Datasets:

huanggab
/

reddit_haiku

Error code:   DatasetGenerationCastError
Exception:    DatasetGenerationCastError
Message:      An error occurred while generating the dataset

All the data files must have the same columns, but at some point there are 7 new columns ({'downs', 'upvote_ratio', 'author_karma', 'author_name', 'permalink', 'title', 'created_utc'}) and 1 missing columns ({'keywords'}).

This happened while the csv dataset builder was generating data using

hf://datasets/huanggab/reddit_haiku/processing_code/reddit-2022-10-20-dump.csv (at revision d9c4b7fe6948e8651d914b111367c4be9f2f0269)

Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 2011, in _prepare_split_single
                  writer.write_table(table)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 585, in write_table
                  pa_table = table_cast(pa_table, self._schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2302, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2256, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              id: string
              Unnamed: 0: int64
              title: string
              author_name: string
              author_karma: int64
              ups: int64
              downs: int64
              upvote_ratio: double
              permalink: string
              created_utc: double
              processed_title: string
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 1542
              to
              {'Unnamed: 0': Value(dtype='int64', id=None), 'id': Value(dtype='string', id=None), 'processed_title': Value(dtype='string', id=None), 'ups': Value(dtype='int64', id=None), 'keywords': Value(dtype='string', id=None)}
              because column names don't match
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1321, in compute_config_parquet_and_info_response
                  parquet_operations = convert_to_parquet(builder)
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 935, in convert_to_parquet
                  builder.download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1027, in download_and_prepare
                  self._download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1122, in _download_and_prepare
                  self._prepare_split(split_generator, **prepare_split_kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1882, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 2013, in _prepare_split_single
                  raise DatasetGenerationCastError.from_cast_error(
              datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
              
              All the data files must have the same columns, but at some point there are 7 new columns ({'downs', 'upvote_ratio', 'author_karma', 'author_name', 'permalink', 'title', 'created_utc'}) and 1 missing columns ({'keywords'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/huanggab/reddit_haiku/processing_code/reddit-2022-10-20-dump.csv (at revision d9c4b7fe6948e8651d914b111367c4be9f2f0269)
              
              Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)

Need help to make the dataset viewer work? Open a discussion for direct support.

