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EKAW
2008
Springer
13 years 7 months ago
Unsupervised Discovery of Compound Entities for Relationship Extraction
In this paper we investigate unsupervised population of a biomedical ontology via information extraction from biomedical literature. Relationships in text seldom connect simple ent...
Cartic Ramakrishnan, Pablo N. Mendes, Shaojun Wang...
WEBI
2010
Springer
13 years 3 months ago
Boosting Biomedical Entity Extraction by Using Syntactic Patterns for Semantic Relation Discovery
Biomedical entity extraction from unstructured web documents is an important task that needs to be performed in order to discover knowledge in the veterinary medicine domain. In ge...
Svitlana Volkova, Doina Caragea, William H. Hsu, J...
EMNLP
2008
13 years 7 months ago
Seeded Discovery of Base Relations in Large Corpora
Relationship discovery is the task of identifying salient relationships between named entities in text. We propose novel approaches for two sub-tasks of the problem: identifying t...
Nicholas Andrews, Naren Ramakrishnan
ACL
2008
13 years 7 months ago
Unsupervised Discovery of Generic Relationships Using Pattern Clusters and its Evaluation by Automatically Generated SAT Analogy
We present a novel framework for the discovery and representation of general semantic relationships that hold between lexical items. We propose that each such relationship can be ...
Dmitry Davidov, Ari Rappoport
ACL
2008
13 years 7 months ago
Classification of Semantic Relationships between Nominals Using Pattern Clusters
There are many possible different semantic relationships between nominals. Classification of such relationships is an important and difficult task (for example, the well known nou...
Dmitry Davidov, Ari Rappoport