Combining Compositional Semantics Modules

在高度移动的人群中，疫苗接种厌恶是一个日益严重的威胁，2008年圣地亚哥的麻疹病例就证明了这一点（http：//www.cdc.gov/mmwr/preview/mmwrhtml/mm5708a3.htm）。可避免的疾病爆发的社会和经济成本非常高，目前正在研究改善依从性的方法，包括由CIHR资助的McGill项目，该项目研究博客中避免接种疫苗的原因，以通过信息宣传活动（Vaccine Sentiment Ontology www.example.com theme = 3）. **这只是使用互联网或社交媒体上免费提供的文本解决的许多重要问题之一。文本处理是一个指数级增长的领域，许多人加入其中，但并不是所有人都配备了必要的工具。任何人都可以处理文本：如果你不小心删除了一半的文本，你已经处理了它。如果，偶然的机会，这剩下的一半有所需的信息，你已经成功地总结了。但是，如果要开发通用的文本处理管道，这些管道可以在各种未经过训练的文本上正常工作，则需要语言复杂性，这通常会导致高度复杂的处理环境。因为探索和发现的标志是以新的方式查看比以前更多的文档，我们正在研究这样的处理管道，并希望加强其鲁棒性和性能，使其成为一个轻量级的，可重新配置的开源基线文本分析工具包，可以由本身没有这种语言洞察力的应用程序构建者利用。我们的努力加入了越来越多的开源模块，我们设计了与各种已经发布的模块的互操作性，而不是提出我们自己的单片处理环境。

Vaccination aversion is a growing threat in highly mobile populations as a case of measles in San Diego in 2008 demonstrates (http://www.cdc.gov/mmwr/preview/mmwrhtml/mm5708a3.htm). The social and economic cost of avoidable outbreaks is very high and means to improve compliance are under current investigation, including a CIHR-funded project at McGill which studies reasons for vaccine avoidance in blogs in an effort to counteract them through information campaigns (Vaccine Sentiment Ontology http://surveillance.mcgill.ca/projects_theme.php?theme=3).**This is only one of the many important issues addressed using text freely available on the internet or on social media. Text processing is an exponential growth area and many join in, not all equipped with essential tools. Anybody can process text: if you accidentally delete half the text, you have processed it. If, per chance, this remaining half has desired information in it, you have summarized successfully. But linguistic sophistication is required if one is to develop general text processing pipelines that work predictably well on a wide variety of texts not trained on, usually leading to highly complex processing environments. Because new ways of looking at more documents than before is the hallmark of exploration and discovery, we are working on just such processing pipelines and hope to strengthen their robustness and their performance into a light-weight, reconfigurable open-source kit of baseline text analysis, that can be harnessed by application builders who do not themselves have this degree of linguistic insight. Our efforts join a growing number of open source modules and we design for interoperability with a variety of already released modules, rather than proposing our own monolithic processing environment.