DellNER is a custom Named Entity Recognition (NER) model that helps identify pre-defined entities in text data, as shown in the following figure. Currently, DellNER helps identify the following entities:

• Hardware entities such as motherboards, hard disk drives, memory
• Software entities such as operating systems, BIOS, Microsoft Office
• Diagnostic tests carried out by technical support agents such as ePSA, BIST
• Diagnostic codes generated during troubleshooting such as:

2000-0141, amber white-off-of

• Technical issues encountered during troubleshooting such as no power, slow performance, no video

Figure 13.        DellNER helps identify pre-defined entities in text data

DellNER was trained on a corpus of more than 1 million case logs generated by technical support agents during troubleshooting for the client business. The training data was bootstrapped using a combination of static term lists and regular expressions. For evaluating model performance, a sample of 1,000 case logs was manually labelled. The model performance is shown in the following table:

Note: DIAGCODE was not included in test results above since there was a very small sample of it in the test set (<10 occurrences).