Fix documentation errors and spelling

Corrects function usage example for text_dublication_detector.py.
Corrects minor spelling errors in project README files.

Author: ma-ilsi

README.md

@@ -2,7 +2,7 @@ SinaTools
 ======================
 Open Source Toolkit for Arabic NLP and NLU developed by [SinaLab](http://sina.birzeit.edu/) at Birzeit University. SinaTools is available through Python APIs, command lines, colabs, and online demos.
 
-See the full list of [Available Packages](https://sina.birzeit.edu/sinatools/), which include: (1) [Morphology Tagging](https://sina.birzeit.edu/sinatools/index.html#morph), (2) [Named Entity Recognition (NER)](https://sina.birzeit.edu/sinatools/index.html#ner), (3) [Word Sense Disambiguation (WSD)](https://sina.birzeit.edu/sinatools/index.html#wsd), (4) [Semantic Relatedness](https://sina.birzeit.edu/sinatools/index.html#sr), (5) [Synonymy Extraction and Evaluation](https://sina.birzeit.edu/sinatools/index.html#se), (6) [Relation Extraction](https://sina.birzeit.edu/sinatools/index.html#re), (7) [Utilities](https://sina.birzeit.edu/sinatools/index.html#u) (diacritic-based word matching, Jaccard similarly, parser, tokenizers, corpora processing, transliteration, etc).
+See the full list of [Available Packages](https://sina.birzeit.edu/sinatools/), which include: (1) [Morphology Tagging](https://sina.birzeit.edu/sinatools/index.html#morph), (2) [Named Entity Recognition (NER)](https://sina.birzeit.edu/sinatools/index.html#ner), (3) [Word Sense Disambiguation (WSD)](https://sina.birzeit.edu/sinatools/index.html#wsd), (4) [Semantic Relatedness](https://sina.birzeit.edu/sinatools/index.html#sr), (5) [Synonymy Extraction and Evaluation](https://sina.birzeit.edu/sinatools/index.html#se), (6) [Relation Extraction](https://sina.birzeit.edu/sinatools/index.html#re), (7) [Utilities](https://sina.birzeit.edu/sinatools/index.html#u) (diacritic-based word matching, Jaccard similarity, parser, tokenizers, corpora processing, transliteration, etc).
 
 See [Demo Pages](https://sina.birzeit.edu/sinatools/).
 
@@ -24,7 +24,7 @@ Some modules in SinaTools require some data files and fine-tuned models to be do
 
 Documentation
 --------
-For information, please refer to the [main page](https://sina.birzeit.edu/sinatools) or the [online domuementation](https://sina.birzeit.edu/sinatools/documentation). 
+For information, please refer to the [main page](https://sina.birzeit.edu/sinatools) or the [online documentation](https://sina.birzeit.edu/sinatools/documentation). 
 
 Citation
 -------

README.rst

@@ -2,7 +2,7 @@ SinaTools
 ======================
 Open Source Toolkit for Arabic NLP and NLU developed by [SinaLab](http://sina.birzeit.edu/) at Birzeit University. SinaTools is available through Python APIs, command lines, colabs, and online demos.
 
-See the full list of [Available Packages](https://sina.birzeit.edu/sinatools/), which include: (1) [Morphology Tagging](https://sina.birzeit.edu/sinatools/index.html#morph), (2) [Named Entity Recognition (NER)](https://sina.birzeit.edu/sinatools/index.html#ner), (3) [Word Sense Disambiguation (WSD)](https://sina.birzeit.edu/sinatools/index.html#wsd), (4) [Semantic Relatedness](https://sina.birzeit.edu/sinatools/index.html#sr), (5) [Synonymy Extraction and Evaluation](https://sina.birzeit.edu/sinatools/index.html#se), (6) [Relation Extraction](https://sina.birzeit.edu/sinatools/index.html#re), (7) [Utilities](https://sina.birzeit.edu/sinatools/index.html#u) (diacritic-based word matching, Jaccard similarly, parser, tokenizers, corpora processing, transliteration, etc).
+See the full list of [Available Packages](https://sina.birzeit.edu/sinatools/), which include: (1) [Morphology Tagging](https://sina.birzeit.edu/sinatools/index.html#morph), (2) [Named Entity Recognition (NER)](https://sina.birzeit.edu/sinatools/index.html#ner), (3) [Word Sense Disambiguation (WSD)](https://sina.birzeit.edu/sinatools/index.html#wsd), (4) [Semantic Relatedness](https://sina.birzeit.edu/sinatools/index.html#sr), (5) [Synonymy Extraction and Evaluation](https://sina.birzeit.edu/sinatools/index.html#se), (6) [Relation Extraction](https://sina.birzeit.edu/sinatools/index.html#re), (7) [Utilities](https://sina.birzeit.edu/sinatools/index.html#u) (diacritic-based word matching, Jaccard similarity, parser, tokenizers, corpora processing, transliteration, etc).
 