Unnamed: 0 int64	id string	processed_title string	ups int64	keywords string
0	1020ac	There's nothing inside/There is nothing outside me/I search on in hope.	5	[('inside', 0.5268), ('outside', 0.3751), ('search', 0.3367), ('hope', 0.272)]
1	107cob	From whole we crumble/Forever lost to chaos/Never one again	1	[('chaos', 0.5962), ('crumble', 0.4749), ('forever', 0.4099), ('lost', 0.3337)]
2	109a51	Indistinctiveness/Immeasurability/Capitalism	3	[('indistinctiveness', 0.7664), ('immeasurability', 0.5407), ('capitalism', 0.5254)]
3	10eysi	Internet is down/Obligations go bye-bye/Office rejoices	9	[('office', 0.5033), ('obligations', 0.4663), ('rejoices', 0.4336), ('internet', 0.3998), ('bye', 0.2772)]
4	10f79k	Cotton in my mouth/Needles in my blood and bones/Hammers in my head.	1	[('needles', 0.5314), ('cotton', 0.4806), ('blood', 0.4004), ('bones', 0.3279), ('hammers', 0.3083)]
5	10h3x8	Mighty Hummingbird/drinks from a grapefruit's blossom;/blots out an airplane	7	[('hummingbird', 0.5706), ('grapefruit', 0.481), ('drinks', 0.3803), ('blossom', 0.3687), ('airplane', 0.3433)]
6	10mgcy	Downvotes fall as sharp/snowflakes of early winter,/an execution.	1	[('snowflakes', 0.5383), ('winter', 0.4421), ('downvotes', 0.3616), ('fall', 0.3603), ('execution', 0.3279)]
7	10oy3o	Seven ships tonight/Guess I should've said goodbye/Saw eight this morning.	1	[('ships', 0.4741), ('seven', 0.441), ('goodbye', 0.4332), ('morning', 0.3336), ('saw', 0.2597)]
8	10qvrn	Big words are so bad/They can ruin a haiku/Refrigerator	0	[('haiku', 0.6461), ('words', 0.4339), ('refrigerator', 0.3415), ('ruin', 0.2549), ('bad', 0.2115)]
9	1124nn	At the end of life/the kings, the queens, and the pawns/are in the same box	43	[('kings', 0.4799), ('pawns', 0.4481), ('queens', 0.3661), ('box', 0.3358), ('life', 0.2961)]
10	113rj0	The "free man's" short life/success measured in money/all work and no play	7	[('money', 0.3652), ('short', 0.3284), ('life', 0.3214), ('work', 0.2969), ('success', 0.2953)]
11	1155zb	Like lemmings off cliffs/humans flock to a leader/who is just as blind	17	[('lemmings', 0.5237), ('flock', 0.4296), ('blind', 0.4019), ('cliffs', 0.3912), ('humans', 0.3527)]
12	115p6t	You left this morning/before I woke. My bed's empty;/my toothbrush minty.	1	[('toothbrush', 0.5477), ('morning', 0.4745), ('minty', 0.4673), ('bed', 0.4549), ('woke', 0.3232)]
13	115qay	You left this morning/before I woke. Bed's empty;/my toothbrush, minty.	3	[('toothbrush', 0.5631), ('minty', 0.4856), ('morning', 0.4775), ('bed', 0.4232), ('woke', 0.3281)]
14	11635f	The world keeps spinning/And nobody notices/But what if it stopped?	9	[('spinning', 0.4683), ('world', 0.3198), ('stopped', 0.2867), ('keeps', 0.1302), ('notices', 0.0953)]
15	116atb	We live our whole lives/to make it safely to death;/why not take some risks?	12	[('risks', 0.5995), ('safely', 0.475), ('death', 0.3317), ('live', 0.2785), ('lives', 0.2744)]
16	117kom	The endless beauty/natures finest gift to all/that girls shining grin.	1	[('beauty', 0.513), ('natures', 0.4346), ('grin', 0.4208), ('endless', 0.3851), ('shining', 0.3564)]
17	117prx	life has a mantra/I am sad to discover/the fun is over	1	[('life', 0.4726), ('mantra', 0.4694), ('sad', 0.3049), ('discover', 0.3041), ('fun', 0.2864)]
18	117t83	If zombies are real/I will break your fucking foot/Gimps are slow as hell	0	[('gimps', 0.5475), ('zombies', 0.5333), ('slow', 0.2621), ('real', 0.2476), ('foot', 0.2466)]
19	119wfn	Buildings will remain/monuments to our excess/but we will be gone	10	[('buildings', 0.5303), ('monuments', 0.5206), ('remain', 0.3772), ('excess', 0.2167), ('gone', 0.2051)]
