- Program Chair:
- Jan Hajič
Welcome back to Europe at ACL 2010! After three years, the ACL crowd is meeting again in Europe, this time at the very north, to escape from the Central European heat it experienced in 2007.
This year, some significant changes can be found under the hood. The call for papers was formulated much more broadly than usual, and this idea brought up by the ACL membership and the Exec and then developed in detail by this year's program chairs, Sandra Carberry and Stephen Clark, really caught on - the number of submissions has been the highest of all times, forcing us to put some activities, such as the SRW, as the fifth track on Tuesday morning. The number of reviewers is hard to compute exactly - but a glimpse into their lists in this year's and previous years' proceedings reveals that we almost certainly set a new record here, too (thank you all!). Also, the proceedings have switched to electronic-only for all events, and adaptation of the START conference automation software has begun towards a fully automated workflow from submission to the production of the final proceedings in pdf format. It has been made possible thanks to Philipp Koehn's and Jing-Shin Chang's willingness to serve as Publication Chairs two years in a row in order to ensure a smooth transition from the semi-manual process employed in the past. However, there was one thing that overshadowed it all: the enthusiastic, meticulously precise and absolutely professional yet in every situation very polite approach of the local arrangements committee headed by Joakim Nivre. His efforts have made my job, as the General Chair, a piece of cake, limited essentially to watching the tons of emails exchanged between the local and other committees and to answering emails like "why wasn't I asked to be an invited speaker?" (obviously, from people no one would consider for this honor anyway).
Proceeding Downloads
Efficient third-order dependency parsers
We present algorithms for higher-order dependency parsing that are "third-order" in the sense that they can evaluate substructures containing three dependencies, and "efficient" in the sense that they require only O(n4) time. Importantly, our new ...
Dependency parsing and projection based on word-pair classification
In this paper we describe an intuitionistic method for dependency parsing, where a classifier is used to determine whether a pair of words forms a dependency edge. And we also propose an effective strategy for dependency projection, where the dependency ...
Bitext dependency parsing with bilingual subtree constraints
This paper proposes a dependency parsing method that uses bilingual constraints to improve the accuracy of parsing bilingual texts (bitexts). In our method, a target-side tree fragment that corresponds to a source-side tree fragment is identified via ...
Computing weakest readings
We present an efficient algorithm for computing the weakest readings of semantically ambiguous sentences. A corpus-based evaluation with a large-scale grammar shows that our algorithm reduces over 80% of sentences to one or two readings, in negligible ...
Identifying generic noun phrases
This paper presents a supervised approach for identifying generic noun phrases in context. Generic statements express rule-like knowledge about kinds or events. Therefore, their identification is important for the automatic construction of knowledge ...
Structural semantic relatedness: a knowledge-based method to named entity disambiguation
Name ambiguity problem has raised urgent demands for efficient, high-quality named entity disambiguation methods. In recent years, the increasing availability of large-scale, rich semantic knowledge sources (such as Wikipedia and WordNet) creates new ...
Correcting errors in speech recognition with articulatory dynamics
We introduce a novel mechanism for incorporating articulatory dynamics into speech recognition with the theory of task dynamics. This system reranks sentence-level hypotheses by the likelihoods of their hypothetical articulatory realizations which are ...
Learning to adapt to unknown users: referring expression generation in spoken dialogue systems
We present a data-driven approach to learn user-adaptive referring expression generation (REG) policies for spoken dialogue systems. Referring expressions can be difficult to understand in technical domains where users may not know the technical 'jargon'...
A risk minimization framework for extractive speech summarization
In this paper, we formulate extractive summarization as a risk minimization problem and propose a unified probabilistic framework that naturally combines supervised and unsupervised summarization models to inherit their individual merits as well as to ...
The human language project: building a Universal Corpus of the world's languages
We present a grand challenge to build a corpus that will include all of the world's languages, in a consistent structure that permits large-scale cross-linguistic processing, enabling the study of universal linguistics. The focal data types, bilingual ...
Bilingual lexicon generation using non-aligned signatures
Bilingual lexicons are fundamental resources. Modern automated lexicon generation methods usually require parallel corpora, which are not available for most language pairs. Lexicons can be generated using non-parallel corpora or a pivot language, but ...
Automatic evaluation method for machine translation using noun-phrase chunking
As described in this paper, we propose a new automatic evaluation method for machine translation using noun-phrase chunking. Our method correctly determines the matching words between two sentences using corresponding noun phrases. Moreover, our method ...