 See [Demo Pages](https://sina.birzeit.edu/sinatools/).
 
@@ -24,7 +24,7 @@ Some modules in SinaTools require some data files and fine-tuned models to be do
 
 Documentation
 --------
-For information, please refer to the [main page](https://sina.birzeit.edu/sinatools) or the [online domuementation](https://sina.birzeit.edu/sinatools/documentation). 
+For information, please refer to the [main page](https://sina.birzeit.edu/sinatools) or the [online documentation](https://sina.birzeit.edu/sinatools/documentation). 
 
 Citation
 -------

SinaTools.egg-info/PKG-INFO

@@ -1,50 +1,54 @@
-Metadata-Version: 2.1
-Name: SinaTools
-Version: 0.1.36
-Summary: Open-source Python toolkit for Arabic Natural Understanding, allowing people to integrate it in their system workflow.
-Home-page: https://github.com/SinaLab/sinatools
-License: MIT license
-Description: SinaTools
-        ======================
-        Open Source Toolkit for Arabic NLP and NLU developed by [SinaLab](http://sina.birzeit.edu/) at Birzeit University. SinaTools is available through Python APIs, command lines, colabs, and online demos.
-        
-        See the full list of [Available Packages](https://sina.birzeit.edu/sinatools/), which include: (1) [Morphology Tagging](https://sina.birzeit.edu/sinatools/index.html#morph), (2) [Named Entity Recognition (NER)](https://sina.birzeit.edu/sinatools/index.html#ner), (3) [Word Sense Disambiguation (WSD)](https://sina.birzeit.edu/sinatools/index.html#wsd), (4) [Semantic Relatedness](https://sina.birzeit.edu/sinatools/index.html#sr), (5) [Synonymy Extraction and Evaluation](https://sina.birzeit.edu/sinatools/index.html#se), (6) [Relation Extraction](https://sina.birzeit.edu/sinatools/index.html#re), (7) [Utilities](https://sina.birzeit.edu/sinatools/index.html#u) (diacritic-based word matching, Jaccard similarly, parser, tokenizers, corpora processing, transliteration, etc).
-        
-        See [Demo Pages](https://sina.birzeit.edu/sinatools/).
-        
-        See the [benchmarking](https://www.jarrar.info/publications/HJK24.pdf), which shows that SinaTools outperformed all related toolkits. 
-        
-        Installation 
-        --------
-        To install SinaTools, ensure you are using Python version 3.10.8, then clone the [GitHub](git://github.com/SinaLab/SinaTools) repository.
-        
-        Alternatively, you can execute the following command:
-        
-        ```bash
-        pip install sinatools
-        ```
-        
-        Installing Models and Data Files
-        --------
-        Some modules in SinaTools require some data files and fine-tuned models to be downloaded. To download these models, please consult the [DataDownload](https://sina.birzeit.edu/sinatools/documentation/cli_tools/DataDownload/DataDownload.html).
-        
-        Documentation
-        --------
-        For information, please refer to the [main page](https://sina.birzeit.edu/sinatools) or the [online domuementation](https://sina.birzeit.edu/sinatools/documentation). 
-        
-        Citation
-        -------
-        Tymaa Hammouda, Mustafa Jarrar, Mohammed Khalilia: [SinaTools: Open Source Toolkit for Arabic Natural Language Understanding](http://www.jarrar.info/publications/HJK24.pdf). In Proceedings of the 2024 AI in Computational Linguistics (ACLing 2024), Procedia Computer Science, Dubai. ELSEVIER.
-        
-        License
-        --------
-        SinaTools is available under the MIT License. See the [LICENSE](https://github.com/SinaLab/sinatools/blob/main/LICENSE) file for more information.
-        
-        Reporting Issues
-        --------
-        To report any issues or bugs, please contact us at "sina.institute.bzu@gmail.com" or visit [SinaTools Issues](https://github.com/SinaLab/sinatools/issues).
-        
-        
-Keywords: sinatools
-Platform: UNKNOWN
-Description-Content-Type: text/markdown
+Metadata-Version: 2.1
+Name: SinaTools
+Version: 0.1.36
+Summary: Open-source Python toolkit for Arabic Natural Understanding, allowing people to integrate it in their system workflow.
+Home-page: https://github.com/SinaLab/sinatools
+License: MIT license
+Keywords: sinatools
+Platform: UNKNOWN
+Description-Content-Type: text/markdown
+License-File: LICENSE
+License-File: AUTHORS.rst
+
+SinaTools
+======================
+Open Source Toolkit for Arabic NLP and NLU developed by [SinaLab](http://sina.birzeit.edu/) at Birzeit University. SinaTools is available through Python APIs, command lines, colabs, and online demos.
+
+See the full list of [Available Packages](https://sina.birzeit.edu/sinatools/), which include: (1) [Morphology Tagging](https://sina.birzeit.edu/sinatools/index.html#morph), (2) [Named Entity Recognition (NER)](https://sina.birzeit.edu/sinatools/index.html#ner), (3) [Word Sense Disambiguation (WSD)](https://sina.birzeit.edu/sinatools/index.html#wsd), (4) [Semantic Relatedness](https://sina.birzeit.edu/sinatools/index.html#sr), (5) [Synonymy Extraction and Evaluation](https://sina.birzeit.edu/sinatools/index.html#se), (6) [Relation Extraction](https://sina.birzeit.edu/sinatools/index.html#re), (7) [Utilities](https://sina.birzeit.edu/sinatools/index.html#u) (diacritic-based word matching, Jaccard similarity, parser, tokenizers, corpora processing, transliteration, etc).
+
+See [Demo Pages](https://sina.birzeit.edu/sinatools/).
+
+See the [benchmarking](https://www.jarrar.info/publications/HJK24.pdf), which shows that SinaTools outperformed all related toolkits. 
+
+Installation 
+--------
+To install SinaTools, ensure you are using Python version 3.10.8, then clone the [GitHub](git://github.com/SinaLab/SinaTools) repository.
+
+Alternatively, you can execute the following command:
+
+```bash
+pip install sinatools
+```
+
+Installing Models and Data Files
+--------
+Some modules in SinaTools require some data files and fine-tuned models to be downloaded. To download these models, please consult the [DataDownload](https://sina.birzeit.edu/sinatools/documentation/cli_tools/DataDownload/DataDownload.html).
+
+Documentation
+--------
+For information, please refer to the [main page](https://sina.birzeit.edu/sinatools) or the [online documentation](https://sina.birzeit.edu/sinatools/documentation). 
+
+Citation
+-------
+Tymaa Hammouda, Mustafa Jarrar, Mohammed Khalilia: [SinaTools: Open Source Toolkit for Arabic Natural Language Understanding](http://www.jarrar.info/publications/HJK24.pdf). In Proceedings of the 2024 AI in Computational Linguistics (ACLing 2024), Procedia Computer Science, Dubai. ELSEVIER.
+
+License
+--------
+SinaTools is available under the MIT License. See the [LICENSE](https://github.com/SinaLab/sinatools/blob/main/LICENSE) file for more information.
+
+Reporting Issues
+--------
+To report any issues or bugs, please contact us at "sina.institute.bzu@gmail.com" or visit [SinaTools Issues](https://github.com/SinaLab/sinatools/issues).
+
+
+

