Summary Explorer is a tool to visually explore the state-of-the-art in text summarization.

By Webis
Last update: Aug 14, 2022
Comments: 11

Summary Explorer

Summary Explorer is a tool to visually inspect the summaries from several state-of-the-art neural summarization models across multiple datasets. It provides a guided assessment of summary quality dimensions such as coverage, faithfulness and position bias. You can inspect summaries from a single model or compare multiple models.

The tool currently hosts the outputs of 55 summarization models across three datasets: CNN DailyMail, XSum, and Webis TL;DR.

To integrate your model in Summary Explorer, please prepare your summaries as described here and contact us.

Accepted at EMNLP 2021 (Demo track). A pre-print version of the paper is available here.

Update 17.03.2022

Refactored the text processing pipeline.
Updated local deployment instructions for custom models.

Use cases

1. View Content Coverage of the Summaries

2. Inspect Hallucinations

3. View Named Entity Coverage of the Summaries

4. Inspect Faithfulness via Relation Alignment

5. Compare Agreement among Summaries

6. View Position Bias of a Model

Adding your own model locally

Text processing

Apply the 5-step text processing pipeline from the text-processing sub-directory as shown below.

Tokenization, sentence segmentation, named entity recognition, relation extraction, flattening redundant relations python3 step_1_nlp_pipeline.py --input_dir ../data/raw_files/ --output_dir ../data/nlp-processed/
Lexical alignment of the summary with the source document using ROUGE python3 step_2_lexical_alignment.py --input_dir ../data/nlp-processed/ --output_dir ../data/lexical-alignments/
Semantic alignment of the summary with the source document using BERTScore python3 step_3_semantic_alignment.py --input_dir ../data/lexical-alignments/ --output_dir ../data/semantic-alignments/
ROUGE scores python3 step_4_automatic_evaluation.py --input_dir ../data/semantic-alignments/ --output_dir ../data/automatic-metrics/
Summary compression, summary factuality (entity and relation level), n-gram abstractiveness python3 step_5_document_overlap_metrics.py --input_dir ../data/automatic-metrics/ --output_dir ../data/document-overlap-metrics/

Next, create a models_details.jsonl file which contains meta information about your models. For e.g.,

{"name": "model_1", "title": "model_1 title", "abstract": "TBD", "human evaluation": "TBD", "url": ""}
{"name": "model_2", "title": "model_2 title", "abstract": "TBD", "human evaluation": "TBD", "url": ""} 
{"name": "references", "title": "References", "abstract": "TBD", "human evaluation": "TBD", "url": ""}

Then, create a config.json file with all the paths to the processed articles, summaries and the models_details.jsonl files. This file must also contain your dataset description. For e.g.,

{
  "dataset": {
    "name": "Dataset X",
    "description": "DATASET \n N Articles \n M Models"
  },
  "path_to_models_details_file": "models_details.jsonl",
  "path_to_articles_file": "articles.jsonl",
  "path_to_summaries_files": {
    "references": "references.jsonl",
    "model_1": "model_1.jsonl",
    "model_2": "model_2.jsonl"
  }
}

Setting up the Django app and importing to the local database

In the ui sub-directory:

Install the dependencies

pip install -r requirements.txt

Create a postgres database

psql --username=postgres
CREATE DATABASE sumviz;

To import the database dump file of all the 55 models hosted online psql -h hostname -d sumviz -U username -f dbexport.sql
To import your own models (via the config.json file created above), run the import_dataset command python manage.py import_dataset -c PATH-TO-config.json

Create a .env file with your database settings. For e.g.,

DEBUG=0
SECRET_KEY=**********
DJANGO_ALLOWED_HOSTS=localhost 127.0.0.1 [::1]
SQL_ENGINE=django.db.backends.postgresql_psycopg2
SQL_DATABASE=sumviz
SQL_USER=postgres
SQL_PASSWORD=****
SQL_HOST=db
SQL_PORT=5432
DATABASE=postgres

Start the server python manage.py runserver
Visit http://127.0.0.1:8000/

Note: The tool is in active development and we plan to add new features. Please feel free to report any issues and provide suggestions.

