# name
Discurse Marker Characterisation Via Clustering: Extrapolation from Supervised to Unsupervised Corpora

# metadata.dc.description.abstract[].value
In this paper we will show how clustering techniques provide empirical evidence for a characterisation of Discourse Markers (DMs) that helps in overcoming the lack of consensus and reduces the cost of building NLP resources based on DMs. By comparison of classifications from hand-tagged and unsupervised corpora we are capable of grounding a notion of DM prototypicality, from which reliable classifications can be obtained from fully unsupervised corpora.

# metadata.dc.publisher[].value
Sociedad Española para el Procesamiento del Lenguaje Natural (SEPLN)

# metadata.dc.relation.ispartof[].value
Procesamiento del lenguaje natural , 2002, num. 29, p. 223-230

# metadata.dc.source[].value
Articles publicats en revistes (Filologia Catalana i Lingüística General)

# metadata.dc.subject.classification[].value
Tractament del llenguatge natural (Informàtica)

# metadata.dc.subject.other[].value
Natural language processing (Computer science)

# metadata.dc.title[].value
Discurse Marker Characterisation Via Clustering: Extrapolation from Supervised to Unsupervised Corpora