G-reen/model-family-detector
Text Classification • Updated
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Model-family detector: steps 2 + 3, cleaned train set (version 3)
The training pool for a classifier that predicts which LLM family (OpenAI / Anthropic / Gemini / Other) wrote a piece of long-form writing, with an auxiliary human-vs-AI head (Human rows are used only by that head). One config per source, identical schema in every config. No balancing or capping has been applied; that is the next step.
from datasets import load_dataset
ds = load_dataset("G-reen/model-family-step23-train", "anthropic_persuasion", split="train")
Funnel
| stage | rows | of step 1 |
|---|---|---|
| step 1 (all configs, incl. the ones later removed) | 3,472,346 | 100% |
| after the rule pre-filter | 1,392,328 | 40.1% |
| first judge: WRITING | 1,096,484 | 31.6% |
| version 3 (this repo) | 730,625 | 21.0% |
Rows by family: OpenAI 119,125, Anthropic 75,958, Gemini 32,307, Other 200,376, Human 302,859.
Forms (judge label): article 265,774, story 168,401, blog_post 88,609, news 57,194, essay 44,659, review 43,537, opinion 18,271, other 15,503, academic 7,152, report 6,652, unknown 5,966, speech 5,567, letter 3,340.
Configs removed in version 2: defactify_valtest (D1 adversarially perturbed text); ahmadreza_human_vs_ai (D2 FLAN answers + truncated Wikipedia leads); hc3 (D4 tokenized human text + Q&A answers); crownelius_opus45 (D5 suspect provenance).
What versions 2 and 3 change
Version 3 (after the second audit)
A second four-part audit of version 2 found the remaining problems listed in reports/step23_v2/AUDIT_MERGED_V2.md.
Version 3 changes:
- Safety sweep redone. Every row of the chat-derived, instruct and fiction configs was reviewed by the LLM on its full text (long texts in overlapping windows) with no keyword pre-filter, and every flagged window was re-checked by a second confirmation prompt; rows are removed only when both agree (or the second pass is unparseable). Rows the version-2 keyword sweep had removed for adult-only or non-sexual content were restored. The step-1 repo was purged with the same list and squashed.
- Second bot templates removed: the koala/vicuna "Give me an introduction over 200 words for , a chemical company in ..." prompt (half of lmsys_chat_1m Other) and the WildChat YouTube video-script bot; plus a generic cap of 20 rows per normalized prompt template in the chat-derived configs. Rows without a prompt-judge form, verse-dominated rows and table rows are dropped there as well.
- Trimming fixed: sentence ends are abbreviation- and initial-aware (Mr., U.S., J.R.R., list numbers) and require a
following capital or quote; sign-off lines, hashtags, URLs, emoji and closing quotes count as complete endings;
dangling
*/**/quotes after a trim are balanced. - Paragraphs: verse, greentext and markdown hard breaks keep their single newlines; wrapped lines are joined only when the break is clearly mid-sentence (no terminal punctuation and a lowercase or comma continuation).
- Opener stripping removes only an acknowledgement paragraph (and a
---right after it); headings and content around rules are never removed; refusal and AI-self-reference checks run on the untouched head, so such rows are dropped rather than trimmed. More opener forms ("Okay, let's", "I will write", "Hi !"). - Tail residue: END markers anywhere in the last quarter (with whatever follows), word-count notes, italic author's
notes, "please note" tails, "Introduction:/Body:/Conclusion:" scaffold labels, "(N words)" budgets, star-rating lines in
the head, "by Your AI Assistant" bylines, every
:::fence variant, "",<start_of_story>. - Encoding: mojibake repaired with ftfy (quotes and dashes left as they are); literal
\nunescaped also in mixed texts when the escape is followed by whitespace, a capital, a digit or a quote (LaTeX commands are lowercase). - Human scraped text: subset-filter spans shorter than 30% of the original and rows that still carry navigation or DailyMail markers are dropped; fallback rows with such markers are dropped; the detokenizer also repairs " . " line markers, curly-quote spacing and "gon na"/"WO N'T"; gsingh_claude_sonnet Human rows (NYT summaries + transcripts) are dropped.
- fastdetector: "Label: title" first lines and trailing label lines are stripped as well; rows left with a hole
where a label was removed ("At, we believe ...") are dropped; rows from "write sloppily" prompts are flagged
adversarial_sloppiness_prompt. - Other drops: wider placeholder patterns (digits, long brackets, "XYZ Company", "______", "${...}"), stricter repetition rule, any structural HTML tag, editlens/imbue edited rows that lexically copy their source, the remaining near-duplicate pairs (now keyed on model id and group key as well as source index), gradtex closed-family rows.
- Test sets: Intel inline bold form labels ("Strengths:") removed, text kept.
- Metadata:
model_erafrom a model-id table that honours date suffixes; model-id aliases unified (claude-sonnet-4.6 -> claude-sonnet-4-6); the first judge's genre and the prompt judge's form are kept separately (judge:<genre>andform:<form>flags;extra.judge_genre,extra.pjudge.form); prompt keys for cross-config grouping are normalized for case, whitespace and quote style and require at least six content words. - Not changed on purpose: screenplays and dialogue scripts that are genuine creative pieces stay; fastdetector rewrites that paraphrase their human source structurally stay; fastdetector Human rows are not genre-filtered; titles, closing offers, double spaces, rule lines, typography, length and the old-model share are handled at training time.
Version 2 (after the first audit)
This is version 2 of the cleaned data. A four-part audit of version 1 (manual reads of about 4,300 rows, trivial-signal probes, full-data hygiene statistics) found residual boilerplate, non-writing chat answers, corrupted sources and several bugs in the first cleaner; the changes below respond to it.