20	11e4aw	The last drop of oil/will be burnt by a tank, in/a war over it	22	[('oil', 0.5184), ('war', 0.482), ('tank', 0.4056), ('burnt', 0.3286), ('drop', 0.3149)]
21	11f8o1	Autumn chill descends/Electric blanket returns/Snug in my cocoon	1	[('blanket', 0.6077), ('autumn', 0.4896), ('cocoon', 0.4582), ('electric', 0.352), ('descends', 0.3179)]
22	11g0dv	Sociopath pee/Trickle down economics/Are one and the same	0	[('sociopath', 0.5391), ('economics', 0.4604), ('trickle', 0.4491), ('pee', 0.3752)]
23	11ir7w	I peer the mirror/I fear the face that I see/Broken yet beating.	5	[('mirror', 0.5843), ('fear', 0.4673), ('beating', 0.3804), ('face', 0.351), ('peer', 0.2778)]
24	11jpv8	I stand at the wall/Looking up in the cracks for/signs from my future	1	[('signs', 0.496), ('wall', 0.4869), ('cracks', 0.3891), ('stand', 0.3626), ('future', 0.3394)]
25	11v30a	The love of my life/The light of my darkened world/May you rest in peace	1	[('darkened', 0.4862), ('peace', 0.436), ('light', 0.3665), ('rest', 0.3519), ('life', 0.3412)]
26	11wwlw	Telltale signs arrive/temper, sickness, bad mornings/hello mom and dad	5	[('signs', 0.5317), ('sickness', 0.4841), ('telltale', 0.4067), ('temper', 0.3708), ('mornings', 0.347)]
27	11zzwg	The Haiku Tune (x-post from/r/video)	1	[('haiku', 0.7076), ('tune', 0.3941), ('video', 0.2435), ('post', 0.2388)]
28	12014m	Wouldn't mind at all/If while floating the waves/One swallows me whole	1	[('floating', 0.5607), ('waves', 0.4525), ('swallows', 0.4321), ('mind', 0.198), ('wouldn', 0.1963)]
29	120fex	Saccharine pop spills/out from the car stereo./It's been a long day.	6	[('spills', 0.4876), ('saccharine', 0.4761), ('pop', 0.4005), ('stereo', 0.3756), ('car', 0.3148)]
30	122kx1	The morning mist fades/in time for the Sun' best gold./Her eyes kept westward.	1	[('sun', 0.4133), ('mist', 0.4058), ('morning', 0.3835), ('fades', 0.3605), ('westward', 0.2558)]
31	123bqu	At city limits/her turn signal waves goodbye/as I keep driving.	5	[('driving', 0.4113), ('signal', 0.3826), ('goodbye', 0.3662), ('waves', 0.3251), ('turn', 0.3065)]
32	125leq	their kids could survive/if they had that stuff you use/to wash off your car	6	[('kids', 0.4085), ('car', 0.2822), ('wash', 0.2568), ('survive', 0.2551), ('stuff', 0.1796)]
33	128dh5	I suck at haikus/I can't think of anything/Refrigerator	0	[('haikus', 0.7284), ('refrigerator', 0.473), ('suck', 0.2569), ('think', 0.1336)]
34	12aj2v	Nature roars her head/some die from the sheer terror/those that don't have ran	6	[('roars', 0.4406), ('nature', 0.382), ('terror', 0.3782), ('die', 0.2695), ('ran', 0.2693)]
35	12cucf	you better do it/or you better not regret/not having done it	1	[('regret', 0.5593), ('better', 0.3096), ('having', 0.2565)]
36	12gtwd	Eyes clouded by tears/Seeing a freshly dug grave/From the inside out	14	[('grave', 0.5316), ('tears', 0.417), ('clouded', 0.3801), ('eyes', 0.3684), ('freshly', 0.3019)]
37	12hl5f	beneath the cover/of howl and other poems/a coin-sized spider	5	[('spider', 0.5268), ('howl', 0.4888), ('poems', 0.4428), ('cover', 0.2484), ('beneath', 0.2304)]
38	12lgzr	Birth in this moment/death in this moment as well/Autumn never fails	2	[('autumn', 0.5938), ('birth', 0.4546), ('death', 0.4014), ('moment', 0.2995), ('fails', 0.2552)]
39	12lho8	Electric torches/Concrete caverns in the sky/We haven't changed much.	1	[('torches', 0.5713), ('caverns', 0.448), ('electric', 0.3645), ('concrete', 0.3119), ('changed', 0.2499)]
