Articles

The ability to accurately determine temporal relations between events is an important task for several natural language processing applications such as Question Answering, Summarization, and Information Extraction. Since current supervised methods require large corpora, which for many languages do not exist, we have focused our attention on approaches with less …...

Nowadays, many influential facts are re- ported multiple times by different sources and in different languages. This paper presents the results of an experiment on deploying cross-lingual information fu- sion techniques for refining the results of a large-scale multilingual news event extrac- tion system. An evaluation on a test cor- …...

We present and evaluate the first method known to us that can create rich non- extract-based opinion summaries from general text (e.g. newspaper articles). We first describe two possible representations for opinion summaries and then present our system OASIS, which identifies, and optionally aggregates, fine-grained opin- ions from the same …...

This paper addresses the problem of multi- lingual text summarisation. The goal is to analyse three approaches for generat- ing summaries in four languages (English, Spanish, German and French), in order to determine the best one to adopt when tack- ling this issue. The proposed approaches rely on: i) language-independent …...

This article explores the portability of a coreference resolver across a variety of eight text genres. Besides newspaper text, we also include administrative texts, au- tocues, texts used for external communi- cation, instructive texts, wikipedia texts, medical texts and unedited new media texts. Three sets of experiments were conducted. First, …...

We investigate how the automatic identi- fication of noun compounds and named entities can contribute to keyphrase ex- traction and we also show how previously identified noun compounds affect named entity recognition and vice versa, how noun compound detection is supported by identified named entities. Our exper- iments demonstrate that …...

Many annotation schemes for discourse relations allow combinations such as tem- poral+cause (for events that are tempo- rally and causally related to each other) and temporal+contrast (for contrasts be- tween subsequent time spans, or between events that are temporally coextensive). However, current approaches for the auto- matic classification of discourse …...

We introduce an incremental entity- mention model for coreference resolution. Our experiments show that it is superior to a non-incremental version in the same en- vironment. The benefits of an incremental architecture are: a reduction of the num- ber of candidate pairs, a means to over- come the problem of …...

We propose a Named Entity (NE) recogni- tion method using rules acquired from un- labeled data. Rules are acquired from au- tomatically labeled data with an NE rec- ognizer. These rules are used to identify NEs, the beginning of NEs, or the end of NEs. The application results of rules …...

The fuzziness of Chinese sentence boundary makes discourse analysis more challenging. Moreover, many articles posted on the Internet are even lack of punctuation marks. In this pa- per, we collect documents written by masters as a reference corpus and propose a model to label the punctuation marks for the given …...

We introduce several models for alignment of etymological data, that is, for finding the best alignment, given a set of etymological data, at the sound or symbol level. This is intended to obtain a means of measuring the quality of the etymological data sets, in terms of their in- ternal …...

As developers of a highly multilingual named entity recognition (NER) system, we face an evaluation resource bottleneck problem: we need evaluation data in many languages, the annotation should not be too time-consuming, and the evaluation re- sults across languages should be compa- rable. We solve the problem by automat- ically …...

This paper describes a new, freely available, highly multilingual named entity resource for person and organisation names that has been compiled over seven years of large-scale multilingual news analysis combined with Wikipedia mining, resulting in 205,000 per- son and organisation names plus about the same number of spelling variants written …...

With the increasing demand for fast and accurate audiovisual translation, subtitlers are starting to consider the use of trans- lation technologies to support their work. An important issue that arises from the use of such technologies is measuring how much effort needs to be put in by the subti- tler …...

In this paper, we present a new hybridisa- tion approach consisting of enriching the phrase table of a phrase-based statistical machine translation system with bilingual phrase pairs matching structural transfer rules and dictionary entries from a shallow- transfer rule-based machine translation sys- tem. We have tested this approach on differ- …...

In this paper we consider whether the thematic document clustering approach of Contextual Document Clustering is able to capture the overall sentiment of a cluster of documents. We provide a novel mechanism to determine the sentiment of a cluster based on the latter approach and assess the approach on three …...

In this paper we present a knowledge-light approach to extract a bilingual lexicon for closely related languages from compara- ble corpora. While in most related work an existing dictionary is used to trans- late context vectors, we take advantage of the similarities between languages in- stead and build a seed …...

Aggregation is a sub-task of Natural Lan- guage Generation (NLG) that improves the conciseness and readability of the text outputted by NLG systems. Till date, approaches towards the aggregation task have been predominantly manual (man- ual analysis of domain specific corpus and development of rules). In this paper, a new …...

This paper proposes a method for automat- ically generating summaries taking into account the information in which users may be interested. Our approach relies on existing model summaries from tourist sites and captures from them the type of information humans use to describe places around the world. Relational patterns are …...

This paper discusses two Hidden Markov Models (HMM) for linking linguistically motivated XTAG grammar and the auto- matically extracted LTAG used by MICA parser. The former grammar is a detailed LTAG enriched with feature structures. And the latter one is a huge size LTAG that due to its statistical nature …...