SEACrowd/indocoref

Indocoref数据集包含来自印尼语维基百科的文章，这些文章满足以下条件：包含大量名词短语，如虚构情节、传记和历史事件；包含代词和命名实体的显著变化。数据集由201篇文章组成，经过五名语言学系本科生的标注，使用了SACR工具进行共指消解标注。数据集支持的任务是共指消解。

The Indocoref dataset consists of articles sourced from Indonesian Wikipedia that satisfy the following criteria: they include a substantial number of noun phrases related to fictional plots, biographies and historical events, and display notable variations in pronouns and named entities. Comprising 201 articles, the dataset was annotated by five undergraduate students majoring in linguistics, with coreference resolution annotation performed using the SACR tool. The task supported by this dataset is coreference resolution.

原始信息汇总

数据集概述

数据集名称

Indocoref

语言

印度尼西亚语

任务类别

指代消解

标签

指代消解

数据集描述

数据集包含来自印度尼西亚语维基百科的文章，这些文章满足以下条件：

• 页面包含许多名词短语，作者主观选择以下内容：(i) 虚构情节，例如电影、电视节目和小说故事的副标题；(ii) 传记（包括虚构角色）；(iii) 历史事件或重要事件。
• 页面包含大量代词和命名实体的变体。我们通过字符串匹配计算文档中第一人称、第二人称、第三人称代词和附着代词的数量。我们使用斯坦福CoreNLP NER标记器（Manning et al., 2014）检查命名实体的数量，该标记器使用从Alfina et al. (2016)的印度尼西亚语语料库训练的模型。
• 维基百科文本的长度为500到2000字。
• 我们从筛选后的维基百科页面子集中抽取了201个页面。我们聘请了五名语言学系本科生作为标注者，他们都是印度尼西亚语母语者。标注工作使用Script d’Annotation des Chanes de Rfrence (SACR)进行，这是一个由Oberle (2018)开发的基于网络的指代消解标注工具。
• 在201个文本中，标注者标记了16,460个提及。

支持任务

指代消解

数据集版本

源版本：1.0.0。SEACrowd版本：2024.06.20。

数据集许可证

MIT

引用

如果使用Indocoref数据集，请引用以下内容：

@inproceedings{artari-etal-2021-multi, title = {{A Multi-Pass Sieve Coreference Resolution for Indonesian}}, author = {Artari, Valentina Kania Prameswara and Mahendra, Rahmad and Jiwanggi, Meganingrum Arista and Anggraito, Adityo and Budi, Indra}, year = 2021, month = {Sep}, booktitle = {Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2021)}, publisher = {INCOMA Ltd.}, address = {Held Online}, pages = {79--85}, url = {https://aclanthology.org/2021.ranlp-1.10}, abstract = {Coreference resolution is an NLP task to find out whether the set of referring expressions belong to the same concept in discourse. A multi-pass sieve is a deterministic coreference model that implements several layers of sieves, where each sieve takes a pair of correlated mentions from a collection of non-coherent mentions. The multi-pass sieve is based on the principle of high precision, followed by increased recall in each sieve. In this work, we examine the portability of the multi-pass sieve coreference resolution model to the Indonesian language. We conduct the experiment on 201 Wikipedia documents and the multi-pass sieve system yields 72.74{%} of MUC F-measure and 52.18{%} of BCUBED F-measure.} }

@article{lovenia2024seacrowd, title={SEACrowd: A Multilingual Multimodal Data Hub and Benchmark Suite for Southeast Asian Languages}, author={Holy Lovenia and Rahmad Mahendra and Salsabil Maulana Akbar and Lester James V. Miranda and Jennifer Santoso and Elyanah Aco and Akhdan Fadhilah and Jonibek Mansurov and Joseph Marvin Imperial and Onno P. Kampman and Joel Ruben Antony Moniz and Muhammad Ravi Shulthan Habibi and Frederikus Hudi and Railey Montalan and Ryan Ignatius and Joanito Agili Lopo and William Nixon and Börje F. Karlsson and James Jaya and Ryandito Diandaru and Yuze Gao and Patrick Amadeus and Bin Wang and Jan Christian Blaise Cruz and Chenxi Whitehouse and Ivan Halim Parmonangan and Maria Khelli and Wenyu Zhang and Lucky Susanto and Reynard Adha Ryanda and Sonny Lazuardi Hermawan and Dan John Velasco and Muhammad Dehan Al Kautsar and Willy Fitra Hendria and Yasmin Moslem and Noah Flynn and Muhammad Farid Adilazuarda and Haochen Li and Johanes Lee and R. Damanhuri and Shuo Sun and Muhammad Reza Qorib and Amirbek Djanibekov and Wei Qi Leong and Quyet V. Do and Niklas Muennighoff and Tanrada Pansuwan and Ilham Firdausi Putra and Yan Xu and Ngee Chia Tai and Ayu Purwarianti and Sebastian Ruder and William Tjhi and Peerat Limkonchotiwat and Alham Fikri Aji and Sedrick Keh and Genta Indra Winata and Ruochen Zhang and Fajri Koto and Zheng-Xin Yong and Samuel Cahyawijaya}, year={2024}, eprint={2406.10118}, journal={arXiv preprint arXiv: 2406.10118} }