IJIS
2008
13 years 4 months ago
2008
The ability to analyse and represent formally semantic relations of terms is a core issue in information retrieval (IR), natural language processing (NLP), and in many related are...
TREC
2000
13 years 5 months ago
2000
CL Research's question-answering system (DIMAP-QA) for TREC-9 significantly extends its semantic relation triple (logical form) technology in which documents are fully parsed...
ACL
2003
13 years 6 months ago
2003
This paper proposes a principled approach for analysis of semantic relations between constituents in compound nouns based on lexical semantic structure. One of the difficulties o...
EACL
2006
ACL Anthology
13 years 6 months ago
2006
ACL Anthology
GOD (General Ontology Discovery) is an unsupervised system to extract semantic relations among domain specific entities and concepts from texts. Operationally, it acts as a search...
EMNLP
2004
13 years 6 months ago
2004
Broad-coverage repositories of semantic relations between verbs could benefit many NLP tasks. We present a semi-automatic method for extracting fine-grained semantic relations bet...
ACL
2006
13 years 6 months ago
2006
We propose a novel method for automatically interpreting compound nouns based on a predefined set of semantic relations. First we map verb tokens in sentential contexts to a fixed...
ACL
2004
13 years 6 months ago
2004
A crucial step toward the goal of automatic extraction of propositional information from natural language text is the identification of semantic relations between constituents in ...
IJCAI
2007
13 years 6 months ago
2007
Most word sense disambiguation (WSD) methods require large quantities of manually annotated training data and/or do not exploit fully the semantic relations of thesauri. We propos...
LREC
2008
13 years 6 months ago
2008
The construction of a wordnet, a labour-intensive enterprise, can be significantly assisted by automatic grouping of lexical material and discovery of lexical semantic relations. ...
LREC
2008
13 years 6 months ago
2008
This paper presents a supervised method for the detection and extraction of Causal Relations from open domain text. First we give a brief outline of the definition of causation an...