Key tasks associated with building NLP solutions include:

1. Query and spell correction

2. Text normalization including query and spelling correction

3. Extracting keywords and named entities from text

4. Data labeling for building ML models

5. Building highly accurate DL models for tasks such as classification, text summarization, natural language understanding, and natural language generation

6. Predictive text for features like auto-complete and Smart Compose

DellNLP implements several text pre-processing functions and incorporates NLP resources such as n-gram dictionaries and word embeddings trained on Dell data.

The primary task of DellNLP is to automatically correct spelling mistakes. The other tasks implemented include text sanitization, predictive text capability, and retrieval of semantically similar terms.

The subsequent sections offer details on design decisions and algorithm components, some of which are included in the following figure:

Figure 4.            DellNLP consists of seven key modules to help extract insights from text data