pith. sign in
Pith Number

pith:GTDMR7TS

pith:2026:GTDMR7TSQU3WARLF2US7JDQWYO
not attested not anchored not stored refs resolved

Wiki Dumps to Training Corpora: South Slavic Case

Cosimo Palma, Mihailo \v{S}kori\'c

A pipeline extracts and filters text from Wikimedia dumps to build clean corpora for seven South Slavic languages.

arxiv:2604.25384 v2 · 2026-04-28 · cs.CL

Add to your LaTeX paper
\usepackage{pith}
\pithnumber{GTDMR7TSQU3WARLF2US7JDQWYO}

Prints a linked badge after your title and injects PDF metadata. Compiles on arXiv. Learn more · Embed verified badge

Record completeness

1 Bitcoin timestamp
2 Internet Archive
3 Author claim open · sign in to claim
4 Citations open
5 Replications open
Portable graph bundle live · download bundle · merged state
The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same current state with the deterministic merge algorithm.

Claims

C1strongest claim

The n-gram-based filtering strategy detects high levels of textual redundancy between articles and removes such low-quality articles from the corpora entirely, yielding linguistically rich texts suitable for language model training.

C2weakest assumption

That repetitive n-gram patterns reliably mark low-quality database-generated articles while preserving original, high-information content across the seven languages.

C3one line summary

A two-phase pipeline extracts clean text from Wikimedia dumps and applies n-gram filtering to remove repetitive low-quality articles for South Slavic language corpora.

References

44 extracted · 44 resolved · 1 Pith anchors

[1] Wiki Dumps to Training Corpora: South Slavic Case 2026 · arXiv:2604.25384
[2] (version code 20260401) 2026
[3] T ext extraction Once the raw dumps are converted into line‑oriented JSON (JSONL) files, each page is processed in batches to extract usable text and metadata
[4] Initial cleaning and parsing : Applies first regex pass to reduce markup noise and parses the text into a structured representation using mwparserfromhell library
[5] Category handling: Identifies and extract category tags into a separate variable, while also removing category markup from the text

Formal links

2 machine-checked theorem links

Cited by

2 papers in Pith

Receipt and verification
First computed 2026-05-20T00:01:42.084522Z
Builder pith-number-builder-2026-05-17-v1
Signature Pith Ed25519 (pith-v1-2026-05) · public key
Schema pith-number/v1.0

Canonical hash

34c6c8fe728537604565d525f48e16c3bf58e9dbef74b018869706bbd0b871e9

Aliases

arxiv: 2604.25384 · arxiv_version: 2604.25384v2 · doi: 10.48550/arxiv.2604.25384 · pith_short_12: GTDMR7TSQU3W · pith_short_16: GTDMR7TSQU3WARLF · pith_short_8: GTDMR7TS
Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/GTDMR7TSQU3WARLF2US7JDQWYO \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 34c6c8fe728537604565d525f48e16c3bf58e9dbef74b018869706bbd0b871e9
Canonical record JSON
{
  "metadata": {
    "abstract_canon_sha256": "d27b87d2a1fcf8ca6d27a0c3918570e7d1bdad2c72cd160c7bd7391b2a6ea7ec",
    "cross_cats_sorted": [],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.CL",
    "submitted_at": "2026-04-28T08:51:37Z",
    "title_canon_sha256": "b3211b2772f07294cb6d545de1715b11ca00518b8f6f133bac194114bd00fc8a"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2604.25384",
    "kind": "arxiv",
    "version": 2
  }
}