[PDF][PDF] Semi-supervised semantic role labeling: Approaching from an unsupervised perspective
I Titov, A Klementiev - Proceedings of COLING 2012, 2012 - aclanthology.org
Reducing the reliance of semantic role labeling (SRL) methods on human-annotated data
has become an active area of research. However, the prior work has largely focused on
either (1) looking into ways to improve supervised SRL systems by producing surrogate
annotated data and reducing sparsity of lexical features or (2) considering completely
unsupervised semantic role induction settings. In this work, we aim to link these two veins of
research by studying how unsupervised techniques can be improved by exploiting small …
has become an active area of research. However, the prior work has largely focused on
either (1) looking into ways to improve supervised SRL systems by producing surrogate
annotated data and reducing sparsity of lexical features or (2) considering completely
unsupervised semantic role induction settings. In this work, we aim to link these two veins of
research by studying how unsupervised techniques can be improved by exploiting small …
[PDF][PDF] Semi-supervised semantic role labeling: Approaching from an unsupervised perspective
ITA Klementiev - Proceedings of the COLING Conference, 2012 - Citeseer
Reducing the reliance of semantic role labeling (SRL) methods on human-annotated data
has become an active area of research. However, the prior work has largely focused on
either (1) looking into ways to improve supervised SRL systems by producing surrogate
annotated data and reducing sparsity of lexical features or (2) considering completely
unsupervised semantic role induction settings. In this work, we aim to link these two veins of
research by studying how unsupervised techniques can be improved by exploiting small …
has become an active area of research. However, the prior work has largely focused on
either (1) looking into ways to improve supervised SRL systems by producing surrogate
annotated data and reducing sparsity of lexical features or (2) considering completely
unsupervised semantic role induction settings. In this work, we aim to link these two veins of
research by studying how unsupervised techniques can be improved by exploiting small …
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