Annotation guidelines used for Semeval task 10 - “Linking Events and Their Participants in Discourse

Annotation guidelines used for Semeval task 10 - “Linking Events and Their Participants in Discourse. Ruppenhofer, J. In pages 1-8, 2010.
abstract bibtex

In this paper, we describe the SemEval-2010 shared task on “Linking Events and Their Par- ticipants in Discourse”. This task is a variant of the classical semantic role labelling task. The novel aspect is that we focus on linking local semantic argument structures across sen- tence boundaries. Speciﬁcally, the task aims at linking locally uninstantiated roles to their co- referents in the wider discourse context (if such co-referents exist). This task is potentially ben- eﬁcial for a number of NLP applications and we hope that it will not only attract researchers from the semantic role labelling community but also from co-reference resolution and infor- mation extraction.

@inProceedings{
 title = {Annotation guidelines used for Semeval task 10 - “Linking Events and Their Participants in Discourse},
 type = {inProceedings},
 year = {2010},
 pages = {1-8},
 id = {8aedd940-a67d-3287-9018-a4808b4836db},
 created = {2011-02-27T18:33:21.000Z},
 file_attached = {false},
 profile_id = {5284e6aa-156c-3ce5-bc0e-b80cf09f3ef6},
 group_id = {066b42c8-f712-3fc3-abb2-225c158d2704},
 last_modified = {2017-03-14T14:36:19.698Z},
 tags = {semantic relations},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 citation_key = {Ruppenhofer2010},
 private_publication = {false},
 abstract = {In this paper, we describe the SemEval-2010 shared task on “Linking Events and Their Par- ticipants in Discourse”. This task is a variant of the classical semantic role labelling task. The novel aspect is that we focus on linking local semantic argument structures across sen- tence boundaries. Speciﬁcally, the task aims at linking locally uninstantiated roles to their co- referents in the wider discourse context (if such co-referents exist). This task is potentially ben- eﬁcial for a number of NLP applications and we hope that it will not only attract researchers from the semantic role labelling community but also from co-reference resolution and infor- mation extraction.},
 bibtype = {inProceedings},
 author = {Ruppenhofer, Josef}
}

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