Articles

Standard algorithms for template-based in- formation extraction (IE) require predefined template schemas, and often labeled data, to learn to extract their slot fillers (e.g., an embassy is the Target of a Bombing tem- plate). This paper describes an approach to template-based IE that removes this require- ment and performs extraction …...

We use search engine results to address a par- ticularly difficult cross-domain language pro- cessing task, the adaptation of named entity recognition (NER) from news text to web queries. The key novelty of the method is that we submit a token with context to a search engine and use similar …...

We analyze collective discourse, a collective human behavior in content generation, and show that it exhibits diversity, a property of general collective systems. Using extensive analysis, we propose a novel paradigm for de- signing summary generation systems that re- flect the diversity of perspectives seen in real- life collective summarization. …...

We investigate automatic geolocation (i.e. identification of the location, expressed as latitude/longitude coordinates) of documents. Geolocation can be an effective means of sum- marizing large document collections and it is an important component of geographic infor- mation retrieval. We describe several simple supervised methods for document geolocation using only the …...

Linking entities with knowledge base (entity linking) is a key issue in bridging the textual data with the structural knowledge base. Due to the name variation problem and the name ambiguity problem, the entity linking decisions are critically depending on the heterogenous knowledge of entities. In this paper, we propose …...

Automated grammar correction techniques have seen improvement over the years, but there is still much room for increased perfor- mance. Current correction techniques mainly focus on identifying and correcting a specific type of error, such as verb form misuse or preposition misuse, which restricts the correc- tions to a limited …...

Spelling correction for keyword-search queries is challenging in restricted domains such as personal email (or desktop) search, due to the scarcity of query logs, and due to the specialized nature of the domain. For that task, this paper presents an algorithm that is based on statistics from the corpus data …...

We consider the problem of correcting errors made by English as a Second Language (ESL) writers and address two issues that are essen- tial to making progress in ESL error correction - algorithm selection and model adaptation to the first language of the ESL learner. A variety of learning algorithms …...

We present a novel approach to grammatical error correction based on Alternating Struc- ture Optimization. As part of our work, we introduce the NUS Corpus of Learner En- glish (NUCLE), a fully annotated one mil- lion words corpus of learner English available for research purposes. We conduct an exten- sive …...

This paper describes an unsupervised dynamic graphical model for morphological segmen- tation and bilingual morpheme alignment for statistical machine translation. The model ex- tends Hidden Semi-Markov chain models by using factored output nodes and special struc- tures for its conditional probability distribu- tions. It relies on morpho-syntactic and lex- ical …...

Most previous studies of morphological dis- ambiguation and dependency parsing have been pursued independently. Morphological taggers operate on n-grams and do not take into account syntactic relations; parsers use the “pipeline” approach, assuming that mor- phological information has been separately obtained. However, in morphologically-rich languages, there is often considerable interaction …...

In this work we address the problem of unsupervised part-of-speech induction by bringing together several strands of research into a single model. We develop a novel hidden Markov model incorporating sophisticated smoothing using a hierarchical Pitman-Yor processes prior, providing an elegant and principled means of incorporating lexical characteristics. Central to …...

Arabic handwriting recognition (HR) is a challenging problem due to Arabic’s con- nected letter forms, consonantal diacritics and rich morphology. In this paper we isolate the task of identification of erroneous words in HR from the task of producing corrections for these words. We consider a variety of linguistic (morphological …...

Most statistical machine translation systems rely on composed rules (rules that can be formed out of smaller rules in the grammar). Though this practice improves translation by weakening independence assumptions in the translation model, it nevertheless results in huge, redundant grammars, making both train- ing and decoding inefficient. Here, we …...

We propose a novel technique of learning how to transform the source parse trees to improve the trans- lation qualities of syntax-based translation mod- els using synchronous context-free grammars. We transform the source tree phrasal structure into a set of simpler structures, expose such decisions to the decoding process, and …...

Tree-to-string translation is syntax-aware and efficient but sensitive to parsing errors. Forest- to-string translation approaches mitigate the risk of propagating parser errors into transla- tion errors by considering a forest of alterna- tive trees, as generated by a source language parser. We propose an alternative approach to generating forests that …...

The local multi bottom-up tree transducer is introduced and related to the (non-contiguous) synchronous tree sequence substitution gram- mar. It is then shown how to obtain a weighted local multi bottom-up tree transducer from a bilingual and biparsed corpus. Finally, the problem of non-preservation of regular- ity is addressed. Three …...

While world knowledge has been shown to improve learning-based coreference resolvers, the improvements were typically obtained by incorporating world knowledge into a fairly weak baseline resolver. Hence, it is not clear whether these benefits can carry over to a stronger baseline. Moreover, since there has been no attempt to apply …...

Cross-document coreference, the task of grouping all the mentions of each entity in a document collection, arises in information ex- traction and automated knowledge base con- struction. For large collections, it is clearly impractical to consider all possible groupings of mentions into distinct entities. To solve the problem we propose …...

We present an ILP-based model of zero anaphora detection and resolution that builds on the joint determination of anaphoricity and coreference model proposed by Denis and Baldridge (2007), but revises it and extends it into a three-way ILP problem also incorporat- ing subject detection. We show that this new model …...