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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)
Web Person Disambiguation is often conducted through clustering web documents to identify different namesakes for a given name. This paper presents a new key-phrased clustering method combined with a second step re-classification to identify outliers to improve cluster performance. For document clustering, the hierarchical agglomerative approach is(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)
Event Mention detection is the first step in tex-tual 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)
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)
We describe CMU's UIMA-based modular automatic question answering (QA) system. This system answers multiple-choice 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)
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)
Coreference resolution is one of the first stages in deep language understanding and its importance has been well recognized in the natural language processing community. In this paper, we propose a generative, unsupervised ranking model for entity coreference resolution by introducing resolution mode variables. Our unsupervised system achieves 58.44% F1(More)
Learning to reason and understand the world's knowledge is a fundamental problem in Artificial Intelligence (AI). Traditional symbolic AI methods were popular in the 1980s, when first-order logic rules were mostly handwritten, and reasoning algorithms were built on top of them. In the 90s, more and more researchers became interested in statistical methods(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)