The ConceptMapper Approach to Named Entity Recognition
The ConceptMapper Approach to Named Entity Recognition
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发表时间：
2010-05
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通讯作者：
M. Tanenblatt;A. Coden;I. Sominsky
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作者：
M. Tanenblatt;A. Coden;I. Sominsky
ConceptMapper是我们创建的一个开源工具，用于根据概念术语（字典）对非结构化文本文档中的提及进行分类，并将命名实体作为输出。它作为UIMA实现（非结构化信息管理体系结构）注释器，并且高度可配置：概念可以来自标准化或专有术语;任意属性可以与字典条目相关联，并且这些属性可以与输出中的命名实体相关联;可以指定许多搜索策略和搜索选项;任何打包为UIMA注释器的标记器都可以用于标记字典，因此可以保证输入和字典具有相同的标记化，从而最小化标记化不匹配错误;并且还可以控制用作输入和生成为输出的UIMA注释的类型和特征。我们描述了ConceptMapper及其配置参数和它们的权衡，然后描述了实验的结果，其中一些参数是不同的，精度和召回率随后测量的任务，在确定概念的收集英语临床报告（结肠癌病理学）。ConceptMapper可从Apache UIMA Sandbox获得，受Apache开源许可证保护。
ConceptMapper is an open source tool we created for classifying mentions in an unstructured text document based on concept terminologies (dictionaries) and yielding named entities as output. It is implemented as a UIMA (Unstructured Information Management Architecture) annotator and is highly configurable: concepts can come from standardised or proprietary terminologies; arbitrary attributes can be associated with dictionary entries, and those attributes can then be associated with the named entities in the output; numerous search strategies and search options can be specified; any tokenizer packaged as a UIMA annotator can be used to tokenize the dictionary, so the same tokenization can be guaranteed for the input and dictionary, minimising tokenization mismatch errors; and the types and features of UIMA annotations used as input and generated as output can also be controlled. We describe ConceptMapper and its configuration parameters and their trade-offs, then describe the results of an experiment wherein some of these parameters are varied and precision and recall are subsequently measured in the task of in identifying concepts in a collection English-language clinical reports (colon cancer pathology). ConceptMapper is available from the Apache UIMA Sandbox, covered by the Apache Open Source license.