The goal of named entity recognition is to predict the label sequence y = {y1,y2, ..., yn} given the input sequence w = {w1,w2, ..., wn}, where wt represents ...
Apr 12, 2021 · It has been shown that named entity recognition (NER) could benefit from incorporating the long-distance structured information captured by dependency trees.
The results demonstrate that the proposed model achieves better performance than previous approaches while requiring fewer parameters. Our further analysis ...
The code are created based on the code of the paper "Dependency-Guided LSTM-CRF Model for Named Entity Recognition", EMNLP 2019.
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Jan 25, 2023 · Integrating dependency information between nonadjacent words can effectively improve the performance of the NER task. To achieve this goal, ...
Sep 23, 2024 · This approach involves training machine learning models on labeled data to identify and classify entities. It uses feature engineering to ...
Better Feature Integration for Named Entity Recognition. Published in NAACL, 2021. Recommended citation: Lu Xu, Zhanming Jie, Wei Lu, and Lidong Bing. 2021 ...
Better Feature Integration for Named Entity Recognition ... We believe this is because both types of features - the contextual information captured by the linear ...
A novel feature integration and entity boundary detection for named entity recognition in cybersecurity ... It combines the graph encoder with the gate mechanism, ...
6 days ago · As NER evolved, the need to automate the extraction of named entities led to the development of methods based on feature engineering. The idea ...