story-to-pack: add the corpora and the catalogue v2/v3

Fourteen corpora split and classified: aesop, bierce, chekhov, holmes,
keefe, lawson, lorimer, maupassant, nobody, plaintales, poe, torchy,
wallingford and winesburg, each with its splitter and the hand-written
groups and pages; catalogue v2 and v3; and the shared splitters
gutenberg_chunks.py, se_split.py and se_build.py.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_019rwKTmug58sEsJ72AuWsEi

tools/story-to-pack/probe/se_build.py

@@ -0,0 +1,30 @@
+"""Standard Ebooks collection -> stories.json + chunks.json, for any corpus directory.
+Usage: python3 se_build.py <dir> "<Volume (Author, year)>"
+Reads the single HTML file in <dir>/corpus/, splits stories with se_split.py (the `se:short-story`
+markup), then cuts scenes with the same rule as chunk.py, jacobs/split_se.py and the Gutenberg
+splitters: paragraph boundaries, ~320 words, a tail kept only if it is at least 80 words."""
+import json, pathlib, sys
+from se_split import split
+
+TARGET = 320
+d, volume = pathlib.Path(sys.argv[1]), sys.argv[2]
+[src] = list((d / 'corpus').glob('*.html'))
+stories = [{'volume': volume, 'title': s['title'], 'words': sum(len(p.split()) for p in s['paras']),
+            'text': '\n\n'.join(s['paras'])} for s in split(src)]
+chunks = []
+for si, s in enumerate(stories):
+    buf, n = [], 0
+    for p in s['text'].split('\n\n'):
+        w = len(p.split())
+        if n + w > TARGET and buf:
+            chunks.append({'story': si, 'title': s['title'], 'volume': volume, 'text': ' '.join(buf), 'words': n})
+            buf, n = [], 0
+        buf.append(p); n += w
+    if buf and n >= 80:
+        chunks.append({'story': si, 'title': s['title'], 'volume': volume, 'text': ' '.join(buf), 'words': n})
+(d / 'stories.json').write_text(json.dumps(stories, indent=1, ensure_ascii=False), encoding='utf-8')
+(d / 'chunks.json').write_text(json.dumps(chunks, ensure_ascii=False), encoding='utf-8')
+for si, s in enumerate(stories):
+    print(f"{si:2} {s['title'][:40]:40} {s['words']:6} words  {sum(c['story'] == si for c in chunks):3} scenes")
+ws = sorted(c['words'] for c in chunks)
+print(f'stories {len(stories)}  scenes {len(chunks)}  words/scene min {ws[0]} median {ws[len(ws)//2]} max {ws[-1]}  total {sum(ws):,}')