(C) 2024 NLP-Lab
More details about the Hoosier Ellipsis Corpus can be found on the NLP-Lab pages. The GitHub repo contains links to other languages and useful code and scripts for data processing.
This repo contains the Mandarin Chinese Ellipsis Sub-corpus of THEC.
Consult the data format specification for details about the structure of the files and the annotation standard used.
- Yuchen Yang
- Damir Cavar
Please use the following snippet to cite our work.
@inproceedings{cavar-etal-2024-typology,
title = "The Typology of Ellipsis: A Corpus for Linguistic Analysis and Machine Learning Applications",
author = "Cavar, Damir and Mompelat, Ludovic and Abdo, Muhammad",
editor = "Hahn, Michael and Sorokin, Alexey and Kumar, Ritesh and Shcherbakov, Andreas and Otmakhova, Yulia and Yang, Jinrui and Serikov, Oleg and Rani, Priya and Ponti, Edoardo M. and Murado{\u{g}}lu, Saliha and Gao, Rena and Cotterell, Ryan and Vylomova, Ekaterina",
booktitle = "Proceedings of the 6th Workshop on Research in Computational Linguistic Typology and Multilingual NLP",
month = mar,
year = "2024",
address = "St. Julian's, Malta",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.sigtyp-1.6",
pages = "46--54",
abstract = "State-of-the-art (SotA) Natural Language Processing (NLP) technology faces significant challenges with constructions that contain ellipses. Although theoretically well-documented and understood, there needs to be more sufficient cross-linguistic language resources to document, study, and ultimately engineer NLP solutions that can adequately provide analyses for ellipsis constructions. This article describes the typological data set on ellipsis that we created for currently seventeen languages. We demonstrate how SotA parsers based on a variety of syntactic frameworks fail to parse sentences with ellipsis, and in fact, probabilistic, neural, and Large Language Models (LLM) do so, too. We demonstrate experiments that focus on detecting sentences with ellipsis, predicting the position of elided elements, and predicting elided surface forms in the appropriate positions. We show that cross-linguistic variation of ellipsis-related phenomena has different consequences for the architecture of NLP systems.",
}