Articles

AbstractA statistical machine translation (SMT) system requires homogeneous training data in order to get domain-sensitive (or context-sensitive) terminology translations. If the data contains various domains, it is difficult for an SMT to learn context-sensitive terminology mappings probabilistically. Yet, terminology translation accuracy is an important issue for MT users. This paper …...

AbstractWe report on an on-going research project aimed at increasing the range of translation equivalents which can be automatically discovered by MT systems. The methodology is based on semi-supervised learning of indirect translation strategies from large comparable corpora and applying them in run-time to generate novel, previously unseen translation equivalents. …...

AbstractWe describe a set of experiments to explore statistical techniques for ranking and selecting the best translations in a graph of translation hypotheses. In a previous paper (Carl, 2007) we have described how the graph of hypotheses is generated through shallow transfer and chunk permutation rules, where nodes consist of …...

AbstractMany applications of computational linguistics are greatly influenced by the quality of corpora available and as automatically generated corpora continue to play an increasingly common role, it is essential that we not overlook the importance of well-constructed and homogeneous corpora. This paper describes an automatic approach to improving the homogeneity …...

AbstractPattern matching, or querying, over annotations is a general purpose paradigm for inspecting, navigating, mining, and transforming annotation repositories - the common representation basis for modern pipelined text-processing frameworks. Configurability of such frameworks and expressiveness of feature structure-based annotation schemes account for the “high density” of some such annotation repositories. …...

AbstractThe number and sizes of parallel corpora keep growing, which makes it necessary to have automatic methods of processing them: combining, checking and improving corpora quality, etc. We here introduce a method which enables performing many of these by exploiting overlapping parallel corpora. The method finds the correspondence between sentence …...

AbstractWe describe the creation of a corpus that supports a real-world hierarchical text categorization task in the domain of electronic rulemaking (eRulemaking). Features of the task and of the eRulemaking domain engender both a non-traditional text categorization corpus and a correspondingly difficult machine learning task. Interannotator agreement results are presented …...

AbstractWe propose a set of heuristics for improving annotation quality of very large corpora efficiently. The Xinhua News portion of the Chinese Gigaword Corpus was tagged independently with both the Peking University ICL tagset and the Academia Sinica CKIP tagset. The corpus-based POS tags mapping will serve as the basis …...

AbstractTo answer the critical need for sharable, reusable annotated resources with rich linguistic annotations, we are developing a Manually Annotated Sub-Corpus (MASC) including texts from diverse genres and manual annotations or manually-validated annotations for multiple levels, including WordNet senses and FrameNet frames and frame elements, both of which have become …...

AbstractThe original Mixer corpus was designed to satisfy developing commercial and forensic needs. The resulting Mixer corpora, Phases 1 through 5, have evolved to support and increasing variety of research tasks, including multilingual and cross-channel recognition. The Mixer Phases 4 and 5 corpora feature a wider variety of channels and …...

AbstractRecent years have seen increased interest within the speaker recognition community in high-level features including, for example, lexical choice, idiomatic expressions or syntactic structures. The promise of speaker recognition in forensic applications drives development toward systems robust to channel differences by selecting features inherently robust to channel difference. Within the …...

This paper presents a method of acquiring knowledge from the Web for noun sense disambiguation. Words, called selectors, are acquired which take the place of an instance of a target word in its local con- text. The selectors serve for the system to essentially learn the areas or concepts of …...

This paper presents our system for the Open Track of the CoNLL 2008 Shared Task (Surdeanu et al., 2008) in Joint De- pendency Parsing1 and Semantic Role La- belling. We use Markov Logic to define a joint SRL model and achieve a semantic F-score of 74.59%, the second best in …...

. In this paper, we propose a new metho- dology based on directed graphs and the TextRank algorithm to automatically in- duce general-specific noun relations from web corpora frequency counts. Different asymmetric association measures are im- plemented to build the graphs upon which the TextRank algorithm is applied and produces …...

We present an incremental Bayesian model for the unsupervised learning of syntactic cate- gories from raw text. The model draws infor- mation from the distributional cues of words within an utterance, while explicitly bootstrap- ping its development on its own partially- learned knowledge of syntactic categories. Testing our model on …...

A fundamental task in sentence compre- hension is to assign semantic roles to sen- tence constituents. The structure-mapping account proposes that children start with a shallow structural analysis of sentences: children treat the number of nouns in the sentence as a cue to its semantic predicate- argument structure, and represent …...

This paper presents an iterative model of knowledge acquisition of gender infor- mation associated with word endings in French. Gender knowledge is represented as a set of rules containing exceptions. Our model takes noun-gender pairs as in- put and constantly maintains a list of rules and exceptions which is both …...

The most accurate unsupervised word seg- mentation systems that are currently avail- able (Brent, 1999; Venkataraman, 2001; Goldwater, 2007) use a simple unigram model of phonotactics. While this sim- plifies some of the calculations, it over- looks cues that infant language acquisition researchers have shown to be useful for segmentation …...

This paper investigates, in a first stage, some methods for the automatic acquisi- tion of verb-particle constructions (VPCs) taking into account their statistical prop- erties and some regular patterns found in productive combinations of verbs and par- ticles. Given the limited coverage pro- vided by lexical resources, such as dictio- …...

Detecting the semantic coherence of a doc- ument is a challenging task and has sev- eral applications such as in text segmenta- tion and categorization. This paper is an attempt to distinguish between a ‘semanti- cally coherent’ true document and a ‘ran- domly generated’ false document through topic detection in …...