Zhengzhong Liu

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Combining deep neural networks with structured logic rules is desirable to harness flexibility and reduce unpredictability of the neural models. We propose a general framework capable of enhancing various types of neural networks (e.g., CNNs and RNNs) with declarative first-order logic rules. Specifically, we develop an iterative distillation method that(More)
In the task of event coreference resolution, recent work has shown the need to perform not only full coreference but also partial coreference of events. We show that subevents can form a particular hierarchical event structure. This paper examines a novel two-stage approach to finding and improving subevent structures. First, we introduce a multiclass(More)
Event coreference is an important task for full text analysis. However, previous work uses a variety of approaches, sources and evaluation, making the literature confusing and the results incommensurate. We provide a description of the differences to facilitate future research. Second, we present a supervised method for event coreference resolution that(More)
Searching for named entities is a common task on the web. Among different named entities, person names are among the most frequently searched terms. However, many people can share the same name and the current search engines are not designed to identify a specific entity, or a namesake. One possible solution is to identify a namesake through clustering(More)
Verb Phrase Ellipsis is a well-studied topic in theoretical linguistics but has received little attention as a computational problem. Here we propose a decomposition of the overall resolution problem into three tasks—target detection, antecedent head resolution, and antecedent boundary detection—and implement a number of computational approaches for each(More)
Event Mention detection is the first step in textual event understanding. Proper evaluation is important for modern natural language processing tasks. In this paper, we present our evaluation algorithm and results during the Event Mention Evaluation pilot study. We analyze the problems of evaluating multiple event mention attributes and discontinuous event(More)
We describe CMU’s UIMA-based modular automatic question answering (QA) system. This system answers multiplechoice English questions for the world history entrance exam. Questions are preceded by short descriptions providing a historical context. Given the context and question-specific instructions, we generate verifiable assertions for each answer choice.(More)
This paper presents the work of the Hong Kong Polytechnic University (PolyUCOMP) team which has participated in the Semantic Textual Similarity task of SemEval-2012. The PolyUCOMP system combines semantic vectors with skip bigrams to determine sentence similarity. The semantic vector is used to compute similarities between sentence pairs using the lexical(More)
Web Person Disambiguation (WPD) is often done through clustering of web documents to identify the different namesakes for a given name. This paper presents a clustering algorithm using key phrases as the basic feature. However, key phrases are used in two different forms to represent the document as well context information surround the name mentions in a(More)