Articles

Most current statistical natural language process- ing models use only local features so as to permit dynamic programming in inference, but this makes them unable to fully account for the long distance structure that is prevalent in language use. We show how to solve this dilemma with Gibbs sam- pling, …...

Conditional random fields (Lafferty et al., 2001) are quite effective at sequence labeling tasks like shal- low parsing (Sha and Pereira, 2003) and named- entity extraction (McCallum and Li, 2003). CRFs are log-linear, allowing the incorporation of arbi- trary features into the model. To train on unlabeled data, we require …...

Stochastic Optimality Theory (Boersma, 1997) is a widely-used model in linguis- tics that did not have a theoretically sound learning method previously. In this pa- per, a Markov chain Monte-Carlo method is proposed for learning Stochastic OT Grammars. Following a Bayesian frame- work, the goal is finding the posterior dis- …...

In this paper we present a quantitative and qualitative analysis of annotation in the Hinoki treebank of Japanese, and in- vestigate a method of speeding annotation by using part-of-speech tags. The Hinoki treebank is a Redwoods-style treebank of Japanese dictionary definition sentences. 5,000 sentences are annotated by three dif- ferent …...

This paper presents the first probabilistic parsing results for French, using the re- cently released French Treebank. We start with an unlexicalized PCFG as a base- line model, which is enriched to the level of Collins’ Model 2 by adding lexical- ization and subcategorization. The lexi- calized sister-head model and …...

Consistency of corpus annotation is an essential property for the many uses of annotated corpora in computational and theoretical linguistics. While some re- search addresses the detection of inconsis- tencies in positional annotation (e.g., part- of-speech) and continuous structural an- notation (e.g., syntactic constituency), no approach has yet been developed …...

In this paper, we present an unlexical- ized parser for German which employs smoothing and suffix analysis to achieve a labelled bracket F-score of 76.2, higher than previously reported results on the NEGRA corpus. In addition to the high accuracy of the model, the use of smooth- ing in an …...

This paper describes a summarization system for technical chats and emails on the Linux kernel. To reflect the complex- ity and sophistication of the discussions, they are clustered according to subtopic structure on the sub-message level, and immediate responding pairs are identified through machine learning methods. A re- sulting summary …...

This paper presents a probabilistic framework, QARLA, for the evaluation of text summarisation systems. The in- put of the framework is a set of man- ual (reference) summaries, a set of base- line (automatic) summaries and a set of similarity metrics between summaries. It provides i) a measure to evaluate …...

We describe a novel approach to statistical machine translation that combines syntactic information in the source language with recent advances in phrasal translation. This method requires a source-language dependency parser, target language word segmentation and an unsupervised word alignment component. We align a parallel corpus, project the source dependency parse …...

We present a statistical phrase-based transla- tion model that uses hierarchical phrases— phrases that contain subphrases. The model is formally a synchronous context-free gram- mar but is learned from a bitext without any syntactic information. Thus it can be seen as a shift to the formal machinery of syntax- based …...

In this paper we describe a novel data structure for phrase-based statistical ma- chine translation which allows for the re- trieval of arbitrarily long phrases while si- multaneously using less memory than is required by current decoder implementa- tions. We detail the computational com- plexity and average retrieval times for …...

Non-sentential utterances (e.g., short- answers as in “Who came to the party?”— “Peter.”) are pervasive in dialogue. As with other forms of ellipsis, the elided ma- terial is typically present in the context (e.g., the question that a short answer an- swers). We present a machine learning approach to the …...

Clarification requests (CRs) in conversa- tion ensure and maintain mutual under- standing and thus play a crucial role in robust dialogue interaction. In this pa- per, we describe a corpus study of CRs in task-oriented dialogue and compare our findings to those reported in two prior studies. We find that …...

Sitting at the intersection between statis- tics and machine learning, Dynamic Bayesian Networks have been applied with much success in many domains, such as speech recognition, vision, and compu- tational biology. While Natural Language Processing increasingly relies on statisti- cal methods, we think they have yet to use Graphical Models …...

In Statistics-Based Summarization - Step One: Sentence Compression, Knight and Marcu (Knight and Marcu, 2000) (K&M) present a noisy-channel model for sen- tence compression. The main difficulty in using this method is the lack of data; Knight and Marcu use a corpus of 1035 training sentences. More data is not …...

The paper considers how to scale up dialogue protocols to multilogue, settings with multiple conversationalists. We extract two benchmarks to evaluate scaled up protocols based on the long distance resolution possibilities of non- sentential utterances in dialogue and multi- logue in the British National Corpus. In light of these benchmarks, …...

This paper regards Question Answering (QA) as Question-Biased Term Extraction (QBTE). This new QBTE approach lib- erates QA systems from the heavy bur- den imposed by question types (or answer types). In conventional approaches, a QA system analyzes a given question and de- termines the question type, and then it …...

This paper presents a corpus study that ex- plores the extent to which captions con- tribute to recognizing the intended mes- sage of an information graphic. It then presents an implemented graphic interpre- tation system that takes into account a va- riety of communicative signals, and an evaluation study showing …...

This paper describes a novel framework for interactive question-answering (Q/A) based on predictive questioning. Gen- erated off-line from topic representations of complex scenarios, predictive ques- tions represent requests for information that capture the most salient (and diverse) aspects of a topic. We present experimen- tal results from large user studies …...