Joint Modeling for Chinese Event Extraction with Rich Linguistic Features
نویسندگان
چکیده
Compared to the amount of research that has been done on English event extraction, there exists relatively little work on Chinese event extraction. We seek to push the frontiers of supervised Chinese event extraction research by proposing two extension to Li et al.'s (2012) state-of-the-art event extraction system. First, we employ a joint modeling approach to event extraction, aiming to address the error propagation problem inherent in Li et al.'s pipeline system architecture. Second, we investigate a variety of rich knowledge sources for Chinese event extraction that encode knowledge ranging from the character level to the discourse level. Experimental results on the ACE 2005 dataset show that our joint-modeling, knowledge-rich approach significantly outperforms Li et al.'s approach. Title and Abstract in Chinese 运用丰富语言学特征的中文事件抽取联合模型 文的事件抽取 中文的事件抽取 Li et al.(2012)的 学 的事件抽取 中文事件抽取的 用 联合模型 Li et al. 中的 中文 抽取 文 的特征 ACE2005 的 运用丰富语言学特征的联合模型 Li et al.的
منابع مشابه
Chinese Event Extraction Using DeepNeural Network with Word Embedding
A lot of prior work on event extraction has exploited a variety of features to represent events. Such methods have several drawbacks: 1) the features are often specific for a particular domain and do not generalize well; 2) the features are derived from various linguistic analyses and are error-prone; and 3) some features may be expensive and require domain expert. In this paper, we develop a C...
متن کاملJoint Modeling of Argument Identification and Role Determination in Chinese Event Extraction with Discourse-Level Information
Argument extraction is a challenging task in event extraction. However, most of previous studies focused on intra-sentence information and failed to extract inter-sentence arguments. This paper proposes a discourse-level joint model of argument identification and role determination to infer those inter-sentence arguments in a discourse. Moreover, to better represent the relationship among relev...
متن کاملEmploying Event Inference to Improve Semi-Supervised Chinese Event Extraction
Although semi-supervised model can extract the event mentions matching frequent event patterns, it suffers much from those event mentions, which match infrequent patterns or have no matching pattern. To solve this issue, this paper introduces various kinds of linguistic knowledge-driven event inference mechanisms to semi-supervised Chinese event extraction. These event inference mechanisms can ...
متن کاملMultivariate Frailty Modeling in Joint Analyzing of Recurrent Events with Terminal Event and its Application in Medical Data
Background and Objectives: In many medical situations, people can experience recurrent events with a terminal event. If the terminal event is considered a censor in this type of data, the assumption of independence in the analysis of survival data may be violated. This study was conducted to investigate joint modeling of frequent events and a final event (death) in breast cancer patients using ...
متن کاملJoint Event Extraction via Recurrent Neural Networks
Event extraction is a particularly challenging problem in information extraction. The stateof-the-art models for this problem have either applied convolutional neural networks in a pipelined framework (Chen et al., 2015) or followed the joint architecture via structured prediction with rich local and global features (Li et al., 2013). The former is able to learn hidden feature representations a...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2012