Configs removed entirely: defactify_valtest (text deliberately perturbed with junk tokens), ahmadreza_human_vs_ai
(FLAN task answers and truncated Wikipedia leads), hc3 (tokenized human answers, Q&A register), crownelius_opus45
(suspect provenance), and the benchmark2026 test set (unreliable model labels). gradtex keeps only fully generated
AI rows. PaLM-2 rows are removed.
Additional row filters (counts per config in the table below):
| reason | drops a row when |
|---|---|
| unsafe_content | sexual content involving minors, bestiality, sexual content about real people, or mass-harm instructions (LMSYS moderation tags, or a keyword pre-filter followed by an LLM check); ordinary adult NSFW is kept |
| pjudge_not_requested_writing / pjudge_not_standalone_piece / pjudge_missing | chat-derived configs only (lmsys_chat_1m, lmsys_gpt5, lmarena x3, wildchat, norquinal_claude, claude_opus_instruct): a second gemma-4-E4B judge that also sees the USER PROMPT must agree that the user asked for a standalone piece of prose (story, essay, article, blog post, op-ed, review, speech, letter) and that the response is that piece rather than an answer addressed to the user |
| bot_template / screenplay / dialogue_script / forum_thread | "[sys1]...[end sys1]" synthetic-data bot output, INT./EXT./FADE screenplay markers, 5+ speaker-label lines making up 30%+ of lines, fake forum threads |
| prompt_template_spam | the "Write an article about ... in chemical industry" bot prompt |
| ai_self_reference | "As an AI language model", "my knowledge cutoff", "I'm Grok/ChatGPT/Claude ..." |
| degenerate_repetition | a 10-word sequence repeated 4+ times |
| mixed_script / html_markup / leak_string / continuation_stub | CJK characters inside English text, link/table/script HTML, content-filter or system-prompt leaks, "[The article continues ...]" stubs |
| refusal / unfilled_placeholder / filler_output / meta_commentary / encoding_damage / structured_form / too_short / exact_duplicate | as in version 1, with wider refusal and placeholder patterns; rows the source flags as refusal-headed are dropped |
| copies_human_structure | fastdetector rewrites whose word 5-gram Jaccard with their human original is >= 0.25 or whose word-sequence similarity is >= 0.5 |
| near_duplicate | one side of every MinHash near-duplicate pair (5-word shingles, Jaccard >= 0.8); when a Human row and an AI row collide the Human row is kept |
| subset_filter_failed | scraped NYT human pages for which the contiguous-subset filter returned nothing usable |
| truncated_unrecoverable | no sentence end in the last 30% of the text |
| gradtex_not_fully_generated / palm2_dropped | see above |
Transforms (recorded as clean:<name> in metadata.quality_flags):
| transform | effect |
|---|---|
| fix_encoding | mojibake repair; literal \n/\t are unescaped only in texts with no real newline and never inside LaTeX commands |
| template_tokens / wrapper_tags / html_tags / canvas_fence | chat-template tokens (<end_of_turn>, <|im_end|>), zero-width characters, <document> wrappers, <br>/<b>/<p> tags (text kept), :::writing fences |
| strip_wrapper_boilerplate / chat_opener | acknowledgement openers ("Sure, here is ...", "Of course!", "Based on the provided context ...") up to 60 words, AI rows only |
| star_line / ai_byline / ui_footer / reply_finished / end_marker / wordcount / note_tail | rating-star lines, "by Claude ..." bylines, ChatGPT UI footer, "Reply finished", "THE END" / "END", "Word count: N" and "(75 words)" budgets, trailing "Note:" paragraphs; AI rows only |
| format_topic_label | fastdetector rewrites that begin with the template's format/topic label ("Knowledge Article / Topic: Finance") |
| llm_subset_filter | scraped human text (NYT pages; editlens/imbue human rows) replaced by the longest clean contiguous span chosen by fastdetector's filter prompt. The kept text is re-extracted from the ORIGINAL characters with is_loose_subset, so it is always a literal substring of the human text; where the check fails the original is kept (flag subset_filter_fallback_original) or, for NYT pages, the row is dropped |
| detokenize | Penn-Treebank spacing ("do n't", " , ", "`` ''") repaired |
| trim_incomplete_tail | text that does not end in terminal punctuation is cut back to its last complete sentence (train and test) |
| canonical_paragraphs | hard-wrapped lines are joined and every paragraph is separated by exactly one blank line |
Deliberately NOT done in the data: titles (markdown headings, bold title lines, "Title:" labels) and closing offers ("Would you like me to ...") are left in place. They are removed at random by the training-time regularizer, together with quote/dash/markdown/whitespace normalization and random chunking.
Metadata: model_era now comes from a model-id table; group_key is a cross-config component id (rows that share a
prompt, a source document or an LMSYS conversation in ANY config share a key; the previous key is in
metadata.extra.group_key_step1); language is en for every row; metadata.extra.pipeline is v3.
