Joel Lang and Mirella Lapata. 2011. Unsupervised Semantic Role Induction via Split-Merge Clustering. In Proceedings of the 49th Annual Meeting of the ...

Jun 19, 2011 · We formulate the induction of semantic roles as a clustering problem and propose a split-merge algorithm which iteratively manipulates clusters ...

An unsupervised method for semantic role induction which holds promise for relieving the data acquisition bottleneck associated with supervised role ...

Bibliographic details on Unsupervised Semantic Role Induction via Split-Merge Clustering.

We present an algorithm that iteratively splits and merges clusters representing semantic roles, thereby leading from an initial clustering to a final ...

We present an algorithm that iteratively splits and merges clusters representing semantic roles, thereby leading from an initial clustering to a final ...

In this paper we describe a method for inducing the semantic roles of verbal arguments directly from unannotated text. We formulate the role induction problem ...

We introduce two Bayesian models for un- supervised semantic role labeling (SRL) task. The models treat SRL as clustering.

In unsupervised semantic role labeling, identifying the role of an argument is usu- ally informed by its dependency relation with the predicate.

Apr 19, 2021 · The learned embeddings are then clustered as per their semantic roles by using the split-merge algorithm (using gold arguments in CoNLL-2009).