Dataset
IDN-Sum
| Τίτλος: | IDN-Sum |
|---|---|
| Συγγραφείς: | Ashwathy T Revi, Stuart E Middleton, David E Millard |
| Στοιχεία εκδότη: | Zenodo |
| Έτος έκδοσης: | 2022 |
| Συλλογή: | Zenodo |
| Θεματικοί όροι: | interactive narratives, extractive summarisation |
| Περιγραφή: | Summarizing Interactive Digital Narratives (IDN) presents some unique challenges to existing text summarization models especially around capturing interactive elements in addition to important plot points. In this paper we describe the first IDN dataset (IDN-Sum) designed specifically for training and testing IDN text summarization algorithms. Our dataset is generated using random playthroughs of 8 IDN episodes, taken from 2 different IDN games, and consists of 10,000 documents. Playthrough documents are annotated through automatic alignment with fan-sourced summaries using a commonly used alignment algorithm. The dataset is released as open source for future researchers to train and test their own approaches for IDN text. Annotated Data folder contains the IDN-Sum data that was automatically annotated using the alignment algorithm. Subfolders hold different versions of data in the format suitable for input to BertSum (bs) from TransformerSum library (https://github.com/HHousen/TransformerSum) and SummaRuNNer(sr) (for implementation at https://github.com/hpzhao/SummaRuNNer). They are are named using convention [model_name]_[summary_length]. Unannotated playthroughs can be found in Cleaned Data folder. |
| Τύπος εγγράφου: | dataset |
| Γλώσσα: | English |
| Relation: | https://zenodo.org/records/7083149; oai:zenodo.org:7083149; https://doi.org/10.5281/zenodo.7083149 |
| DOI: | 10.5281/zenodo.7083149 |
| Διαθεσιμότητα: | https://doi.org/10.5281/zenodo.7083149 https://zenodo.org/records/7083149 |
| Rights: | Creative Commons Attribution Share Alike 3.0 Unported ; cc-by-sa-3.0 ; https://creativecommons.org/licenses/by-sa/3.0/legalcode |
| Αριθμός Καταχώρησης: | edsbas.8BA4CD23 |
| Βάση Δεδομένων: | BASE |
| FullText | Text: Availability: 0 CustomLinks: – Url: https://doi.org/10.5281/zenodo.7083149# Name: EDS - BASE (ns324271) Category: fullText Text: View record from BASE |
|---|---|
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| IllustrationInfo | |
| Items | – Name: Title Label: Title Group: Ti Data: IDN-Sum – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Ashwathy+T+Revi%22">Ashwathy T Revi</searchLink><br /><searchLink fieldCode="AR" term="%22Stuart+E+Middleton%22">Stuart E Middleton</searchLink><br /><searchLink fieldCode="AR" term="%22David+E+Millard%22">David E Millard</searchLink> – Name: Publisher Label: Publisher Information Group: PubInfo Data: Zenodo – Name: DatePubCY Label: Publication Year Group: Date Data: 2022 – Name: Subset Label: Collection Group: HoldingsInfo Data: Zenodo – Name: Subject Label: Subject Terms Group: Su Data: <searchLink fieldCode="DE" term="%22interactive+narratives%22">interactive narratives</searchLink><br /><searchLink fieldCode="DE" term="%22extractive+summarisation%22">extractive summarisation</searchLink> – Name: Abstract Label: Description Group: Ab Data: Summarizing Interactive Digital Narratives (IDN) presents some unique challenges to existing text summarization models especially around capturing interactive elements in addition to important plot points. In this paper we describe the first IDN dataset (IDN-Sum) designed specifically for training and testing IDN text summarization algorithms. Our dataset is generated using random playthroughs of 8 IDN episodes, taken from 2 different IDN games, and consists of 10,000 documents. Playthrough documents are annotated through automatic alignment with fan-sourced summaries using a commonly used alignment algorithm. The dataset is released as open source for future researchers to train and test their own approaches for IDN text. Annotated Data folder contains the IDN-Sum data that was automatically annotated using the alignment algorithm. Subfolders hold different versions of data in the format suitable for input to BertSum (bs) from TransformerSum library (https://github.com/HHousen/TransformerSum) and SummaRuNNer(sr) (for implementation at https://github.com/hpzhao/SummaRuNNer). They are are named using convention [model_name]_[summary_length]. Unannotated playthroughs can be found in Cleaned Data folder. – Name: TypeDocument Label: Document Type Group: TypDoc Data: dataset – Name: Language Label: Language Group: Lang Data: English – Name: NoteTitleSource Label: Relation Group: SrcInfo Data: https://zenodo.org/records/7083149; oai:zenodo.org:7083149; https://doi.org/10.5281/zenodo.7083149 – Name: DOI Label: DOI Group: ID Data: 10.5281/zenodo.7083149 – Name: URL Label: Availability Group: URL Data: https://doi.org/10.5281/zenodo.7083149<br />https://zenodo.org/records/7083149 – Name: Copyright Label: Rights Group: Cpyrght Data: Creative Commons Attribution Share Alike 3.0 Unported ; cc-by-sa-3.0 ; https://creativecommons.org/licenses/by-sa/3.0/legalcode – Name: AN Label: Accession Number Group: ID Data: edsbas.8BA4CD23 |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.8BA4CD23 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.5281/zenodo.7083149 Languages: – Text: English Subjects: – SubjectFull: interactive narratives Type: general – SubjectFull: extractive summarisation Type: general Titles: – TitleFull: IDN-Sum Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Ashwathy T Revi – PersonEntity: Name: NameFull: Stuart E Middleton – PersonEntity: Name: NameFull: David E Millard IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Type: published Y: 2022 Identifiers: – Type: issn-locals Value: edsbas – Type: issn-locals Value: edsbas.oa |
| ResultId | 1 |