Datasets:
Tasks:
Text Classification
Modalities:
Text
Formats:
csv
Languages:
English
Size:
10K - 100K
ArXiv:
License:
Vasily Alexeev commited on
Commit ·
f2e1d62
1
Parent(s): c841396
add info about reproduction
Browse files- README.md +18 -0
- SHA256SUMS +1 -1
README.md
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@@ -182,6 +182,24 @@ Both UTF-8 CSV files have exactly `id,raw_text,vw_text` columns and lexicographi
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NOOW means occurrence order after normalization, not original or reversible prose. English preprocessing uses Python 3.11.15, NLTK 3.9.2 and NLTK-data commit `550b6625bcef1f2abff2ff770a5a0d272c9c6b2a`: WordPunctTokenizer, lowercase, lowercased input token length at least 2 before POS tagging and lemmatization, `averaged_perceptron_tagger_eng`, WordNet POS mapping J/V/N/R with noun fallback, English stopword removal and `lemma.isalpha()` filtering. Output lemmas are not filtered by length and can contain one character. Names are not masked. Near-duplicate shingles use lowercased WordPunct body tokens of length at least two containing letters only.
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## Loading and metadata
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The default configuration is `noow`; the alternative is `bow`. Both expose the full retained population as `corpus`:
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NOOW means occurrence order after normalization, not original or reversible prose. English preprocessing uses Python 3.11.15, NLTK 3.9.2 and NLTK-data commit `550b6625bcef1f2abff2ff770a5a0d272c9c6b2a`: WordPunctTokenizer, lowercase, lowercased input token length at least 2 before POS tagging and lemmatization, `averaged_perceptron_tagger_eng`, WordNet POS mapping J/V/N/R with noun fallback, English stopword removal and `lemma.isalpha()` filtering. Output lemmas are not filtered by length and can contain one character. Names are not masked. Near-duplicate shingles use lowercased WordPunct body tokens of length at least two containing letters only.
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## Reproduce from source
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The shared standalone code is in the [SciNews preprocessing folder](https://huggingface.co/datasets/TopicNet/SciNews/tree/main/preprocessing). Follow its [setup and code-download instructions](https://huggingface.co/datasets/TopicNet/SciNews/blob/main/preprocessing/README.md) to download only that folder at a full commit revision, create the locked Linux x86-64 environment with Python 3.11.15, and record a full server build and verification. Access follows the SciNews repository's permissions. No parent project checkout, BigARTM or TopicNet installation is needed.
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From the directory containing the downloaded `preprocessing/` folder, choose writable source storage and fresh output and scratch paths. First obtain the original `ReadMe.txt` from the [official version 6 release](https://data.mendeley.com/datasets/9rw3vkcfy4/6) and place it at `/path/to/sources/wos/ReadMe.txt`, preserving its exact bytes. Its required size and SHA-256 are listed in the shared instructions and checked by the command:
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```bash
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python preprocessing/prepare.py download --dataset wos-46985 --sources-dir /path/to/sources
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python preprocessing/prepare.py build --dataset wos-46985 \
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--sources-dir /path/to/sources \
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--output-dir /path/to/rebuilt/WOS-46985/data \
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--scratch-dir /path/to/scratch/wos-46985
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python preprocessing/prepare.py verify --dataset wos-46985 \
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--data-dir /path/to/rebuilt/WOS-46985/data
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```
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The download validates the manually supplied notice and provides pinned `wos/WebOfScience.zip` and NLTK resources under the source directory. All three WOS selectors share these sources; the selector above builds WOS-46985. Build and verify run offline after setup. The output contains only `noow.csv`, `bow.csv`, `labels.json`, `splits.json` and `hierarchy.json`; verification compares them with the recorded SHA-256 values. Builds refuse to overwrite outputs. Preserve failed output and scratch files, and use fresh paths for a retry. The shared code's MIT license does not change the source-text rights below.
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## Loading and metadata
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The default configuration is `noow`; the alternative is `bow`. Both expose the full retained population as `corpus`:
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SHA256SUMS
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947f03cf79a99d7f9061220c575021c918ae95f64ab75c4112917be804fb51cd .gitattributes
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-
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6da4ab1e624c4ef61c46600d727770f873ff4db3c15541fb481e7af8a715c0ec SOURCE_README.txt
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039c213b7d7cc3dd2256418443bfc23a8a3e927eadd87ffe5ac08a34f692aebd data/bow.csv
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1f714d3a953c7e3517f647f431d9a5d75f429b05574e66336166f2d5476a1f47 data/hierarchy.json
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947f03cf79a99d7f9061220c575021c918ae95f64ab75c4112917be804fb51cd .gitattributes
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951233a0d25af7650750a0cc4772d7cc3d6f6bf673c2143e375e2d5bfcf682f5 README.md
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6da4ab1e624c4ef61c46600d727770f873ff4db3c15541fb481e7af8a715c0ec SOURCE_README.txt
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039c213b7d7cc3dd2256418443bfc23a8a3e927eadd87ffe5ac08a34f692aebd data/bow.csv
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1f714d3a953c7e3517f647f431d9a5d75f429b05574e66336166f2d5476a1f47 data/hierarchy.json
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