Workshop on Animacy and Information Status Annotation

众所周知，为了有效地沟通，仅用符合语法的句子是不够的。需要从听者知道或感兴趣的内容开始，从中获得想要传达的新信息。作为一个纯粹的研究课题，了解人类说话者如何做到这一点很重要，但它也具有非常重要的实际意义：使人类和机器能够以自然语言进行交流将有助于完成各种信息传输任务，包括辅导、搜索和翻译。为了在目前正在进行的语言研究之外取得进展，需要一个统一的、普遍接受的编码系统来处理影响这部分语言理解的现象。在计算语言学中，标记文本和注释语料库的统一标准越来越被认为是进步的关键；它们使研究人员能够确保他们应用类别的方式是一致的。它们还允许使用机器学习方法来帮助研究人员获得新的见解并更有效地分析更多文本。这个研讨会项目重点关注这个编码问题的两个方面，即理解“话语状态”（所提到的所指对象对于话语来说是新的还是已经熟悉的？）和“生命力”（例如所指对象是人类、机器、昆虫还是建筑物？）的概念。该研讨会汇集了语言学家和计算机科学家，其目标是为这两个重要类别的语言内容创建黄金标准编码程序。然后，研究结果将通过与关键计算机科学工作组有联系的几个大型语言注释项目的支持进行传播。

It is well known that in order to communicate effectively, it is not enough to speak in grammatical sentences. One needs to start from what the hearer knows or is interested in and get from there to the new information that one wants to convey. Understanding how human speakers do this is important as a pure research topic but it is also of great practical importance: enabling humans and machines to communicate in natural language will help with a variety of information transfer tasks, including tutoring, search, and translation. To make headway beyond the linguistic studies that are currently underway, a unified, universally accepted coding system for the phenomena that influence this part of language understanding is needed. In computational linguistics, uniform standards for marking text and annotating corpora are increasingly recognized as the key to progress; they allow researchers to make sure that they are consistent in the way they apply categories. They also allow the use of machine learning methods to help researchers to gain new insights and to analyze more texts more efficiently.This workshop project focuses on two aspects of this coding problem, an understanding of the notions of 'discourse status' (is the referent being mentioned new to the discourse or already familiar?) and of 'animacy' (e.g. is the referent a human, a machine, an insect, a building?). The workshop brings together linguists and computer scientists with the goal of creating a gold standard coding procedure for these two important categories of linguistic content. The findings will then be disseminated through the auspices of several large linguistic annotation projects that have ties to key computer science working groups.