Articles

We present a new method for directly working with typed unification grammars in which type unification is not well-defined. This is often the case, as large-scale HPSG grammars now usually have type systems for which many pairs do not have least upper bounds. Our method yields a unification algorithm that …...

The standard training regime for transition-based dependency parsers makes use of an oracle, which predicts an optimal transition sequence for a sentence and its gold tree. We present an improved oracle for the arc-eager transition system, which provides a set of optimal transitions for every valid parser configuration, including configurations …...

We present a novel approach for jointly disambiguating and clustering known and unknown concepts and entities with Markov Logic. Concept and entity disambiguation is the task of identifying the correct concept or entity in a knowledge base for a single- or multi-word noun (mention) given its context. Concept and entity …...

While there have been many studies on measuring the size of learners’ vocabulary or the vocabulary they should learn, there have been few studies on what kind of words learners actually know. Therefore, we investigated theoretically and practically important models for predicting second language learners’ vocabulary and propose another model …...

In this paper, we propose a time-line based framework for topic summarization in Twitter. We summarize topics by sub-topics along time line to fully capture rapid topic evolution in Twitter. Specifically, we rank and select salient and diversified tweets as a summary of each sub-topic. We have observed that ranking …...

We present a simple and straightforward alignment algorithm for monotone many-to-many alignments in grapheme-to-phoneme conversion and related fields such as morphology, and discuss a few noteworthy extensions. Moreover, we specify combinatorial formulas for monotone many-to-many alignments and decoding in G2P which indicate that exhaustive enumeration is generally possible, so that …...

Semantic query sub-network is the representation of a natural language query as a graph of semantically connected words. Such sub-networks can be identified as sub-graphs in larger ontologies like DBpedia or Google knowledge graph, which allows for domain and concepts identification, especially in noisy queries. In this paper, we present …...

Information structure, i.e the way speakers construct sentences to present new information in the context of old, can capture rich linguistic information about the discourse structure of scientific documents. Information structure has been found useful for important Natural Language Processing (NLP) tasks, such as information retrieval and extraction. Since scientific …...

Named entity recognition (NER) has been extensively studied for the names of genes and gene products but there are few proposed solutions for phenotypes. Phenotype terms are expected to play a key role in inferring gene function in complex heritable diseases but are intrinsi- cally difficult to analyse due to …...

In the biomedical field, the key to access information is the use of specialized terms. However, in most of Indo-European languages, these terms are complex morphological structures. The aim of the presented work is to identify the various meaningful components of these terms and use this analysis to improve biomedical …...

Many evaluation issues for grammatical error detection have previously been overlooked, making it hard to draw meaningful comparisons between different approaches, even when they are evaluated on the same corpus. To begin with, the three-way contingency between a writer’s sentence, the annotator’s correction, and the system’s output makes evaluation more …...

Integration of domain specific knowledge into a general purpose statistical machine translation (SMT) system poses challenges due to insufficient bilingual corpora. In this paper we propose a simplification-translation-restoration (STR) framework for domain adaptation in SMT by simplifying domain specific segments of a text. For an in-domain text, we identify the …...

Compared to the amount of research that has been done on English event extraction, there exists relatively little work on Chinese event extraction. We seek to push the frontiers of supervised Chinese event extraction research by proposing two extension to Li et al.'s (2012) state-of-the-art event extraction system. First, we …...

Linguistic steganography is a form of covert communication using natural language to conceal the existence of the hidden message, which is usually achieved by systematically making changes to a cover text. This paper proposes a linguistic steganography method using word ordering as the linguistic transformation. We show that the word …...

This paper describes two methods for checking the acceptability of adjective deletion in noun phrases. The first method uses the Google n-gram corpus to check the fluency of the remaining context after an adjective is removed. The second method trains an SVM model using n-gram counts and other measures to …...

We address the challenge of automatically generating questions from topics. We consider that each topic is associated with a body of texts containing useful information about the topic. Questions are generated by exploiting the named entity information and the predicate argument structures of the sentences present in the body of …...

This paper applies sentence compression models for the task of query-focused multi-document summarization in order to investigate if sentence compression improves the overall summariza- tion performance. Both compression and summarization are considered as global optimization problems and solved using integer linear programming (ILP). Three different models are built depending on …...

Classifying documents according to the sentiment they convey (whether positive or neg- ative) is an important problem in computational linguistics. There has not been much work done in this area on general techniques that can be applied effectively to multiple languages, nor have very large data sets been used in …...

Disambiguation to Wikipedia (D2W) is the task of linking mentions of concepts in text to their corresponding Wikipedia entries. Most previous work has focused on linking terms in formal texts (e.g. newswire) to Wikipedia. Linking terms in short informal texts (e.g. tweets) is difficult for systems and humans alike as …...

A problem that crops up repeatedly in shallow and deep syntactic parsing approaches to South Asian languages like Urdu/Hindi is the proper treatment of complex predications. Problems for the NLP of complex predications are posed by their productiveness and the ill understood nature of the range of their combinatorial possibilities. …...