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        <title>Gold Corpus for Telegraphic Summarization</title>
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    <name type="personal">
        <namePart type="given">Chanakya</namePart>
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        <namePart type="given">Srivenkata</namePart>
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            <title>Proceedings of the First Workshop on Linguistic Resources for Natural Language Processing</title>
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            <namePart type="given">Peter</namePart>
            <namePart type="family">Machonis</namePart>
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    <abstract>Most extractive summarization techniques operate by ranking all the source sentences and then select the top ranked sentences as the summary. Such methods are known to produce good summaries, especially when applied to news articles and scientific texts. However, they don’t fare so well when applied to texts such as fictional narratives, which don’t have a single central or recurrent theme. This is because usually the information or plot of the story is spread across several sentences. In this paper, we discuss a different summarization technique called Telegraphic Summarization. Here, we don’t select whole sentences, rather pick short segments of text spread across sentences, as the summary. We have tailored a set of guidelines to create such summaries and, using the same, annotate a gold corpus of 200 English short stories.</abstract>
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        <date>2018-08</date>
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%0 Conference Proceedings
%T Gold Corpus for Telegraphic Summarization
%A Malireddy, Chanakya
%A Somisetty, Srivenkata N. M.
%A Shrivastava, Manish
%Y Machonis, Peter
%Y Barreiro, Anabela
%Y Kocijan, Kristina
%Y Silberztein, Max
%S Proceedings of the First Workshop on Linguistic Resources for Natural Language Processing
%D 2018
%8 August
%I Association for Computational Linguistics
%C Santa Fe, New Mexico, USA
%F malireddy-etal-2018-gold
%X Most extractive summarization techniques operate by ranking all the source sentences and then select the top ranked sentences as the summary. Such methods are known to produce good summaries, especially when applied to news articles and scientific texts. However, they don’t fare so well when applied to texts such as fictional narratives, which don’t have a single central or recurrent theme. This is because usually the information or plot of the story is spread across several sentences. In this paper, we discuss a different summarization technique called Telegraphic Summarization. Here, we don’t select whole sentences, rather pick short segments of text spread across sentences, as the summary. We have tailored a set of guidelines to create such summaries and, using the same, annotate a gold corpus of 200 English short stories.
%U https://aclanthology.org/W18-3810
%P 71-77

Markdown (Informal)

[Gold Corpus for Telegraphic Summarization](https://aclanthology.org/W18-3810) (Malireddy et al., LR4NLP 2018)

• Gold Corpus for Telegraphic Summarization (Malireddy et al., LR4NLP 2018)

ACL

• Chanakya Malireddy, Srivenkata N M Somisetty, and Manish Shrivastava. 2018. Gold Corpus for Telegraphic Summarization. In Proceedings of the First Workshop on Linguistic Resources for Natural Language Processing, pages 71–77, Santa Fe, New Mexico, USA. Association for Computational Linguistics.