Articles

Definition questions represent a largely unex- plored area of question answering—they are different from factoid questions in that the goal is to return as many relevant “nuggets” of information about a concept as possible. We describe a multi-strategy approach to an- swering such questions using a database con- structed offline …...

One of the first steps towards understanding natural multimodal language is aligning ges- ture and speech, so that the appropriate ges- tures ground referential pronouns in the speech. This paper presents a novel technique for gesture-speech alignment, inspired by salience- based approaches to anaphoric pronoun reso- lution. We use a …...

Moderate-sized rule-based spoken language models for recognition and understanding are easy to develop and provide the ability to rapidly prototype conversational applications. However, scalability of such systems is a bot- tleneck due to the heavy cost of authoring and maintenance of rule sets and inevitable brittle- ness due to lack …...

This paper reports some experiments that com- pare the accuracy and performance of two stochastic parsing systems. The currently pop- ular Collins parser is a shallow parser whose output contains more detailed semantically- relevant information than other such parsers. The XLE parser is a deep-parsing system that couples a Lexical …...

A given entity, representing a person, a location or an organization, may be mentioned in text in multiple, ambiguous ways. Understanding natural language requires identifying whether different mentions of a name, within and across documents, represent the same entity. We develop an unsupervised learning approach that is shown to resolve …...

In this paper, we will compare and evaluate the effectiveness of different statistical methods in the task of cross-document coreference resolution. We created entity models for different test sets and compare the following disambiguation and clustering techniques to cluster the entity models in order to create coreference chains: Incremental Vector …...

Entity detection and tracking is a relatively new addition to the repertoire of natural language tasks. In this paper, we present a statistical language-independent framework for identify- ing and tracking named, nominal and pronom- inal references to entities within unrestricted text documents, and chaining them into clusters corresponding to each …...

We present a technique for augmenting annotated training data with hierarchical word clusters that are automatically derived from a large unannotated corpus. Cluster membership is encoded in features that are incorporated in a discriminatively trained tagging model. Active learning is used to select training examples. We evaluate the technique for …...

With the increasing use of research paper search engines, such as CiteSeer, for both lit- erature search and hiring decisions, the accu- racy of such systems is of paramount impor- tance. This paper employs Conditional Ran- dom Fields (CRFs) for the task of extracting various common fields from the headers …...

Systems that automatically discover semantic classes have emerged in part to address the limitations of broad-coverage lexical re- sources such as WordNet and Cyc. The cur- rent state of the art discovers many semantic classes but fails to label their concepts. We propose an algorithm labeling semantic classes and for …...

Maximum entropy models are a common mod- eling technique, but prone to overfitting. We show that using an exponential distribution as a prior leads to bounded absolute discounting by a constant. We show that this prior is better motivated by the data than previous techniques such as a Gaussian prior, …...

We present a coreference resolver called BABAR that uses contextual role knowledge to evaluate possible antecedents for an anaphor. BABAR uses information extraction patterns to identify contextual roles and creates four contextual role knowledge sources using unsu- pervised learning. These knowledge sources determine whether the contexts surrounding an anaphor and …...

State-of-the-art pronoun interpretation sys- tems rely predominantly on morphosyntac- tic contextual features. While the use of deep knowledge and inference to improve these models would appear technically in- feasible, previous work has suggested that predicate-argument statistics mined from naturally-occurring data could provide a useful approximation to such knowledge. We test …...

This paper reveals some important properties of CFSs and applications in Chinese natural language processing (NLP). We have previously proposed a method for extracting Chinese frequent strings that contain unknown words from a Chinese corpus [Lin and Yu 2001]. We found that CFSs contain many 4-character strings, 3-word strings, and …...

In order to achieve fast, high quality Part-of-speech (pos) tagging, algorithms should achieve high accuracy and require less manually proofreading. This study aimed to achieve these goals by defining a new criterion of tagging reliability, the estimated final accuracy of the tagging under a fixed amount of proofreading, to be …...

This article studies different aspects of a new approach for word sense disambiguation using statistical information gains from a target language monolingual corpus. Here, the source language is English and the target one is Persian, and this disambiguation method in those aspects which gives desirable results can be directly applied …...

. We describe a Machine Translation (MT) approach that is specifically designed to enable rapid development of MT for languages with limited amounts of online resources. Our approach assumes the availability of a small number of bi-lingual speakers of the two languages, but these need not be linguistic experts. The …...

. How can recent advances in automating the evaluation of machine translation (MT) engines be applied to automate the evaluation of more complex embedded MT systems? In this paper, we describe initial evaluation testing of FALCon, an embedded MT system where hard-copy documents are scanned into bit-mapped images, converted into …...

. . The paper proposes a model for translation between syntactically similar languages of acceding countries. This model is based on the presupposition that the translation of related languages should exploit the relatedness by using as simple methods and tools as possible. In the first part the paper discusses the …...

This paper introduces a new approach to translation memories. The proposed translation technology uses linguistic analysis (morphology and parsing) to determine similarity between two source-language segments, and attempts to assemble a sensible transltion using translations of source-language chunks if the entire source segment was not found. This is achieved by …...