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 "anaphora and coreference resolution a review"):
  Abstract: Entity resolution aims at resolving repeated references to an entity in a document and forms a core component of natural language processing (NLP) research. This field possesses immense potential to improve the performance of other NLP fields like machine translation, sentiment analysis, paraphrase detection, summarization, etc. The area of entity resolution in NLP has seen proliferation of research in two separate sub-areas namely: anaphora resolution and coreference resolution. Through this review article, we aim at clarifying the scope of these two tasks in entity resolution. We also carry out a detailed analysis of the datasets, evaluation metrics and research methods that have been adopted to tackle this NLP problem. This survey is motivated with the aim of providing the reader with a clear understanding of what constitutes this NLP problem and the issues that require attention.

Includes members:
  Member "recent trends in deep learning based personality detection":
    also connected through other hyperedges:
      (none)
  Member "solving hard coreference problems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "winogrande an adversarial winograd schema challenge at scale")
  Member "sentiment and sarcasm classification with multitask learning":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "recent trends in deep learning based personality detection")
  Member "end to end neural coreference resolution":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "domain independent extraction of scientific concepts from research articles")
  Member "a mention ranking model for abstract anaphora resolution":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "argumentative relation classification as plausibility ranking")
  Member "evaluating discourse phenomena in neural machine translation":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "toward making the most of context in neural machine translation")
  Member "lexical features in coreference resolution to be used with caution":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "contextualized embeddings in named entity recognition an empirical study on generalization")
  Member "recent trends in deep learning based natural language processing":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "sqwa stochastic quantized weight averaging for improving the generalization capability of low precision deep neural networks")

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)