{
 "row": "data-portraits",
 "address": "Data Portraits",
 "addresses": [
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 "extracted": "2026-11-01",
 "extractor": "Claude (Opus 5.5), subagent, one extractor (unaudited, §3.8)",
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 "B_note": "The field B (§0.4, §3.1(a)), in two pools and kept apart by origin. B_D, the disclosed pool: 'card', every card on the transcript's rail (B2 dataportraits.org, the entity's site; B1, B3–B8 the homonyms' cards, B5 and B7 unreachable, B6 a video card). B_R, the reference pool: 'own_page', the arXiv abstract (B9, the census's source), the paper (B10) and the sketch front ends (B12, HTTP 502); 'wikipedia', the record of absence (B11). A source in both is carried once, in B_D.",
 "lineage_note": "Lineages by sense; the field and the archive share them where an archive claim states the same sense. See row.objects.P.rail for each lineage with its earliest source.",
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 "counts": {
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  "fetched": 7,
  "unreachable": 5,
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  "claims_B_D": 19,
  "claims_B_R": 33,
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   "pool": "B_D"
  },
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   "card": "Data Portraits — Data Portraits",
   "fetched": "card; B2.html sha256 5967547b30c0d39f, HTTP 200 at 2026-11-01T15:13:42Z",
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   "pool": "B_D"
  },
  {
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   "card": "Zinn Education Project — W. E. B. Du Bois's Data Portraits: Visualizing Black America - Zinn Education Project",
   "fetched": "card; B3.html sha256 e26b7dbd03002904, HTTP 200 at 2026-11-01T15:14:26Z",
   "origin": "card (homonym) (B_D)",
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  },
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   "card": "Pentagram — TED Data Portraits - Pentagram",
   "fetched": "card; B4.html sha256 e120a28cf59c7142, HTTP 200 at 2026-11-01T15:14:27Z",
   "origin": "card (homonym) (B_D)",
   "pool": "B_D"
  },
  {
   "id": "B5",
   "card": "SparkMap — W.E.B. Du Bois & Data Visualization History - SparkMap",
   "fetched": "unreachable: no URL found by WebSearch on the card's title and site; title and snippet only",
   "origin": "card (homonym) (B_D)",
   "pool": "B_D"
  },
  {
   "id": "B6",
   "card": "YouTube·University of Massachusetts Amherst Libraries — W. E. B. Du Bois's Data Portraits: Visualizing Black America",
   "fetched": "video card: title only",
   "origin": "card (homonym) (B_D)",
   "pool": "B_D"
  },
  {
   "id": "B7",
   "card": "MIT Media Lab — Data Portraits - MIT Media Lab",
   "fetched": "unreachable: TLS failure (self-signed certificate in chain) at 2026-11-01T15:14:27Z and 15:14:42Z; title and snippet only",
   "origin": "card (homonym) (B_D)",
   "pool": "B_D"
  },
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   "card": "ARTnews.com — 10 Painstakingly Crafted Data Portraits That Reveal Strange Details of People's ...",
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   "origin": "card (homonym) (B_D)",
   "pool": "B_D"
  },
  {
   "id": "B9",
   "card": "arXiv — [2303.03919] Data Portraits: Recording Foundation Model Training Data (census source)",
   "fetched": "own page (census copy data-portraits--arxiv); B9.html sha256 0a499acc8164a2d2, HTTP 200 at 2026-11-01T05:07:12Z, matching the manifest",
   "origin": "own_page (B_R)",
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   "card": "arXiv — Data Portraits: Recording Foundation Model Training Data (PDF, v2)",
   "fetched": "own page; B10.pdf sha256 13d6b6d27a507a4a, HTTP 200 at 2026-11-01T15:14:30Z",
   "origin": "own_page (B_R)",
   "pool": "B_R"
  },
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   "id": "B11",
   "card": "Wikipedia — no article 'Data Portraits' (HTTP 404); search for \"Data Portraits\"",
   "fetched": "wikipedia; four titles HTTP 404 at 2026-11-01T15:14:31–33Z; search HTTP 200 (sha256 39f19b42595c6af7)",
   "origin": "wikipedia (B_R)",
   "pool": "B_R"
  },
  {
   "id": "B12",
   "card": "dataportraits.org — the Pile, Stack and Stack V2 sketch front ends (HTTP 502)",
   "fetched": "own pages; HTTP 502 at 2026-11-01T15:14:29Z–15:15:09Z; recorded unread",
   "origin": "own_page (B_R)",
   "pool": "B_R"
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 ],
 "field_by_origin": {
  "cards": [
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    "pool": "B_D",
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    "files": {
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      "sha256": "2d8c62c8abf433dba538700415ac1e4f16bc4f2e5434869dc0415b776be6dd40"
     },
     "B1.txt": {
      "path": "datasets/negative-of-the-negative/v2/intake/data-portraits-20261101/B1.txt",
      "sha256": "05ffdf5ab82d444b0c7a6176a0b7c91e2627b9a11ec3226e4573c7856e2666bd"
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    },
    "fetched": {
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     "agent": "Mozilla/5.0 (compatible; traininglayerliterature-census)",
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     "http": "200",
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     "final_url": "https://giorgialupi.com/data-portraits-at-ted2017",
     "raw": "datasets/negative-of-the-negative/v2/intake/data-portraits-20261101/B1.html",
     "raw_sha256": "2d8c62c8abf433dba538700415ac1e4f16bc4f2e5434869dc0415b776be6dd40",
     "text": [
      "datasets/negative-of-the-negative/v2/intake/data-portraits-20261101/B1.txt"
     ],
     "note": "found by WebSearch on the card's title and site; the page carries the project; the snippet's 'Project: … Concept:' line is the card renderer's summary and is not on the page"
    },
    "surfaced_by_T": [
     "T1 card 1"
    ],
    "names_operator": "no (the entity's authors are not named)",
    "names_archive": "no (none of the Crimson Hexagonal Archive, Alexanarch, Lee Sharks, traininglayerliterature.org, machinemediation, EA-WG-CAPTURES-01 in the saved text, card title and snippet)",
    "note": "In B_D as the card is (BRIEF-NEW-ROW-LAYER, substitution 7): recorded with its sense, its kernel ledgered for the disambiguation and the first question.",
    "card_title": "Data Portraits at TED — giorgialupi",
    "card_snippet": "Project: Data Portraits at TED 2017 (Vancouver) by Accurat, commissioned by TED and David Stark Design for Target's social space. Concept: Personal questionnair..."
