Transformer assisted joint entity and relation extraction
US12346657B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Aug 8, 2022 |
| Grant date | Jul 1, 2025 |
| Priority date | — |
| Expiry date | Jul 30, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F2221/034
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Systems and methods are provided for adapting a pretrained language model to perform cybersecurity-specific named entity recognition and relation extraction. The method includes introducing a pretrained language model and a corpus of security text to a model adaptor, and generating a fine-tuned language model through unsupervised training utilizing the security text corpus. The method further includes combining a joint extraction model from a head for joint extraction with the fine-tuned language model to form an adapted joint extraction model that can perform entity and relation label prediction. The method further includes applying distant labels to security text in the corpus of security text to produce security text with distant labels, and performing Distant Supervision Training for joint extraction on the adapted joint extraction model using the security text to transform the adapted joint extraction model into a Security Language Model for name-entity recognition (NER) and relation extraction (RE).
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.