40	12q20c	As upvotes increase/Wit of comments will decrease/Proportionately	1	[('comments', 0.4371), ('increase', 0.4291), ('decrease', 0.3993), ('upvotes', 0.3733), ('proportionately', 0.3532)]
41	12rhim	The consolation prize goes/To the ladies at/The barbecue booth, hooray!	0	[('consolation', 0.5482), ('barbecue', 0.4674), ('prize', 0.4242), ('hooray', 0.3526), ('ladies', 0.3374)]
42	12u64a	Vacancy/my heart is a hotel/you have rented all the rooms.	0	[('hotel', 0.6226), ('vacancy', 0.604), ('rooms', 0.5273), ('rented', 0.4915), ('heart', 0.364)]
43	12x3hy	The pen is lifted/The Creation's flow ceases/We are out of ink	1	[('pen', 0.5602), ('ink', 0.4901), ('creation', 0.4297), ('flow', 0.3834), ('ceases', 0.3046)]
44	137jf6	Meet you at a bar/Our Bodies Coalesce/Breakfast after dawn	1	[('breakfast', 0.5295), ('meet', 0.452), ('dawn', 0.4285), ('bar', 0.4104), ('coalesce', 0.3593)]
45	13a85w	Man paints by streetlight/Lone Star Party Bus/Austin is exhausting	0	[('austin', 0.4313), ('streetlight', 0.415), ('paints', 0.3986), ('bus', 0.3591), ('exhausting', 0.2675)]
46	13c4mt	You put the lime in/the coconut to fix the/belly ache , You put...	1	[('coconut', 0.5641), ('lime', 0.5125), ('belly', 0.3935), ('ache', 0.3165), ('fix', 0.1253)]
47	13cvvz	sharp clanks from coiled wire/dodge deep holes in iced pavement/a very blown shock	1	[('shock', 0.45), ('coiled', 0.4001), ('pavement', 0.3968), ('dodge', 0.3075), ('clanks', 0.3059)]
48	13hyrd	Sweat and tears everyday/my will and focus rises above/conquer everything.	1	[('sweat', 0.4647), ('tears', 0.4507), ('everyday', 0.3978), ('conquer', 0.391), ('rises', 0.3232)]
49	13ixxj	Sitting at my desk/My butt is starting to sleep/Hope it doesn't snore	1	[('snore', 0.5946), ('sleep', 0.5057), ('sitting', 0.4088), ('desk', 0.3981), ('butt', 0.392)]
50	13jqza	Stupid flattened tire./I curse the frigid night, and/wait for CAA.	1	[('tire', 0.4958), ('caa', 0.4929), ('flattened', 0.3667), ('frigid', 0.3506), ('curse', 0.3084)]
51	13qrl9	OP is a fag/bro, he doesn't even lift/jimmies are rustled	4	[('jimmies', 0.4604), ('lift', 0.4291), ('rustled', 0.4145), ('fag', 0.3958), ('op', 0.2905)]
52	13s23z	Making a haiku/deal with it, mother fucker/upvotes to the left	10	[('haiku', 0.6968), ('upvotes', 0.3217), ('fucker', 0.3144), ('mother', 0.2965), ('left', 0.2745)]
53	13smm0	socks, they smell of bleach/haven't done laundry this week/filthy, RedTube socks	11	[('socks', 0.6772), ('laundry', 0.6547), ('bleach', 0.5294), ('smell', 0.4693), ('filthy', 0.3307)]
54	13ujiz	Chilling with homies/I need watermelon now/so I used welfare	0	[('watermelon', 0.642), ('welfare', 0.5147), ('homies', 0.372), ('chilling', 0.3369), ('used', 0.1907)]
55	13uqzu	ornithology/wave behaviors all in one/glorious haiku	1	[('haiku', 0.6771), ('wave', 0.5543), ('ornithology', 0.4554), ('behaviors', 0.2797), ('glorious', 0.1785)]
56	13wlr4	"How'd you spell 'haiku?'"/"It's, uh, H-A-I-K-U"/"Gee, thanks for the help."	30	[('haiku', 0.7202), ('spell', 0.2989), ('gee', 0.176), ('uh', 0.1754), ('help', 0.1671)]
57	13y720	Electricity/flashing across the night sky;/illuminating	0	[('flashing', 0.6011), ('electricity', 0.5167), ('illuminating', 0.4944), ('night', 0.4151), ('sky', 0.3766)]
58	13z1d6	I dream of you God/I know the world is ending/But none will hear me	1	[('dream', 0.3969), ('world', 0.3582), ('ending', 0.3446), ('god', 0.3227), ('hear', 0.321)]
59	1402me	We golden flashes/Fall for the same emptiness/As darkness consumes	3	[('darkness', 0.5611), ('flashes', 0.4892), ('emptiness', 0.4863), ('golden', 0.443), ('consumes', 0.2958)]
