多标签传染病新闻事件语料库
包含多标签传染病新闻事件文本片段及标注，用于传染病事件检测与信息抽取。
基本信息
资源简介
多标签传染病新闻事件语料库
【数据内容】
源站原始描述：Multi-label Infectious Disease News Event Corpus. Contribute to jpiskorski/infectious-diseases-events development by creating an account on GitHub
【适用方向】
文本类数据可用于医学自然语言处理，如命名实体识别、信息抽取与文本分类。
【获取与许可】
源站页面：https://github.com/jpiskorski/infectious-diseases-events
下载信息
注册下载
需要注册 Kaggle 账号并登录后下载，适合需要跟踪下载记录和使用 API 的用户。
暂未开放公开下载
无需注册即可直接获取公开样本或文档，适合快速预览和评估数据集质量。
免登录有偿下载
公开数据集受托下载与技术交付服务。
提供高速下载与技术交付服务（收技术服务费，非数据销售）
暂未开放当前数据集主要来源为 Kaggle 公开托管，完整影像包建议通过原始链接或 Kaggle API 获取。
使用方式
数据集获取
git clone https://github.com/jpiskorski/infectious-diseases-events.git
curl -L -o repo.zip https://github.com/jpiskorski/infectious-diseases-events/archive/refs/heads/main.zip
unzip repo.zip
源站 README 摘录（使用方式）
[AVAILABLE from 2 APRIL 2023]
This repository contains the Multi-label Infectious Disease News Event Corpus
mentioned in the following paper:
Multi-label Infectious Disease News Event Corpus.
Jakub Piskorski, Nicolas Stefanovitch, Brian Doherty, Jens P. Linge,
Sopho Kharazi, Jas Mantero, Guillaume Jacquet, Alessio Spadaro and Giulia Teodori.
In Proceedings of Text2Story 2023: Sixth International Workshop on Narrative Extraction
from Texts held in conjunction with the 45th European Conference on Information Retrieval,
Dublin, Ireland, 2023.
Please cite using this reference: https://github.com/jpiskorski/infectious-diseases-events/blob/main/reference.bib
The archive contains three files:
- infectious_diseases_finegrained_grained.txt
The text snippets labelled with fine-grained event types.
The text snippets and the labels are separated by tabs. - infectious_diseases_coarse_grained.txt
The text snippets labelled with coarse-grained event types.
The text snippets and the labels are separated by tabs. - Annotation_guidelines.pdf
The draft version of the annotation guidelines used by the annotators. A new complete version will be released soon.
NOTE: new updated version 1.1 available since 25 May 2023 (small fixes related to inconsistent labels and removing some redundant entries)
数据加载示例（表格/文本类）
import pandas as pd, glob, os
files = (glob.glob(os.path.join(path, "**", "*.csv"), recursive=True)
+ glob.glob(os.path.join(path, "**", "*.tsv"), recursive=True)
+ glob.glob(os.path.join(path, "**", "*.xlsx"), recursive=True))
print("数据文件:", files)
df = pd.read_csv(files[0])
print(df.shape); print(df.columns.tolist()); print(df.head(3))
数据缺失？
依托陕西、四川两大基地，我们与超过十家三甲医院建立直接合作关系，覆盖合规授权、采集治理、专业标注、数据交付的全流程，为AI医疗团队提供即拿即用的高质量临床数据。
⚡️ 需要数据支持或标注服务？立即联系我们获取专业方案。