   },
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    "origin": "card (homonym)",
    "pool": "B_D",
    "role": "Overview card 3 (another entity of the name)",
    "card": "Zinn Education Project — W. E. B. Du Bois's Data Portraits: Visualizing Black America - Zinn Education Project",
    "url": "https://www.zinnedproject.org/materials/du-bois-data-portraits/",
    "kind": "Overview card of a homonym",
    "sense": "homonym: W. E. B. Du Bois's data portraits (1900) and the 2018 book",
    "snippet": "Book: W. E. B. Du Bois's Data Portraits: Visualizing Black America (2018, 144 pages, Princeton Architectural Press). Creators: W. E. B. Du Bois Center at Univer...",
    "files": {
     "B3.html": {
      "path": "datasets/negative-of-the-negative/v2/intake/data-portraits-20261101/B3.html",
      "sha256": "e26b7dbd030029048c6f8866ae42ac35386c190c06039ee42f7fd54a0737400a"
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     "B3.txt": {
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    "fetched": {
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     "agent": "Mozilla/5.0 (compatible; traininglayerliterature-census)",
     "read": "2026-11-01T15:14:26Z",
     "http": "200",
     "url": "https://www.zinnedproject.org/materials/du-bois-data-portraits/",
     "final_url": "https://www.zinnedproject.org/materials/du-bois-data-portraits/",
     "raw": "datasets/negative-of-the-negative/v2/intake/data-portraits-20261101/B3.html",
     "raw_sha256": "e26b7dbd030029048c6f8866ae42ac35386c190c06039ee42f7fd54a0737400a",
     "text": [
      "datasets/negative-of-the-negative/v2/intake/data-portraits-20261101/B3.txt"
     ],
     "note": "found by WebSearch on the card's title and site; the page carries the snippet's book entry"
    },
    "surfaced_by_T": [
     "T1 card 3"
    ],
    "names_operator": "no (the entity's authors are not named)",
    "names_archive": "no (none of the Crimson Hexagonal Archive, Alexanarch, Lee Sharks, traininglayerliterature.org, machinemediation, EA-WG-CAPTURES-01 in the saved text, card title and snippet)",
    "note": "In B_D as the card is (BRIEF-NEW-ROW-LAYER, substitution 7): recorded with its sense, its kernel ledgered for the disambiguation and the first question.",
    "card_title": "W. E. B. Du Bois's Data Portraits: Visualizing Black America - Zinn Education Project",
    "card_snippet": "Book: W. E. B. Du Bois's Data Portraits: Visualizing Black America (2018, 144 pages, Princeton Architectural Press). Creators: W. E. B. Du Bois Center at Univer..."
   },
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    "origin": "card (homonym)",
    "pool": "B_D",
    "role": "Overview card 4 (another entity of the name)",
    "card": "Pentagram — TED Data Portraits - Pentagram",
    "url": "https://www.pentagram.com/work/ted-data-portraits/story",
    "kind": "Overview card of a homonym",
    "sense": "homonym: Giorgia Lupi, TED Data Portraits (Pentagram)",
    "snippet": "Recognizing what they had in common at a glance, attendees found it easy to start. Recognizing what they had in common at a glance, attendees found it easy to s...",
    "files": {
     "B4.html": {
      "path": "datasets/negative-of-the-negative/v2/intake/data-portraits-20261101/B4.html",
      "sha256": "e120a28cf59c714240bcd07aa7f894a7fd54bdbc8216acdfd98e7a0a37764b44"
     },
     "B4.txt": {
      "path": "datasets/negative-of-the-negative/v2/intake/data-portraits-20261101/B4.txt",
      "sha256": "21031e22d13aff62ebb0e4ed7371e885f64db9d7d21112fece8b20cd1ec417ba"
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    },
    "fetched": {
     "census_copy": false,
     "agent": "Mozilla/5.0 (compatible; traininglayerliterature-census)",
     "read": "2026-11-01T15:14:27Z",
     "http": "200",
     "url": "https://www.pentagram.com/work/ted-data-portraits/story",
     "final_url": "https://www.pentagram.com/work/ted-data-portraits/story",
     "raw": "datasets/negative-of-the-negative/v2/intake/data-portraits-20261101/B4.html",
     "raw_sha256": "e120a28cf59c714240bcd07aa7f894a7fd54bdbc8216acdfd98e7a0a37764b44",
     "text": [
      "datasets/negative-of-the-negative/v2/intake/data-portraits-20261101/B4.txt"
     ],
     "note": "found by WebSearch on the card's title and site; the page carries the snippet's caption"
    },
    "surfaced_by_T": [
     "T1 card 4"
    ],
    "names_operator": "no (the entity's authors are not named)",
    "names_archive": "no (none of the Crimson Hexagonal Archive, Alexanarch, Lee Sharks, traininglayerliterature.org, machinemediation, EA-WG-CAPTURES-01 in the saved text, card title and snippet)",
    "note": "In B_D as the card is (BRIEF-NEW-ROW-LAYER, substitution 7): recorded with its sense, its kernel ledgered for the disambiguation and the first question.",
    "card_title": "TED Data Portraits - Pentagram",
    "card_snippet": "Recognizing what they had in common at a glance, attendees found it easy to start. Recognizing what they had in common at a glance, attendees found it easy to s..."
