# News Article Retrieval in Context for Event-centric Narrative Creation

arXiv: https://arxiv.org/abs/2106.16053 · HTML: https://mlsanity.com/paper/2106.16053/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 12 of its 53 references that are in the map.
- First posted on arXiv 30 Jun 2021.

## Builds on (most cited first, 12 of 12)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [Pretrained Transformers for Text Ranking: BERT and Beyond](https://mlsanity.com/paper/2010.06467/) (2020)
- [Query Resolution for Conversational Search with Limited Supervision](https://mlsanity.com/paper/2005.11723/) (2020)
- [Understanding the Behaviors of BERT in Ranking](https://mlsanity.com/paper/1904.07531/) (2019)
- [EventKG: A Multilingual Event-Centric Temporal Knowledge Graph](https://mlsanity.com/paper/1804.04526/) (2018)
- [Simple Applications of BERT for Ad Hoc Document Retrieval](https://mlsanity.com/paper/1903.10972/) (2019)
- [A Context-Aware Citation Recommendation Model with BERT and Graph Convolutional Networks](https://mlsanity.com/paper/1903.06464/) (2019)
- [QUOTUS: The Structure of Political Media Coverage as Revealed by Quoting Patterns](https://mlsanity.com/paper/1504.01383/) (2015)
- [Searching for Relevant Lessons Learned Using Hybrid Information Retrieval Classifiers: A Case Study in Software Engineering](https://mlsanity.com/paper/1812.05168/) (2018)
- [Context-Based Quotation Recommendation](https://mlsanity.com/paper/2005.08319/) (2020)
- [Weakly-supervised Contextualization of Knowledge Graph Facts](https://mlsanity.com/paper/1805.02393/) (2018)
- [HapPenIng: Happen, Predict, Infer -- Event Series Completion in a Knowledge Graph](https://mlsanity.com/paper/1909.06219/) (2019)

## Built on by (most cited first, 3 of 3)

- [MsPrompt: Multi-step Prompt Learning for Debiasing Few-shot Event Detection](https://mlsanity.com/paper/2305.09335/) (2023)
- [Lost in Recursion: Mining Rich Event Semantics in Knowledge Graphs](https://mlsanity.com/paper/2404.16405/) (2024)
- [RA-MTR: A Retrieval Augmented Multi-Task Reader based Approach for Inspirational Quote Extraction from Long Documents](https://mlsanity.com/paper/2502.12124/) (2025)

## Abstract (arXiv)

Writers such as journalists often use automatic tools to find relevant content to include in their narratives. In this paper, we focus on supporting writers in the news domain to develop event-centric narratives. Given an incomplete narrative that specifies a main event and a context, we aim to retrieve news articles that discuss relevant events that would enable the continuation of the narrative. We formally define this task and propose a retrieval dataset construction procedure that relies on existing news articles to simulate incomplete narratives and relevant articles. Experiments on two datasets derived from this procedure show that state-of-the-art lexical and semantic rankers are not sufficient for this task. We show that combining those with a ranker that ranks articles by reverse chronological order outperforms those rankers alone. We also perform an in-depth quantitative and qualitative analysis of the results that sheds light on the characteristics of this task.