Ask To The Point: Open-Domain Entity-Centric Question Generation
We introduce a new task called *entity-centric question generation* (ECQG), motivated by real-world applications such as topic-specific learning, assisted reading, and fact-checking. The task aims to generate questions from an entity perspective. To solve ECQG, we propose a coherent PLM-based framework GenCONE with two novel modules: content focusing and question verification. The content focusing module first identifies a focus as "what to ask" to form draft questions, and the question verification module refines the questions afterwards by verifying the answerability. We also construct a large-scale open-domain dataset from SQuAD to support this task. Our extensive experiments demonstrate that GenCONE significantly and consistently outperforms various baselines, and two modules are effective and complementary in generating high-quality questions.
Code (1)
Tasks
Fact CheckingQuestion GenerationQuestion-GenerationMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
OEKG: The Open Event Knowledge Graph
Accessing and understanding contemporary and historical events of global impact such as the US elections and the Olympic Games is a major prerequisite for cross-lingual event analytics that investigate event causes, perc…
ArticlesImage RetrievalKnowledge Graphsnamed-entity-recognition+4Can a Frozen Pretrained Language Model be used for Zero-shot Neural Retrieval on Entity-centric Questions?
Neural document retrievers, including dense passage retrieval (DPR), have outperformed classical lexical-matching retrievers, such as BM25, when fine-tuned and tested on specific question-answering datasets. However, it …
Domain GeneralizationLanguage ModelingLanguage ModellingPassage Retrieval+2Simple Entity-Centric Questions Challenge Dense Retrievers
Open-domain question answering has exploded in popularity recently due to the success of dense retrieval models, which have surpassed sparse models using only a few supervised training examples. However, in this paper, w…
Data AugmentationOpen-Domain Question AnsweringPassage RetrievalQuestion Answering+1Entity Retrieval for Answering Entity-Centric Questions
The similarity between the question and indexed documents is a crucial factor in document retrieval for retrieval-augmented question answering. Although this is typically the only method for obtaining the relevant docume…
Entity RetrievalQuestion AnsweringRetrievalECIS-VQG: Generation of Entity-centric Information-seeking Questions from Videos
Previous studies on question generation from videos have mostly focused on generating questions about common objects and attributes and hence are not entity-centric. In this work, we focus on the generation of entity-cen…
Fact CheckingQuestion GenerationQuestion-Generation