Validate US phone area-code candidates using sources with documented reuse terms

オープン
#1,140 コメント 1 件 リアクション 0 件 担当者 0 名 GitHub で見る

メンテナーはふだん 1 日以内に返信

まだ誰も着手していません。

評価

難易度
5/5
見積もり時間
1週間以上
初心者へのやさしさ
35/100
issue の種類
バグ
明瞭さ
明確に書かれている
活発さ
活発
技術スタック
python
領域
data

調査の方向性

Start with data_designer/engine/sampling_gen/entities/phone_number.py and reproduce the 98933 example using PhoneNumber.from_zip_prefix; then inspect the sampler and rebuild tests and the lookup’s manifest, NOTICE, build report, and reconciliation. Identify reusable sources with documented terms and reproducible inputs, validate country, geographic use, active status, and state association, and add regression coverage for invalid or foreign codes and wrong-state associations. Done means regenerating the lookup while preserving ZIP identifiers, population weights, and valid overlay candidates without restoring NANPA-derived exclusions.

索引モデルが issue の本文から書いたものです。

説明

bug

Removing NANPA-derived screening in #1139 restores erroneous Wikidata dialing-code statements to the US phone sampler. We are accepting this data-quality regression for that PR and tracking replacement validation here.

At PR commit 2a6126e0643ad4017ecd5bf78e44077c2b9e31cf:

  • ZIP 98933 always selects 590; before #1139 it selected 509.
  • Indianapolis ZIP 46201 can select unassigned 486.
  • California ZIP 95417 can select Canadian 639.

Reproduce the first example through the public sampler helper:

from data_designer.engine.sampling_gen.entities.phone_number import PhoneNumber

print(PhoneNumber.from_zip_prefix("98933"))
# The area code is always 590.

Comparison with the previously pinned screening reference found 19 newly sampleable codes that fail US/geographic/in-service checks. In total, 91 ZIPs contain a non-US, non-geographic, or out-of-service candidate, accounting for approximately 0.253% of the nationwide sampler probability. This is separate from approximate ZIP boundaries or uncertain overlay market shares.

The current 307 sampler/rebuild tests pass because they verify artifact consistency, weights, numeric shape, and selected regional examples; they do not establish numbering validity.

Expected outcome
  • Establish replacement validation for country, geographic use, active status, and state association using sources with documented reuse terms and reproducible inputs.
  • Regenerate the lookup and update its manifest, NOTICE, build report, and reconciliation.
  • Add regression coverage for invalid/foreign codes and wrong-state associations while preserving ZIP identifiers, population weights, and valid overlay candidates.
  • Keep NANPA-derived exclusions out of the replacement; copying the old list back would restore the dependency #1139 removes.

Review evidence: https://github.com/NVIDIA-NeMo/DataDesigner/pull/1139#issuecomment-6694018381

主要言語
Python
スター
2.4k
フォーク
243
平均マージ
1日 3時間
マージ済み PR(30日)
88

環境構築

はじめの一歩

  1. issue を最後まで読み、次にプロジェクトのコントリビューションガイドを読みます。
  2. 着手することを issue にコメントします — 二人が同じ作業をするのを防げます。
  3. リポジトリをフォークし、ブランチを切って変更します。
  4. issue 番号を参照したプルリクエストを送ります。

NVIDIA-NeMo/DataDesigner のほかの issue

NVIDIA-NeMo/DataDesigner の issue をすべて見る

似ている issue

Python の issue をもっと見る

新しい issue をメールで受け取る

初心者向けの GitHub issue を短くまとめたダイジェスト。