J13-1008 complex syntactic patterns , and embedding useful morphological features
D15-1031 We study the problem of jointly embedding a knowledge base and a text corpus
D15-1191 Abstract We consider the problem of embedding knowledge graphs ( KGs ) into
W05-0627 the largest probability among embedding ones are kept . After predicting
P14-1011 learns how to transform semantic embedding space in one language to the
C86-1008 axiomatic theory of dialogue , embedding rhetorical patterns , focusing
J10-3010 extrinsic evaluation is done by embedding the expansion systems into a
H91-1024 there is , for example , much more embedding of requests in hypotheticals
J80-1001 grammars have a straightforward embedding , but which permit various transformations
D14-1062 relevance for the in-domain task . By embedding our latent domain phrase model
J09-1002 TransType ideas , the innovative embedding proposed here consists in using
C86-1088 . The analysis is completed by embedding the DRS representing the text
D15-1205 </title> R Abstract Compositional embedding models build a representation
J82-3001 different . The intuitive notion of " embedding a linguistic theory into a model
P14-1138 penalty function that ensures word embedding consistency across two directional
E89-1033 has been implemented , and an embedding of this in an interactive parsing
D15-1038 completion impute missing facts by embedding knowledge graphs in vector spaces
P06-2071 from the image and text of the embedding web page . We evaluate our method
S14-2011 provides dense , low-dimensional embedding for each fragment which allows
C80-1074 Fl ) , nominalization ( FII ) , embedding ( fill ) , connecting ( FIV )
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