60	140z6p	Light shines from afar/Pain, Freedom, Death, Happiness/The world is ending	6	[('happiness', 0.4383), ('light', 0.4341), ('ending', 0.4308), ('world', 0.3848), ('afar', 0.376)]
61	148ogt	dead flies, for our eyes/our pleasure, their sacrifice/rubber ducky Bitch!	1	[('flies', 0.5978), ('sacrifice', 0.4088), ('dead', 0.3771), ('ducky', 0.3454), ('eyes', 0.3427)]
62	149lma	First, a bachelor's/then, M.B.A. and J.D./Where's my fucking job?	1	[('bachelor', 0.6342), ('job', 0.2958), ('fucking', 0.0958)]
63	14dj9n	Time and time again/celebrities say Haikus/and don't realize it	1	[('haikus', 0.6962), ('celebrities', 0.3562), ('realize', 0.233), ('say', 0.228), ('time', 0.2157)]
64	14gs5c	Heaven's deep blue vault/Crowded with opulent clouds/Kites of the kami.	11	[('clouds', 0.5258), ('heaven', 0.4413), ('vault', 0.4395), ('kites', 0.3752), ('kami', 0.3651)]
65	14jlgh	A bridge is so vast/Crossing gaps and joining friends/Worldly and within.	9	[('bridge', 0.714), ('crossing', 0.4866), ('gaps', 0.318), ('joining', 0.3108), ('friends', 0.2996)]
66	14mgs2	Yay! New subreddit/I know it will be funny!/Damn. It's not at all.	11	[('subreddit', 0.3618), ('new', 0.3175), ('funny', 0.3042), ('yay', 0.215), ('know', 0.1452)]
67	14n02k	Man dies at eighty/Dropped soap in prison shower/Was brutally stabbed	1	[('soap', 0.4588), ('stabbed', 0.4292), ('shower', 0.3227), ('brutally', 0.3109), ('eighty', 0.256)]
68	14n29d	Migrating birds meet/On the water's green sloped shore./Water treatment plant.	7	[('birds', 0.5346), ('plant', 0.426), ('shore', 0.3844), ('migrating', 0.3615), ('water', 0.3562)]
69	14rmjb	I wrote a haiku,/I didn't enjoy it much,/So I threw it out.	2	[('haiku', 0.7413), ('wrote', 0.3028), ('threw', 0.2189), ('didn', 0.2027), ('enjoy', 0.1433)]
70	14vfu9	A spherical shape/The sun's bright essence contained/Within a white orb	2	[('orb', 0.5162), ('spherical', 0.488), ('essence', 0.4229), ('sun', 0.4196), ('shape', 0.2947)]
71	1515r5	I'm new around here/you all seem like nice people/God damn, this is hard	1	[('hard', 0.3213), ('new', 0.2678), ('people', 0.1972), ('nice', 0.1774), ('like', 0.1661)]
72	152isi	With claw locked in beak/Crushed in a landslide they keep/Fighting Forever	12	[('beak', 0.5316), ('claw', 0.5206), ('fighting', 0.3691), ('forever', 0.3527), ('crushed', 0.3307)]
73	153x5j	575 By Belly Peterson is FREE through 12/21/12 (Kindle Edition) - Please share your thoughts	0	[('kindle', 0.5709), ('free', 0.3116), ('575', 0.2919), ('edition', 0.2776), ('21', 0.187)]
74	157oli	You should not be afraid/the world is not going to end/Back to regularly scheduled programming	0	[('programming', 0.4549), ('afraid', 0.3561), ('scheduled', 0.3542), ('end', 0.2174), ('world', 0.1663)]
75	15dvul	I walked through a field/Looking as I went along/What is looking back?	4	[('field', 0.4814), ('walked', 0.4467), ('looking', 0.2721), ('went', 0.2519)]
76	15gsho	Oh how dreams haunt me/Show me false reality/Life lived in fake time	6	[('dreams', 0.4438), ('haunt', 0.4256), ('reality', 0.4145), ('fake', 0.3698), ('lived', 0.3479)]
77	15ltlz	A parting of ways/A bittersweet heart still beats/A confusing life	1	[('parting', 0.5448), ('bittersweet', 0.5424), ('heart', 0.5043), ('life', 0.4272), ('confusing', 0.3483)]
78	15mav7	A love felt so warm/summer breeze sparkling in air/soul captured in flight	1	[('breeze', 0.4132), ('soul', 0.3971), ('summer', 0.3908), ('love', 0.3878), ('sparkling', 0.3871)]
79	15n23e	The sky and the cloud/Two companions through my life/Artists up above	6	[('sky', 0.5432), ('artists', 0.5391), ('cloud', 0.4556), ('companions', 0.3325), ('life', 0.2948)]
