human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "opentapioca lightweight entity linking for wikidata"
  Abstract: We propose a simple Named Entity Linking system that can be trained from Wikidata only. This demonstrates the strengths and weaknesses of this data source for this task and provides an easily reproducible baseline to compare other systems against. Our model is lightweight to train, to run and to keep synchronous with Wikidata in real time.

Connected through hyperedge HE-1 (induced by source paper "context aware entity linking with attentive neural networks on wikidata knowledge graph"):
  with members:
    - "a survey on recent advances in named entity recognition from deep learning models"
    - "end to end neural entity linking"
    - "deeptype multilingual entity linking by neural type system evolution"
    - "syntax aware language modeling with recurrent neural networks"
    - "attention is all you need"
    - "deep joint entity disambiguation with local neural attention"
    - "effective approaches to attention based neural machine translation"
    - "tagme on the fly annotation of short text fragments by wikipedia entities"

Connected through hyperedge HE-2 (induced by source paper "falcon 2 0 an entity and relation linking tool over wikidata"):
  with members:
    - "context aware entity linking with attentive neural networks on wikidata knowledge graph"
    - "neural collective entity linking"
    - "end to end neural entity linking"
    - "deeptype multilingual entity linking by neural type system evolution"
    - "no one is perfect analysing the performance of question answering components over the dbpedia knowledge graph"
    - "mag a multilingual knowledge base agnostic and deterministic entity linking approach"
    - "deep joint entity disambiguation with local neural attention"
    - "tagme on the fly annotation of short text fragments by wikipedia entities"

Question: Please tell me which class the center node 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)