createmomo/CRF-Layer-on-the-Top-of-BiLSTM
The CRF Layer was implemented by using Chainer 2.0. Please see more details here: https://createmomo.github.io/2017/09/12/CRF_Layer_on_the_Top_of_BiLSTM_1/
This project offers a detailed explanation and implementation of a Conditional Random Field (CRF) layer combined with a Bidirectional Long Short-Term Memory (BiLSTM) network. It helps in recognizing specific entities within text, such as names of people, organizations, or locations. You would input raw text data, and it would output the same text with identified and tagged entities. This is useful for researchers or developers working on natural language processing tasks.
208 stars. No commits in the last 6 months.
Use this if you are a developer or researcher looking for a foundational understanding and practical Chainer implementation of BiLSTM-CRF for Named Entity Recognition.
Not ideal if you are looking for a ready-to-use application or a high-level library to perform Named Entity Recognition without needing to understand the underlying implementation details.
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Last pushed
Mar 26, 2022
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