# Code Book for the Annotation of Diverse Cross-Document Coreference of Entities in News Articles

arXiv: https://arxiv.org/abs/2310.12064 · HTML: https://mlsanity.com/paper/2310.12064/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 3 of its 20 references that are in the map.
- First posted on arXiv 18 Oct 2023.

## Builds on (most cited first, 3 of 3)

- [Towards A Reliable Ground-Truth For Biased Language Detection](https://mlsanity.com/paper/2112.07421/) (2021)
- [XCoref: Cross-document Coreference Resolution in the Wild](https://mlsanity.com/paper/2109.05252/) (2021)
- [Towards Evaluation of Cross-document Coreference Resolution Models Using Datasets with Diverse Annotation Schemes](https://mlsanity.com/paper/2109.05250/) (2021)

## Abstract (arXiv)

This paper presents a scheme for annotating coreference across news articles, extending beyond traditional identity relations by also considering near-identity and bridging relations. It includes a precise description of how to set up Inception, a respective annotation tool, how to annotate entities in news articles, connect them with diverse coreferential relations, and link them across documents to Wikidata's global knowledge graph. This multi-layered annotation approach is discussed in the context of the problem of media bias. Our main contribution lies in providing a methodology for creating a diverse cross-document coreference corpus which can be applied to the analysis of media bias by word-choice and labelling.