Citation

@inproceedings{syed:2021,
    title = "Summary Explorer: Visualizing the State of the Art in Text Summarization",
    author = {Syed, Shahbaz  and
      Yousef, Tariq  and
      Al Khatib, Khalid  and
      J{\"a}nicke, Stefan  and
      Potthast, Martin},
    booktitle = "Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing: System Demonstrations",
    year = "2021",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2021.emnlp-demo.22"
}

Acknowledgements

We sincerely thank all the authors who made their code and model outputs publicly available, meta evaluations of Fabbri et al., 2020 and Bhandari et al., 2020, and the summarization leaderboard at NLP-Progress.

We hope this encourages more authors to share their models and summaries to help track the qualitative progress in text summarization research.

Github

https://github.com/webis-de/summary-explorer

Comments(11)

1

Bump loader-utils from 1.4.0 to 1.4.1 in /ui/frontend
Bumps loader-utils from 1.4.0 to 1.4.1.
Release notes

Sourced from loader-utils's releases.
v1.4.1

1.4.1 (2022-11-07)

Bug Fixes
- security problem (#220) (4504e34)
Changelog

Sourced from loader-utils's changelog.
1.4.1 (2022-11-07)

Bug Fixes
- security problem (#220) (4504e34)
Commits
- 8f082b3 chore(release): 1.4.1
- 4504e34 fix: security problem (#220)
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2

Bump follow-redirects from 1.13.0 to 1.14.7 in /ui/frontend
Bumps follow-redirects from 1.13.0 to 1.14.7.
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- 2ede36d Release version 1.14.7 of the npm package.
- 8b347cb Drop Cookie header across domains.
- 6f5029a Release version 1.14.6 of the npm package.
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- 2ad9e82 Carry over Host header on relative redirects (#172)
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3

Bump django from 3.0.6 to 3.1.12 in /ui
Bumps django from 3.0.6 to 3.1.12.
Commits
- 625d3c1 [3.1.x] Bumped version for 3.1.12 release.
- 203d4ab [3.1.x] Fixed CVE-2021-33571 -- Prevented leading zeros in IPv4 addresses.
- 20c67a0 [3.1.x] Fixed CVE-2021-33203 -- Fixed potential path-traversal via admindocs'...
- aa8781c [3.1.x] Confirmed release date for Django 3.1.12, and 2.2.24.
- a4eb07a [3.1.x] Fixed typo in MiddlewareMixin deprecation note.
- c7fdc79 [3.1.x] Added stub release notes and date for Django 3.1.12 and 2.2.24.
- 024e969 [3.1.x] Changed IRC references to Libera.Chat.
- c53a76b [3.1.x] Post-release version bump.
- 6efdf1b [3.1.x] Bumped version for 3.1.11 release.
- b7d4a6f [3.1.x] Fixed #32718 -- Relaxed file name validation in FileField.
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4

Bump djangorestframework from 3.11.0 to 3.11.2 in /ui
Bumps djangorestframework from 3.11.0 to 3.11.2.
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- 4121b01 Deprecate urlize_quoted_links in favor of Django's built-in urlize
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5

Bump follow-redirects from 1.13.0 to 1.14.8 in /ui/frontend
Bumps follow-redirects from 1.13.0 to 1.14.8.
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- 3d81dc3 Release version 1.14.8 of the npm package.
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- 2ede36d Release version 1.14.7 of the npm package.
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- 6f5029a Release version 1.14.6 of the npm package.
- af706be Ignore null headers.
- d01ab7a Release version 1.14.5 of the npm package.
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6

Bump decode-uri-component from 0.2.0 to 0.2.2 in /ui/frontend
Bumps decode-uri-component from 0.2.0 to 0.2.2.
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v0.2.2
- Prevent overwriting previously decoded tokens 980e0bf
https://github.com/SamVerschueren/decode-uri-component/compare/v0.2.1...v0.2.2

v0.2.1
- Switch to GitHub workflows 76abc93
- Fix issue where decode throws - fixes #6 746ca5d
- Update license (#1) 486d7e2
- Tidelift tasks a650457
- Meta tweaks 66e1c28
https://github.com/SamVerschueren/decode-uri-component/compare/v0.2.0...v0.2.1
Commits
- a0eea46 0.2.2
- 980e0bf Prevent overwriting previously decoded tokens
- 3c8a373 0.2.1
- 76abc93 Switch to GitHub workflows
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- 486d7e2 Update license (#1)
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7

Bump loader-utils from 1.4.0 to 1.4.2 in /ui/frontend
Bumps loader-utils from 1.4.0 to 1.4.2.
Release notes

Sourced from loader-utils's releases.
v1.4.2

1.4.2 (2022-11-11)

