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---
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. |