Final configs
| config | rows | mean words | OpenAI | Anthropic | Gemini | Other | Human | license |
|---|---|---|---|---|---|---|---|---|
| anthropic_persuasion | 1,308 | 244 | 0 | 1,134 | 0 | 0 | 174 | cc-by-nc-sa-4.0 |
| biscope | 19,797 | 487 | 8,427 | 7,872 | 2,928 | 0 | 570 | cc-by-nc-nd-4.0 (HF card; GitHub says cc-by-sa-4.0) |
| claude_opus_instruct | 5,587 | 500 | 0 | 5,587 | 0 | 0 | 0 | apache-2.0 (prompts from unlicensed Norquinal set) |
| editlens_iclr | 41,829 | 352 | 7,623 | 8,682 | 7,456 | 2,733 | 15,335 | none stated; gated with non-commercial-only access terms |
| fastdetector_train_stat | 398,100 | 593 | 3,098 | 1,702 | 0 | 124,816 | 268,484 | none stated (own data; Common Crawl upstream, ODC-By) |
| ghostbuster_essay | 6,276 | 534 | 4,331 | 981 | 0 | 0 | 964 | cc-by-3.0 (third-party re-upload); human essays IvyPanda (copyrighted) |
| ghostbuster_news | 6,226 | 489 | 4,329 | 936 | 0 | 0 | 961 | cc-by-3.0; human text Reuters RCV1 (research agreement) |
| ghostbuster_stories | 6,469 | 535 | 4,594 | 974 | 0 | 0 | 901 | cc-by-3.0; human text r/WritingPrompts |
| gradtex | 3,204 | 356 | 0 | 0 | 0 | 3,204 | 0 | cc-by-4.0 over MAGE (apache-2.0); upstream corpora incl. non-commercial sources |
| gryphe_gpt4o_wp | 3,734 | 1171 | 3,734 | 0 | 0 | 0 | 0 | none stated (HF default all rights reserved) |
| gryphe_opus_wp | 8,956 | 838 | 3,007 | 5,949 | 0 | 0 | 0 | none stated (HF default all rights reserved) |
| gsingh_claude_sonnet | 4,523 | 384 | 0 | 4,523 | 0 | 0 | 0 | none stated; NYT content |
| gsingh_gemini_flash | 3,401 | 353 | 0 | 0 | 3,401 | 0 | 0 | none stated; NYT content |
| gsingh_train | 33,256 | 433 | 1,301 | 0 | 0 | 29,918 | 2,037 | none stated; NYT content (Defactify-4 train) |
| imbue_demo | 33,498 | 384 | 6,472 | 6,335 | 7,258 | 0 | 13,433 | cc-by-nc-sa-4.0 |
| lmarena_100k | 5,922 | 459 | 1,111 | 561 | 630 | 3,620 | 0 | none stated in YAML; README: prompts cc-by-4.0, outputs under provider ToS |
| lmarena_140k | 2,925 | 610 | 421 | 632 | 453 | 1,419 | 0 | cc-by-4.0 (prompts); outputs under provider ToS |
| lmarena_55k | 4,753 | 348 | 1,384 | 549 | 127 | 2,693 | 0 | apache-2.0 (Kaggle re-host) |
| lmsys_chat_1m | 12,274 | 281 | 138 | 201 | 0 | 11,935 | 0 | LMSYS-Chat-1M Dataset License Agreement (gated; no redistribution) |
| lmsys_gpt5 | 8,532 | 403 | 8,532 | 0 | 0 | 0 | 0 | cc-by-4.0 (card); prompts from LMSYS-Chat-1M (no redistribution) |
| norquinal_claude | 13,818 | 273 | 0 | 13,818 | 0 | 0 | 0 | none stated (HF default all rights reserved) |
| opus_storygen | 5,660 | 396 | 0 | 5,660 | 0 | 0 | 0 | none stated (HF default all rights reserved) |
| storyscope | 49,851 | 4409 | 9,897 | 9,862 | 10,054 | 20,038 | 0 | MIT (prompts derived from Books3) |
| wildchat | 50,726 | 558 | 50,726 | 0 | 0 | 0 | 0 | ODC-BY |
Version-3 filters, per config
Candidates are the rows that passed the step-2a rule pre-filter. A row can hit several reasons.
| config | candidates | first judge not WRITING | pjudge_not_requested_writing | gradtex_not_fully_generated | prompt_template_spam | unfilled_placeholder | bot_template | dialogue_script | copies_human_structure | prompt_template_cap | screenplay | verse | truncated_unrecoverable | pjudge_not_standalone_piece | subset_filter_failed | mixed_script | gradtex_closed_family_dropped | degenerate_repetition | refusal | ai_self_reference | near_duplicate | too_short | unsafe_content | palm2_dropped | scrape_residue | encoding_damage | meta_commentary | gsingh_claude_human_dropped | table | html_markup | structured_form | continuation_stub | forum_thread | filler_output | label_hole | leak_string | kept |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| anthropic_persuasion | 1,310 | 0 | 0 | 0 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1,308 |
| biscope | 20,234 | 39 | 0 | 0 | 0 | 15 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | 0 | 0 | 42 | 0 | 27 | 7 | 15 | 248 | 4 | 2 | 0 | 0 | 1 | 5 | 0 | 0 | 0 | 31 | 0 | 0 | 0 | 0 | 0 | 19,797 |
| claude_opus_instruct | 10,454 | 882 | 3,194 | 0 | 0 | 60 | 0 | 115 | 0 | 0 | 26 | 426 | 33 | 110 | 0 | 2 | 0 | 1 | 0 | 3 | 0 | 0 | 5 | 0 | 0 | 0 | 16 | 0 | 0 | 0 | 2 | 1 | 0 | 0 | 0 | 0 | 5,587 |
| editlens_iclr | 44,370 | 831 | 0 | 0 | 0 | 699 | 0 | 0 | 39 | 0 | 0 | 0 | 53 | 0 | 306 | 7 | 0 | 9 | 17 | 0 | 30 | 113 | 12 | 0 | 426 | 4 | 13 | 0 | 0 | 1 | 4 | 0 | 0 | 1 | 0 | 0 | 41,829 |
