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- 598 creator antonio-toral.
- 598 creator nilda-ruimy.
- 598 creator riccardo-del-gratta.
- 598 type InProceedings.
- 598 label "Simple-Clips ongoing research: more information with less data by implementing inheritance".
- 598 sameAs 598.
- 598 abstract "This paper presents the application of inheritance to the formal taxonomy (is-a) of a semantically rich Language Resource based on the Generative Lexicon theory, SIMPLE-CLIPS. The aim is to lighten the representation of its semantic layer by reducing the number of encoded relations. A prediction calculation on the impact of introducing inheritance regarding space occupancy is carried out, yielding a significant space reduction of 22%. This is corroborated by its actual application, which reduces the number of explicitly encoded relations in this lexicon by 18.4%. Later on, we study the issues that inheritance poses to the Language Resources, and discuss sensitive solutions to tackle each of them, including examples. Finally, we present a discussion on the application of inheritance, from which two side effect advantages arise: consistency enhancement and inference capabilities.".
- 598 hasAuthorList authorList.
- 598 hasTopic Linguistics.
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- 598 keyword "Knowledge representation".
- 598 keyword "Lexicon, lexical database".
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- 598 title "Simple-Clips ongoing research: more information with less data by implementing inheritance".
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- 599 creator alfio-massimiliano-gliozzo.
- 599 creator davide-picca.
- 599 creator massimiliano-ciaramita.
- 599 type InProceedings.
- 599 label "Supersense Tagger for Italian".
- 599 sameAs 599.
- 599 abstract "In this paper we present the procedure we followed to develop the Italian Super Sense Tagger. In particular, we adapted the English SuperSense Tagger to the Italian Language by exploiting a parallel sense labeled corpus for training. As for English, the Italian tagger uses a fixed set of 26 semantic labels, called supersenses, achieving a slightly lower accuracy due to the lower quality of the Italian training data. Both taggers accomplish the same task of identifying entities and concepts belonging to a common set of ontological types. This parallelism allows us to define effective methodologies for a broad range of cross-language knowledge acquisition tasks".
- 599 hasAuthorList authorList.
- 599 hasTopic Linguistics.
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- 599 keyword "Acquisition, Machine Learning".
- 599 keyword "Named Entity recognition".
- 599 keyword "Tagging".
- 599 title "Supersense Tagger for Italian".
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- 60 creator barbara-di-eugenio.
- 60 creator peter-c-nelson.
- 60 creator zhuli-xie.
- 60 type InProceedings.
- 60 label "From Extracting to Abstracting: Generating Quasi-abstractive Summaries".
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- 60 abstract "In this paper, we investigate quasi-abstractive summaries, a new type of machine-generated summaries that do not use whole sentences, but only fragments from the source. Quasi-abstractive summaries aim at bridging the gap between human-written abstracts and extractive summaries. We present an approach that learns how to identify sets of sentences, where each set contains fragments that can be used to produce one sentence in the abstract; and then uses these sets to produce the abstract itself. Our experiments show very promising results. Importantly, we obtain our best results when the summary generation is anchored by the most salient Noun Phrases predicted from the text to be summarized.".
- 60 hasAuthorList authorList.
- 60 hasTopic Linguistics.
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- 60 keyword "Generation".
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- 60 keyword "Summarisation".
- 60 title "From Extracting to Abstracting: Generating Quasi-abstractive Summaries".
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