This project is based on the work described at [1]. The original code referred to in the paper is now hosted and can be downloaded from here. The code has then been significantly improved, undergone a lot of refactorization and re-implementation, and therefore, may not work with the cache included in the published data here.
In addition to TableMiner+, this project provides implementation of several other semantic table interpretation algorithms, including: Joint Inference based on Liamye2011, and Semantic Message Passing based on Mulwad2013. However, due to many things out of our control (e.g., use of in-house software in original works, different versions of knowledge bases), please note that we cannot guarantee identical replication of the original systems or reproduction of experiment results.
Part of this work was funded by the EPSRC project LODIE - Linked Open Data for Information Extraction, EP/ J019488/1.
Apache 2.0
- Place a copy of STI on your computer
- Run mvninstal.bat to add two libraries to your local maven repository
- Download test data, from here
- Unzip the test data, into e.g., [sti_data]
- Navigate into [sti_data/dataset], unzip, depending on the test cases: imdb.tar.gz for the IMDB dataset; musicbrainz.tar.gz for the MusicBrainz dataset; Limaye200.tar.gz for the Limaye200 dataset; Limaye_complete.tar.gz for the LimayeAll dataset
- Configure your local copy of STI
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- open 'sti.properties', as a minimum, you need to change 'sti.home', and 'sti.cache.main.dir'. Please follow the documentation inside the property file
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- open 'kbsearch.properties', as a minimum, you need to change 'kb.search.result.stoplistfile', and 'fb.query.api.key' to use your own Freebase API key
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- open 'websearch.properties', as a minimum, you need to change 'bing.keys' to use your own bing web search key
- Run a test case. For example, to run TMP, use: uk.ac.shef.dcs.sti.experiment.TableMinerPlusBatch "[sti_data/Limaye200]" "[output_dir]" "/[sit_home_dir]/sti.properties"
Note: 'sti.properties' distributed with code is a default configuration for Limaye200 and LimayeAll datasets; for IMDB and MusicBrainz datasets, you can edit a template inside '/resources'. For both IMDB and MusicBrainz, you may want to provide the VM variable '-Djava.util.logging.config.file=' to configure the logging output of the any23-sti module (which can produce too many logs).
[1] Under minor revision review: http://www.semantic-web-journal.net/content/effective-and-efficient-semantic-table-interpretation-using-tableminer-0