contains scientific terms and phrases from various disciplines, compiled from multiple sources. |
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### Dataset Description |
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The dataset was created by web scraping scientific glossaries from sources like Wikipedia, NASA, and other academic references. Additionally, some terms were generated using ChatGPT-4.0. |
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It is designed for **token classification**, meaning it includes both scientific and non-scientific words (e.g., common words like *"or"*, *"and"*, as well as names of foods and animals). |
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I trained a classification model on this dataset and found that it tends to misclassify named entities (such as people’s names) as scientific terms. Therefore, for better classification results, it is recommended to use **spaCy’s entity recognition**, such as: |
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```python |
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import spacy |
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nlp = spacy.load("en_core_web_sm") |
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``` |
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## Dataset Creation |
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The dataset was compiled through a combination of: |
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Web scraping from Wikipedia, NASA, and other scientific glossaries. |
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AI-generated terms using ChatGPT-4.0. |
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### Dataset Goal |
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The primary objective of this dataset is to aid in the simplification of scientific papers by improving entity recognition and classification. |
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## Contact Information |
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For more details or inquiries, you can reach me via email: jonicohen97@gmail.com |
