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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/

Python 100.00%

machine-learning natural-language-processing named-entity-recognition bilstm-crf-model bilstm-crf

crf-layer-on-the-top-of-bilstm's Introduction

CRF-Layer-on-the-Top-of-BiLSTM (BiLSTM-CRF)

The article series include:

Introduction - the general idea of the CRF layer on the top of BiLSTM for named entity recognition tasks
A Detailed Example - a toy example to explain how CRF layer works step-by-step
Chainer Implementation - a chainer implementation of the CRF Layer

Links:

CRF Layer on the Top of BiLSTM - 1 Outline and Introduction
CRF Layer on the Top of BiLSTM - 2 CRF Layer (Emission and Transition Score)
CRF Layer on the Top of BiLSTM - 3 CRF Loss Function
CRF Layer on the Top of BiLSTM - 4 Real Path Score
CRF Layer on the Top of BiLSTM - 5 The Total Score of All the Paths
CRF Layer on the Top of BiLSTM - 6 Infer the Labels for a New Sentence
CRF Layer on the Top of BiLSTM - 7 Chainer Implementation Warm Up
CRF Layer on the Top of BiLSTM - 8 Demo Code

GitHub: https://github.com/createmomo/CRF-Layer-on-the-Top-of-BiLSTM

Wechat Public Account

Please note that: The Wechat Public Account is avaiable now! If you found this article is useful and would like to found more information about this series, please subscribe to the public account by your Wechat! (2020-04-03)

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crf-layer-on-the-top-of-bilstm's Issues

could you provide more details in this article?

Hello, Thank you for explaining CRF layer. Could you provide more information in this article so I could reference it in my thesis?
Thank you in advance!

Have you resolved the unreasonable crf output sequence issue

Just wondering have you resolved the unreasonable crf output sequence such as:
word1 O
word2 I-PERSON
word3 I-ORG
If you have solved this issue, how?

quenstion about crf layer

hi creatrmomo，I have some quentions about crf layer. first，in crf theory, the likelyhood function is based on the observations, as I see in this demo, the emission and transition score are only computed based on the lstm outputs, so should we name this layer crf?I think this name is not so accurate. Second, when we calculate all path scores, why use expression previous+obs+transitions, where previous is transposed? I am still confused . Thank you for your reply.

How to save the trained model parameters？

hello，If I want to save the parameters of the trained model for later use, what should I do？

Does CRF layer support multi-label classification?

My label is multi-label , it must predict a vector rather than a scalar label.
Does this CRF layer support this ? if don't, why?

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