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---
dataset_info:
- config_name: auto
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  - name: id
    dtype: string
  - name: context
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  - name: fields
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  - name: metadata
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  download_size: 3083883
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- config_name: book
  features:
  - name: id
    dtype: string
  - name: context
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  - name: fields
    dtype: string
  - name: metadata
    dtype: string
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    num_examples: 250
  - name: test
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    num_examples: 250
  download_size: 4421087
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- config_name: camera
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  - name: context
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  - name: fields
    dtype: string
  - name: metadata
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- config_name: job
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  - name: context
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  - name: fields
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  - name: metadata
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- config_name: movie
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  - name: fields
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- config_name: nbaplayer
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    dtype: string
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- config_name: restaurant
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  - name: fields
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- config_name: university
  features:
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  dataset_size: 11018752
configs:
- config_name: auto
  data_files:
  - split: train
    path: auto/train-*
  - split: validation
    path: auto/validation-*
  - split: test
    path: auto/test-*
- config_name: book
  data_files:
  - split: train
    path: book/train-*
  - split: validation
    path: book/validation-*
  - split: test
    path: book/test-*
- config_name: camera
  data_files:
  - split: train
    path: camera/train-*
  - split: validation
    path: camera/validation-*
  - split: test
    path: camera/test-*
- config_name: job
  data_files:
  - split: train
    path: job/train-*
  - split: validation
    path: job/validation-*
  - split: test
    path: job/test-*
- config_name: movie
  data_files:
  - split: train
    path: movie/train-*
  - split: validation
    path: movie/validation-*
  - split: test
    path: movie/test-*
- config_name: nbaplayer
  data_files:
  - split: train
    path: nbaplayer/train-*
  - split: validation
    path: nbaplayer/validation-*
  - split: test
    path: nbaplayer/test-*
- config_name: restaurant
  data_files:
  - split: train
    path: restaurant/train-*
  - split: validation
    path: restaurant/validation-*
  - split: test
    path: restaurant/test-*
- config_name: university
  data_files:
  - split: train
    path: university/train-*
  - split: validation
    path: university/validation-*
  - split: test
    path: university/test-*
license: other
source_datasets: []
tags:
- decision-model
---

# swde

SWDE (Hao et al., SIGIR 2011) attribute records over the visible text of real web pages.

SWDE has 124,291 product, book, job, movie, player, restaurant, car and university pages from 80
websites (8 verticals, 10 sites each), each page one entity, with page-level values of 3 to 5
attributes per vertical labelled by per-site handcrafted regular expressions over DOM text nodes
(procedural labels; ``<NULL>`` when the page has no value). Each page's HTML is converted to
visible text (``VisibleText``) and every value is located verbatim, word-bounded, after decoding
character references and collapsing whitespace; attributes with an unlocated value are left out,
never turned into nulls. Pages longer than ``window`` characters are cut to one window holding
every located value. One config per vertical; one row per page with ``fields`` =
``{attribute: [[(start, value), ...] per distinct value]}`` (JSON, empty for a labelled null).
SWDE has no official split: each vertical's ten sites are split by hash (8 train, 1 validation,
1 test; ``swde_split``), so evaluation websites are unseen. Pages are template-generated, so each
site contributes its ``pages_per_site`` lowest-hash eligible pages.

Original data: [original distribution](http://web.archive.org/web/20210630013015id_/https://codeplexarchive.blob.core.windows.net/archive/projects/swde/swde.zip). Repackaged as parquet for [tasksource](https://github.com/sileod/tasksource) by [scripts/repackage_dataset/web_extraction.py](https://github.com/sileod/tasksource/blob/main/scripts/repackage_dataset/web_extraction.py#L440).

[Conversion provenance](provenance.json): source revisions, hashes, configuration and exclusions.