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 "a factoid question answering system for vietnamese"):
  Abstract: In this paper, we describe the development of an end-to-end factoid question answering system for the Vietnamese language. This system combines both statistical models and ontology-based methods in a chain of processing modules to provide high-quality mappings from natural language text to entities. We present the challenges in the development of such an intelligent user interface for an isolating language like Vietnamese and show that techniques developed for inflectional languages cannot be applied "as is". Our question answering system can answer a wide range of general knowledge questions with promising accuracy on a test set.

Includes members:
  Member "building a semantic role labelling system for vietnamese":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "vietnamese semantic role labelling")
  Member "ripple down rules for question answering":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a fast and accurate vietnamese word segmenter")
  Member "nnvlp a neural network based vietnamese language processing toolkit":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "on the vietnamese name entity recognition a deep learning method approach")
  Member "vietnamese named entity recognition using token regular expressions and bidirectional inference":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "on the vietnamese name entity recognition a deep learning method approach")
  Member "open question answering with weakly supervised embedding models":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "neural graph embedding methods for natural language processing")
  Member "question answering with subgraph embeddings":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "navigation based candidate expansion and pretrained language models for citation recommendation")

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)