Laura Hasler


2009

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Proceedings of the Workshop on Events in Emerging Text Types
Constantin Orasan | Laura Hasler | Corina Forăscu
Proceedings of the Workshop on Events in Emerging Text Types

2008

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The QALL-ME Benchmark: a Multilingual Resource of Annotated Spoken Requests for Question Answering
Elena Cabrio | Milen Kouylekov | Bernardo Magnini | Matteo Negri | Laura Hasler | Constantin Orasan | David Tomás | Jose Luis Vicedo | Guenter Neumann | Corinna Weber
Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08)

This paper presents the QALL-ME benchmark, a multilingual resource of annotated spoken requests in the tourism domain, freely available for research purposes. The languages currently involved in the project are Italian, English, Spanish and German. It introduces a semantic annotation scheme for spoken information access requests, specifically derived from Question Answering (QA) research. In addition to pragmatic and semantic annotations, we propose three QA-based annotation levels: the Expected Answer Type, the Expected Answer Quantifier and the Question Topical Target of a request, to fully capture the content of a request and extract the sought-after information. The QALL-ME benchmark is developed under the EU-FP6 QALL-ME project which aims at the realization of a shared and distributed infrastructure for Question Answering (QA) systems on mobile devices (e.g. mobile phones). Questions are formulated by the users in free natural language input, and the system returns the actual sequence of words which constitutes the answer from a collection of information sources (e.g. documents, databases). Within this framework, the benchmark has the twofold purpose of training machine learning based applications for QA, and testing their actual performance with a rapid turnaround in controlled laboratory setting.

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Centering Theory for Evaluation of Coherence in Computer-Aided Summaries
Laura Hasler
Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08)

This paper investigates a new evaluation method for assessing the coherence of computer-aided summaries, justified by the inappropriacy of existing evaluation methods for this task. It develops a metric for Centering Theory (CT), a theory of local coherence and salience, to measure coherence in pairs of extracts and abstracts produced in a computer-aided summarisation environment. 100 news text summaries (50 pairs of extracts and their corresponding abstracts) are analysed using CT and the metric is applied to obtain a score for each summary; the summary with the higher score out of a pair is considered more coherent. Human judgement is also obtained to allow a comparison with the CT evaluation to assess the validity of the development of CT as a useful evaluation metric in computer-aided summarisation.

2006

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Computer-aided summarisation – what the user really wants
Constantin Orăsan | Laura Hasler
Proceedings of the Fifth International Conference on Language Resources and Evaluation (LREC’06)

Computer-aided summarisation is a technology developed at the University of Wolverhampton as a complement to automatic summarisation, to produce high quality summaries with less effort. To achieve this, a user-friendly environment which incorporates several well-known summarisation methods has been developed. This paper presents the main features of the computer-aided summarisation environment and explains the changes introduced to it as a result of user feedback.

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NPs for Events: Experiments in Coreference Annotation
Laura Hasler | Constantin Orasan | Karin Naumann
Proceedings of the Fifth International Conference on Language Resources and Evaluation (LREC’06)

This paper describes a pilot project which developed a methodology for NP and event coreference annotation consisting of detailed annotation schemes and guidelines. In order to develop this, a small sample annotated corpus in the domain of terrorism/security was built. The methodology developed can be used as a basis for large-scale annotation to produce much-needed resources. In contrast to related projects, ours focused almost exclusively on the development of annotation guidelines and schemes, to ensure that future annotations based on this methodology capture the phenomena both reliably and in detail. The project also involved extensive discussions in order to redraft the guidelines, as well as major extensions to PALinkA, our existing annotation tool, to accommodate event as well as NP coreference annotation.

2004

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“Why do you Ignore me?” - Proof that not all Direct Speech is Bad
Laura Hasler
Proceedings of the Fourth International Conference on Language Resources and Evaluation (LREC’04)

In the automatic summarisation of written texts, direct speech is usually deemed unsuitable for inclusion in important sentences. This is due to the fact that humans do not usually include such quotations when they create summaries. In this paper, we argue that despite generally negative attitudes, direct speech can be useful for summarisation and ignoring it can result in the omission of important and relevant information. We present an analysis of a corpus of annotated newswire texts in which a substantial amount of speech is marked by different annotators, and describe when and why direct speech can be included in summaries. In an attempt to make direct speech more appropriate for summaries, we also describe rules currently being developed to transform it into a more summary-acceptable format.

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A Comparison of Summarisation Methods Based on Term Specificity Estimation
Constantin Orăsan | Viktor Pekar | Laura Hasler
Proceedings of the Fourth International Conference on Language Resources and Evaluation (LREC’04)

2003

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CAST: A computer-aided summarisation tool
Constantin Orasan | Ruslan Mitkov | Laura Hasler
10th Conference of the European Chapter of the Association for Computational Linguistics