SLIMER-IT: Show Less Instruct More Entity Recognition - Italian language

SLIMER-IT is an LLM specifically instructed for zero-shot NER on Italian language.

Github repository: https://github.com/andrewzamai/SLIMER_IT

Instructed on a reduced number of tags (PER, ORG, LOC), it is designed to tackle never-seen-before Named Entity tags by leveraging a prompt enriched with a DEFINITION and GUIDELINES for the NE to be extracted.

Built with Meta Llama 3, based on the Italian instruction-tuned version swap-uniba/LLaMAntino-3-ANITA-8B-Inst-DPO-ITA

from vllm import LLM, SamplingParams

vllm_model = LLM(model="expertai/SLIMER-IT")

sampling_params = SamplingParams(temperature=0, max_tokens=128)

prompts = [prompter.generate_prompt(instruction, input) for instruction, input in instruction_input_pairs]
responses = vllm_model.generate(prompts, sampling_params)

Citation

If you find SLIMER-IT useful in your research or work, please cite the following paper:

@misc{zamai2024slimeritzeroshotneritalian,
      title={SLIMER-IT: Zero-Shot NER on Italian Language}, 
      author={Andrew Zamai and Leonardo Rigutini and Marco Maggini and Andrea Zugarini},
      year={2024},
      eprint={2409.15933},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2409.15933}, 
}