论文标题
多跳的事实检查政治主张
Multi-Hop Fact Checking of Political Claims
论文作者
论文摘要
最近的工作提出了用于研究复杂自然语言推理的多跳模型和数据集。需要多跳推理的一个值得注意的任务是事实检查，其中一组连接的证据作品导致对索赔的最终裁决。但是，现有的数据集要么不提供有关黄金证据页面的注释，要么是唯一由（发烧）组成的数据集，主要由可以通过简单推理进行事实检查并人为构建的索赔。在这里，我们研究了对自然发生的索赔的更复杂的主张验证，该主张与相互联系的证据块有多个啤酒花。我们：1）构建一个小的注释数据集，即政治霍普（Politihop），以索赔验证的证据判决； 2）将其与现有的多跳数据集进行比较； 3）研究如何将知识从更广泛的内部和外部资源转移到政治上。我们发现，任务很复杂，并通过建筑实现最佳性能，该体系结构专门将推理与证据作品结合结合结合使用域转移学习。
Recent work has proposed multi-hop models and datasets for studying complex natural language reasoning. One notable task requiring multi-hop reasoning is fact checking, where a set of connected evidence pieces leads to the final verdict of a claim. However, existing datasets either do not provide annotations for gold evidence pages, or the only dataset which does (FEVER) mostly consists of claims which can be fact-checked with simple reasoning and is constructed artificially. Here, we study more complex claim verification of naturally occurring claims with multiple hops over interconnected evidence chunks. We: 1) construct a small annotated dataset, PolitiHop, of evidence sentences for claim verification; 2) compare it to existing multi-hop datasets; and 3) study how to transfer knowledge from more extensive in- and out-of-domain resources to PolitiHop. We find that the task is complex and achieve the best performance with an architecture that specifically models reasoning over evidence pieces in combination with in-domain transfer learning.
