Giter Site home page Giter Site logo

psunlpgroup / xsemplr Goto Github PK

View Code? Open in Web Editor NEW
9.0 9.0 1.0 12.78 MB

Data and code for ACL 2023 paper XSemPLR: Cross-Lingual Semantic Parsing in Multiple Natural Languages and Meaning Representations

License: MIT License

Python 44.43% Shell 55.57%
benchmark crosslingual-semantic-parser natural-language-processing semantic-parsing

xsemplr's People

Contributors

chatc avatar

Stargazers

 avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar

Watchers

 avatar  avatar  avatar  avatar  avatar  avatar

Forkers

wxskl

xsemplr's Issues

Issue: Missing Files and Dependencies in mT5 on mSpider Dataset Reproduction

Description:

Hello!
First of all, thank you for open-sourcing your amazing work.

I encountered some issues while trying to reproduce the results of mT5 on the mSpider dataset. (setting: monolingual training on english, which will be used for zero-shot cross-lingual evaluation on other languages). I followed your provided script located here.

Missing dependencies
In order to install the required dependencies, I followed the instructions provided here. However, I couldn't locate the "py3.7pytorch1.8.yaml" file in your repository. It seems to be missing. Could you please upload the dependency file so that I can proceed with the installation?

Missing files

  1. The file mspider.py in line 93 to 113 is responsible for constructing the mSpider dataset. However, the required file for the "db_path" is missing in the repository. As a workaround, I used the original spider db provided from here. Can I use their released db? Additionally, it would be very helpful if you could provide instructions on how to handle this.

  2. The files mspider.py and spider.py require importing "from third_party.miscs.bridge_content_encoder import get_database_matches," but the "miscs" folder is missing from the repository. It would be greatly appreciated if you could upload the missing folder. While searching for similar code, I found a file here in the PICARD repository. Can I use that file as a substitute? Also, It would be amazing if you could upload that file .

  3. In order to evaluate the results, the configuration file used for training requires the spider evaluator, located here. However, the spider evaluator is missing from the "model/UniPSP/metric" directory. Could you please upload the spider evaluator? As a temporary solution, I tried using similar code from here, but the results are not reproducible.
    Could you upload the spider evaluator?

Thank you for your attention to these issues.

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.