---
license: mit
language:
- en
base_model:
- google-t5/t5-large
---
## CASENT

CASENT is a lightweight multi-label entity classification model designed for extremely large label space (e.g., UFET and WikiData). It can also be used for entity extraction and tagging when integrated with a span detector.
CASENT offers several advantages compared to previous methods: 1) Standard maximum likelihood training; 2) Efficient inference through a single autoregressive decoding pass; 3) Calibrated confidence scores; 4) Strong generalization performance to unseen domains and types.

Paper: [Calibrated Seq2Seq Models for Efficient and Generalizable Ultra-fine Entity Typing](https://arxiv.org/pdf/2311.00835) (EMNLP 2023 Findings)

Repository & Demo: https://github.com/yanlinf/CASENT

Contact: yanlin@megagon.ai