Articles

In this paper we consider the problem of label- ing the languages of words in mixed-language documents. This problem is approached in a weakly supervised fashion, as a sequence la- beling problem with monolingual text sam- ples for training data. Among the approaches evaluated, a conditional random field model trained …...

In this paper we propose a new approach to the generation of pseudowords, i.e., artificial words which model real polysemous words. Our approach simultaneously addresses the two important issues that hamper the gener- ation of large pseudosense-annotated datasets: semantic awareness and coverage. We eval- uate these pseudowords from three different …...

Non-expert annotation services like Amazon’s Mechanical Turk (AMT) are cheap and fast ways to evaluate systems and provide categor- ical annotations for training data. Unfortu- nately, some annotators choose bad labels in order to maximize their pay. Manual iden- tification is tedious, so we experiment with an item-response model. It …...

This paper explores the relationship between explicit and predictive models of incremental speech under- standing in a dialogue system that supports a finite set of user utterance meanings. We present a method that enables the approximation of explicit under- standing using information implicit in a predictive understanding model for the …...

We present open dialogue management and its application to relational databases. An open dialogue manager generates dialogue states, ac- tions, and default strategies from the semantics of its application domain. We define three open dialogue management tasks. First, vocabulary selection finds the intelligible attributes in each database table. Second, focus …...

Grice characterized communication in terms of the cooperative principle, which enjoins speakers to make only contributions that serve the evolving conversational goals. We show that the cooperative principle and the associ- ated maxims of relevance, quality, and quan- tity emerge from multi-agent decision theory. We utilize the Decentralized Partially Observ- …...

This paper proposes to study the problem of identifying intention posts in online discus- sion forums. For example, in a discussion fo- rum, a user wrote “I plan to buy a camera,” which indicates a buying intention. This in- tention can be easily exploited by advertisers. To the best of …...

Threaded discussion forums provide an im- portant social media platform. Its rich user generated content has served as an important source of public feedback. To automatically discover the viewpoints or stances on hot is- sues from forum threads is an important and useful task. In this paper, we propose a …...

Within the SemEval-2013 evaluation exercise, the TempEval-3 shared task aims to advance research on temporal information processing. It follows on from TempEval-1 and -2, with: a three-part struc- ture covering temporal expression, event, and tem- poral relation extraction; a larger dataset; and new single measures to rank systems – in …...

The ClearTK-TimeML submission to Temp- Eval 2013 competed in all English tasks: identi- fying events, identifying times, and identifying temporal relations. The system is a pipeline of machine-learning models, each with a small set of features from a simple morpho-syntactic an- notation pipeline, and where temporal relations are only predicted …...

We study multi-source transfer parsing for resource-poor target languages; specifically methods for target language adaptation of delexicalized discriminative graph-based de- pendency parsers. We first show how recent insights on selective parameter sharing, based on typological and language-family features, can be applied to a discriminative parser by carefully decomposing its model …...

We describe a novel approach to detecting empty categories (EC) as represented in de- pendency trees as well as a new metric for measuring EC detection accuracy. The new metric takes into account not only the position and type of an EC, but also the head it is a dependent …...

Information extraction from microblog posts is an important task, as today microblogs cap- ture an unprecedented amount of information and provide a view into the pulse of the world. As the core component of information extrac- tion, we consider the task of Twitter entity linking in this paper. In the …...

Hidden properties of social media users, such as their ethnicity, gender, and location, are of- ten reflected in their observed attributes, such as their first and last names. Furthermore, users who communicate with each other of- ten have similar hidden properties. We pro- pose an algorithm that exploits these insights …...

In this work, we study the problem of mea- suring relational similarity between two word pairs (e.g., silverware:fork and clothing:shirt). Due to the large number of possible relations, we argue that it is important to combine mul- tiple models based on heterogeneous informa- tion sources. Our overall system consists of …...

We present a novel approach to automatic metaphor identification, that discovers both metaphorical associations and metaphorical expressions in unrestricted text. Our sys- tem first performs hierarchical graph factor- ization clustering (HGFC) of nouns and then searches the resulting graph for metaphorical connections between concepts. It then makes use of the …...

The dominant yet ageing IBM and HMM word alignment models underpin most popular Statistical Machine implementations in use today.Translation Though beset by the limitations of implausible independence assumptions, intractable optimisation problems, and an excess of tunable parameters, these models provide a scalable and reliable starting point for inducing translation systems. …...

We present three approaches to lexical chain- ing based on the LDA topic model and eval- uate them intrinsically on a manually anno- tated set of German documents. After motivat- ing the choice of statistical methods for lexi- cal chaining with their adaptability to different languages and subject domains, we …...

We propose a new algorithm to approximately extract top-scoring hypotheses from a hyper- graph when the score includes an N–gram language model. In the popular cube prun- ing algorithm, every hypothesis is annotated with boundary words and permitted to recom- bine only if all boundary words are equal. However, many …...

This paper examines tuning for statistical ma- chine translation (SMT) with respect to mul- tiple evaluation metrics. We propose several novel methods for tuning towards multiple ob- jectives, including some based on ensemble decoding methods. Pareto-optimality is a nat- ural way to think about multi-metric optimiza- tion (MMO) and our …...