80	15ntcf	World of warcraft trick/a frozen gift, running, bye/never-ending kite.	1	[('kite', 0.6688), ('warcraft', 0.5579), ('trick', 0.3896), ('gift', 0.3553), ('frozen', 0.3096)]
81	15nweu	I rescued her from him/now she needs rescuing/from me.	1	[('rescued', 0.5912), ('rescuing', 0.582), ('needs', 0.2264)]
82	15qqy3	Perhaps a window/or perhaps a mirror bright/words fly to paper	2	[('paper', 0.4968), ('window', 0.4486), ('mirror', 0.4082), ('bright', 0.378), ('words', 0.3719)]
83	15rtnh	Sure, covetous hands/Unhinge the topmost button/Of my cotton blouse	0	[('blouse', 0.5486), ('covetous', 0.4907), ('cotton', 0.3657), ('button', 0.339), ('hands', 0.3309)]
84	15shoh	The birds sing a song/That is uplifting and bright/In this world's darkness.	3	[('birds', 0.5175), ('darkness', 0.4567), ('sing', 0.4217), ('uplifting', 0.4162), ('song', 0.367)]
85	15stny	Night falls in winter/silent snow canvas of black/birdsong bursting forth	6	[('birdsong', 0.5762), ('snow', 0.5212), ('winter', 0.5084), ('falls', 0.4515), ('night', 0.4188)]
86	15tduc	Hotboxed five-seater/Bullshitting with a stranger/Infatuation.	0	[('infatuation', 0.5193), ('seater', 0.4692), ('hotboxed', 0.4666), ('stranger', 0.3308), ('bullshitting', 0.3209)]
87	15topg	As the sun rises/I look to heaven's wonders/Grateful for today	7	[('wonders', 0.4408), ('heaven', 0.4395), ('sun', 0.369), ('rises', 0.3672), ('grateful', 0.354)]
88	15umvz	Sexy, spunky girl/tolerates my silliness./Means the world to me.	27	[('silliness', 0.4999), ('tolerates', 0.4344), ('spunky', 0.432), ('means', 0.4125), ('girl', 0.3723)]
89	15xmdq	[#3] As the night unwinds/I can not help but wonder/If you're with the stars.	7	[('stars', 0.4991), ('unwinds', 0.4132), ('night', 0.4035), ('wonder', 0.2106), ('help', 0.1655)]
90	1608jg	[4]I lie here speechless/Gaze fixed upon the heavens/The sky beckons me	5	[('sky', 0.423), ('heavens', 0.3639), ('speechless', 0.3623), ('gaze', 0.3324), ('lie', 0.1956)]
91	1633u0	[#5] Open up the sky/So my pain will wash away/Let me see again	1	[('sky', 0.4137), ('pain', 0.38), ('wash', 0.2735), ('open', 0.2715), ('let', 0.2138)]
92	164hb0	The honey bucket/sits, awaiting excrement/falling like the rain.	1	[('bucket', 0.4995), ('honey', 0.4752), ('excrement', 0.4736), ('rain', 0.4605), ('falling', 0.3279)]
93	165z3j	hope in her eyes/brings out a social shyness/world where we are free	1	[('shyness', 0.4827), ('hope', 0.3573), ('social', 0.3269), ('world', 0.2702), ('eyes', 0.2678)]
94	166g1x	Orpheus runs sober/overcast clear blue sky/stuck behind glass	1	[('orpheus', 0.5908), ('glass', 0.3852), ('sky', 0.367), ('sober', 0.3657), ('overcast', 0.2811)]
95	166ilc	I'm new to haikus/I need to practice it more/To become awesome.	1	[('haikus', 0.7472), ('practice', 0.2866), ('new', 0.1555), ('need', 0.1462), ('awesome', 0.1382)]
96	167c3m	How would you escape/weiner, weiner, in my pants/in case of a fire	1	[('weiner', 0.5629), ('escape', 0.4669), ('pants', 0.3855), ('case', 0.1794)]
97	167gt5	Sleeping is my drug/My bed being the dealer/My alarm the law	32	[('sleeping', 0.5316), ('bed', 0.5164), ('alarm', 0.4881), ('dealer', 0.4437), ('drug', 0.4193)]
98	167p9y	I cooked a pizza/cut that bastard into squares/and ate the corners	0	[('pizza', 0.4449), ('cooked', 0.4256), ('corners', 0.3881), ('ate', 0.36), ('cut', 0.3574)]
99	167uyn	who is this she asks/says to stay out of her life/delete her number	1	[('delete', 0.3819), ('number', 0.3339), ('stay', 0.2967), ('life', 0.2781), ('asks', 0.2308)]