build/lib/sinatools/utils/text_dublication_detector.py

@@ -34,7 +34,7 @@ def removal(csv_file, columnName, finalFileName, deletedFileName, similarityThre
     .. code-block:: python
     
         from sinatools.utils.text_dublication_detector import removal
-        removal("/path/to/csv/file1", sentences, "/path/to/csv/file2", 0.8)
+        removal("/path/to/csv/file1", "sentences", "/path/to/final/file", "/path/to/deleted/file", 0.8)
     """
 
     # Read CSV file
@@ -129,4 +129,4 @@ def textToVector(text):
 # deletedFileName = "Arabic-Oct7-Feb12DeletedSent.csv"
 
 # result = removal(csvFile, columnName, finalFileName, deletedFileName, similarityThreshold)
-# print(result)
+# print(result)

sinatools/utils/text_dublication_detector.py

@@ -34,7 +34,7 @@ def removal(csv_file, columnName, finalFileName, deletedFileName, similarityThre
     .. code-block:: python
     
         from sinatools.utils.text_dublication_detector import removal
-        removal("/path/to/csv/file1", sentences, "/path/to/csv/file2", 0.8)
+        removal("/path/to/csv/file1", "sentences", "/path/to/final/file", "/path/to/deleted/file", 0.8)
     """
 
     # Read CSV file
@@ -129,4 +129,4 @@ def textToVector(text):
 # deletedFileName = "Arabic-Oct7-Feb12DeletedSent.csv"
 
 # result = removal(csvFile, columnName, finalFileName, deletedFileName, similarityThreshold)
-# print(result)
+# print(result)