Using coreference chains for text summarization

Azzam, Saliha; Humphreys, Kevin; Gaizauskas, Robert

doi:10.3115/1608810.1608825

Cited by 58 publications

(37 citation statements)

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“…The mere task of producing the same results as those produced by humans is difficult and largely unsolved. There is nonetheless a strong interest in automatically identifying coreference links as they are needed by information extraction to merge different pieces of information referring to the same entity (McCarthy and Lehnert, 1995), by text summarization to produce a coherent and fluent summary (Azzam et al, 1999;Steinberger et al, 2007), by question answering to disambiguate references along a document (Morton, 1999;Vicedo and Ferrández, 2006), and by machine translation to translate pronouns correctly. Recently, state-of-the-art coreference resolution systems have been helpful for sentiment analysis (Nicolov et al, 2008), textual entailment Abad et al, 2010), citation matching and databases (Wick et al, 2009), machine reading (Poon et al, 2010), for learning narrative schemas (Chambers and Jurafsky, 2008), and for recovering implicit arguments (Gerber and Chai, 2010;Ruppenhofer et al, 2010).…”

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confidence: 99%

Coreference resolution: an empirical study based on SemEval-2010 shared Task 1

Màrquez

Recasens

Sapena

2012

Lang Resources & Evaluation

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This paper presents an empirical evaluation of coreference resolution that covers several interrelated dimensions. The main goal is to complete the comparative analysis from the SemEval-2010 task on Coreference Resolution in Multiple Languages. To do so, the study restricts the number of languages and systems involved, but extends and deepens the analysis of the system outputs, including a more qualitative discussion. The paper compares three automatic coreference resolution systems for three languages (English, Catalan and Spanish) in four evaluation settings, and using four evaluation measures. Given that our main goal is not to provide a comparison between resolution algorithms, these are merely used as tools to shed light on the different conditions under which coreference resolution is evaluated. Although the dimensions are strongly interdependent, making it very difficult to extract general principles, the study reveals a series of interesting issues in relation to coreference resolution: the portability of systems across languages, the influence of the type and quality of input annotations, and the behavior of the scoring measures.

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confidence: 99%

Coreference resolution: an empirical study based on SemEval-2010 shared Task 1

Màrquez

Recasens

Sapena

2012

Lang Resources & Evaluation

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“…However, the use of coreference chains is not novel in TS. The first approaches can be found in Baldwin and Morton (1998) and Azzam, Humphreys and Gaizauskas (1999). The main assumption is that the longest coreference chain indicates the main topic of the document, and shorter chains represent subtopics.…”

Section: The Process Of Summarisation From a Computational Perspectivementioning

confidence: 99%

COMPENDIUM: a text summarisation tool for generating summaries of multiple purposes, domains, and genres

Lloret¹,

Palomar²

2012

Nat. Lang. Eng.

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In this paper, we present a Text Summarisation tool, compendium, capable of generating the most common types of summaries. Regarding the input, single-and multi-document summaries can be produced; as the output, the summaries can be extractive or abstractiveoriented; and finally, concerning their purpose, the summaries can be generic, query-focused, or sentiment-based. The proposed architecture for compendium is divided in various stages, making a distinction between core and additional stages. The former constitute the backbone of the tool and are common for the generation of any type of summary, whereas the latter are used for enhancing the capabilities of the tool. The main contributions of compendium with respect to the state-of-the-art summarisation systems are that (i) it specifically deals with the problem of redundancy, by means of textual entailment; (ii) it combines statistical and cognitive-based techniques for determining relevant content; and (iii) it proposes an abstractive-oriented approach for facing the challenge of abstractive summarisation. The evaluation performed in different domains and textual genres, comprising traditional texts, as well as texts extracted from the Web 2.0, shows that compendium is very competitive and appropriate to be used as a tool for generating summaries.

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“…An early approach works with coreference chains [1] to estimate the sentences of a summary. Turney extracts important phrases by learned rules [12], while Mihalcea and Tarau build graphs using Page Rank and a similarity function between two sentences [7].…”

Section: Related Workmentioning

confidence: 99%

“…The extraction of relevant statements for a MRA is related to several kinds of areas: the automated creation of Text Summaries [1,6,7,12], Information Extraction [3,13] and Opinion Mining [8,9,11].…”

Section: Related Workmentioning

confidence: 99%

Extraction of Statements in News for a Media Response Analysis

Scholz

Conrad

2013

Natural Language Processing and Information Systems

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Abstract. The extraction of statements is an essential step in a Media Response Analysis (MRA), because statements in news represent the most important information for a customer of a MRA and can be used as the underlying data for Opinion Mining in newspaper articles. We propose a machine learning approach to tackle this problem. For each sentence, our method extracts different features which indicate the importance of a sentence for a MRA. Classified sentences are filtered through a density-based clustering, before selected sentences are combined to statements. In our evaluation, this technique achieved better results than comparison methods from Text Summarization and Opinion Mining on two real world datasets.

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Using coreference chains for text summarization

Cited by 58 publications

References 6 publications

Coreference resolution: an empirical study based on SemEval-2010 shared Task 1

Coreference resolution: an empirical study based on SemEval-2010 shared Task 1

COMPENDIUM: a text summarisation tool for generating summaries of multiple purposes, domains, and genres

Extraction of Statements in News for a Media Response Analysis

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