Round 2
-Round 2 dataset will consist of metadata of a number of relational tables and - a custom ontology. Stay tuned. -
-From 75bdb7f50306be9f8c5ca567791639ea60f9d613 Mon Sep 17 00:00:00 2001
From: Oktie Hassanzadeh Round 1
JSONL file with each line containing a mapping of a column ID to an array of DBpedia property URIs and scores,
which will be sorted in descending order by score for evaluation. Round 1 data has one mapping for each column,
which is the most relevant property it maps to (e.g., if the column is about movie directors, the correct
- mapping should be https://dbpedia.org/ontology/director). In Round 2, each column may map to more than one
- property/class, or no property/class at all. The provided evaluation script measures Hit@1 and Hit@5. Other
- measures may be added for final evaluation and in Round 2.
Round 2 dataset will consist of metadata of a number of relational tables and - a custom ontology. Stay tuned. -
-Submission: Are you ready? Then, submit up to 4 result sets for the test - set using the Submission Form.
-+ Round 2 dataset + consists of a select set of open data table metadata + that need to be mapped to a custom glossary (dictionary of term labels and descriptions).
-Check out the README file + for input/output format, sample input/output, and an evaluation script. Note that the output of the mapping is a + JSONL file with each line containing a mapping of a column ID to an array of glossary items and scores, + which will be sorted in descending order by score for evaluation. Similar to Round 1 data, Round 2 data has one + mapping for each column, + which is the most relevant glossary item it maps to. We acknowledge that there may be more than one relevant + glossary item suitable for each column, which is why we use Hit@k scores for evaluation. We may use additional + scores that are not included in the evaluate.py script for the final ranking of the submissions.
+ - - - +