   },
   {
    "id": "B5",
    "origin": "card (homonym)",
    "pool": "B_D",
    "role": "Overview card 5 (another entity of the name)",
    "card": "SparkMap — W.E.B. Du Bois & Data Visualization History - SparkMap",
    "url": null,
    "kind": "Overview card of a homonym",
    "sense": "homonym: W. E. B. Du Bois's data portraits (SparkMap)",
    "snippet": "Sociologist W.E.B. Du Bois created sixty hand-drawn \"data portraits\" between 1897 and 1990 with Atlanta University students and scholars, visualizing Black Amer...",
    "files": {},
    "fetched": {
     "census_copy": false,
     "result": "unreachable: no URL found; WebSearch on the card's title and site ('SparkMap \"W.E.B. Du Bois\" Data Visualization History'; 'sparkmap.org W.E.B. Du Bois sixty hand-drawn \"data portraits\" Atlanta University'; 'SparkMap blog Du Bois data visualization history') returned other pages on Du Bois's charts and no SparkMap page; not fetched; the card's title and snippet its only text (§3.1(a))"
    },
    "surfaced_by_T": [
     "T1 card 5"
    ],
    "names_operator": "no (the entity's authors are not named)",
    "names_archive": "no (none of the Crimson Hexagonal Archive, Alexanarch, Lee Sharks, traininglayerliterature.org, machinemediation, EA-WG-CAPTURES-01 in the saved text, card title and snippet)",
    "note": "In B_D as the card is (BRIEF-NEW-ROW-LAYER, substitution 7): recorded with its sense, its kernel ledgered for the disambiguation and the first question. The snippet's 'between 1897 and 1990' is recorded as rendered.",
    "card_title": "W.E.B. Du Bois & Data Visualization History - SparkMap",
    "card_snippet": "Sociologist W.E.B. Du Bois created sixty hand-drawn \"data portraits\" between 1897 and 1990 with Atlanta University students and scholars, visualizing Black Amer..."
   },
   {
    "id": "B6",
    "origin": "card (homonym)",
    "pool": "B_D",
    "role": "Overview card 6 (another entity of the name; a video card, 5m)",
    "card": "YouTube·University of Massachusetts Amherst Libraries — W. E. B. Du Bois's Data Portraits: Visualizing Black America",
    "url": null,
    "kind": "video card of a homonym",
    "sense": "homonym: W. E. B. Du Bois's Data Portraits (a University of Massachusetts Amherst Libraries video)",
    "snippet": null,
    "files": {},
    "fetched": {
     "census_copy": false,
     "result": "video card: title only (no snippet on the rail); admitted through its title (§3.1(a)); a WebSearch on the title and channel found no video URL; not fetched"
    },
    "surfaced_by_T": [
     "T1 card 6"
    ],
    "names_operator": "no (the entity's authors are not named)",
    "names_archive": "no (none of the Crimson Hexagonal Archive, Alexanarch, Lee Sharks, traininglayerliterature.org, machinemediation, EA-WG-CAPTURES-01 in the saved text, card title and snippet)",
    "note": "In B_D as the card is (BRIEF-NEW-ROW-LAYER, substitution 7): recorded with its sense, its kernel ledgered for the disambiguation and the first question.",
    "card_title": "W. E. B. Du Bois's Data Portraits: Visualizing Black America",
    "card_snippet": null
   },
   {
    "id": "B7",
    "origin": "card (homonym)",
    "pool": "B_D",
    "role": "Overview card 7 (another entity of the name)",
    "card": "MIT Media Lab — Data Portraits - MIT Media Lab",
    "url": "https://www.media.mit.edu/projects/data-portraits/overview/",
    "kind": "Overview card of a homonym",
    "sense": "homonym: Judith Donath's data portraits (MIT Media Lab)",
    "snippet": "Data portraits depict their subjects' accumulated data rather than their faces. They can be visualizations of discussion contributions, browsing histories, soci...",
    "files": {},
    "fetched": {
     "census_copy": false,
     "agent": "Mozilla/5.0 (compatible; traininglayerliterature-census)",
     "read": "2026-11-01T15:14:27Z",
     "http": "000",
     "url": "https://www.media.mit.edu/projects/data-portraits/overview/",
     "result": "unreachable: TLS failure ('SSL certificate problem: self-signed certificate in certificate chain') for https://www.media.mit.edu/projects/data-portraits/overview/ (15:14:27Z) and https://www.media.mit.edu/publications/data-portraits/ (15:14:28Z), both found by WebSearch; one retry of the first with the proxy's CA bundle named explicitly (15:14:42Z), the same failure; verification never disabled; the card's title and snippet its only text (§3.1(a)); fetch.log"
    },
    "surfaced_by_T": [
     "T1 card 7"
    ],
    "names_operator": "no (the entity's authors are not named)",
    "names_archive": "no (none of the Crimson Hexagonal Archive, Alexanarch, Lee Sharks, traininglayerliterature.org, machinemediation, EA-WG-CAPTURES-01 in the saved text, card title and snippet)",
    "note": "In B_D as the card is (BRIEF-NEW-ROW-LAYER, substitution 7): recorded with its sense, its kernel ledgered for the disambiguation and the first question.",
    "card_title": "Data Portraits - MIT Media Lab",
    "card_snippet": "Data portraits depict their subjects' accumulated data rather than their faces. They can be visualizations of discussion contributions, browsing histories, soci..."
