Giter Club home page Giter Club logo

neleval's Introduction

Entity linking evaluation

Python evaluation scripts for TAC entity linking and related wikification, named entity disambiguation, and within- and cross-document coreference tasks.

It aims for fast and flexible coreference resolution and sophisticated named entity recognition evaluation, such as partial scores for partial overlap between gold and system mentions. CEAF, in particular, is much faster to calculate here than in the CoNLL-11/12 scorer. It boasts features such as configurable metrics; accounting for or ignoring cross-document coreference (see the evaluate --by-doc flag); plotting to compare evaluation by system, measure and corpus subset; and bootstrap-based confidence interval calculation for document-wise evaluation metrics.

Requires that python (2.7, with Py3k support experimental/partial) be installed on your system with numpy (and preferably scipy for fast CEAF calculation) and joblib. matplotlib is required for the plot-systems command.

See a list of commands with:

./nel --help

Or install onto your Python path (e.g. with pip install git+https://github.com/wikilinks/neleval) then

python -m neleval --help

TAC-KBP 2014 EDL quickstart

./scripts/run_tac14_evaluation.sh \
    /path/to/gold.xml \              # TAC14 gold standard queries/mentions
    /path/to/gold.tab \              # TAC14 gold standard link and nil annotations
    /system/output/directory \       # directory containing (only) TAC14 system output files
    /script/output/directory \       # directory to which results are written
    number_of_jobs                   # number of jobs for parallel mode

Each file in in the system output directory is scored against gold.tab.

Similar facility is available for TAC-KBP'15 EDL.

More details

See the project wiki for more details.

References

This project extends the work described in:

It was used as the official scorer for Entity (Discovery and) Linking in 2014 and 2015:

  • Heng Ji, Joel Nothman and Ben Hachey (2014), "Overview of TAC-KBP2014 Entity Discovery and Linking Tasks", In Proceedings of the Text Analysis Conference.
  • Heng Ji, Joel Nothman, Ben Hachey and Radu Florian (2015), "Overview of TAC-KBP2015 Tri-lingual Entity Discovery and Linking Tasks", In Proceedings of the Text Analysis Conference.

neleval's People

Contributors

benhachey avatar jnothman avatar wejradford avatar

Watchers

 avatar  avatar  avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.