Higher-order Relation Schema Induction using Tensor Factorization with Back-off and Aggregation

Madhav Nimishakavi, Manish Gupta, Partha Talukdar


Abstract
Relation Schema Induction (RSI) is the problem of identifying type signatures of arguments of relations from unlabeled text. Most of the previous work in this area have focused only on binary RSI, i.e., inducing only the subject and object type signatures per relation. However, in practice, many relations are high-order, i.e., they have more than two arguments and inducing type signatures of all arguments is necessary. For example, in the sports domain, inducing a schema win(WinningPlayer, OpponentPlayer, Tournament, Location) is more informative than inducing just win(WinningPlayer, OpponentPlayer). We refer to this problem as Higher-order Relation Schema Induction (HRSI). In this paper, we propose Tensor Factorization with Back-off and Aggregation (TFBA), a novel framework for the HRSI problem. To the best of our knowledge, this is the first attempt at inducing higher-order relation schemata from unlabeled text. Using the experimental analysis on three real world datasets we show how TFBA helps in dealing with sparsity and induce higher-order schemata.
Anthology ID:
P18-1146
Volume:
Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Month:
July
Year:
2018
Address:
Melbourne, Australia
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
1575–1584
Language:
URL:
https://aclanthology.org/P18-1146
DOI:
10.18653/v1/P18-1146
Bibkey:
Cite (ACL):
Madhav Nimishakavi, Manish Gupta, and Partha Talukdar. 2018. Higher-order Relation Schema Induction using Tensor Factorization with Back-off and Aggregation. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 1575–1584, Melbourne, Australia. Association for Computational Linguistics.
Cite (Informal):
Higher-order Relation Schema Induction using Tensor Factorization with Back-off and Aggregation (Nimishakavi et al., ACL 2018)
Copy Citation:
PDF:
https://aclanthology.org/P18-1146.pdf
Poster:
 P18-1146.Poster.pdf
Code
 madhavcsa/TFBA