Open information extraction using Wikipedia
Information-extraction (IE) systems seek to distill semantic relations from natural-language text, but most systems use supervised learning of relation-specific examples and are thus limited by the availability of training data. Open IE systems such as ...
SystemT: an algebraic approach to declarative information extraction
- Laura Chiticariu,
- Rajasekar Krishnamurthy,
- Yunyao Li,
- Sriram Raghavan,
- Frederick R. Reiss,
- Shivakumar Vaithyanathan
As information extraction (IE) becomes more central to enterprise applications, rule-based IE engines have become increasingly important. In this paper, we describe SystemT, a rule-based IE system whose basic design removes the expressivity and ...
Extracting social networks from literary fiction
We present a method for extracting social networks from literature, namely, nineteenth-century British novels and serials. We derive the networks from dialogue interactions, and thus our method depends on the ability to determine when two characters are ...
Pseudo-word for phrase-based machine translation
The pipeline of most Phrase-Based Statistical Machine Translation (PB-SMT) systems starts from automatically word aligned parallel corpus. But word appears to be too fine-grained in some cases such as non-compositional phrasal equivalences, where no ...
Hierarchical search for word alignment
We present a simple yet powerful hierarchical search algorithm for automatic word alignment. Our algorithm induces a forest of alignments from which we can efficiently extract a ranked k-best list. We score a given alignment within the forest with a ...
"Was it good? It was provocative." Learning the meaning of scalar adjectives
Texts and dialogues often express information indirectly. For instance, speakers' answers to yes/no questions do not always straightforwardly convey a 'yes' or 'no' answer. The intended reply is clear in some cases (Was it good? It was great!) but ...
Importance-Driven Turn-Bidding for spoken dialogue systems
Current turn-taking approaches for spoken dialogue systems rely on the speaker releasing the turn before the other can take it. This reliance results in restricted interactions that can lead to inefficient dialogues. In this paper we present a model we ...
Entity-based local coherence modelling using topological fields
One goal of natural language generation is to produce coherent text that presents information in a logical order. In this paper, we show that topological fields, which model high-level clausal structure, are an important component of local coherence in ...
Syntactic and semantic factors in processing difficulty: an integrated measure
The analysis of reading times can provide insights into the processes that underlie language comprehension, with longer reading times indicating greater cognitive load. There is evidence that the language processor is highly predictive, such that prior ...
Rebanking CCGbank for improved NP interpretation
Once released, treebanks tend to remain unchanged despite any shortcomings in their depth of linguistic analysis or coverage of specific phenomena. Instead, separate resources are created to address such problems. In this paper we show how to improve ...
BabelNet: building a very large multilingual semantic network
In this paper we present BabelNet -- a very large, wide-coverage multilingual semantic network. The resource is automatically constructed by means of a methodology that integrates lexicographic and encyclopedic knowledge from WordNet and Wikipedia. In ...
Fully unsupervised core-adjunct argument classification
The core-adjunct argument distinction is a basic one in the theory of argument structure. The task of distinguishing between the two has strong relations to various basic NLP tasks such as syntactic parsing, semantic role labeling and subcategorization ...
Towards open-domain Semantic Role Labeling
Current Semantic Role Labeling technologies are based on inductive algorithms trained over large scale repositories of annotated examples. Frame-based systems currently make use of the FrameNet database but fail to show suitable generalization ...
A Bayesian method for robust estimation of distributional similarities
Existing word similarity measures are not robust to data sparseness since they rely only on the point estimation of words' context profiles obtained from a limited amount of data. This paper proposes a Bayesian method for robust distributional word ...
Recommendation in Internet forums and blogs
The variety of engaging interactions among users in social medial distinguishes it from traditional Web media. Such a feature should be utilized while attempting to provide intelligent services to social media participants. In this article, we present a ...
Learning phrase-based spelling error models from clickthrough data
This paper explores the use of clickthrough data for query spelling correction. First, large amounts of query-correction pairs are derived by analyzing users' query reformulation behavior encoded in the clickthrough data. Then, a phrase-based error ...
Inducing domain-specific semantic class taggers from (almost) nothing
This research explores the idea of inducing domain-specific semantic class taggers using only a domain-specific text collection and seed words. The learning process begins by inducing a classifier that only has access to contextual features, forcing it ...
Learning 5000 relational extractors
Many researchers are trying to use information extraction (IE) to create large-scale knowledge bases from natural language text on the Web. However, the primary approach (supervised learning of relation-specific extractors) requires manually-labeled ...