- API docs
- CLI
- Integration guides
- Blog
- How machines learn to understand words: a guide to embeddings in NLP
- Prompt-based learning with Transformers
- Efficient Transformers II: knowledge distillation & fine-tuning
- Efficient Transformers I: attention mechanisms
- Deep hierarchical unsupervised intent modelling: getting value without training data
- Fixing annotating bias with Communications Mining
- Active learning: better ML models in less time
- It's all in the numbers - assessing model performance with metrics
- Why model validation is important
- Comparing Communications Mining and Google AutoML for conversational data intelligence
General field extraction
Communications Mining extracts two kinds of output from unstructured text: labels and general fields. Labels describe the entire message, e.g. "Cancellation", "Trade Failure", or "Urgent". General fields refer to specific parts of the message, e.g. "Counterparty Name", "Customer ID", or "Cancellation Date".
In a downstream process, labels are used to triage, prioritize, and decide what kind of action should be taken. General fields are used to fill in fields of requests. For example, a downstream process may filter messages to those that have the "Cancellation" label, and then use the extracted "Customer ID" and "Cancellation Date" general fields to call an API to automatically process the cancellation.