   },
   {
    "id": "B8",
    "origin": "card (homonym)",
    "pool": "B_D",
    "role": "Overview card 8 (another entity of the name)",
    "card": "ARTnews.com — 10 Painstakingly Crafted Data Portraits That Reveal Strange Details of People's ...",
    "url": "https://www.artnews.com/art-news/news/data-portraits-reveal-strange-details-2474/",
    "kind": "Overview card of a homonym",
    "sense": "homonym: Judith Donath's data portraits (ARTnews, 30 June 2014)",
    "snippet": "Your tweets, your Instagrams, your Facebook status updates, your search history—it's all a part of your data portrait. And right now, by reading this article, y...",
    "files": {
     "B8.html": {
      "path": "datasets/negative-of-the-negative/v2/intake/data-portraits-20261101/B8.html",
      "sha256": "bf5fb12c784943a1e43c4d6edf2784d38d20b3e54ad705c47550d893699c6cc8"
     },
     "B8.txt": {
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    "fetched": {
     "census_copy": false,
     "agent": "Mozilla/5.0 (compatible; traininglayerliterature-census)",
     "read": "2026-11-01T15:15:07Z",
     "http": "200",
     "url": "https://www.artnews.com/art-news/news/data-portraits-reveal-strange-details-2474/",
     "final_url": "https://www.artnews.com/art-news/news/data-portraits-reveal-strange-details-2474/",
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     "note": "URL from ARTnews's tag page for Ben Durham (found by WebSearch; fetched as tries/artnews-tag.html), which links the article by its title; the page carries the snippet's opening"
    },
    "surfaced_by_T": [
     "T1 card 8"
    ],
    "names_operator": "no (the entity's authors are not named)",
    "names_archive": "no (none of the Crimson Hexagonal Archive, Alexanarch, Lee Sharks, traininglayerliterature.org, machinemediation, EA-WG-CAPTURES-01 in the saved text, card title and snippet)",
    "note": "In B_D as the card is (BRIEF-NEW-ROW-LAYER, substitution 7): recorded with its sense, its kernel ledgered for the disambiguation and the first question.",
    "card_title": "10 Painstakingly Crafted Data Portraits That Reveal Strange Details of People's ...",
    "card_snippet": "Your tweets, your Instagrams, your Facebook status updates, your search history—it's all a part of your data portrait. And right now, by reading this article, y..."
   }
  ],
  "own_pages": [
   {
    "id": "B9",
    "origin": "own_page",
    "pool": "B_R",
    "role": "the entity's own page (the arXiv abstract; the census's one source, data-portraits--arxiv)",
    "card": "arXiv — [2303.03919] Data Portraits: Recording Foundation Model Training Data",
    "url": "https://arxiv.org/abs/2303.03919",
    "kind": "own page (the paper's abstract page)",
    "sense": "the entity",
    "files": {
     "B9.html": {
      "path": "datasets/negative-of-the-negative/v2/intake/data-portraits-20261101/B9.html",
      "sha256": "0a499acc8164a2d26699162d1c8a5890c9bd74686f68d213fac02b5e5fc79b90"
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     "src": "data-portraits--arxiv",
     "read": "2026-11-01T05:07:12Z",
     "http": "200",
     "url": "https://arxiv.org/abs/2303.03919",
     "final_url": "https://arxiv.org/abs/2303.03919",
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     "agrees": true,
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  },
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   "source": "B2",
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   "locus": "Our Implementations: Your Dataset",
   "quote": "Code on Github! … if you'd like us to build our system on your data.",
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   "source": "B2",
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   "quote": "author = {Marone, Marc and {Van Durme}, Benjamin}, booktitle={Thirty-seventh Conference on Neural Information Processing Systems Datasets and Benchmarks Track},",
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   "quote": "Foundation models are trained on increasingly immense and opaque datasets. Even while these models are now key in AI system building, it can be difficult to answer the straightforward question: has the model already encountered a given example during training?",
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   "quote": "We therefore propose a widespread adoption of Data Portraits: artifacts that record training data and allow for downstream inspection.",
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   "quote": "First we outline the properties of such an artifact and discuss how existing solutions can be used to increase transparency.",
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   "source": "B9",
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   "quote": "We then propose and implement a solution based on data sketching, stressing fast and space efficient querying.",
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   "source": "B9",
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   "quote": "Using our tools, we document a popular language modeling corpus (The Pile) and a recently released code modeling dataset (The Stack).",
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   "source": "B9",
   "origin": "own_page",
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   "locus": "Abstract",
   "quote": "We show that our solution enables answering questions about test set leakage and model plagiarism.",
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   "quote": "Our tool is lightweight and fast, costing only 3% of the dataset size in overhead.",
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   "source": "B9",
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   "quote": "We release a live interface of our tools at this https URL and call on dataset and model creators to release Data Portraits as a complement to current documentation practices.",
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   "locus": "Comments; Submission history",
