Skip to main content

A framework for disambiguation

Project description

Tarte

A secondary layer for pie for disambiguation

What it aims to do

  • This tagger is supposed to come as a secondary layer for lemma that should be disambiguated.
  • Its core object (Tarte) should filter things that need to be disambiguated
  • Its training capacities should reorganize a training set so that it dispatch training samples across all sets and it should not care about sample not containing unambiguous tokens.
  • It takes POS, lemma context and form characters into the network to predict the disambiguated form.

Notes

  • Given that not all sentences will have things to disambiguate, pretraining vector might be an important task. It is possible with PyTorch to load Gensim data easily. This would require to generate temps file where lemma AND pos are fed to fake sentences.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

nlp_tarte-0.0.1.tar.gz (20.6 kB view details)

Uploaded Source

Built Distribution

nlp_tarte-0.0.1-py2.py3-none-any.whl (25.6 kB view details)

Uploaded Python 2 Python 3

File details

Details for the file nlp_tarte-0.0.1.tar.gz.

File metadata

  • Download URL: nlp_tarte-0.0.1.tar.gz
  • Upload date:
  • Size: 20.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.13.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.1.0 requests-toolbelt/0.9.1 tqdm/4.23.3 CPython/3.6.8

File hashes

Hashes for nlp_tarte-0.0.1.tar.gz
Algorithm Hash digest
SHA256 d08a64d07595fd83d290d82ddd992160ab66be8d521cf7b6eb4a8f9c9529a1e8
MD5 5dabac05f9454d83e405bdcfc6a7b590
BLAKE2b-256 8f6c1ffbcb00902a806668f9bc58c35be7d91dbc93070d0934ece0757fb92c23

See more details on using hashes here.

File details

Details for the file nlp_tarte-0.0.1-py2.py3-none-any.whl.

File metadata

  • Download URL: nlp_tarte-0.0.1-py2.py3-none-any.whl
  • Upload date:
  • Size: 25.6 kB
  • Tags: Python 2, Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.13.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.1.0 requests-toolbelt/0.9.1 tqdm/4.23.3 CPython/3.6.8

File hashes

Hashes for nlp_tarte-0.0.1-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 bc82d3828c13e34944b51bc737f369ab94a3621d1151227342546b599596e295
MD5 7c8c484c31778b329bf58f33d3942854
BLAKE2b-256 fc662b2fcef56a4c92d82888d74c4711db95fa0aea445a841c29c73275629c58

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page