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Article summary:
1. The article presents CONVEX, an unsupervised method for answering incomplete questions over a knowledge graph.
2. The core of the method is a graph exploration algorithm that expands a frontier to find candidate answers for the current question.
3. To evaluate CONVEX, the authors released ConvQuestions, a crowdsourced benchmark with 11,200 distinct conversations from five different domains.
Article analysis:
The article appears to be reliable and trustworthy in its presentation of the research findings and conclusions. The authors provide detailed descriptions of their methodology and results, as well as references to related work in the field. The authors also present ConvQuestions, a crowdsourced benchmark with 11,200 distinct conversations from five different domains, which provides evidence for their claims about the effectiveness of CONVEX. Furthermore, the authors provide clear explanations of their methods and results throughout the paper.
The only potential bias in this article is that it focuses solely on one approach to conversational question answering over knowledge graphs (CONVEX). While this approach may be effective in certain contexts, it is possible that other approaches could be more effective in other contexts or scenarios. Additionally, while the authors do discuss related work in this field, they do not explore any counterarguments or alternative approaches to conversational question answering over knowledge graphs.