conll2003

The shared task of CoNLL-2003 concerns language-independent named entity recognition. We will concentrate on
four types of named entities: persons, locations, organizations and names of miscellaneous entities that do
not belong to the previous three groups.

The CoNLL-2003 shared task data files contain four columns separated by a single space. Each word has been put on
a separate line and there is an empty line after each sentence. The first item on each line is a word, the second
a part-of-speech (POS) tag, the third a syntactic chunk tag and the fourth the named entity tag. The chunk tags
and the named entity tags have the format I-TYPE which means that the word is inside a phrase of type TYPE. Only
if two phrases of the same type immediately follow each other, the first word of the second phrase will have tag
B-TYPE to show that it starts a new phrase. A word with tag O is not part of a phrase. Note the dataset uses IOB2
tagging scheme, whereas the original dataset uses IOB1.

For more details see https://www.clips.uantwerpen.be/conll2003/ner/ and https://www.aclweb.org/anthology/W03-0419

CoNLL-2003联合任务的共同目标是关注与语言无关的命名实体识别。本任务将专注于四种类型的命名实体：人物、地点、组织以及不属于前三种类型的其他实体的名称。CoNLL-2003联合任务的数据文件包含四列，由单个空格分隔。每个单词单独占据一行，并且每句话之后都有一个空行。每行的第一个项目是单词，第二个是词性（POS）标签，第三个是句法块标签，第四个是命名实体标签。块标签和命名实体标签的格式为I-TYPE，这意味着单词位于类型为TYPE的短语之内。只有当两个相同类型的短语紧挨着时，第二个短语的首个单词将具有B-TYPE标签，以表明它标志着新短语的开始。标签为O的单词不属于任何短语。请注意，该数据集使用IOB2标签方案，而原始数据集使用IOB1方案。有关更详细信息，请参阅https://www.clips.uantwerpen.be/conll2003/ner/和https://www.aclweb.org/anthology/W03-0419。

搜集汇总

背景与挑战

背景概述

conll2003数据集是一个用于命名实体识别任务的数据集，包含四种类型的命名实体标注，采用IOB2标记方案，适用于训练和评估NER模型。