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: "corpus annotation for parser evaluation"
  Abstract: We describe a recently developed corpus annotation scheme for evaluating parsers that avoids shortcomings of current methods. The scheme encodes grammatical relations between heads and dependents, and has been used to mark up a new public-domain corpus of naturally occurring English text. We show how the corpus can be used to evaluate the accuracy of a robust parser, and relate the corpus to extant resources.

Connected through hyperedge HE-1 (induced by source paper "computational register analysis and synthesis"):
  with members:
    - "style transfer through back translation"
    - "survey of the state of the art in natural language generation core tasks applications and evaluation"
    - "controlling linguistic style aspects in neural language generation"
    - "style transfer in text exploration and evaluation"
    - "shakespearizing modern language using copy enriched sequence to sequence models"
    - "machine learning in automated text categorization"

Connected through hyperedge HE-2 (induced by source paper "framework and resources for natural language parser evaluation"):
  with members:
    - "a common xml based framework for syntactic annotations"
    - "joint and conditional estimation of tagging and parsing models"
    - "exploiting diversity in natural language processing combining parsers"
    - "atlas a flexible and extensible architecture for linguistic annotation"
    - "measuring efficiency in high accuracy broad coverage statistical parsing"

Connected through hyperedge HE-3 (induced by source paper "using existing systems to supplement small amounts of annotated grammatical relations training data"):
  with members:
    - "exploiting diversity in natural language processing combining parsers"
    - "learning transformation rules to find grammatical relations"
    - "cascaded grammatical relation assignment"
    - "supervised grammar induction using training data with limited constituent information"

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)