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: "sparql as a foreign language"
  Abstract: In the last years, the Linked Data Cloud has achieved a size of more than 100 billion facts pertaining to a multitude of domains. However, accessing this information has been significantly challenging for lay users. Approaches to problems such as Question Answering on Linked Data and Link Discovery have notably played a role in increasing information access. These approaches are often based on handcrafted and/or statistical models derived from data observation. Recently, Deep Learning architectures based on Neural Networks called seq2seq have shown to achieve state-of-the-art results at translating sequences into sequences. In this direction, we propose Neural SPARQL Machines, end-to-end deep architectures to translate any natural language expression into sentences encoding SPARQL queries. Our preliminary results, restricted on selected DBpedia classes, show that Neural SPARQL Machines are a promising approach for Question Answering on Linked Data, as they can deal with known problems such as vocabulary mismatch and perform graph pattern composition.

Connected through hyperedge HE-1 (induced by source paper "neural machine translating from natural language to sparql"):
  with members:
    - "seq2sql generating structured queries from natural language using reinforcement learning"
    - "semantic parsing natural language into sparql improving target language representation with neural attention"
    - "neural machine translation for query construction and composition"
    - "attention is all you need"
    - "an encoder decoder framework translating natural language to database queries"
    - "convolutional sequence to sequence learning"
    - "language to logical form with neural attention"
    - "google s neural machine translation system bridging the gap between human and machine translation"

Connected through hyperedge HE-2 (induced by source paper "neural machine translation for query construction and composition"):
  with members:
    - "seq2sql generating structured queries from natural language using reinforcement learning"
    - "universal sentence encoder"
    - "zero shot question generation from knowledge graphs for unseen predicates and entity types"
    - "neural symbolic machines learning semantic parsers on freebase with weak supervision"
    - "neural programmer interpreters"

Connected through hyperedge HE-3 (induced by source paper "semantic parsing syntactic assurance to target sentence using lstm encoder cfg decoder"):
  with members:
    - "language to logical form with neural attention"
    - "using linguistic analysis to translate arabic natural language queries to sparql"
    - "neural machine translation by jointly learning to align and translate"
    - "learning to map sentences to logical form structured classification with probabilistic categorial grammars"

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)