This dataset has been created within the framework of the European Language Resource Coordination (ELRC) Connecting Europe Facility - Automated Translation (CEF.AT) action. For further information on the project: http://lr-coordination.eu. The Hellenic Ministry of Foreign Affairs Greek-English a...
This dataset has been created within the framework of the European Language Resource Coordination (ELRC) Connecting Europe Facility - Automated Translation (CEF.AT) action. For further information on the project: http://lr-coordination.eu. Information on the "Hallituskausi 2011–" translation mem...
ID: ELRA-W0220 This dataset has been created within the framework of the European Language Resource Coordination (ELRC) Connecting Europe Facility - Automated Translation (CEF.AT) action. For further information on the project: http://lr-coordination.eu. The "Hallituskausi 2007–2011" translat...
This dataset has been created within the framework of the European Language Resource Coordination (ELRC) Connecting Europe Facility - Automated Translation (CEF.AT) action. For further information on the project: http://lr-coordination.eu. Greek laws, ratification of International Conventions ag...
GREC is a semantically annotated corpus of 240 MEDLINE abstracts (167 on the subject of E. coli species and 73 on the subject of the Human species) which is intended for training IE systems and/or resources which are used to extract events from biomedical literature.
GistSumm (GIST SUMMarizer) is a summarization tool for Portuguese. It uses the gist as a guideline to identify and select text segments to include in the final extract. Automatically produced extracts have been evaluated under the light of gist preservation and textuality.
Tweets annotated with geographic coordinates
The GENIA tagger analyzes English sentences and outputs the base forms, part-of-speech tags, chunk tags, and named entity tags. The tagger is specifically tuned for biomedical text such as MEDLINE abstracts.
A corpus of 2,000 MEDLINE abstracts, collected using the three MeSH terms human, blood cells and transcription factors. The corpus is available in three formats: 1) A text file containing part-of-speech (POS) annotation, based on the Penn Treebank format, 2) An XML file containing inline POS anno...
The corpus consists of 1000 MEDLINE abstracts. It is a subset of the original GENIA POS & term corpus, which was selected using the three MeSH terms human, blood cells and transcription factors. In each sentence, three types of information are annotated 1) biomedical terms are identified and assi...