   "quote": "NeurIPS 2023 Datasets and Benchmarks … [v1] Mon, 6 Mar 2023 04:22:33 UTC (651 KB) … [v2] Thu, 14 Dec 2023 16:55:42 UTC (614 KB)",
   "claim": "venue and versions: NeurIPS 2023 Datasets and Benchmarks; v1 6 March 2023, v2 14 December 2023",
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   "locus": "title block",
   "quote": "Marc Marone Benjamin Van Durme Johns Hopkins University",
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  },
  "F24": {
   "source": "B10",
   "origin": "own_page",
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   "locus": "§1 Introduction",
   "quote": "The critical property of a data portrait is membership inference: whether an example was part of a data collection.",
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  },
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   "source": "B10",
   "origin": "own_page",
   "pool": "B_R",
   "locus": "§1 Introduction",
   "quote": "In discussing these tools we consider three perspectives: content creators (owners), scientists, and content consumers. Creators wish to know whether a dataset contains their content (e.g. copywritten code).",
   "claim": "three perspectives: content creators, scientists, content consumers; creators want to know whether a dataset contains their content",
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   "kernel": false,
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  },
  "F26": {
   "source": "B10",
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   "locus": "§2.1 Documentation Artifacts",
   "quote": "We view a Data Portrait as a complementary type of documentation artifact - one that answers the membership question.",
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  },
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   "source": "B10",
   "origin": "own_page",
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   "locus": "§3 Data Portraits",
   "quote": "We outline desirable properties of a dataset documentation tool built around membership inference, recognizing that some may induce tradeoffs. 1. Fast: An artifact should support low latency programmatic access. 2. Lightweight: An artifact should not be much more expensive than storing the original data. 3. Avoids Redistribution:",
   "claim": "the desirable properties of a membership tool: fast, lightweight, avoiding redistribution, local, indexing, match flexibility, with tradeoffs",
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   "kind": "definition",
   "kernel": false,
   "const": false,
   "lineage": "the sketch: Bloom filter, strided n-grams, hashes",
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   "quote_ok": true,
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  },
  "F28": {
   "source": "B10",
   "origin": "own_page",
   "pool": "B_R",
   "locus": "§3 Data Portraits (Other Implementations)",
   "quote": "Given these tradeoffs, we use a probabilistic approach for membership inference: a data sketch.",
   "claim": "after weighing grep, full-text indexes and suffix arrays, a probabilistic approach: a data sketch",
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   "kind": "function",
   "kernel": false,
   "const": false,
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   "date": "2023-12-14 (v2)",
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  },
  "F29": {
   "source": "B10",
   "origin": "own_page",
   "pool": "B_R",
   "locus": "§3.1 Bloom Filter Sketching",
   "quote": "Bloom filters are similar to hash tables, but they store only the hash of a data element rather than storing the element itself. … Bloom filters can output false positives but never false negatives.",
   "claim": "a Bloom filter stores only hashes of elements; it can give false positives, never false negatives",
   "modality": "documented",
   "kind": "definition",
   "kernel": true,
   "const": false,
   "lineage": "the sketch: Bloom filter, strided n-grams, hashes",
   "sense": "the entity",
   "date": "2023-12-14 (v2)",
   "quote_ok": true,
   "checked_against": "datasets/negative-of-the-negative/v2/intake/data-portraits-20261101/B10.txt (whitespace-normalised; multi-part quotes joined by ' … ', each part checked)"
  },
  "F30": {
   "source": "B10",
   "origin": "own_page",
   "pool": "B_R",
   "locus": "§3.2 Bloom Filter Construction",
   "quote": "This reduces space requirements but carries the risk of missing some string of interest if it is split by a tile boundary in the corpus.",
   "claim": "storing strided n-grams saves space and risks missing a string split by a tile boundary",
   "modality": "self-description",
   "kind": "limit",
   "kernel": false,
   "const": false,
   "lineage": "the sketch: Bloom filter, strided n-grams, hashes",
   "sense": "the entity",
   "date": "2023-12-14 (v2)",
   "quote_ok": true,
   "checked_against": "datasets/negative-of-the-negative/v2/intake/data-portraits-20261101/B10.txt (whitespace-normalised; multi-part quotes joined by ' … ', each part checked)"
  },
  "F31": {
   "source": "B10",
   "origin": "own_page",
   "pool": "B_R",
   "locus": "§3.2 (Redistribution)",
   "quote": "Since Bloom filters distribute only hashes, they provide some obfuscation. … Note that in principle, proprietary LLM providers (e.g ChatGPT [29]) could release a Bloom filter based Data Portrait without revealing their exact training data – only the hashes of some substrings.",
   "claim": "distributing only hashes obfuscates the data; a proprietary provider could in principle release a portrait without revealing its training data",
   "modality": "interpretation",
   "kind": "function",
   "kernel": false,
   "const": false,
   "lineage": "the sketch: Bloom filter, strided n-grams, hashes",
   "sense": "the entity",
   "date": "2023-12-14 (v2)",
   "quote_ok": true,
   "checked_against": "datasets/negative-of-the-negative/v2/intake/data-portraits-20261101/B10.txt (whitespace-normalised; multi-part quotes joined by ' … ', each part checked)"