| fastdetector_train_stat | 444,631 | 20,309 | 0 | 0 | 0 | 705 | 0 | 0 | 20,446 | 0 | 0 | 0 | 1,805 | 0 | 0 | 1,409 | 0 | 546 | 14 | 23 | 304 | 740 | 0 | 0 | 0 | 693 | 283 | 0 | 0 | 85 | 21 | 0 | 0 | 3 | 15 | 0 | 398,100 |
| ghostbuster_essay | 6,325 | 7 | 0 | 0 | 0 | 9 | 0 | 0 | 0 | 0 | 0 | 0 | 2 | 0 | 0 | 0 | 0 | 11 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 5 | 0 | 0 | 0 | 11 | 5 | 0 | 0 | 0 | 0 | 6,276 |
| ghostbuster_news | 6,949 | 1 | 0 | 0 | 0 | 643 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 15 | 0 | 0 | 0 | 0 | 0 | 6 | 0 | 0 | 0 | 0 | 61 | 0 | 0 | 0 | 0 | 6,226 |
| ghostbuster_stories | 6,521 | 7 | 0 | 0 | 0 | 20 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 4 | 2 | 15 | 1 | 1 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 6,469 |
| gradtex | 64,465 | 491 | 0 | 58,901 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 16 | 1,850 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3,204 |
| gryphe_gpt4o_wp | 3,738 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 3,734 |
| gryphe_opus_wp | 9,028 | 0 | 0 | 0 | 0 | 8 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 3 | 0 | 0 | 58 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 8,956 |
| gsingh_claude_sonnet | 5,075 | 75 | 0 | 0 | 0 | 18 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 11 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 446 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 4,523 |
| gsingh_gemini_flash | 4,716 | 79 | 0 | 0 | 0 | 1,231 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 14 | 0 | 1 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 | 0 | 0 | 0 | 0 | 3,401 |
| gsingh_train | 47,946 | 1,310 | 0 | 0 | 0 | 10,278 | 0 | 0 | 0 | 0 | 0 | 0 | 629 | 0 | 1,657 | 8 | 0 | 136 | 13 | 188 | 519 | 11 | 0 | 0 | 1 | 0 | 22 | 0 | 0 | 2 | 1 | 0 | 0 | 1 | 0 | 0 | 33,256 |
| imbue_demo | 35,249 | 590 | 0 | 0 | 0 | 16 | 0 | 0 | 8 | 0 | 0 | 0 | 52 | 0 | 454 | 12 | 0 | 43 | 8 | 4 | 110 | 90 | 15 | 0 | 323 | 1 | 18 | 0 | 0 | 1 | 6 | 0 | 0 | 0 | 0 | 0 | 33,498 |
| lmarena_100k | 39,441 | 15,268 | 16,462 | 0 | 0 | 498 | 0 | 353 | 0 | 74 | 27 | 380 | 93 | 179 | 0 | 58 | 0 | 48 | 24 | 40 | 12 | 15 | 22 | 0 | 0 | 1 | 11 | 0 | 13 | 6 | 1 | 0 | 1 | 1 | 0 | 0 | 5,922 |
| lmarena_140k | 36,920 | 19,241 | 13,916 | 0 | 0 | 327 | 0 | 36 | 0 | 0 | 1 | 138 | 31 | 150 | 0 | 21 | 0 | 23 | 7 | 17 | 1 | 9 | 7 | 0 | 0 | 0 | 5 | 0 | 112 | 4 | 8 | 0 | 0 | 0 | 0 | 1 | 2,925 |
| lmarena_55k | 34,853 | 12,014 | 15,826 | 0 | 0 | 466 | 0 | 429 | 0 | 5 | 114 | 587 | 85 | 218 | 0 | 77 | 0 | 35 | 37 | 45 | 4 | 16 | 9 | 264 | 0 | 1 | 4 | 0 | 2 | 0 | 6 | 0 | 2 | 0 | 0 | 1 | 4,753 |
| lmsys_chat_1m | 146,996 | 48,571 | 42,625 | 0 | 31,716 | 2,378 | 0 | 584 | 0 | 4,900 | 34 | 752 | 247 | 730 | 0 | 146 | 0 | 363 | 332 | 436 | 38 | 40 | 800 | 650 | 0 | 1 | 9 | 0 | 0 | 3 | 9 | 0 | 1 | 4 | 0 | 0 | 12,274 |
| lmsys_gpt5 | 57,909 | 32,116 | 15,627 | 0 | 18 | 959 | 0 | 32 | 0 | 0 | 1 | 263 | 5 | 247 | 0 | 4 | 0 | 3 | 14 | 19 | 2 | 25 | 12 | 0 | 0 | 0 | 5 | 0 | 52 | 1 | 5 | 0 | 0 | 0 | 0 | 0 | 8,532 |
| norquinal_claude | 26,089 | 3,063 | 8,077 | 0 | 0 | 77 | 0 | 124 | 0 | 0 | 12 | 506 | 31 | 288 | 0 | 9 | 0 | 1 | 0 | 1 | 0 | 70 | 0 | 0 | 0 | 0 | 24 | 0 | 3 | 1 | 1 | 4 | 0 | 2 | 0 | 0 | 13,818 |
| opus_storygen | 5,667 | 0 | 0 | 0 | 0 | 6 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 5,660 |
| storyscope | 51,218 | 40 | 0 | 0 | 0 | 104 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | 0 | 0 | 242 | 0 | 186 | 490 | 32 | 0 | 0 | 111 | 0 | 0 | 0 | 173 | 0 | 0 | 11 | 0 | 3 | 0 | 3 | 0 | 0 | 49,851 |
| wildchat | 188,275 | 46,961 | 20,749 | 0 | 1,460 | 5,529 | 23,168 | 19,497 | 0 | 13,602 | 5,745 | 518 | 121 | 865 | 0 | 68 | 0 | 220 | 497 | 594 | 65 | 0 | 60 | 0 | 0 | 0 | 33 | 0 | 65 | 44 | 14 | 6 | 24 | 2 | 0 | 0 | 50,726 |
Version-3 transforms applied (rows changed), per config
| config | kept | canonical_paragraphs | trim_incomplete_tail | format_topic_label | scaffold_label | llm_subset_filter | chat_opener | detokenize | end_marker | wordcount | fix_encoding | reply_finished | canvas_fence | note_tail | star_line | ai_byline | wrapper_tags | template_tokens | html_tags | leading_rule | strip_reasoning_trace |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| anthropic_persuasion | 1,308 | 861 | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| biscope | 19,797 | 2,413 | 204 | 0 | 1,313 | 0 | 1,141 | 4 | 3 | 115 | 0 | 0 | 0 | 0 | 0 | 3 | 0 | 2 | 0 | 3 | 0 |
