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Knowledge Graph Question Answering Datasets and Their Generalizability: Are They Enough for Future Research?. (arXiv:2205.06573v1 [cs.CL])
cs.CL updates on arXiv.org arxiv.org
Existing approaches on Question Answering over Knowledge Graphs (KGQA) have
weak generalizability. That is often due to the standard i.i.d. assumption on
the underlying dataset. Recently, three levels of generalization for KGQA were
defined, namely i.i.d., compositional, zero-shot. We analyze 25 well-known KGQA
datasets for 5 different Knowledge Graphs (KGs). We show that according to this
definition many existing and online available KGQA datasets are either not
suited to train a generalizable KGQA system or that the datasets are based …
arxiv datasets future graph knowledge knowledge graph question answering research