Sirvi Autor "Nabiyev, Rasul" järgi

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Collaborative Multi-Agent Architecture for Domain-Agnostic Named Entity Recognition
(Tartu Ülikool, 2025) Nabiyev, Rasul; Šuvalov, Hendrik, juhendaja; Masing, Karl-Oskar, juhendaja; Tartu Ülikool. Loodus- ja täppisteaduste valdkond; Tartu Ülikool. Arvutiteaduse instituut
Named Entity Recognition(NER) traditionally requires extensive domain-specific training data to achieve satisfactory performance for a given domain. Recent advancements in large language models have enabled the development of NER systems without supervised training, though this approach still requires careful prompt engineering and may need external knowledge augmentation during inference. This thesis introduces a novel domain-agnostic NER framework based on a collaborative multi-agent architecture that can adapt to any domain given only entity definitions and their descriptions. The framework consists of 4 high-level components: a team of agents, a metaprompter, a chat supervisor and a grounding engine. The system requires no training data or prompt engineering for new domains, operating as a few-shot solution for NER tasks. The framework's performance is evaluated across 4 distinct domains using standard NER benchmark datasets. Our evaluation shows that the multi-agent approach outperforms the baseline of few-shot NER with single LLM call in 3 out of 4 benchmarks, suggesting a promising direction for domain-agnostic NER. Ablation studies demonstrate varying effectiveness of each component on the system's performance depending on the domain, with the combination of three specialized agents and grounding engine proving generally most effective in all tested domains.