Frame Semantic Transformer#
Frame-based semantic parsing library trained on FrameNet 1.7 and built on HuggingFace’s T5 Transformer
Live Demo: chanind.github.io/frame-semantic-transformer
Installation#
Frame Semantic Transformer releases are hosted on PyPI, and can be installed using pip as below:
pip install frame-semantic-transformer
Basic usage#
The main entry to interacting with the library is the FrameSemanticTransformer class, as shown below. For inference the detect_frames() method is likely all that is needed to perform frame parsing.
from frame_semantic_transformer import FrameSemanticTransformer
frame_transformer = FrameSemanticTransformer()
result = frame_transformer.detect_frames("The hallway smelt of boiled cabbage and old rag mats.")
print(f"Results found in: {result.sentence}")
for frame in result.frames:
print(f"FRAME: {frame.name}")
for element in frame.frame_elements:
print(f"{element.name}: {element.text}")