基于机器阅读理解的事件检测方法

doi:10.13229/j.cnki.jdxbgxb.20220335

Abstract

Abstract:

In order to improve the performance of event detection task， this article redefines this task as a prompt paradigm. This paradigm uses question-answer pairs to transform event detection into machine reading problems. A pre-training model called WLBert-BiGRU is applied to predict the event triggers in QA pairs. The model uses Weight-Layers strategy to enrich the semantic representation ability of Bert model， and uses Bi-GRU to strengthen the prediction ability of the model to the event triggers. The proposed method is evaluated in ACE2005 data set， the results show that the F1 scores in event trigger recognition and classification have reached 78.1% and 75.1% respectively， which is 4.18% and 4.3% higher than the existing work.

Key words: artificial intelligence, event detection, natural language processing, machine reading comprehension

CLC Number:

TP391.1

Liu LIU,Kun DING,Shan-shan LIU,Ming LIU. Event detection method as machine reading comprehension[J].Journal of Jilin University(Engineering and Technology Edition), 2024, 54(2): 533-539.

Figures/Tables 9

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References 22

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问题模板	Which is the trigger in the sentence？
	What happened in the event？
	Which is the trigger？
	trigger
	verb

参数	数量（数值）
Epoch	6
Batch size	8
Learning rate	4×10^-5
Warm proportion	0.1
Dropout	0.1

模型	触发词识别			触发词分类
模型	p_i	r_i	f₁_i	p	r	f₁
DMCNN^［12］	80.4	67.7	73.5	75.6	63.6	69.1
JRNN^［13］	68.5	75.7	71.9	66.0	73.0	69.3
HNN^［14］	80.8	71.5	75.9	84.6	64.9	73.4
Joint3EE^［21］	70.5	74.5	72.5	68.0	71.8	69.8
baseline^［2］	74.3	77.4	75.8	71.1	73.7	72.4
WLBert-GRU	80.3	76	78.1	77.2	73.1	75.1

问题模板	触发词识别			触发词分类
问题模板	p_i	r_i	f₁_i	p	r	f₁
Which is the trigger in the sentence？	80.9	72.8	76.6	78.7	70.7	74.5
What happened in the event？	78.3	74.4	76.3	75.9	72.2	74.0
Which is the trigger？	76.3	76.0	76.2	73.9	73.6	73.7
trigger	74.6	77.8	76.2	72.5	75.6	74.0
verb	80.3	76.0	78.1	77.2	73.1	75.1
Bert+fine-tune	69.8	76.2	72.8	67.2	73.2	70.0

Event detection method as machine reading comprehension

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