Bug Fixes
- ReDoS problem (#226) (17cbf8f)
v1.4.1

1.4.1 (2022-11-07)

Bug Fixes
- security problem (#220) (4504e34)
Changelog

Sourced from loader-utils's changelog.
1.4.2 (2022-11-11)

Bug Fixes
- ReDoS problem (#226) (17cbf8f)
1.4.1 (2022-11-07)

Bug Fixes
- security problem (#220) (4504e34)
Commits
- 331ad50 chore(release): 1.4.2
- 17cbf8f fix: ReDoS problem (#226)
- 8f082b3 chore(release): 1.4.1
- 4504e34 fix: security problem (#220)
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8

Bump minimatch from 3.0.4 to 3.1.2 in /ui/frontend
Bumps minimatch from 3.0.4 to 3.1.2.
Commits
- 699c459 3.1.2
- 2f2b5ff fix: trim pattern
- 25d7c0d 3.1.1
- 55dda29 fix: treat nocase:true as always having magic
- 5e1fb8d 3.1.0
- f8145c5 Add 'allowWindowsEscape' option
- 570e8b1 add publishConfig for v3 publishes
- 5b7cd33 3.0.6
- 20b4b56 [fix] revert all breaking syntax changes
- 2ff0388 document, expose, and test 'partial:true' option
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9

Bump terser from 4.8.0 to 4.8.1 in /ui/frontend
Bumps terser from 4.8.0 to 4.8.1.
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v4.8.1 (backport)
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10

Bump numpy from 1.19.5 to 1.22.0 in /ui
Bumps numpy from 1.19.5 to 1.22.0.
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v1.22.0

NumPy 1.22.0 Release Notes

NumPy 1.22.0 is a big release featuring the work of 153 contributors spread over 609 pull requests. There have been many improvements, highlights are:
- Annotations of the main namespace are essentially complete. Upstream is a moving target, so there will likely be further improvements, but the major work is done. This is probably the most user visible enhancement in this release.
- A preliminary version of the proposed Array-API is provided. This is a step in creating a standard collection of functions that can be used across application such as CuPy and JAX.
- NumPy now has a DLPack backend. DLPack provides a common interchange format for array (tensor) data.
- New methods for quantile, percentile, and related functions. The new methods provide a complete set of the methods commonly found in the literature.
- A new configurable allocator for use by downstream projects.
These are in addition to the ongoing work to provide SIMD support for commonly used functions, improvements to F2PY, and better documentation.

The Python versions supported in this release are 3.8-3.10, Python 3.7 has been dropped. Note that 32 bit wheels are only provided for Python 3.8 and 3.9 on Windows, all other wheels are 64 bits on account of Ubuntu, Fedora, and other Linux distributions dropping 32 bit support. All 64 bit wheels are also linked with 64 bit integer OpenBLAS, which should fix the occasional problems encountered by folks using truly huge arrays.

Expired deprecations

Deprecated numeric style dtype strings have been removed

Using the strings "Bytes0", "Datetime64", "Str0", "Uint32", and "Uint64" as a dtype will now raise a TypeError.

(gh-19539)

Expired deprecations for loads, ndfromtxt, and mafromtxt in npyio

numpy.loads was deprecated in v1.15, with the recommendation that users use pickle.loads instead. ndfromtxt and mafromtxt were both deprecated in v1.17 - users should use numpy.genfromtxt instead with the appropriate value for the usemask parameter.

(gh-19615)
... (truncated)
Commits
- 4adc87d Merge pull request #20685 from charris/prepare-for-1.22.0-release
- fd66547 REL: Prepare for the NumPy 1.22.0 release.
- 125304b wip
- c283859 Merge pull request #20682 from charris/backport-20416
- 5399c03 Merge pull request #20681 from charris/backport-20954
- f9c45f8 Merge pull request #20680 from charris/backport-20663
- 794b36f Update armccompiler.py
- d93b14e Update test_public_api.py
- 7662c07 Update init.py
- 311ab52 Update armccompiler.py
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11

Bump lodash from 4.17.20 to 4.17.21 in /ui/frontend
Bumps lodash from 4.17.20 to 4.17.21.
Commits
- f299b52 Bump to v4.17.21
- c4847eb Improve performance of toNumber, trim and trimEnd on large input strings
- 3469357 Prevent command injection through _.template's variable option
- See full diff in compare view
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