Articles

We address the problem of identifying mul- tiword expressions in a language, focus- ing on English phrasal verbs. Our poly- glot ranking approach integrates frequency statistics from translated corpora in 50 dif- ferent languages. Our experimental eval- uation demonstrates that combining statisti- cal evidence from many parallel corpora us- ing …...

Reordering poses one of the greatest chal- lenges in Statistical Machine Translation re- search as the key contextual information may well be beyond the confine of translation units. We present the “Anchor Graph” (AG) model where we use a graph structure to model global contextual information that is crucial for …...

Bilingual lexicons are central components of machine translation and cross-lingual infor- mation retrieval systems. Their manual con- struction requires strong expertise in both lan- guages involved and is a costly process. Sev- eral automatic methods were proposed as an alternative but they often rely on resources available in a limited …...

 Web users are increasingly looking for structured data, such as lyrics, job, or recipes, using unstructured queries on the web. However, retrieving relevant results from such data is a challenging problem due to the unstructured language of the web queries. In this paper, we propose a method to improve …...

This paper proposes a framework for automat- ically engineering features for two important tasks of question answering: answer sentence selection and answer extraction. We represent question and answer sentence pairs with lin- guistic structures enriched by semantic infor- mation, where the latter is produced by auto- matic classifiers, e.g., question …...

A large number of Open Relation Extrac- tion approaches have been proposed recently, covering a wide range of NLP machinery, from “shallow” (e.g., part-of-speech tagging) to “deep” (e.g., semantic role labeling–SRL). A natural question then is what is the trade- off between NLP depth (and associated com- putational cost) versus …...

Joint compression and summarization has been used recently to generate high quality summaries. However, such word-based joint optimization is computationally expensive. In this paper we adopt the ‘sentence compression + sentence selection’ pipeline approach for compressive summarization, but propose to perform summary guided compression, rather than generic sentence-based compression. To …...

Web search can be enhanced in powerful ways if to- ken spans in Web text are annotated with disambiguated entities from large catalogs like Freebase. Entity anno- tators need to be trained on sample mention snippets. Wikipedia entities and annotated pages offer high-quality labeled data for training and evaluation. Unfortunately, …...

This paper introduces a method for extract- ing fine-grained class labels (“countries with double taxation agreements with india”) from Web search queries. The class labels are more numerous and more diverse than those pro- duced by current extraction methods. Also extracted are representative sets of instances (singapore, united kingdom) for …...

In this paper we present an unsupervised ap- proach to relational information extraction. Our model partitions tuples representing an observed syntactic relationship between two named entities (e.g., “X was born in Y” and “X is from Y”) into clusters correspond- ing to underlying semantic relation types (e.g., BornIn, Located). Our …...

In situated dialogue, humans and agents have mismatched capabilities of perceiving the shared environment. Their representations of the shared world are misaligned. Thus referring expression generation (REG) will need to take this discrepancy into consider- ation. To address this issue, we developed a hypergraph-based approach to account for group-based spatial …...

Human engagement in narrative is partially driven by reasoning about discourse relations between narrative events, and the expectations about what is likely to happen next that results from such reasoning. Researchers in NLP have tackled modeling such expectations from a range of perspectives, including treating it as the inference of …...

This paper describes a method that predicts which trades players execute during a win- lose game. Our method uses data collected from chat negotiations of the game The Set- tlers of Catan and exploits the conversation to construct dynamically a partial model of each player’s preferences. This in turn yields …...

Entity disambiguation works by linking am- biguous mentions in text to their correspond- ing real-world entities in knowledge base. Re- cent collective disambiguation methods en- force coherence among contextual decisions at the cost of non-trivial inference processes. We propose a fast collective disambiguation approach based on stacking. First, we train …...

This paper contributes an approach for expressing non-concatenative morphological phenomena, such as stem derivation Semitic languages, in terms of a mildlyin context-sensitive grammar formalism. This offers a convenient level of modelling ab- straction while remaining computationally tractable. The nonparametric Bayesian frame- work of adaptor grammars is extended to this richer …...

Morphology and syntax interact considerably in many languages and language processing should pay attention to these interdependen- cies. We analyze the effect of syntactic fea- tures when used in automatic morphology pre- diction on four typologically different lan- guages. We show that predicting morphology for languages with highly ambiguous word …...

Nowadays supervised sequence labeling models can reach competitive performance on the task of Chinese word segmenta- tion. However, the ability of these mod- els is restricted by the availability of an- notated data and the design of features. We propose a scalable semi-supervised fea- ture engineering approach. In contrast to …...

Many errors in coreference resolution come from semantic mismatches due to inadequate world knowledge. Errors in named-entity linking (NEL), on the other hand, are of- ten caused by superficial modeling of entity context. This paper demonstrates that these two tasks are complementary. We introduce NECO, a new model for named …...

Coreference resolution plays a critical role in discourse analysis. This paper focuses on exploiting zero pronouns to improve Chi- nese coreference resolution. In particular, a simplified semantic role labeling framework is proposed to identify clauses and to detect zero pronouns effectively, and two effective methods (refining syntactic parser and refining …...

Current automatic machine translation sys- tems are not able to generate error-free trans- lations and human intervention is often re- quired to correct their output. Alternatively, an interactive framework that integrates the human knowledge into the translation pro- cess has been presented in previous works. Here, we describe a new …...