  },
  "F32": {
   "source": "B10",
   "origin": "own_page",
   "pool": "B_R",
   "locus": "§4.1 Constructing Portraits",
   "quote": "Further examples in this paper use a sketch built on character n-grams of length 50. … In effect, a 50 character span is already a good document fingerprint.",
   "claim": "the sketch uses character n-grams of length 50, a span the authors find a good document fingerprint",
   "modality": "documented",
   "kind": "fact",
   "kernel": false,
   "const": false,
   "lineage": "the sketch: Bloom filter, strided n-grams, hashes",
   "sense": "the entity",
   "date": "2023-12-14 (v2)",
   "quote_ok": true,
   "checked_against": "datasets/negative-of-the-negative/v2/intake/data-portraits-20261101/B10.txt (whitespace-normalised; multi-part quotes joined by ' … ', each part checked)"
  },
  "F33": {
   "source": "B10",
   "origin": "own_page",
   "pool": "B_R",
   "locus": "§4.1 The Pile",
   "quote": "The structure takes only 27 GB on disk and has a false positive rate of 1 × 10−3",
   "claim": "the Pile portrait: 27 GB on disk, false positive rate 1 × 10⁻³",
   "modality": "documented",
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   "kernel": false,
   "const": false,
   "lineage": "size and speed",
   "sense": "the entity",
   "date": "2023-12-14 (v2)",
   "quote_ok": true,
   "checked_against": "datasets/negative-of-the-negative/v2/intake/data-portraits-20261101/B10.txt (whitespace-normalised; multi-part quotes joined by ' … ', each part checked)"
  },
  "F34": {
   "source": "B10",
   "origin": "own_page",
   "pool": "B_R",
   "locus": "§4.4 Code Generation",
   "quote": "This artifact exactly documents the training data used in StarCoder, a 15.5B parameter code generation model [25]. … This plugin implements a plagiarism check by calling our Portrait service.",
   "claim": "the Stack portrait documents StarCoder's training data exactly and powers a plugin's plagiarism check",
   "modality": "documented",
   "kind": "fact",
   "kernel": false,
   "const": false,
   "lineage": "corpora recorded: The Pile, The Stack, The Stack V2",
   "sense": "the entity",
   "date": "2023-12-14 (v2)",
   "quote_ok": true,
   "checked_against": "datasets/negative-of-the-negative/v2/intake/data-portraits-20261101/B10.txt (whitespace-normalised; multi-part quotes joined by ' … ', each part checked)"
  },
  "F35": {
   "source": "B10",
   "origin": "own_page",
   "pool": "B_R",
   "locus": "§4.4 Code Generation",
   "quote": "Our Portrait service acts as a lightweight first-pass check for model plagiarism and additional tools from Li et al. [25] can be used to further assess attribution.",
   "claim": "the service is a first-pass plagiarism check; attribution needs further tools",
   "modality": "self-description",
   "kind": "limit",
   "kernel": false,
   "const": false,
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   "date": "2023-12-14 (v2)",
   "quote_ok": true,
   "checked_against": "datasets/negative-of-the-negative/v2/intake/data-portraits-20261101/B10.txt (whitespace-normalised; multi-part quotes joined by ' … ', each part checked)"
  },
  "F36": {
   "source": "B10",
   "origin": "own_page",
   "pool": "B_R",
   "locus": "§4.2 WMT Overlap",
   "quote": "we cannot conclude whether translation targets are memorized by a specific model, but our Pile-based sketch shows that some test data has leaked.",
   "claim": "a finding and its limit: some WMT test data has leaked into the Pile; whether a specific model memorized it cannot be concluded",
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  },
  "F37": {
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   "pool": "B_R",
   "locus": "§4.3 Overlap Detection",
   "quote": "Target summaries from XSum have the highest incidence of overlap with the Pile. … This suggests that some LDC files are publicly exposed and scraped into LLM corpora",
   "claim": "XSum summaries overlap the Pile most; some LDC files appear scraped into LLM corpora",
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   "lineage": "uses: leakage, plagiarism, creators",
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   "date": "2023-12-14 (v2)",
   "quote_ok": true,
   "checked_against": "datasets/negative-of-the-negative/v2/intake/data-portraits-20261101/B10.txt (whitespace-normalised; multi-part quotes joined by ' … ', each part checked)"
  },
  "F38": {
   "source": "B10",
   "origin": "own_page",
   "pool": "B_R",
   "locus": "§5.1 False Positives",
   "quote": "We first find that there are no chained matches when querying our system with novel New York Times text. … we next find a false positive rate of 7 × 10−4",
   "claim": "on novel text, no chained matches and a measured false positive rate of 7 × 10⁻⁴",
   "modality": "documented",
   "kind": "fact",
   "kernel": false,
   "const": false,
   "lineage": "limits and error",
   "sense": "the entity",
   "date": "2023-12-14 (v2)",
   "quote_ok": true,
   "checked_against": "datasets/negative-of-the-negative/v2/intake/data-portraits-20261101/B10.txt (whitespace-normalised; multi-part quotes joined by ' … ', each part checked)"
  },
  "F39": {
   "source": "B10",
   "origin": "own_page",
   "pool": "B_R",
   "locus": "§6 Impact and Limitations",
   "quote": "Our work is limited in that we focus on studying only a few datasets. … We stress a lightweight and efficient hash-based approach to membership testing, but this comes with certain trade-offs such as false positives and the inability to retrieve the context surrounding a match.",
   "claim": "the stated limits: few datasets; false positives; no retrieval of the context around a match",
   "modality": "self-description",
   "kind": "limit",
   "kernel": true,
   "const": false,
   "lineage": "limits and error",
   "sense": "the entity",
   "date": "2023-12-14 (v2)",
   "quote_ok": true,
