The Cross-linguistic Role of Animacy in Grammar Structures
Nina Gregorio, Matteo Gay, Sharon Goldwater, Edoardo M. Ponti
Abstract
Animacy is a semantic feature of nominals and follows a hierarchy: personal pronouns > human > animate > inanimate. In several languages, animacy imposes hard constraints on grammar. While it has been argued that these constraints may emerge from universal soft tendencies, it has been difficult to provide empirical evidence for this conjecture due to the lack of data annotated with animacy classes. In this work, we first propose a method to reliably classify animacy classes of nominals in 11 languages from 5 families, leveraging multilingual large language models (LLMs) and word sense disambiguation datasets. Then, through this newly acquired data, we verify that animacy displays consistent cross-linguistic tendencies in terms of preferred morphosyntactic constructions, although not always in line with received wisdom: animacy in nouns correlates with the alignment role of agent, early positions in a clause, and syntactic pivot (e.g., for relativisation), but not necessarily with grammatical subjecthood. Furthermore, the behaviour of personal pronouns in the hierarchy is idiosyncratic as they are rarely plural and relativised, contrary to high-animacy nouns.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Builds on3
- FlashAttention-2: Faster Attention with Better Parallelism and Work PartitioningTri DaoICLR 2024 · 2,600 citations
- XL-WSD: An Extra-Large and Cross-Lingual Evaluation Framework for Word Sense DisambiguationTommaso Pasini, Alessandro Raganato, Roberto NavigliAAAI 2021 · 76 citations
- Composable Sparse Fine-Tuning for Cross-Lingual TransferAlan Ansell, Edoardo Maria Ponti, Anna Korhonen, Ivan VulicACL 2022
Related papers
- When Language Models Fall in Love: Animacy Processing in Transformer Language ModelsMichael Hanna, Yonatan Belinkov, Sandro PezzelleEMNLP 2023 · 2 citations
- Minimally-Supervised Joint Learning of Event Volitionality and Subject Animacy ClassificationHirokazu Kiyomaru, Sadao KurohashiAAAI 2022
- Do LLM Agents Mirror Socio-Cognitive Effects in Power-Asymmetric Conversations?Anvesh Rao Vijjini, Sagar Manjunath, Snigdha ChaturvediACL 2026
- Different types of syntactic agreement recruit the same units within large language modelsDaria Kryvosheieva, Andrea Gregor de Varda, Evelina Fedorenko, Greta TuckuteACL 2026 · 3 citations
- Women, Infamous, and Exotic Beings: A Comparative Study of Honorific Usages in Wikipedia and LLMs for Bengali and HindiSourabrata Mukherjee, Atharva Mehta, Sougata Saha, Akhil Arora et al.EMNLP 2025
