---

language: en
license: unknown
widget:
- text: "<ARG1>She fell</ARG1> because <ARG0>he pushed her</ARG0> ."
  example_title: "Causal Example 1"
- text: "<ARG0>He pushed her</ARG0> , <ARG1>causing her to fall</ARG1>."
  example_title: "Causal Example 2"
- text: "<ARG0>She fell</ARG0> because <ARG1>he pushed her</ARG1> ."
  example_title: "Non-causal Example 1"
- text: "<ARG1>He is Billy</ARG1> and <ARG0>he pushed her</ARG0>."
  example_title: "Non-causal Example 2"
---

Binary causal sentence classification with argument prompts: 

* LABEL_0 = Non-causal
* LABEL_1 = Causal (ARG0 causes ARG1)

Trained on multiple datasets.
For Causal sequences, try swapping the arguments to observe the prediction results.