{
  "row": "nanogenmo",
  "address": "NaNoGenMo",
  "entity": "NaNoGenMo (National Novel Generation Month; nanogenmo.github.io): in its own words an activity in which participants spend November writing code that generates a novel of 50k+ words and share at least one novel and its source code, organised as a community on GitHub, one repository per edition, 2013 to 2025, official admins @dariusk and @hugovk, 'based on an idea Darius Kazemi tweeted on a whim'; formalized in the traininglayerliterature.org layer census (https://www.traininglayerliterature.org/aggregators/nanogenmo), 2026-11-01",
  "row_type": "C (a public entity on which the archive bears: an annual event series and archive of code-generated novels shared with their source code; an entity of the traininglayerliterature.org layer census)",
  "aliases": [
    {
      "pattern": "\\bNaNoGenMo\\b",
      "flags": "i"
    },
    {
      "pattern": "\\bNational Novel Generation Month\\b",
      "flags": "i"
    },
    {
      "pattern": "\\bnanogenmo\\.github\\.io\\b",
      "flags": "i"
    }
  ],
  "classes": [
    {
      "term": "novels and other long texts generated by code (computer-generated literature, story and text generation)",
      "pattern": "\\b(computer[- ]generated (novels?|texts?|books?|literature|prose|fiction|poetry|poems?)|(code|program|programs|software)[- ]generated (novels?|texts?|books?)|generated novels?|novel generation|story generation|procedural(ly)? generat\\w+ (texts?|novels?|literature|prose|poetry|poems?)|generative (literature|fiction|poetry|text))\\b",
      "flags": "i",
      "basis": "field: B1 (own page and card 1, The Goal: 'Spend the month of November writing code that generates a novel of 50k+ words.'); B4 (card 4, Liza Daly: 'Every November, a hundred or so people write computer programs that attempt to generate \"novels.\"'); B5 (card 5, CenterConsulting: 'writing computer code that generates a novel rather than writing one by hand'). The layer census's kind, record_object and area 'machine-composition' ('Reception becoming composition: readers, models and practices that make new writing from what they read') for the entity (TLL record)."
    },
    {
      "term": "generated texts made from existing source text (a public-domain novel taken whole, corpora, Markov chains over a corpus)",
      "pattern": "\\b(Project Gutenberg|public[- ]domain (texts?|corpus|corpora|books?|novels?)|Markov chains?|source texts? (taken|reused|recombined))\\b",
      "flags": "i",
      "basis": "field: B1 (The Rules: 'It could literally grab a random novel from Project Gutenberg.'; Resources: 'corpora, a repository of public domain lists of things'); B4 (card 4: 'makes smart use of Markov chains, a good corpus'); B5 (card 5: 'Early entries used Markov chains, scraped text, and procedural tricks'). The layer census's record.in_layer and record.makes and its relation 'uses' project-gutenberg (TLL record)."
    },
    {
      "term": "procedural and computational generation of literary text (composition delegated to a program: the machine as method)",
      "pattern": "\\b(procedural(ly)? (generat\\w+|poetry|poetics|texts?|lineage|tricks|composition|literature)|computational (poetry|poetics|literature|creativity)|text generators?|poetry generators?)\\b",
      "flags": "i",
      "basis": "field: B5 (card 5, CenterConsulting: 'Early entries used Markov chains, scraped text, and procedural tricks'); B4 (card 4, Liza Daly: 'Many NaNoGenMo projects rely on substituting words based on their semantic relationships to each other'); B1 (The Goal: 'writing code that generates a novel'). The layer census's area 'machine-composition' and its question ('what does a program make into a novel of 50k+ words, from which sources') for the entity (TLL record)."
    }
  ],
  "classes_note": "Three classes, each sourced by the field B and the layer census record. (1) novels and long texts generated by code: B1, B4, B5; TLL kind, record_object, area machine-composition. (2) generated texts made from existing source text: B1, B4, B5; TLL record.in_layer, record.makes, relation uses project-gutenberg. (3) procedural and computational generation of literary text: B5, B4, B1; TLL area machine-composition and question. Class (3) was added after the first string pass and before its candidates were read: classes (1) and (2) returned 23 sentences in 15 deposits, all of them on Project Gutenberg as a source packaging, public-domain licences or the adjective 'novel', none on generated literature; the pass was rerun with the third class. The census anchors are read at their passages whatever the string pass returns: #186 at the four practices (the machine as subject, collaborator, method, reader) and the procedural lineage, since the field describes code that generates novels (writing through the machine as method, in #186's table); #1543 at machine composition, the four coordinates of an output (source status, composition class, uptake, provenance), the dependence requirement and the recursive loop x → M → y → corpus, since the layer census places the entity in the area machine-composition and its record.makes describes novels made from existing text. 'NaNoWriMo' (National Novel Writing Month) is a distinct entity the field names as the event's inspiration and is not an alias; NaPoGenMo, NaOpGenMo and NaMoGenMo are sister events and distinct entities; Darius Kazemi and Hugo van Kemenade (hugovk) are its admins and are not aliases. No sourced class is given for 'shared with its source code' (the archive's vocabulary of source code is software and repository practice); the sharing rule is read through the anchors only.",
  "exclude_deposits": [],
  "notes": "entity-keyed pass, 2026-11-01, on the brief rebuild/negative-of-the-negative/v010/BRIEF-NEW-ROW-LAYER.md (with v09/BRIEF-NEW-ROW-AGGREGATOR.md, -LABOR.md, -LEFT.md); address 'NaNoGenMo' (nanogenmo-aio-20261101, OBS-5f58f9b11be4, ADDR-60ff4ea844ef), Google AI Overview (expanded), signed out, incognito. The archive's own records of the entity (the Capture Registry's findings, reading and analysis; the traininglayerliterature.org layer census record) are ledgered beside the deposits as CAP-1-NN and TLL-NN.",
  "hop_from": [
    186,
    1543,
    400,
    1012
  ]
}