End of preview.

Dataset Card for "Reddit Haiku"

This dataset contains haikus from the subreddit /r/haiku scraped and filtered between October 19th and 10th 2022, combined with a previous dump of that same subreddit packaged by ConvoKit as part of the Subreddit Corpus, which is itself a subset of pushshift.io's big dump.

A main motivation for this dataset was to collect an alternative haiku dataset for evaluation, in particular for evaluating Fabian Mueller's Deep Haiku model which was trained on the Haiku datasets of hjhalani30 and bfbarry, which are also available on huggingface hub.

Fields

The fields are post id (id), the content of the haiku (processed_title), upvotes (ups), and topic keywords (keywords). Topic keywords for each haiku have been extracted with the KeyBERT library and truncated to top-5 keywords.

Usage

This dataset is intended for evaluation, hence there is only one split which is test.

from datasets import load_dataset

d=load_dataset('huanggab/reddit_haiku', data_files='test':'merged_with_keywords.csv'})  # use data_files or it will result in error
>>> print(d['train'][0])
#{'Unnamed: 0': 0, 'id': '1020ac', 'processed_title': "There's nothing inside/There is nothing outside me/I search on in hope.", 'ups': 5, 'keywords': "[('inside', 0.5268), ('outside', 0.3751), ('search', 0.3367), ('hope', 0.272)]"}

There is code for scraping and processing in processing_code, and a subset of the data with more fields such as author Karma, downvotes and posting time at processing_code/reddit-2022-10-20-dump.csv.

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