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 "beyond majority voting generating evaluation scales using item response theory"):
  Abstract: We introduce Item Response Theory (IRT) from psychometrics as an alternative to majority voting to create an IRT gold standard ($GS_{IRT}$). IRT describes characteristics of individual items in $GS_{IRT}$ - their difficulty and discriminating power - and is able to account for these characteristics in its estimation of human intelligence or ability for an NLP task. In this paper, we evaluated IRT's model-fitting of a majority vote gold standard designed for Recognizing Textual Entailment (RTE), denoted as $GS_{RTE}$. By collecting human responses and fitting our IRT model, we found that up to 31% of $GS_{RTE}$ were not useful in building $GS_{IRT}$ for RTE. In addition, we found low inter-annotator agreement for some items in $GS_{RTE}$ suggesting that more work is needed for creating intelligent gold-standards.

Includes members:
  Member "representing meaning with a combination of logical and distributional models":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "eat2seq a generic framework for controlled sentence transformation without task specific training")
  Member "a large annotated corpus for learning natural language inference":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "contextual lensing of universal sentence representations")

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)