Entity Linking in Queries: Efficiency vs. Effectiveness
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Entity Linking in Queries: Efficiency vs. Effectiveness

This repository contains resources developed within the following paper:

F. Hasibi, K. Balog, and S.E. Bratsberg. “Entity Linking in Queries: Efficiency vs. Effectiveness”,
In proceedings of 39th European Conference on Information Retrieval (ECIR ’17), April 2017.

You can check the paper and presentation for detailed information.

The repository is structured as follows:

  • nordlys/: Code required for running all the experiments
  • data/: Query set and data required for running the code
  • qrels/: Qrels files for ERD and Y-ERD test collections
  • runs/: Run files reported in the paper
  • scripts/: Run and evaluation scripts


Check the nordlys/erd/ for the implementation of ''candidate entity ranking'' and ''disambiguation'' methods. To generate each of the runs, check scripts/run_scripts.sh.

Python v2.7 is required for running the code.


The index and surface form dictionary required for running this code are described in the paper. You can also contact the authors to get them directly. The following files under the data folder are also required for running the code:

  • Y-ERD.tsv: The Y-ERD test collection
  • Trec_beta*.txt: The ERD test collection
  • fb_dbp_snapshot.txt: Snapshot of proper named entities. This file is the intersection of DBpedia 3.9 and Freebase snapshot of proper named entities provided by the ERD challenge 2014 (fb_snapshot_original.tsv.zip is the original file from the ERD challenge).


There are two groups of qrels files, used for 1) ''candidate entity ranking'', and 2) ''disambiguation'' steps. The qrels/*_trec.qrels files belong to the first group, and qrels/*_elq.qrels files belong to the second one.


If you use the resources presented in this repository, please cite:

   author =    {Hasibi, Faegheh and Balog, Krisztian and Bratsberg, Svein Erik},
   title =     {Entity Linking in Queries: Efficiency vs. Effectiveness},
   booktitle = {Proceedings of 39th European Conference on Information Retrieval},
   series =    {ECIR '17},
   year =      {2017},
   pages=      {40--53},
   publisher = {Springer},
   DOI =       {https://doi.org/10.1007/978-3-319-56608-5_4}


If you have any questions, feel free to contact Faegheh Hasibi at faegheh.hasibi@ntnu.no.