SharmisthaJat, updated 🕥 2022-12-07 23:49:35

RE-DS-Word-Attention-Models

Paper Link: http://www.akbc.ws/2017/papers/15_paper.pdf Abstract: Distant Supervision (DS) is a popular technique for developing relation extractors starting with limited supervision. We note that most of the sentences in the distant supervision setting are very long and may bene t from word attention for better sentence representation. Our contributions in this paper are threefold. Firstly, we propose two novel word attention models for distantly-supervised relation extraction: (1) a Bi-GRU based word attention model (BGWA), (2) an entity-centric attention model (EA), and a combination model which combines multiple complementary models using weighted voting method for improved relation extraction. Secondly, we introduce GDS, a new distant supervision dataset for relation extraction. GDS removes test data noise present in all previous distant-supervision benchmark datasets, making credible automatic evaluation possible. Thirdly, through extensive experiments on multiple real-world datasets, we demonstrate effectiveness of the proposed methods

Citation: Please cite article https://arxiv.org/abs/1804.06987 , if you find this code useful.

Software required

python 2.7, pytorch 0.1.12 (preferred), also works with pytorch 0.4.0 (tested) cuda 8.0, numpy 1.12.1, sklearn 0.18.2

Running the Model Files

The folder Codes/Models/ has the files for the 3 models: 1. BGWA.py : Bi-GRU based word attention model 2. EA.py : Entity-centric attention model 3. PCNN.py : Piecewise convolutional neural model 4. ENSEMBLE.py : Ensemble model for relation extraction

files 1,2,3 can be run in the following way: python2.7 <file> <data directory> <train file name> <test file name> <dev file name> <word embedding file name> The command has 5 arguments 1. : The name of the directory containing the processed files 2. : The name (not the path) of the processed train file 3. : The name (not the path) of the processed test file 4. : The name (not the path) of the processed dev file 5. : The name (not the path) of the processed word embedding file

File 4 can be run using the following command

``` python2.7 ENSEMBLE.py

``` e.g: Codes/Models$ python2.7 ENSEMBLE.py ../../Data/Ensemble_Data/gids/

Please extract the preprocessed files for riedel dataset before using ensemble model by running the following command

Codes/Models$ unzip ../../Data/Ensemble_Data/riedel2010/preprocessed_dataset.zip

Preprocessing the files

The folder Code/Preprocess/ has the files for preprocessing the data. For the Reidel2010 dataset, just run the file preprocess.sh to get the output files in the same folder. There will be some intermediate files, but the final processed files will have the following name: 1. train_final.p : The processed train files 2. test_final.p : The processed test files 3. dev_final.p : The processed dev files

For the GIDS dataset, just run the file preprocess_GIDS.sh to get the output files in the same folder. There will be some intermediate files, but the final processed files will have the following name: 1. train_final.p : The processed train files 2. test_final.p : The processed test files 3. dev_final.p : The processed dev files

For the two datasets used in the paper you can find pre-processed files at 'Data/Ensemble_Data/gids/preprocessed_dataset/' and 'Data/Ensemble_Data/riedel2010/preprocessed_dataset.zip' (extract in same folder)

Saved Models and PR files

Find all the models and saved pr files from the following public link:

Results_&_ Models

(Generated Precision-Recall (PR) files have precision in 1st column and recall in the second column)

Issues

Bump certifi from 2017.11.5 to 2022.12.7

opened on 2022-12-07 23:49:34 by dependabot[bot]

Bumps certifi from 2017.11.5 to 2022.12.7.

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Bump nbconvert from 5.3.1 to 6.5.1

opened on 2022-08-23 17:14:23 by dependabot[bot]

Bumps nbconvert from 5.3.1 to 6.5.1.

Release notes

Sourced from nbconvert's releases.

Release 6.5.1

No release notes provided.

6.5.0

What's Changed

New Contributors

Full Changelog: https://github.com/jupyter/nbconvert/compare/6.4.5...6.5

6.4.3

What's Changed

New Contributors

Full Changelog: https://github.com/jupyter/nbconvert/compare/6.4.2...6.4.3

6.4.0

What's Changed

New Contributors

... (truncated)

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Bump mistune from 0.8.3 to 2.0.3

opened on 2022-07-29 22:27:46 by dependabot[bot]

Bumps mistune from 0.8.3 to 2.0.3.

Release notes

Sourced from mistune's releases.

Version 2.0.2

Fix escape_url via lepture/mistune#295

Version 2.0.1

Fix XSS for image link syntax.

Version 2.0.0

First release of Mistune v2.

Version 2.0.0 RC1

In this release, we have a Security Fix for harmful links.

Version 2.0.0 Alpha 1

This is the first release of v2. An alpha version for users to have a preview of the new mistune.

Version 0.8.4

  • Support an escaped pipe char in a table cell. #150
  • Fix ordered and unordered list. #152
  • Fix spaces between = in HTML tags
  • Add max_recursive_depth for list and blockquote.
  • Fix fences code block.
Changelog

Sourced from mistune's changelog.

Changelog

Here is the full history of mistune v2.

Version 2.0.4


Released on Jul 15, 2022

    

  • Fix url plugin in &lt;a&gt; tag
    • 

  • Fix * formatting
    • 



Version 2.0.3

Released on Jun 27, 2022

  • Fix table plugin
  • Security fix for CVE-2022-34749

Version 2.0.2


Released on Jan 14, 2022

Fix escape_url


Version 2.0.1

Released on Dec 30, 2021

XSS fix for image link syntax.

Version 2.0.0


Released on Dec 5, 2021

This is the first non-alpha release of mistune v2.


Version 2.0.0rc1

Released on Feb 16, 2021

Version 2.0.0a6


</tr></table>

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Commits
  • 3f422f1 Version bump 2.0.3
  • a6d4321 Fix asteris emphasis regex CVE-2022-34749
  • 5638e46 Merge pull request #307 from jieter/patch-1
  • 0eba471 Fix typo in guide.rst
  • 61e9337 Fix table plugin
  • 76dec68 Add documentation for renderer heading when TOC enabled
  • 799cd11 Version bump 2.0.2
  • babb0cf Merge pull request #295 from dairiki/bug.escape_url
  • fc2cd53 Make mistune.util.escape_url less aggressive
  • 3e8d352 Version bump 2.0.1
  • Additional commits viewable in compare view


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Bump numpy from 1.13.3 to 1.22.0

opened on 2022-06-21 21:17:11 by dependabot[bot]

Bumps numpy from 1.13.3 to 1.22.0.

Release notes

Sourced from numpy's releases.

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)

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Bump notebook from 5.2.2 to 6.4.12

opened on 2022-06-16 23:13:03 by dependabot[bot]

Bumps notebook from 5.2.2 to 6.4.12.

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Bump ipython from 5.5.0 to 7.16.3

opened on 2022-01-21 19:35:34 by dependabot[bot]

Bumps ipython from 5.5.0 to 7.16.3.

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Sharmistha

Joint PhD Student @ Indian Institute of Science (IISc) and Carnegie Mellon University (CMU)

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