| claude_opus_instruct | 5,587 | 4,528 | 83 | 0 | 66 | 0 | 5 | 0 | 26 | 46 | 0 | 0 | 0 | 1 | 0 | 24 | 0 | 0 | 0 | 0 | 0 |
| editlens_iclr | 41,829 | 10,795 | 1,128 | 0 | 476 | 4,929 | 63 | 791 | 4 | 2 | 319 | 0 | 0 | 8 | 570 | 0 | 0 | 1 | 4 | 6 | 0 |
| fastdetector_train_stat | 398,100 | 383,930 | 14,372 | 13,622 | 334 | 0 | 0 | 1,441 | 7 | 288 | 500 | 0 | 3 | 0 | 17 | 0 | 325 | 9 | 71 | 6 | 0 |
| ghostbuster_essay | 6,276 | 6,210 | 19 | 0 | 2,287 | 0 | 0 | 18 | 0 | 509 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 9 | 0 | 0 | 0 |
| ghostbuster_news | 6,226 | 6,205 | 41 | 0 | 1,177 | 0 | 3 | 0 | 1 | 93 | 1 | 0 | 0 | 0 | 0 | 3 | 0 | 0 | 0 | 2 | 0 |
| ghostbuster_stories | 6,469 | 6,412 | 80 | 0 | 1 | 0 | 0 | 0 | 9 | 170 | 0 | 0 | 0 | 0 | 0 | 31 | 0 | 1 | 0 | 2 | 0 |
| gradtex | 3,204 | 181 | 5 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 |
| gryphe_gpt4o_wp | 3,734 | 173 | 52 | 0 | 1 | 0 | 0 | 0 | 5 | 2 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 8 | 1 | 3 | 0 |
| gryphe_opus_wp | 8,956 | 463 | 19 | 0 | 1 | 0 | 0 | 0 | 175 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 |
| gsingh_claude_sonnet | 4,523 | 277 | 0 | 0 | 122 | 0 | 1,585 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| gsingh_gemini_flash | 3,401 | 2,909 | 27 | 0 | 16 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 139 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| gsingh_train | 33,256 | 8,506 | 608 | 0 | 1,192 | 2,036 | 8 | 0 | 64 | 189 | 3 | 0 | 0 | 136 | 0 | 0 | 0 | 198 | 0 | 4 | 0 |
| imbue_demo | 33,498 | 13,867 | 779 | 0 | 18 | 3,070 | 8 | 3,906 | 5 | 972 | 1,582 | 0 | 1,087 | 2 | 58 | 0 | 0 | 3 | 2 | 2 | 0 |
| lmarena_100k | 5,922 | 1,978 | 257 | 0 | 292 | 0 | 637 | 1 | 53 | 19 | 0 | 0 | 0 | 29 | 0 | 0 | 0 | 10 | 2 | 1 | 0 |
| lmarena_140k | 2,925 | 1,422 | 222 | 0 | 65 | 0 | 508 | 0 | 59 | 23 | 0 | 0 | 0 | 20 | 2 | 0 | 0 | 0 | 9 | 1 | 2 |
| lmarena_55k | 4,753 | 1,402 | 798 | 0 | 234 | 0 | 643 | 0 | 10 | 10 | 0 | 0 | 0 | 18 | 1 | 0 | 0 | 9 | 4 | 1 | 0 |
| lmsys_chat_1m | 12,274 | 2,011 | 2,571 | 0 | 609 | 0 | 842 | 2 | 5 | 44 | 11 | 0 | 0 | 6 | 0 | 0 | 0 | 35 | 65 | 2 | 0 |
| lmsys_gpt5 | 8,532 | 7,231 | 238 | 0 | 569 | 0 | 1,400 | 0 | 37 | 4 | 0 | 0 | 0 | 0 | 5 | 0 | 1 | 0 | 1 | 15 | 0 |
| norquinal_claude | 13,818 | 13,020 | 1,095 | 0 | 10 | 0 | 12 | 8 | 0 | 28 | 0 | 0 | 0 | 0 | 0 | 0 | 4 | 3 | 1 | 0 | 0 |
| opus_storygen | 5,660 | 3,985 | 0 | 0 | 0 | 0 | 0 | 0 | 47 | 1 | 0 | 0 | 0 | 0 | 0 | 502 | 0 | 0 | 0 | 0 | 0 |
| storyscope | 49,851 | 14,326 | 637 | 0 | 5 | 0 | 87 | 2 | 3,692 | 40 | 3 | 0 | 0 | 189 | 0 | 0 | 0 | 1 | 1 | 0 | 17 |
| wildchat | 50,726 | 16,883 | 1,858 | 0 | 3,007 | 0 | 1,037 | 2 | 1,157 | 102 | 14 | 2,188 | 0 | 258 | 1 | 2 | 0 | 14 | 122 | 139 | 0 |
Step 2a: rule pre-filter (unchanged from version 1)
| rule | drops a row when |
|---|---|
| too_short | fewer than 150 whitespace tokens |
| code | a ``` fence, or 3+ code-looking lines (def/import/#include/SELECT/function/const/braces/HTML tags/print/console.log) |
| list_dominated | 8+ list lines that make up 60%+ of the non-empty lines |
| redaction_token | PRESIDIO_ANONYMIZED_* or NAME_n / EMAIL_n / PHONE_NUMBER_n placeholders (they fingerprint WildChat / LMSYS) |
| error_or_ui_junk | API error strings, scraped ChatGPT UI junk (source flags is_error_string / ui_scrape_junk, or a leading error message) |
| flagged_duplicate | step-1 flag duplicate_of: (Gryphe stories inside Crownelius, Norquinal/Opus rows inside ahmadreza) |
| label_unreliable | step-1 flag label_unreliable (ahmadreza's unidentified 'GPT4' block) |
| context_dependent | lmarena-140k rows that continue a hidden earlier turn |
| near_copy_edit | AI edit of a human text whose embedding distance to the source is below 0.1 (EditLens / Imbue cosine_score) |
| non_english | langdetect P(en) < 0.9 on the first 1,500 characters (only evaluated when no other rule fired) |
| exact_duplicate | lower-cased, whitespace-collapsed text already seen in this split (the first occurrence is kept; sources are visited in a fixed priority order so originals win over compilations) |
