We describe the SemEval task of extracting keyphrases and relations between them from scientific documents, which is crucial for understanding which publications describe which processes, tasks and materials. Although this was a new task, we had a total of 26 submissions across 3 evaluation scenarios. We expect the task and the findings reported in this paper to be relevant for researchers working on understanding scientific content, as well as the broader knowledge base population and information extraction communities
Abstract: With the currently growing interest in the Semantic Web, keywords/metad-ata extraction is ...
Doctor of PhilosophyDepartment of Computer ScienceCornelia CarageaDoina CarageaScholarly digital lib...
The keyphrases of a document are the textual units that characterize its content such as the topics ...
International audienceThis paper describes the first task on semantic relation extraction and classi...
Abstract: Scientific publications are essential sources of information for researchers across variou...
Large repositories of scientific literature call for the development of robust methods to extract ...
Mapping a research domain can be of great significance for understanding and structuring the state-o...
We present NTNU’s systems for Task A (prediction of keyphrases) and Task B (labelling as Material, P...
The keyphrase extraction task is a fundamental and challenging task designed to automatically extrac...
Abstract. This paper describes the organization and results of the automatic keyphrase extrac-tion t...
International audienceThe ScienceIE task at SemEval-2017 introduced an epistemological classificatio...
peer-reviewedTopical annotation of documents with keyphrases is a proven method for revealing the su...
We describe methods for extracting interesting factual relations from scientific texts in computatio...
Automatically assigning keyphrases to documents has a great variety of applications. Here we focus o...
International audienceThe Semeval task 5 was an opportunity for experimenting with the key term ex- ...
Abstract: With the currently growing interest in the Semantic Web, keywords/metad-ata extraction is ...
Doctor of PhilosophyDepartment of Computer ScienceCornelia CarageaDoina CarageaScholarly digital lib...
The keyphrases of a document are the textual units that characterize its content such as the topics ...
International audienceThis paper describes the first task on semantic relation extraction and classi...
Abstract: Scientific publications are essential sources of information for researchers across variou...
Large repositories of scientific literature call for the development of robust methods to extract ...
Mapping a research domain can be of great significance for understanding and structuring the state-o...
We present NTNU’s systems for Task A (prediction of keyphrases) and Task B (labelling as Material, P...
The keyphrase extraction task is a fundamental and challenging task designed to automatically extrac...
Abstract. This paper describes the organization and results of the automatic keyphrase extrac-tion t...
International audienceThe ScienceIE task at SemEval-2017 introduced an epistemological classificatio...
peer-reviewedTopical annotation of documents with keyphrases is a proven method for revealing the su...
We describe methods for extracting interesting factual relations from scientific texts in computatio...
Automatically assigning keyphrases to documents has a great variety of applications. Here we focus o...
International audienceThe Semeval task 5 was an opportunity for experimenting with the key term ex- ...
Abstract: With the currently growing interest in the Semantic Web, keywords/metad-ata extraction is ...
Doctor of PhilosophyDepartment of Computer ScienceCornelia CarageaDoina CarageaScholarly digital lib...
The keyphrases of a document are the textual units that characterize its content such as the topics ...