Git Product home page Git Product logo

legal_summarization's Introduction

Plain English Summarization of Contracts

Please cite our NAACL NLLP Workshop paper as:

@inproceedings{manor-li-2019-plain,
    title = "Plain {E}nglish Summarization of Contracts",
    author = "Manor, Laura  and
      Li, Junyi Jessy",
    booktitle = "Proceedings of the Natural Legal Language Processing Workshop 2019",
    month = jun,
    year = "2019",
    address = "Minneapolis, Minnesota",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/W19-2201",
    pages = "1--11",
}

Files

Data

This dataset consists of the data included in the quantitative analysis as described in the paper. Sets which had a reference summary with more tokens than the original text are excluded. Each set consists of:

  • uid: unique identification string
  • original_text: cleaned & parsed original text
  • reference_summary: cleaned & parsed reference summary
  • doc: name of the document which the original text is from

TL;DRLegal

Each tldrlegal set may also have:

  • title: "title" of the set (from website)

TOS;DR

Each tos;dr set may also have:

  • note: Mostly empty, a space for additional notes from the annotator
  • urls: URL of the respective company
  • case_text: raw text from the "case" (from website)
  • case_code: annotation for "case" text
  • title_text: raw text from the "title" (from website)
  • title_code: annotation for "title" text
  • tldr_text: raw text from the "tldr" (from website)
  • tldr_code: annotation for "tldr"

A note on annotation:

  • Each code begins with a number, which is the 'ranking' of the quality of the respective text as chosen by the annotator
  • A code may also have a letter, which stands for:
    • s: standard -- this exact text (without company names) occurs at least one other time in a different set.
    • j: jurisdication -- this text deals with jurisdiction
    • q-: quote(-) -- this text is excerpt of the original text
    • d: description -- this text is a description of what the original text talks about, but may not give details

legal_summarization's People

Contributors

lauramanor avatar

Watchers

James Cloos 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.