| --- |
| language: |
| - en |
| pipeline_tag: token-classification |
| tags: |
| - legal |
| license: mit |
| --- |
| |
| # Knowledge Graph Extraction for Cyber incidents |
| This model has been finetuned with SecureBERT (https://arxiv.org/abs/2204.02685) |
| on the CASIE dataset (https://ieeexplore.ieee.org/document/9776031). We have implemented the approach described in the CASIE paper. |
|
|
| # Model Description |
| The following description is taken from the CASIE paper: |
|
|
| - An **event nugget** is a word or phrase that most clearly expresses the event occurrence. These differ from event triggers in that they can be multi-word phrases. |
|
|
| - An **event argument** is an event participant or property value. They can be taggable entities involved in the event, such as person or organization, or attributes that specify important information, such as time or amount. |
|
|
| - A **role** is a semantic relation between an event nugget and an argument. Each event type specifies the roles it can have and constraints on the arguments that can fill them. |
|
|
| - A **realis** value specifies whether or not an event occurred and can be one of the three values: Actual (event actually happened), Other (failed event, future event), or Generic (an undetermined/non-specific event, such as referring to the concept of phishing attacks). |
|
|
| # Example |
|  |
|
|
| # Usage |
| ``` |
| from transformers import AutoModelForTokenClassification |
| model = AutoModelForTokenClassification.from_pretrained("CyberPeace-Institute/Cybersecurity-Knowledge-Graph", trust_remote_code=True) |
| |
| input_text = "This is a Cybersecurity-related text." |
| |
| output = model(input_text) |
| ``` |
| IMPORTANT! : To get the Argument to Role coreferences, use the dedicated **space**! You can download the models under "arg_role_models/". |
