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 "lithium nlp a system for rich information extraction from noisy user generated text on social media"):
  Abstract: In this paper, we describe the Lithium Natural Language Processing (NLP) system - a resource-constrained, high- throughput and language-agnostic system for information extraction from noisy user generated text on social media. Lithium NLP extracts a rich set of information including entities, topics, hashtags and sentiment from text. We discuss several real world applications of the system currently incorporated in Lithium products. We also compare our system with existing commercial and academic NLP systems in terms of performance, information extracted and languages supported. We show that Lithium NLP is at par with and in some cases, outperforms state- of-the-art commercial NLP systems.

Includes members:
  Member "dawt densely annotated wikipedia texts across multiple languages":
    also connected through other hyperedges:
      (none)
  Member "high throughput and language agnostic entity disambiguation and linking on user generated data":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "dawt densely annotated wikipedia texts across multiple languages")
  Member "global entity ranking across multiple languages":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "dawt densely annotated wikipedia texts across multiple languages")
  Member "mining half a billion topical experts across multiple social networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "dawt densely annotated wikipedia texts across multiple languages")
  Member "identifying actionable messages on social media":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "analyzing users sentiment towards popular consumer industries and brands on twitter")
  Member "a new anew evaluation of a word list for sentiment analysis in microblogs":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "how impersonators exploit instagram to generate fake engagement")

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.AI(Artificial Intelligence)