Articles

In this paper, we propose and demonstrate Exploratory Relation Extraction (ERE), a novel approach to identifying and extracting relations from large text corpora based on user-driven and data-guided incremental exploration. We draw upon ideas from the information seeking paradigm of Exploratory Search (ES) to enable an exploration process in which …...

With recent advances in the areas of knowledge engineering and information extraction, the task of linking textual mentions of named entities to corresponding ones in a knowledge base has received much attention. The rich, structured information in state-of-the-art knowledge bases can be leveraged to facilitate this task. Although recent approaches …...

In this paper we explicitly consider source language syntactic information in both rule extraction and decoding for hierarchical phrase-based translation. We obtain tree-to-string rules by the GHKM method and use them to complement Hiero-style rules. All these rules are then employed to decode new sentences with source language parse trees. …...

We investigate the usefulness of syntactic knowledge in estimating the quality of English-French translations. We find that dependency and constituency tree kernels perform well but the error rate can be further reduced when these are combined with hand-crafted syntactic features. Both types of syntactic features provide information which is complementary …...

Translation retrieval aims to find the most likely translation among a set of target-language strings for a given source-language string. Previous studies consider the single-best translation as a query for information retrieval, which may result in translation error propagation. To alleviate this problem, we propose to use the query lattice, …...

Most of the widely-used automatic evaluation metrics consider only the local fragments of the references and translations, and they ignore the evaluation on the syntax level. Current syntax- based evaluation metrics try to introduce syntax information but suffer from the poor pars- ing results of the noisy machine translations. To …...

We consider the problem of automatically paraphrasing a text in order to find an equivalent text that contains a given acrostic. A text contains an acrostic, if the first letters of a range of consecutive lines form a word or phrase. Our approach turns this paraphrasing task into an optimization …...

The relationship between how people describe objects and when they choose to point is complex and likely to be influenced by factors related to both perceptual and discourse context. In this paper, we explore these interactions using machine-learning on a dialogue corpus, to identify multimodal referential strategies that can be …...

We describe two systems for text simplification using typed dependency structures, one that performs lexical and syntactic simplification, and another that performs sentence compression optimised to satisfy global text constraints such as lexical density, the ratio of difficult words, and text length. We report a substantial evaluation that demonstrates the …...

We propose a novel unsupervised extractive approach for summarizing online reviews by ex- ploiting review helpfulness ratings. In addition to using the helpfulness ratings for review-level filtering, we suggest using them as the supervision of a topic model for sentence-level content scoring. The proposed method is metadata-driven, requiring no human …...

In this paper, we systematically explore lexicalized and non-lexicalized local syntactic features for the task of Native Language Identification (NLI). We investigate different types of feature representations in single- and cross-corpus settings, including two representations inspired by a variationist perspective on the choices made in the linguistic system. To combine …...

There is a growing interest in automatically predicting the gender and age of authors from texts. However, most research so far ignores that language use is related to the social identity of speak- ers, which may be different from their biological identity. In this paper, we combine insights from sociolinguistics …...

Mother tongue interference is the phenomenon where linguistic systems of a mother tongue are transferred to another language. Recently, Nagata and Whittaker (2013) have shown that language family relationship among mother tongues is preserved in English written by Indo- European language speakers because of mother tongue interference. At the same …...

Class-based language modeling (LM) is a long-studied and effective approach to overcome data sparsity in the context of n-gram model training. In statistical machine translation (SMT), differ- ent forms of class-based LMs have been shown to improve baseline translation quality when used in combination with standard word-level LMs but no …...

In this paper, we propose a recurrent neural network-based tuple sequence model (RNNTSM) that can help phrase-based translation model overcome the phrasal independence assumption. Our RNNTSM can potentially capture arbitrary long contextual information during estimating probabilities of tuples in continuous space. It, however, has severe data sparsity problem due to …...

In this work, we discuss the benefits of using automatically parsed corpora to study language variation. The study of language variation is an area of linguistics in which quantitative methods have been particu- larly successful. We argue that the large datasets that can be obtained using automatic annotation can help …...

Completely data-driven grammar training is prone to over-fitting. Human-defined word class knowledge is useful to address this issue. However, the manual word class taxonomy may be unreliable and irrational for statistical natural language processing, aside from its insufficient linguistic phenomena coverage and domain adaptivity. In this paper, a formalized representation …...

In this paper we show how the task of syntactic parsing of non-segmented texts, including com- pound recognition, can be represented as constraints between phrase-structure parsers and CRF sequence labellers. In order to build a joint system we use dual decomposition, a way to com- bine several elementary systems which …...

Traditional Statistical Machine Translation (SMT) systems heuristically extract synchronous structures from word alignments, while synchronous grammar induction provides better so- lutions that can discard heuristic method and directly obtain statistically sound bilingual syn- chronous structures. This paper proposes Synchronous Constituent Context Model (SCCM) for synchronous grammar induction. The SCCM is …...

Previous research on annotation projection for parser induction across languages showed only limited success and often required substantial language-specific post-processing to fix inconsis- tencies and to lift the performance onto a useful level. Model transfer was introduced as another quite successful alternative and much research has been devoted to this …...