Sukhareva, Maria ; Eckle-Kohler, Judith ; Habernal, Ivan ; Gurevych, Iryna (2016)
Crowdsourcing a Large Dataset of Domain-Specific Context-Sensitive Semantic Verb Relations.
Portoroz, Slovenia
Konferenzveröffentlichung, Bibliographie
Kurzbeschreibung (Abstract)
We present a new large dataset of 12403 context-sensitive verb relations manually annotated via crowdsourcing. These relations capture fine-grained semantic information between verb-centric propositions, such as temporal or entailment relations. We propose a novel semantic verb relation scheme and design a multi-step annotation approach for scaling-up the annotations using crowdsourcing. We employ several quality measures and report on agreement scores. The resulting dataset is available under a permissive CreativeCommons license. It represents a valuable resource for various applications, such as automatic information consolidation or automatic summarization.
| Typ des Eintrags: | Konferenzveröffentlichung |
|---|---|
| Erschienen: | 2016 |
| Autor(en): | Sukhareva, Maria ; Eckle-Kohler, Judith ; Habernal, Ivan ; Gurevych, Iryna |
| Art des Eintrags: | Bibliographie |
| Titel: | Crowdsourcing a Large Dataset of Domain-Specific Context-Sensitive Semantic Verb Relations |
| Sprache: | Englisch |
| Publikationsjahr: | Mai 2016 |
| Verlag: | European Language Resources Association (ELRA) |
| Buchtitel: | Proceedings of the 10th International Conference on Language Resources and Evaluation (LREC 2016) |
| Veranstaltungsort: | Portoroz, Slovenia |
| URL / URN: | http://www.lrec-conf.org/proceedings/lrec2016/pdf/494_Paper.... |
| Zugehörige Links: | |
| Kurzbeschreibung (Abstract): | We present a new large dataset of 12403 context-sensitive verb relations manually annotated via crowdsourcing. These relations capture fine-grained semantic information between verb-centric propositions, such as temporal or entailment relations. We propose a novel semantic verb relation scheme and design a multi-step annotation approach for scaling-up the annotations using crowdsourcing. We employ several quality measures and report on agreement scores. The resulting dataset is available under a permissive CreativeCommons license. It represents a valuable resource for various applications, such as automatic information consolidation or automatic summarization. |
| Freie Schlagworte: | UKP_reviewed;UKP_p_DIP;Crowdsourcing, Semantic relations, dataset |
| ID-Nummer: | TUD-CS-2016-0021 |
| Fachbereich(e)/-gebiet(e): | 20 Fachbereich Informatik 20 Fachbereich Informatik > Ubiquitäre Wissensverarbeitung DFG-Graduiertenkollegs DFG-Graduiertenkollegs > Graduiertenkolleg 1994 Adaptive Informationsaufbereitung aus heterogenen Quellen |
| Hinterlegungsdatum: | 31 Dez 2016 14:29 |
| Letzte Änderung: | 24 Jan 2020 12:03 |
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