human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "cail2019 scm a dataset of similar case matching in legal domain"):
  Abstract: In this paper, we introduce CAIL2019-SCM, Chinese AI and Law 2019 Similar Case Matching dataset. CAIL2019-SCM contains 8,964 triplets of cases published by the Supreme People's Court of China. CAIL2019-SCM focuses on detecting similar cases, and the participants are required to check which two cases are more similar in the triplets. There are 711 teams who participated in this year's competition, and the best team has reached a score of 71.88. We have also implemented several baselines to help researchers better understand this task. The dataset and more details can be found from this https URL.

Includes members:
  Member "neural legal judgment prediction in english":
    also connected through other hyperedges:
      (none)
  Member "interpretable charge predictions for criminal cases learning to generate court views from fact descriptions":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "jec qa a legal domain question answering dataset")
  Member "cail2018 a large scale legal dataset for judgment prediction":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "jec qa a legal domain question answering dataset")
  Member "overview of cail2018 legal judgment prediction competition":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "cjrc a reliable human annotated benchmark dataset for chinese judicial reading comprehension")
  Member "bert pre training of deep bidirectional transformers for language understanding":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "multi simlex a large scale evaluation of multilingual and cross lingual lexical semantic similarity")
  Member "matching natural language sentences with hierarchical sentence factorization":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a deep generative model for graphs supervised subset selection to create diverse realistic graphs with applications to power networks synthesis")
  Member "learning to predict charges for criminal cases with legal basis":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "jec qa a legal domain question answering dataset")
  Member "event identification as a decision process with non linear representation of text":
    also connected through other hyperedges:
      (none)

Question: Please tell me which class the source paper belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.CL(Computation and Language)