Distinguishing Address vs. Reference Mentions of Personal Names in Text

Vinodkumar Prabhakaran, Aida Mostafazadeh Davani, Melissa Ferguson, Stav Atir


Abstract
Detecting named entities in text has long been a core NLP task. However, not much work has gone into distinguishing whether an entity mention is addressing the entity vs. referring to the entity; e.g., John, would you turn the light off? vs. John turned the light off. While this distinction is marked by a vocative case marker in some languages, many modern Indo-European languages such as English do not use such explicit vocative markers, and the distinction is left to be interpreted in context. In this paper, we present a new annotated dataset that captures the address vs. reference distinction in English, an automatic tagger that performs at 85% accuracy in making this distinction, and demonstrate how this distinction is important in NLP and computational social science applications in English language.
Anthology ID:
2023.findings-acl.425
Volume:
Findings of the Association for Computational Linguistics: ACL 2023
Month:
July
Year:
2023
Address:
Toronto, Canada
Editors:
Anna Rogers, Jordan Boyd-Graber, Naoaki Okazaki
Venue:
Findings
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
6801–6809
Language:
URL:
https://aclanthology.org/2023.findings-acl.425
DOI:
10.18653/v1/2023.findings-acl.425
Bibkey:
Cite (ACL):
Vinodkumar Prabhakaran, Aida Mostafazadeh Davani, Melissa Ferguson, and Stav Atir. 2023. Distinguishing Address vs. Reference Mentions of Personal Names in Text. In Findings of the Association for Computational Linguistics: ACL 2023, pages 6801–6809, Toronto, Canada. Association for Computational Linguistics.
Cite (Informal):
Distinguishing Address vs. Reference Mentions of Personal Names in Text (Prabhakaran et al., Findings 2023)
Copy Citation:
PDF:
https://preview.aclanthology.org/emnlp22-frontmatter/2023.findings-acl.425.pdf