   "checked_against": "datasets/negative-of-the-negative/v2/intake/data-portraits-20261101/B10.txt (whitespace-normalised; multi-part quotes joined by ' … ', each part checked)"
  },
  "F40": {
   "source": "B10",
   "origin": "own_page",
   "pool": "B_R",
   "locus": "§6 Impact and Limitations",
   "quote": "That is, an open plagiarism detection tool could be used to avoid plagiarism detection.",
   "claim": "a stated risk: an open plagiarism detector could be used to evade detection",
   "modality": "self-description",
   "kind": "limit",
   "kernel": false,
   "const": false,
   "lineage": "limits and error",
   "sense": "the entity",
   "date": "2023-12-14 (v2)",
   "quote_ok": true,
   "checked_against": "datasets/negative-of-the-negative/v2/intake/data-portraits-20261101/B10.txt (whitespace-normalised; multi-part quotes joined by ' … ', each part checked)"
  },
  "F41": {
   "source": "B10",
   "origin": "own_page",
   "pool": "B_R",
   "locus": "§6 Impact and Limitations",
   "quote": "For example, a non-technical content creator could search for their material in a documented dataset.",
   "claim": "a hoped use: a non-technical content creator searching for their material in a documented dataset",
   "modality": "self-description",
   "kind": "function",
   "kernel": false,
   "const": false,
   "lineage": "uses: leakage, plagiarism, creators",
   "sense": "the entity",
   "date": "2023-12-14 (v2)",
   "quote_ok": true,
   "checked_against": "datasets/negative-of-the-negative/v2/intake/data-portraits-20261101/B10.txt (whitespace-normalised; multi-part quotes joined by ' … ', each part checked)"
  },
  "F42": {
   "source": "B10",
   "origin": "own_page",
   "pool": "B_R",
   "locus": "§7 Conclusions and Future Work",
   "quote": "proposed the adoption of Data Portraits: records supporting membership inference on the data used to train a model. … call for dataset and model creators to release some form of Data Portrait as part of their essential documentation.",
   "claim": "the conclusion's definition: records supporting membership inference on a model's training data, and a call for their release as essential documentation",
   "modality": "stipulation",
   "kind": "definition",
   "kernel": false,
   "const": false,
   "lineage": "what it is: artifacts that record training data",
   "sense": "the entity",
   "date": "2023-12-14 (v2)",
   "quote_ok": true,
   "checked_against": "datasets/negative-of-the-negative/v2/intake/data-portraits-20261101/B10.txt (whitespace-normalised; multi-part quotes joined by ' … ', each part checked)"
  },
  "F43": {
   "source": "B1",
   "origin": "card (homonym)",
   "pool": "B_D",
   "locus": "page text",
   "quote": "For the Target space at TED 2017 in Vancouver, we designed and produced unique visual Data Portraits of the attendees: visual designs based on answers to simple but evocative questions that we turned into wearable buttons to spark conversations and connections for the five days of the event.",
   "claim": "homonym: Giorgia Lupi's (Accurat's) TED 2017 Data Portraits, wearable buttons designed from attendees' answers",
   "modality": "documented",
   "kind": "fact",
   "kernel": true,
   "const": false,
   "lineage": "the other entities of the name",
   "sense": "homonym: Giorgia Lupi / Accurat, Data Portraits at TED 2017",
   "date": "2017 (the project); page undated",
   "quote_ok": true,
   "checked_against": "datasets/negative-of-the-negative/v2/intake/data-portraits-20261101/B1.txt (whitespace-normalised; multi-part quotes joined by ' … ', each part checked)"
  },
  "F44": {
   "source": "B3",
   "origin": "card (homonym)",
   "pool": "B_D",
   "locus": "page text",
   "quote": "Book — Non-fiction. By the W. E. B. Du Bois Center at University of Massachusetts Amherst. 2018. 144 pages. … W. E . B. Du Bois’s Data Portraits is the first complete publication of W. E. B. Du Bois’s groundbreaking charts, graphs, and maps presented at the 1900 Paris Exposition.",
   "claim": "homonym: the 2018 book W. E. B. Du Bois's Data Portraits, the first complete publication of Du Bois's charts, graphs and maps of the 1900 Paris Exposition",
   "modality": "documented",
   "kind": "fact",
   "kernel": true,
   "const": false,
   "lineage": "the other entities of the name",
   "sense": "homonym: W. E. B. Du Bois's data portraits (1900) and the 2018 book",
   "date": "2018 (the book); 1900 (the charts)",
   "quote_ok": true,
   "checked_against": "datasets/negative-of-the-negative/v2/intake/data-portraits-20261101/B3.txt (whitespace-normalised; multi-part quotes joined by ' … ', each part checked)"
  },
  "F45": {
   "source": "B4",
   "origin": "card (homonym)",
   "pool": "B_D",
   "locus": "page text",
   "quote": "For the Target-sponsored social space at TED 2017 in Vancouver, Giorgia Lupi designed and produced unique visual Data Portraits for attendees to spark conversations and connections among them during the five-day conference. … The team generated more than 500 data portraits during the five-day conference.",
   "claim": "homonym: Pentagram's account of Lupi's TED 2017 Data Portraits, more than 500 made",
   "modality": "documented",
   "kind": "fact",
   "kernel": true,
   "const": false,
   "lineage": "the other entities of the name",
   "sense": "homonym: Giorgia Lupi, TED Data Portraits (Pentagram)",
   "date": "2017 (the project); page undated",
   "quote_ok": true,
   "checked_against": "datasets/negative-of-the-negative/v2/intake/data-portraits-20261101/B4.txt (whitespace-normalised; multi-part quotes joined by ' … ', each part checked)"
  },
  "F46": {
   "source": "B5",
   "origin": "card (homonym)",
   "pool": "B_D",
   "locus": "card snippet (unreachable)",
   "quote": "Sociologist W.E.B. Du Bois created sixty hand-drawn \"data portraits\" between 1897 and 1990 with Atlanta University students and scholars, visualizing Black Amer...",
