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 "a study of recent contributions on information extraction"):
  Abstract: This paper reports on modern approaches in Information Extraction (IE) and its two main sub-tasks of Named Entity Recognition (NER) and Relation Extraction (RE). Basic concepts and the most recent approaches in this area are reviewed, which mainly include Machine Learning (ML) based approaches and the more recent trend to Deep Learning (DL) based methods.

Includes members:
  Member "deep learning applied to nlp":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "benchmark performance of machine and deep learning based methodologies for urdu text document classification")
  Member "a survey of deep learning methods for relation extraction":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "fine tuning bert for joint entity and relation extraction in chinese medical text")
  Member "a brief survey of text mining classification clustering and extraction techniques":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "flowsense a natural language interface for visual data exploration within a dataflow system")
  Member "relation extraction from clinical texts using domain invariant convolutional neural network":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "reflex flexible framework for relation extraction in multiple domains")
  Member "combining neural networks and log linear models to improve relation extraction":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "relation adversarial network for low resource knowledgegraph completion")

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.IR(Information Retrieval)