Papers by Igor Rozhkov

1 papers
Learning Nested Named Entity Recognition from Flat Annotations (2026.eacl-srw)

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Challenge: Named entity recognition (NER) requires expensive multi-level annotation.
Approach: They evaluate four approaches to learning nested structure from flat annotations alone . on NEREL, a Russian benchmark, they find the best method achieves 26.37% inner F1 .
Outcome: The proposed method closes 40% of the gap to full nested supervision on a Russian benchmark with 29 entity types where 21% of entities are nest.

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