Abstract graphs, abstract paths, grounded paths for Freebase and NELL

Version 1.1
Nastase, Vivi; Kotnis, Bhushan, 2019, "Abstract graphs, abstract paths, grounded paths for Freebase and NELL", https://doi.org/10.11588/data/AVLFPZ, heiDATA, V1
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Description

We describe a method for representing knowledge graphs that capture an intensional representation of the original extensional information. This representation is very compact, and it abstracts away from individual links, allowing us to find better path candidates, as shown by the results of link prediction using this information.

The data in this archive consists of the abstract graphs built from several configurations of Freebase and NELL (used in the experiments described in Gardner et al. 2014), the abstract paths extracted from these graphs, the grounded paths and the negative sampling used in the experiments described in (Nastase and Kotnis, 2019). The motivation for this work was to find better patterns in knowledge graphs than those obtained using the PRA approach.

This dataset contains:

  •  AbstractGraphs_Garder2014data.tar.gz: the abstract graphs
  • AbstractPathsGroundedPaths.tar.gz: the abstract paths, grounded paths, train/test data and the corresponding negative samples (for each abstract graph)

For a brief description of the data in each archive, please see README_AbstractGraphs.txt.

Subject Arts and Humanities; Computer and Information Science
Keyword knowledge graph, abstract graph, link prediction, targeted information extraction
Related Publication

Nastase, V. and Kotnis, B. (2019). Abstract Graphs and Abstract Paths for Knowledge Graph Completion. In Proceedings of the Eighth Joint Conference on Lexical and Computational Semantics (*SEM 2019), June 6-7 2019, Minneapolis, USA.

url: https://www.aclweb.org/anthology/S19-1016
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AbstractGraphs_Garder2014data.tar.gz
Gzip Archive - 2.5 GB
Published Jul 15, 2019
6 Downloads
MD5: dc2a64fb2d88cccf5e62d9400cbca1af
Data
AbstractPathsGroundedPaths.tar.gz
Gzip Archive - 204.7 MB
Published Jul 15, 2019
5 Downloads
MD5: 6dfafe4e7d5b29a882b59f43ec9eb4ae
Data
README_AbstractGraphs.txt
Plain Text - 2.7 KB
Published Jul 15, 2019
25 Downloads
MD5: 4c073cf79f74569a44e3687f97b0be91
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