| prefix_duplicate | normalized characters 150-450 already seen in this split (the window skips a title or opening line so same-prompt generations are not merged on a shared headline) |
| config | step-1 rows | kept | dropped by reason |
|---|---|---|---|
| ahmadreza_human_vs_ai | 290,323 | 43,000 (14.8%) | too_short 198,459, label_unreliable 44,761, flagged_duplicate 36,254, code 13,414, list_dominated 7,175, non_english 622, prefix_duplicate 1 |
| anthropic_persuasion | 1,313 | 1,310 (99.8%) | too_short 3 |
| biscope | 48,394 | 20,234 (41.8%) | too_short 26,041, exact_duplicate 1,839, code 884, list_dominated 160, prefix_duplicate 18, non_english 6 |
| claude_opus_instruct | 13,669 | 10,454 (76.5%) | list_dominated 1,783, code 1,062, too_short 364, non_english 66, prefix_duplicate 3 |
| crownelius_opus45 | 2,538 | 566 (22.3%) | flagged_duplicate 1,871, list_dominated 97, code 12 |
| defactify_valtest | 21,927 | 20,707 (94.4%) | too_short 908, list_dominated 162, error_or_ui_junk 126, exact_duplicate 70, prefix_duplicate 57, code 13, non_english 10 |
| editlens_iclr | 80,610 | 44,370 (55.0%) | near_copy_edit 19,675, too_short 18,763, exact_duplicate 1,548, list_dominated 464, prefix_duplicate 55, code 26, non_english 24 |
| fastdetector_train_stat | 528,524 | 444,631 (84.1%) | too_short 72,170, list_dominated 10,587, prefix_duplicate 776, code 451, non_english 97, error_or_ui_junk 1 |
| ghostbuster_essay | 6,958 | 6,325 (90.9%) | list_dominated 611, too_short 21, non_english 1 |
| ghostbuster_news | 7,000 | 6,949 (99.3%) | too_short 35, prefix_duplicate 12, exact_duplicate 2, non_english 1, list_dominated 1 |
| ghostbuster_stories | 7,000 | 6,521 (93.2%) | too_short 475, list_dominated 2, prefix_duplicate 2, code 1 |
| gradtex | 142,214 | 64,465 (45.3%) | too_short 72,256, exact_duplicate 5,347, prefix_duplicate 116, list_dominated 17, non_english 10, code 3 |
| gryphe_gpt4o_wp | 3,741 | 3,738 (99.9%) | code 2, non_english 1 |
| gryphe_opus_wp | 9,030 | 9,028 (100.0%) | code 2 |
| gsingh_claude_sonnet | 5,968 | 5,075 (85.0%) | prefix_duplicate 435, exact_duplicate 270, too_short 163, list_dominated 22, code 3 |
| gsingh_gemini_flash | 5,857 | 4,716 (80.5%) | exact_duplicate 777, too_short 157, list_dominated 125, prefix_duplicate 79, code 3 |
| gsingh_train | 51,181 | 47,946 (93.7%) | too_short 2,188, list_dominated 756, error_or_ui_junk 285, prefix_duplicate 145, non_english 59, exact_duplicate 54, code 33 |
| hc3 | 85,431 | 29,676 (34.7%) | too_short 51,664, redaction_token 6,839, exact_duplicate 1,391, error_or_ui_junk 173, code 29, non_english 4, prefix_duplicate 2, list_dominated 1 |
| imbue_demo | 86,208 | 35,249 (40.9%) | too_short 39,814, near_copy_edit 16,454, list_dominated 429, exact_duplicate 59, prefix_duplicate 34, non_english 25, code 24 |
| lmarena_100k | 212,268 | 39,441 (18.6%) | too_short 97,694, list_dominated 40,068, code 27,953, non_english 21,130, exact_duplicate 69, prefix_duplicate 16 |
| lmarena_140k | 271,129 | 36,920 (13.6%) | too_short 81,444, list_dominated 74,815, context_dependent 54,581, code 49,870, non_english 25,985, prefix_duplicate 34, exact_duplicate 20, redaction_token 1 |
| lmarena_55k | 114,850 | 34,853 (30.3%) | too_short 57,070, list_dominated 13,937, code 11,120, exact_duplicate 3,104, non_english 508, prefix_duplicate 14 |
| lmsys_chat_1m | 998,573 | 146,996 (14.7%) | too_short 649,227, redaction_token 176,595, code 94,549, list_dominated 56,661, non_english 31,595, exact_duplicate 214, prefix_duplicate 143, error_or_ui_junk 64 |
| lmsys_gpt5 | 192,482 | 57,909 (30.1%) | too_short 84,176, code 35,980, list_dominated 26,322, non_english 324, prefix_duplicate 5 |
| norquinal_claude | 33,190 | 26,089 (78.6%) | too_short 4,933, code 1,733, list_dominated 1,247, non_english 144 |
| opus_storygen | 5,668 | 5,667 (100.0%) | too_short 1 |
| storyscope | 51,336 | 51,218 (99.8%) | too_short 92, code 11, non_english 8, list_dominated 6, prefix_duplicate 2 |
| wildchat | 194,964 | 188,275 (96.6%) | code 2,639, redaction_token 1,607, list_dominated 1,077, non_english 881, prefix_duplicate 496, exact_duplicate 3 |
Step 2b: first LLM judge (unchanged from version 1)
Every surviving row was judged by google/gemma-4-E4B-it (vLLM, temperature 0, bf16, text cut to the first 700
words) with a fixed prompt asking for one line of JSON {"label": "WRITING"|"NOT_WRITING", "genre": ...}.
