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Incorporating Structured Commonsense Knowledge in Story Completion

arXiv 1811.00625 ↗First posted 1 Nov 2018cs.CLcited by 23

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Abstract (arXiv)

The ability to select an appropriate story ending is the first step towards perfect narrative comprehension. Story ending prediction requires not only the explicit clues within the context, but also the implicit knowledge (such as commonsense) to construct a reasonable and consistent story. However, most previous approaches do not explicitly use background commonsense knowledge. We present a neural story ending selection model that integrates three types of information: narrative sequence, sentiment evolution and commonsense knowledge. Experiments show that our model outperforms state-of-the-art approaches on a public dataset, ROCStory Cloze Task , and the performance gain from adding the additional commonsense knowledge is significant.

Key facts. Cited by 23 papers in the map (data through 7 Oct 2026). First posted on arXiv 1 Nov 2018.

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Citing papers per year: 2021: 3; 2022: 11; 2023: 4; 2024: 5.

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  1. 2022MISC: A MIxed Strategy-Aware Model Integrating COMET for Emotional Support Conversationcited by 84
  2. 2021Integrating Visuospatial, Linguistic and Commonsense Structure into Story Visualizationcited by 51
  3. 2021Structure-Aware Abstractive Conversation Summarization via Discourse and Action Graphscited by 36
  4. 2022Summarization as Indirect Supervision for Relation Extractioncited by 31
  5. 2024Multi-Agent Collaboration via Cross-Team Orchestrationcited by 30
  6. 2022Acquiring and Modelling Abstract Commonsense Knowledge via Conceptualizationcited by 17
  7. 2022TAGPRIME: A Unified Framework for Relational Structure Extractioncited by 15
  8. 2022Coalescing Global and Local Information for Procedural Text Understandingcited by 10
  9. 2024Through the Theory of Mind's Eye: Reading Minds with Multimodal Video Large Language Modelscited by 9
  10. 2022C3KG: A Chinese Commonsense Conversation Knowledge Graphcited by 8
  11. 2024Controllable Text Generation in the Instruction-Tuning Eracited by 7
  12. 2022A Graph Enhanced BERT Model for Event Predictioncited by 5
11 more
  1. 2022Cross-Domain Aspect Extraction using Transformers Augmented with Knowledge Graphscited by 4
  2. 2023M-SENSE: Modeling Narrative Structure in Short Personal Narratives Using Protagonist's Mental Representationscited by 3
  3. 2024DECRL: A Deep Evolutionary Clustering Jointed Temporal Knowledge Graph Representation Learning Approachcited by 3
  4. 2023Transferring Procedural Knowledge across Commonsense Taskscited by 2
  5. 2024A Systematic Evaluation of Large Language Models for Natural Language Generation Taskscited by 2
  6. 2022An Ion Exchange Mechanism Inspired Story Ending Generator for Different Characterscited by 1
  7. 2022A Commonsense-Infused Language-Agnostic Learning Framework for Enhancing Prediction of Political Polarity in Multilingual News Headlinescited by 1
  8. 2021Understanding in Artificial Intelligencecited by 0
  9. 2022Unsupervised Neural Stylistic Text Generation using Transfer learning and Adapterscited by 0
  10. 2023Advancing Relation Extraction through Language Probing with Exemplars from Set Co-Expansioncited by 0
  11. 2023Enhancing Sentiment Analysis Results through Outlier Detection Optimizationcited by 0