Update README.md

README.md

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----
-license: other
-license_name: research-only
-license_link: LICENSE
----
+---
+license: other
+license_name: research-only
+license_link: LICENSE
+language:
+- en
+---
+Dataset Card: Processed 5 Scientific Books Sentence Pairs
+Dataset Description
+Language: English (scientific/technical domain)
+
+License: Research use only (derived from copyrighted books, full texts not redistributed)
+
+Dataset Summary: This dataset contains sentence pairs extracted from 5 scientific books. Each book was processed with GROBID to obtain structured text from PDF files. Sentences were segmented and paired for training sentence-transformer models on semantic similarity tasks. To ensure balance, a maximum of 6,000 sentences per book was included.
+Dataset Structure
+Data Instances
+Each entry is a pair of sentences:
+
+```json
+{
+  "sentence_0": "Some of the generated samples that had been achieved with this architecture already in 2014 can be seen in Figure 3.14.",
+  "sentence_1": "Conditioning on Text: So far, only image generation has been covered, completely ignoring textual input."
+}
+```
+Data Splits
+All data is in the "train" split.
+
+Total size: ~66424 sentence pairs.
+
+Balanced across 5 books (≤6000 sentences per book).
+
+Dataset Creation
+Curation Rationale
+The dataset was created to provide high-quality sentence pairs for training and evaluating sentence-transformer models in the scientific domain. Limiting to 6000 sentences per book ensures balanced representation and reduces copyright risks.
+
+Source Data
+Books: 5 scientific/technical books (copyrighted, not redistributed).
+
+Extraction: PDFs processed with GROBID → structured text → sentence segmentation (NLTK).
+
+Pairs: Constructed from consecutive sentences and curated positive/negative examples.
+
+Data Extraction Logic
+Raw PDFs processed with GROBID.
+
+Sentences segmented with NLTK.
+
+Maximum 6000 sentences per book included.
+
+Sentence pairs generated for semantic similarity training.
+
+Additional Information
+Citation
+If you use this dataset, please cite:
+
+```bibtex
+@misc{aghakhani2025synergsticrag,
+  author       = {Danial Aghakhani Zadeh},
+  title        = {Processed 5 Scientific Books Sentence Pairs},
+  year         = {2025},
+  publisher    = {Hugging Face},
+  howpublished = {\url{https://huggingface.co/datasets/DigitalAsocial/ds-tb-5-g}}
+}
+```
+
+Personal and Sensitive Information
+The dataset consists of scientific/technical text.
+
+No personal or sensitive information is included.
+
+Bias, Risks, and Limitations
+Texts reflect the style and biases of their original authors.
+
+Dataset is domain-specific (scientific books) and may not generalize to everyday language.
+
+Full copyrighted texts are not included; only derived sentence pairs are shared.
+
+Notice and Takedown Policy
+If you believe this dataset contains material that infringes copyright, please contact us with:
+
+Your contact information
+
+Reference to the original work
+
+Identification of the material claimed to be infringing
+
+We will comply with legitimate requests by removing affected sources from future releases.
+
+Dataset Curators
+Created by Danial for research on sentence-transformers and semantic similarity.
+
+License
+Derived from copyrighted books.
+
+Shared under Research Use Only license.
+
+Full texts are not redistributed.