WRITING is defined as a self-contained piece of prose meant to be read on its own (blog post, essay, op-ed, article,
news story, short story, review, letter, speech), several paragraphs of continuous sentences; NOT_WRITING covers chat
replies that address the user, direct answers, how-tos and step lists, outlines and bullet points, tables, code or
math, poems and lyrics, roleplay and dialogue scripts, templates with placeholders, summaries of another document,
product and marketing copy, email threads and structured review forms, or text that is more than a third lists,
tables, headings or code. Rows judged NOT_WRITING, rows whose verdict could not be parsed, and rows the judge never
saw are all dropped. Rows that restate a line of their own prompt (headline, abstract) are kept and flagged echoes_prompt and counted separately below. The genre the judge returned is kept in
metadata.quality_flags as judge:<genre> and in metadata.extra.judge_genre.
Schema
| column | type | meaning |
|---|---|---|
| text | string | the AI (or human) text exactly as the source provides it; no cleaning has been applied in step 1 |
| model_family | string | OpenAI, Anthropic, Gemini, Other, Human. Gemma models count as Other; PaLM-2 rows were removed |
| model_id | string | normalized lowercase model identifier (human for human rows); the source's raw id is in metadata.model_id_raw |
| metadata | struct | identical 19 fields in every row (below) |
metadata fields:
| field | type | meaning |
|---|---|---|
| source_dataset | string | Hugging Face id / URL of the source |
| source_split | string | split, config or file within the source |
| source_index | string | row id within the source (traceability) |
| group_key | string | g:<hash>: a cross-config component id; rows that share a prompt, a source document or an LMSYS conversation in ANY config share a key (the step-1 key is in extra.group_key_step1). Join rows between versions on source_dataset + source_split + source_index + model_id; source_index alone is not unique in every config |
| is_human | bool | human-written text |
| is_fully_ai | bool/null | true = written by the model from a prompt; false = AI edit / paraphrase / blend of a human text; null for human rows |
| model_id_raw | string | model identifier as given by the source |
| model_era | string | 2022-23, 2024, 2025+ from a model-id table (date suffixes win) or human |
| generation_date | string/null | date or range the source states or implies |
| language | string/null | ISO-639-1 where known, else the source's label |
| word_count | int32 | whitespace tokens in text |
| domain | string/null | coarse: news, fiction, essay, blog, review, opinion, nonfiction, academic, academic_review, web_edu, social, email, qa, chat, instruct, code, legal, business, other |
| genre | string/null | the source's finer label (theme, section, category, WebOrganizer format, prompt type) |
| prompt | string/null | user prompt / instruction / title when the source provides it |
| system_prompt | string/null | system prompt when the source provides it |
| upstream | string | the human corpus the text or prompt derives from |
| license | string | the source's stated license and the main caveat |
| quality_flags | list | source-level flags, e.g. ai_edited, self_paraphrased, writing_enhancement, prompt_unreliable, duplicate_of:<source>, is_erotica, ui_scrape_junk, is_error_string, context_dependent, wf_bot_template, wf_code, wf_longform_writing, flag_preamble, flag_refusal_head, redacted_*, toxic_*, label_unreliable, source_subsampled, rewrite_of_human_source, gradtex_<scenario> |
| extra | string | JSON object with every remaining source-specific field (scores, battle winners, moderation, temperatures, ...) |
Source notes
anthropic_persuasion: Anthropic/persuasion: 1,313 persuasive arguments (median 243 words) on 75 claims by claude-1.3, claude-instant-1.2, claude-2, claude-3-haiku, claude-3-opus, plus 19 Control rows (Claude 2) and 174 human arguments. Ratings collapsed to one row per argument.
biscope: HanxiGuo/BiScope_Data: essays (IvyPanda), creative (r/WritingPrompts), Yelp, Arxiv and code by gpt-3.5-turbo, gpt-4-turbo-preview, claude-3-opus, claude-3-sonnet, gemini-1.0-pro (2024), with self-paraphrased variants (flag self_paraphrased). 885 of its human essays also appear in ghostbuster_essay.
claude_opus_instruct: nothingiisreal/Claude-3-Opus-Instruct-15K (v1 + v2 + extra): single-turn claude-3-opus-20240229 responses to Norquinal prompts (Bedrock, mid-2024).
editlens_iclr: pangram/editlens_iclr (gated, non-commercial terms): human text (news, FineWeb-Edu, r/WritingPrompts, Amazon/Google reviews, Enron) plus fully AI 'synthetic mirroring' generations and AI edits by gpt-4.1-2025-04-14, claude-sonnet-4-20250514, gemini-2.5-flash and Llama-3.3-70B (test splits). metadata.extra carries cosine_score (1.0 = fully AI); ai_edited rows are flagged.
fastdetector_train_stat: G-reen/fastdetector-train-stat-train: Common Crawl prose filtered to contiguous text, rewritten by 12 generators (gpt-5.6-luna, gpt-4.1-mini, claude-haiku-4-5, deepseek-v4.1-flash, Gemma-4-31B, Qwen3.8-27B, Llama-3.3-70B, Mistral-Small-4, Granite-4.2, Ornith-1.5, Laguna-S-2.1) with rewrite/revise/direct/indirect-reference prompts. Only rows with cosdist > 0.1 (Qwen3-Embedding-4B) are kept; every human original is included once. metadata.genre = WebOrganizer format, extra has cosdist/jaccard/levenshtein/prompt_type.
