Articles

We introduce alignment models for Machine Trans- lation that take into account the context of a source word when determining its translation. Since the use of these contexts alone causes data sparsity prob- lems, we develop a decision tree algorithm for clus- tering the contexts based on optimisation of the …...

Nominals frequently surface without overtly expressed arguments. In order to measure the potential benefit of nominal SRL for down- stream processes, such nominals must be ac- counted for. In this paper, we show that a state-of-the-art nominal SRL system with an overall argument F1 of 0.76 suffers a perfor- mance …...

Recent applications of Tree-Adjoining Gram- mar (TAG) to the domain of semantics as well as new attention to syntactic phenomena have given rise to increased interested in more ex- pressive and complex multicomponent TAG formalisms (MCTAG). Although many con- structions can be modeled using tree-local MCTAG (TL-MCTAG), certain applications require …...

Unsupervised grammar induction models tend to employ relatively simple models of syntax when compared to their supervised counter- parts. Traditionally, the unsupervised mod- els have been kept simple due to tractabil- ity and data sparsity concerns. In this paper, we introduce basic valence frames and lexi- cal information into an …...

We investigate the problem of unsupervised part-of-speech tagging when raw parallel data is available in a large number of languages. Patterns of ambiguity vary greatly across lan- guages and therefore even unannotated multi- lingual data can serve as a learning signal. We propose a non-parametric Bayesian model that connects related …...

We present a family of priors over probabilis- tic grammar weights, called the shared logistic normal distribution. This family extends the partitioned logistic normal distribution, en- abling factored covariance between the prob- abilities of different derivation events in the probabilistic grammar, providing a new way to encode prior knowledge about …...

We present an unsupervised approach to re- constructing ancient word forms. The present work addresses three limitations of previous work. First, previous work focused on faith- fulness features, which model changes be- tween successive languages. We add marked- ness features, which model well-formedness within each language. Second, we introduce universal …...

Conventional approaches to Chinese word segmentation treat the problem as a character- based tagging task. Recently, semi-Markov models have been applied to the problem, in- corporating features based on complete words. In this paper, we propose an alternative, a latent variable model, which uses hybrid in- formation based on both …...

We present a method for performing machine transliteration without any parallel resources. We frame the transliteration task as a deci- pherment problem and show that it is possi- ble to learn cross-language phoneme mapping tables using only monolingual resources. We compare various methods and evaluate their accuracies on a standard …...

Word sense disambiguation is the process of determining which sense of a word is used in a given context. Due to its importance in understanding semantics of natural languages, word sense disambiguation has been exten- sively studied in Computational Linguistics. However, existing methods either are brit- tle and narrowly focus …...

This paper presents and compares WordNet- based and distributional similarity approaches. The strengths and weaknesses of each ap- proach regarding similarity and relatedness tasks are discussed, and a combination is pre- sented. Each of our methods independently provide the best results in their class on the RG and WordSim353 datasets, …...

We supplement WordNet entries with infor- mation on the subjectivity of its word senses. Supervised classifiers that operate on word sense definitions in the same way that text classifiers operate on web or newspaper texts need large amounts of training data. The re- sulting data sparseness problem is aggravated by …...

This paper introduces an integrative approach to automatic word sense subjectivity annota- tion. We use features that exploit the hier- archical structure and domain information in lexical resources such as WordNet, as well as other types of features that measure the sim- ilarity of glosses and the overlap among sets …...

In this paper we explore a learning-based ap- proach to the problem of predicting language impairment in children. We analyzed sponta- neous narratives of children and extracted fea- tures measuring different aspects of language including morphology, speech fluency, lan- guage productivity and vocabulary. Then, we evaluated a learning-based approach and …...

Knowledge-based parsers are now accu- rate, fast and robust enough to be used to obtain syntactic annotations for very large corpora fully automatically. We argue that such parsed corpora are an interesting new resource for linguists. The argument is illustrated by means of a number of re- cent results which …...

In this position paper, I argue that in order to create truly language-independent NLP systems, we need to incorporate linguis- tic knowledge. The linguistic knowledge in question is not intricate rule systems, but generalizations from linguistic typol- ogy about the range of variation in linguis- tic structures across languages. 1...

As my title suggests, this position paper focuses on the relevance of linguistics in NLP instead of asking the inverse question. Although the ques- tion about the role of computational linguistics in the study of language may theoretically be much more interesting than the selected topic, I feel that my …...

It is remarkable if any relationship at all persists between computational linguists (CL) and that part of general linguis- tics comprising the mainstream of MIT transformational-generative (TG) theoreti- cal syntax. If the lines are still open, it rep- resents something of a tribute to CL prac- titioners’ tolerance — a …...

This paper discusses some of the ways that the “statistical revolution” has changed and continues to change the relationship between linguistics and computational lin- guistics. I claim that it is more useful in parsing to make an open world assumption about possible linguistic structures, rather than the closed world assumption …...

Without lengthy, iterative refinement of guidelines, and equally lengthy and itera- tive training of annotators, the level of in- ter-subjective agreement on simple tasks of phonetic, phonological, syntactic, se- mantic, and pragmatic annotation is shockingly low. This is a significant practical problem in speech and language technology, but it poses …...