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Implementation of AAAI 21 paper: Nested Named Entity Recognition with Partially Observed TreeCRFs

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title

Yao Fu, Chuanqi Tan, Mosha Chen, Songfang Huang and Fei Huang. Nested Named Entity Recognition with Partially Observed TreeCRFs. AAAI 2021. [arxiv]

Train:

python train.py --output_dir {OUTPUT_DIR} --model_type bert --config_name {BERT_CONFIG} --model_name_or_path {BERT_DIR} --train_file {TRAIN_FILE} --predict_file {DEV_FILE} --test_file {TEST_FILE} --max_seq_length 64 --per_gpu_train_batch_size 48 --per_gpu_eval_batch_size 48 --do_train --do_predict --learning_rate 3e-5 --num_train_epochs 100 --overwrite_output_dir --save_steps 1000 --dataset {DATASET_NAME}} --potential_normalization True --structure_smoothing_p 0.98 --parser_type deepbiaffine --latent_size 1 --seed 12345

Test:

python train.py --output_dir {CHECKPOINT_DIR} --model_type bert --config_name {BERT_CONFIG} --model_name_or_path {BERT_DIR} --train_file {TRAIN_FILE} --predict_file {DEV_FILE} --test_file {TEST_FILE} --max_seq_length 128 --per_gpu_train_batch_size 24 --per_gpu_eval_batch_size 24 --do_predict --learning_rate 3e-5 --num_train_epochs 100 --overwrite_output_dir --save_steps 1000 --dataset {DATASET_NAME}} --potential_normalization True --structure_smoothing_p 0.98 --parser_type deepbiaffine --latent_size 1 --seed 12345

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