   "claim": "homonym: SparkMap's card on Du Bois's sixty hand-drawn data portraits with Atlanta University students (the snippet's '1990' as rendered)",
   "modality": "documented",
   "kind": "fact",
   "kernel": true,
   "const": false,
   "lineage": "the other entities of the name",
   "sense": "homonym: W. E. B. Du Bois's data portraits (SparkMap)",
   "date": "undated (snippet only)",
   "quote_ok": true,
   "checked_against": "the card's title and snippet in the registry (cite_list), whitespace-normalised"
  },
  "F47": {
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   "origin": "card (homonym)",
   "pool": "B_D",
   "locus": "video card title (5m; University of Massachusetts Amherst Libraries)",
   "quote": "W. E. B. Du Bois's Data Portraits: Visualizing Black America",
   "claim": "homonym: a five-minute video by the UMass Amherst Libraries on the Du Bois book",
   "modality": "documented",
   "kind": "fact",
   "kernel": true,
   "const": false,
   "lineage": "the other entities of the name",
   "sense": "homonym: W. E. B. Du Bois's Data Portraits (video)",
   "date": "undated (title only)",
   "quote_ok": true,
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  },
  "F48": {
   "source": "B7",
   "origin": "card (homonym)",
   "pool": "B_D",
   "locus": "card snippet (unreachable)",
   "quote": "Data portraits depict their subjects' accumulated data rather than their faces. They can be visualizations of discussion contributions, browsing histories, soci...",
   "claim": "homonym: the MIT Media Lab's data portraits, depicting subjects' accumulated data in place of their faces",
   "modality": "documented",
   "kind": "definition",
   "kernel": true,
   "const": false,
   "lineage": "the other entities of the name",
   "sense": "homonym: Judith Donath's data portraits (MIT Media Lab)",
   "date": "undated (snippet only)",
   "quote_ok": true,
   "checked_against": "the card's title and snippet in the registry (cite_list), whitespace-normalised"
  },
  "F49": {
   "source": "B8",
   "origin": "card (homonym)",
   "pool": "B_D",
   "locus": "article, ¶2; date",
   "quote": "June 30, 2014 … digital media scholar Judith Donath defines data portraits as “depictions of people made by visualizing data by and about them.”",
   "claim": "homonym: Judith Donath's definition of data portraits, as ARTnews reported it in 2014",
   "modality": "attributed",
   "kind": "definition",
   "kernel": true,
   "const": false,
   "lineage": "the other entities of the name",
   "sense": "homonym: Judith Donath's data portraits (ARTnews)",
   "date": "2014-06-30",
   "quote_ok": true,
   "checked_against": "datasets/negative-of-the-negative/v2/intake/data-portraits-20261101/B8.txt (whitespace-normalised; multi-part quotes joined by ' … ', each part checked)"
  },
  "F50": {
   "source": "B11",
   "origin": "wikipedia",
   "pool": "B_R",
   "locus": "index.php?title=Data_Portraits&action=raw (and Data_portraits, Data_portrait, the paper's title)",
   "quote": "Error: 404, Not Found",
   "claim": "the encyclopedia has no article titled Data Portraits, data portraits, data portrait, or the paper's title (HTTP 404 for each raw fetch)",
   "modality": "documented",
   "kind": "fact",
   "kernel": false,
   "const": false,
   "lineage": "the encyclopedia and the name",
   "sense": "the name (encyclopedia)",
   "date": "2026-11-01 (read)",
   "quote_ok": true,
   "checked_against": "datasets/negative-of-the-negative/v2/intake/data-portraits-20261101/B11.txt (whitespace-normalised; multi-part quotes joined by ' … ', each part checked)"
  },
  "F51": {
   "source": "B11",
   "origin": "wikipedia",
   "pool": "B_R",
   "locus": "api.php search for \"Data Portraits\"",
   "quote": "\"totalhits\":7",
   "claim": "the encyclopedia's search for the phrase returns seven articles (the Du Bois book cited in several; none on the paper's artifact)",
   "modality": "documented",
   "kind": "fact",
   "kernel": false,
   "const": false,
   "lineage": "the encyclopedia and the name",
   "sense": "the name (encyclopedia)",
   "date": "2026-11-01 (read)",
   "quote_ok": true,
   "checked_against": "datasets/negative-of-the-negative/v2/intake/data-portraits-20261101/B11-search.json (whitespace-normalised; multi-part quotes joined by ' … ', each part checked)"
  },
  "F52": {
   "source": "B12",
   "origin": "own_page",
   "pool": "B_R",
   "locus": "pile.dataportraits.org; stack.dataportraits.org; stack-v2.dataportraits.org",
   "quote": "error code: 502",
   "claim": "the three sketch front ends answered HTTP 502 on 2026-11-01",
   "modality": "documented",
   "kind": "fact",
   "kernel": false,
   "const": false,
   "lineage": "publication, lifecycle and access",
   "sense": "the entity",
   "date": "2026-11-01 (read)",
   "quote_ok": true,
   "checked_against": "datasets/negative-of-the-negative/v2/intake/data-portraits-20261101/B12-pile.html (whitespace-normalised; multi-part quotes joined by ' … ', each part checked)"
  }
 },
 "field_sources": {
  "B1": "giorgialupi — Data Portraits at TED — giorgialupi",
  "B2": "Data Portraits — Data Portraits",
  "B3": "Zinn Education Project — W. E. B. Du Bois's Data Portraits: Visualizing Black America - Zinn Education Project",
  "B4": "Pentagram — TED Data Portraits - Pentagram",
  "B5": "SparkMap — W.E.B. Du Bois & Data Visualization History - SparkMap",
  "B6": "YouTube·University of Massachusetts Amherst Libraries — W. E. B. Du Bois's Data Portraits: Visualizing Black America",
  "B7": "MIT Media Lab — Data Portraits - MIT Media Lab",
  "B8": "ARTnews.com — 10 Painstakingly Crafted Data Portraits That Reveal Strange Details of People's ...",
  "B9": "arXiv — [2303.03919] Data Portraits: Recording Foundation Model Training Data",
  "B10": "arXiv — Data Portraits: Recording Foundation Model Training Data (PDF, v2)",
  "B11": "Wikipedia — no article 'Data Portraits' (HTTP 404); search for \"Data Portraits\"",
  "B12": "dataportraits.org — the Pile, Stack and Stack V2 sketch front ends (HTTP 502)"
 }
}