Sms Corpus With Pos And Ner
Project Overview:
Objective
The “SMS Corpus with POS and NER” project is aimed at creating a comprehensive dataset of text messages, which have been enriched with linguistic annotations. This dataset is intended to train machine learning models for various applications including sentiment analysis, automated chatbots, and language understanding systems.
Scope
This project encompasses the collection of SMS data from diverse sources and the detailed annotation of this data with POS tags and NER labels.
Sources
- User-contributed Data: Collecting SMS data directly from consenting individuals.
- Publicly Available Text Datasets: Integrating text message datasets available in the public domain.
- Collaborations with Telecom Providers: Partnering with telecom companies to access a wider range of SMS data
Data Collection Metrics
- Total SMS Messages Collected: 50,000
- User-contributed Data: 30,000
- Public Domain Datasets: 10,000
- Telecom Providers: 10,000
Annotation Process
Stages
- POS Tagging: Assigning part of speech tags to each word in the SMS messages.
- Named Entity Recognition: Labeling named entities like person names, locations, organizations, etc., in the texts.
Annotation Metrics
- SMS Messages with POS Tags: 50,000
- SMS Messages with NER Labels: 50,000
Quality Assurance
Stages
Annotation Verification: Implementing a review process involving linguistic experts to ensure the accuracy of POS and NER labels.
Data Quality Control: Filtering out irrelevant or poorly formatted SMS messages to maintain high data quality.
QA Metrics
- Annotation Review Cases: 5,000
- Data Cleansing: Curating and refining the dataset for optimal quality.
Conclusion
The “SMS Corpus with POS and NER” project showcases our commitment to providing high-quality, annotated datasets for advancing the field of natural language processing and machine learning. This carefully curated and annotated SMS corpus is an invaluable resource for developing sophisticated language models that can understand and interpret human text effectively. Our dataset stands as a testament to our expertise in data collection and annotation, offering a robust foundation for future technological advancements in various applications.
Quality Data Creation
Guaranteed TAT
ISO 9001:2015, ISO/IEC 27001:2013 Certified
HIPAA Compliance
GDPR Compliance
Compliance and Security
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