The dataset created focuses on the Pakistan Military by collecting five types of entities from Wikipedia: weapons, ranks, dates, operations, and locations. An open-source NER annotator was utilized for annotation, ensuring accurate labeling of data. Post-annotation, the data underwent cleaning and balancing processes. The final dataset comprises 660 neutral and 660 anti-military sentiment samples, totaling 1320 samples. This balanced dataset serves as a valuable resource for sentiment analysis, providing insights into public sentiment regarding military-related topics.

Dataset Files

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[1] Muhammad Ayub, "Entities Extraction for OSINT", IEEE Dataport, 2024. [Online]. Available: http://dx.doi.org/10.21227/6z7k-nw14. Accessed: Apr. 25, 2025.
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author = {Muhammad Ayub },
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title = {Entities Extraction for OSINT},
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Muhammad Ayub. (2024). Entities Extraction for OSINT. IEEE Dataport. http://dx.doi.org/10.21227/6z7k-nw14
Muhammad Ayub, 2024. Entities Extraction for OSINT. Available at: http://dx.doi.org/10.21227/6z7k-nw14.
Muhammad Ayub. (2024). "Entities Extraction for OSINT." Web.
1. Muhammad Ayub. Entities Extraction for OSINT [Internet]. IEEE Dataport; 2024. Available from : http://dx.doi.org/10.21227/6z7k-nw14
Muhammad Ayub. "Entities Extraction for OSINT." doi: 10.21227/6z7k-nw14