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 "information extraction based on named entity for tourism corpus"):
  Abstract: Tourism information is scattered around nowadays. To search for the information, it is usually time consuming to browse through the results from search engine, select and view the details of each accommodation. In this paper, we present a methodology to extract particular information from full text returned from the search engine to facilitate the users. The approach is based on name entity recognition (NER). The main steps are 1) building training data and 2) building the model. The key task is the building training data: First, the tourism data are gathered and the vocabularies are built. Several minor steps include sentence extraction, relation and name entity extraction for tagging purpose. Then, the recognition model of a given entity type can be built. From the experiments, given hotel description, the model can extract the desired entity,i.e, name, location, facility as well as relation type. The extracted data can further be stored as a structured information, e.g., in the ontology format, for future querying and inference. The model for automatic named entity identification, based on machine learning, yields the error ranging 5%-25%.

Includes members:
  Member "a survey on recent advances in named entity recognition from deep learning models":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "span based joint entity and relation extraction with transformer pre training")
  Member "a survey of the usages of deep learning in natural language processing":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "on the computation of counterfactual explanations a survey")
  Member "bert pre training of deep bidirectional transformers for language understanding":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "multi simlex a large scale evaluation of multilingual and cross lingual lexical semantic similarity")
  Member "conceptnet 5 5 an open multilingual graph of general knowledge":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a study of the tasks and models in machine reading comprehension")
  Member "google s neural machine translation system bridging the gap between human and machine translation":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "automl zero evolving machine learning algorithms from scratch")

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)