Automatic Generation of the Draft Procuratorial Suggestions Based on an Extractive Summarization Method: BERTSLCA

The automatic generation of the draft procuratorial suggestions is to extract the description of illegal facts, administrative omission, description of laws and regulations, and other information from the case documents. Previously, the existing deep learning methods mainly focus on context-free word embeddings when addressing legal domain-specific extractive summarization tasks, which cannot get a better semantic understanding of the text and in turn leads to an adverse summarization performance. To this end, we propose a novel deep contextualized embeddings-based method BERTSLCA to conduct the extractive summarization task. The model is mainly based on the variant of BERT called BERTSUM. Firstly, the input document is fed into BERTSUM to get sentence-level embeddings. Then, we design an extracting architecture to catch the long dependency between sentences utilizing the Bi-Long Short-Term Memory (Bi-LSTM) unit, and at the end of the architecture, three cascaded convolution kernels with different sizes are designed to extract the relationships between adjacent sentences. Last, we introduce an attention mechanism to strengthen the ability to distinguish the importance of different sentences. To the best of our knowledge, this is the first work to use the pretrained language model for extractive summarization tasks in the field of Chinese judicial litigation. Experimental results on public interest litigation data and CAIL 2020 dataset all demonstrate that the proposed method achieves competitive performance.

Access to Justice: Environmental Non-Governmental Organisations According to the Aarhus Regulation

Article 10 of the Aarhus Regulation provides an opportunity for environmental non-governmental organisations (hereafter ENGOs) to request an internal review to an EU institution or body that has adopted an administrative act under environmental law, or should have done so in the case of an alleged administrative omission. The criteria that have to be met for an ENGO to be entitled to make this request are defined in Article 11 of the Regulation. Together, these criteria can be regarded as the criteria which define an ENGO at the European Union level. The aim of this article is to investigate whether these criteria are sufficiently clear and whether they contribute to the objective of providing wide access for ENGOs to the internal review procedure. In order to understand the aim the EU institutions had in mind when they decided on the standing criteria, this article examines how these criteria were selected by analysing the legislative documents that resulted in the adoption of the Aarhus Regulation. It helps to identify whether the Commission is currently interpreting these criteria in line with the spirit with which they have been defined. Furthermore, internal review requests which provide insights into the scope of the Article 11 criteria have been selected in order to understand how the European Commission currently interprets the standing criteria. Finally, a conclusion is provided on the questions raised, together with recommendations for improvement and further research.