ghostbuster_essay: polsci/ghostbuster-essay-cleaned: IvyPanda student essays vs gpt-3.5-turbo (5 prompt variants) and Claude (2023, version unstated). Claude prompt alignment is unrecoverable (flag prompt_unreliable).
ghostbuster_news: Ghostbuster reuter/ folder (vivek3141/ghostbuster-data): Reuters RCV1 articles vs gpt-3.5-turbo (3 prompt variants) and Claude 1.x (2023). claude/{i} files were generated for prompt i+1 and are re-aligned here.
ghostbuster_stories: Ghostbuster wp/ folder: r/WritingPrompts stories vs gpt-3.5-turbo and Claude 1.x (2023), same alignment fix. All 1,000 human stories also appear in biscope.
gradtex: elisabeth-pl-pl/GRADTEX (built on MAGE): mostly human-text edits (polish/completion/paraphrase/style) by Gemma-4, Mistral, and in the test split claude-sonnet-4.6, gpt-5.4-mini, gemini-3.5-flash, qwen3.5-27b, gemma-4-e4b, plus old MAGE davinci/gpt-3.5 rows. is_fully_ai marks fully generated rows; scenario in quality_flags.
gryphe_gpt4o_wp: Gryphe/ChatGPT-4o-Writing-Prompts: chatgpt-4o-latest (Aug-Sep 2024) stories for ~3,000 r/WritingPrompts prompts (median 1,172 words; 45% contain markdown).
gryphe_opus_wp: Gryphe/Opus-WritingPrompts: two claude-3-opus-20240229 generations per prompt (May-Jun 2024) plus a gpt-3.5-turbo file over the same prompts. 13-18% tagged Erotica (flag is_erotica). ~2,990 prompts shared with gryphe_gpt4o_wp.
gsingh_claude_sonnet: gsingh1-py/Claude-sonnet: NYT-abstract + RAG-context prompted news articles by Claude 3.5 Sonnet at 5 temperatures (0.2-1.0) over 989 URLs; human rows are scraped NYT pages with navigation text.
gsingh_gemini_flash: gsingh1-py/Gemini_1.5_flash: same 989 NYT prompts as gsingh_claude_sonnet answered by Gemini 1.5 Flash at 5 temperatures.
gsingh_train: gsingh1-py/train = Defactify-4 train split: 7,321 NYT prompts answered by gpt-4o, gemma-2-9b, mistral-7b, qwen-2-72b, llama-3-8b, yi-large, plus scraped NYT human pages. Open-model prompt row-shift in the source corrected (metadata.extra.prompt_alignment_fixed).
imbue_demo: DarrenJiaImbue/ai-detection-demo-dataset: EditLens-style design with claude-sonnet-4-6, gpt-5.3-chat-latest, gemini-3-flash-preview over news, FineWeb-Edu, r/WritingPrompts, Amazon/Yelp reviews, Twitter. 12% of gpt-5.3 rows are wrapped in ':::writing' canvas fences.
lmarena_100k: lmarena-ai/arena-human-preference-100k (Jun-Aug 2024): one row per battle side (first assistant turn), 55 model ids; metadata.extra has winner, opponent, criteria, is_code/is_math, refusal tag.
lmarena_140k: lmarena-ai/arena-human-preference-140k (Apr-Jul 2025): one row per battle side, 53 model ids incl. Claude 4, Gemini 2.5, o3, GPT-4.1; extra has creative_writing tag, criteria, evaluation_order (context_dependent flag = later turn of a hidden session).
lmarena_55k: lmarena-ai/arena-human-preference-55k (2023-24, Kaggle train split): one row per battle side, 64 model ids incl. claude-1/2, palm-2, gpt-4-0314 and many ChatGPT-distilled open models.
lmsys_chat_1m: lmsys/lmsys-chat-1m (gated): first assistant turn of 1M 2023 conversations from 25 models incl. claude-1/2/instant, palm-2, gpt-3.5/4, vicuna, llama-2; moderation scores in extra.
lmsys_gpt5: ytz20/LMSYS-Chat-GPT-5-Chat-Response: LMSYS-Chat-1M prompts re-answered by gpt-5-chat (Aug-Nov 2025, exact snapshot unpublished). 66% of responses end with a 'Would you like me to...' offer (flag wf_chatty_* / see extra).
norquinal_claude: Norquinal/claude_multi_instruct_30k (+1k): 2023 Claude (version unstated; claude-1/instant/2 era) single-turn instruct responses.
opus_storygen: nothingiisreal/Short-Storygen-v2: 5,668 claude-3-opus-20240229 short stories; 521 carry 'By the AI ...' bylines, 60% open with a title line.
storyscope: jjrussell10/storyscope (arXiv 2604.03136): 10,272 Books3-derived prompts answered by gpt-5.4, claude-sonnet-4.6, gemini-3-flash, deepseek-v3.2, kimi-k2.5 (median 2.6k-6.4k words). Human stories not released. Refusal/preamble/word-count-trailer flags in quality_flags.
wildchat: allenai/WildChat-4.8M public release (3.2M conversations, Apr 2023-Jul 2025, 15 OpenAI model ids): first assistant turn of every conversation whose response passed the loose long-form filter (English, >= 250 words, no code). Writing heuristics wf_* in quality_flags/extra; PRESIDIO redaction tokens flagged.
Known limitations
- Formatting, typography and length still differ by family and source; they are handled by the training-time regularizer, and evaluation should apply the same normalization.
- The web-prose register (blog, news, knowledge articles) is covered almost only by Human and Other rows; the closed families are mostly fiction, news rewrites, essays and requested pieces from chat logs.
- Both judges are a 4B-class model; verdicts are soft labels.
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