Datasets:

ruanchaves
/

stan_small

Languages: English

Multilinguality: monolingual

Size Categories: unknown

Language Creators: machine-generated

Annotations Creators: expert-generated

Source Datasets: original

ArXiv:

Tags: word-segmentation

License: unknown

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index (int32)	hashtag (string)	segmentation (string)	alternatives (sequence)
0	"Typo3"	"Typo3"	{ "segmentation": [ "TYPO3" ] }
1	"KolacheFactory"	"Kolache Factory"	{ "segmentation": [] }
2	"moanmondays"	"moan mondays"	{ "segmentation": [] }
3	"semantic"	"semantic"	{ "segmentation": [] }
4	"babypunch"	"baby punch"	{ "segmentation": [] }
5	"flossylove"	"flossy love"	{ "segmentation": [] }
6	"justsayin"	"just sayin"	{ "segmentation": [] }
7	"Logies"	"Logies"	{ "segmentation": [ "logies" ] }
8	"football3s"	"football 3s"	{ "segmentation": [] }
9	"prosehos"	"prose hos"	{ "segmentation": [ "prosehos" ] }
10	"blisters"	"blisters"	{ "segmentation": [] }
11	"homebirth"	"home birth"	{ "segmentation": [] }
12	"Continental"	"Continental"	{ "segmentation": [] }
13	"kentuckyderby"	"kentucky derby"	{ "segmentation": [] }
14	"iPhoneForAlonis"	"iPhone For Alonis"	{ "segmentation": [] }
15	"gr8conf"	"gr8conf"	{ "segmentation": [ "gr8 conf", "GR8Conf" ] }
16	"TWELVE"	"TWELVE"	{ "segmentation": [] }
17	"follow"	"follow"	{ "segmentation": [] }
18	"nobitchassnessfriday"	"no bitchassness friday"	{ "segmentation": [ "no bitchass ness friday", "no bitch assness friday" ] }
19	"openspacecode"	"openspacecode"	{ "segmentation": [ "OpenSpace code", "open space code" ] }
20	"thegreenteen"	"the green teen"	{ "segmentation": [] }
21	"medifast"	"medifast"	{ "segmentation": [] }
22	"Geek"	"Geek"	{ "segmentation": [] }
23	"Liverpool"	"Liverpool"	{ "segmentation": [] }
24	"phpvikinger"	"php vikinger"	{ "segmentation": [] }
25	"xenocide"	"xenocide"	{ "segmentation": [] }
26	"campcourage"	"camp courage"	{ "segmentation": [] }
27	"stillnotreadyfor100degreeweatherbutluvPhx"	"still not ready for 100 degree weather but luv Phx"	{ "segmentation": [] }
28	"McFly"	"McFly"	{ "segmentation": [] }
29	"SharePoint"	"SharePoint"	{ "segmentation": [] }
30	"LemonTree"	"Lemon Tree"	{ "segmentation": [] }
31	"ccnet"	"ccnet"	{ "segmentation": [ "CCNet" ] }
32	"hamthrax"	"hamthrax"	{ "segmentation": [ "Hamthrax" ] }
33	"PeopleBrowsr"	"People Browsr"	{ "segmentation": [ "people browsr", "PeopleBrowsr" ] }
34	"maddie"	"maddie"	{ "segmentation": [] }
35	"sota09"	"sota 09"	{ "segmentation": [] }
36	"sagepay"	"sage pay"	{ "segmentation": [] }
37	"unfollow"	"unfollow"	{ "segmentation": [] }
38	"london2009"	"london 2009"	{ "segmentation": [] }
39	"charitytuesday"	"charity tuesday"	{ "segmentation": [] }
40	"ItsGrimUpNorth"	"Its Grim Up North"	{ "segmentation": [ "It s Grim Up North" ] }
41	"elementsc"	"element sc"	{ "segmentation": [] }
42	"twares"	"twares"	{ "segmentation": [] }
43	"steviewonder"	"stevie wonder"	{ "segmentation": [ "Stevie wonder" ] }
44	"fartingloud"	"farting loud"	{ "segmentation": [] }
45	"beerfriday"	"beer friday"	{ "segmentation": [] }
46	"jonaslive"	"jonas live"	{ "segmentation": [ "Jonas live" ] }
47	"vegas"	"vegas"	{ "segmentation": [ "Vegas" ] }
48	"appstore"	"appstore"	{ "segmentation": [ "app store" ] }
49	"PUGHUG"	"PUG HUG"	{ "segmentation": [ "pug hug" ] }
50	"nerdprom"	"nerd prom"	{ "segmentation": [] }
51	"otalia"	"otalia"	{ "segmentation": [ "Otalia" ] }
52	"girlcrush"	"girl crush"	{ "segmentation": [] }
53	"Hunchback"	"Hunchback"	{ "segmentation": [] }
54	"trafficza"	"traffic za"	{ "segmentation": [] }
55	"writechat"	"writechat"	{ "segmentation": [ "WriteChat", "write chat" ] }
56	"codecompletion"	"code completion"	{ "segmentation": [] }
57	"magic"	"magic"	{ "segmentation": [] }
58	"cartoonavie"	"cartoon avie"	{ "segmentation": [] }
59	"HsvTweetup"	"Hsv Tweetup"	{ "segmentation": [] }
60	"stc09"	"stc09"	{ "segmentation": [ "stc 09" ] }
61	"wishiwasinLA"	"wish i was in LA"	{ "segmentation": [ "wish I was in LA" ] }
62	"Prabhakaran"	"Prabhakaran"	{ "segmentation": [] }
63	"lions2009"	"lions 2009"	{ "segmentation": [ "Lions 2009" ] }
64	"dongle"	"dongle"	{ "segmentation": [] }
65	"heartballoon"	"heart balloon"	{ "segmentation": [] }
66	"spymaster"	"spymaster"	{ "segmentation": [] }
67	"UFC97"	"UFC97"	{ "segmentation": [ "UFC 97" ] }
68	"twittermusical"	"twitter musical"	{ "segmentation": [] }
69	"COBOL"	"COBOL"	{ "segmentation": [] }
70	"familyhistory"	"family history"	{ "segmentation": [] }
71	"webdu"	"webdu"	{ "segmentation": [ "webDU", "web du" ] }
72	"makerfaire"	"maker faire"	{ "segmentation": [] }
73	"sleep"	"sleep"	{ "segmentation": [] }
74	"Bruins"	"Bruins"	{ "segmentation": [] }
75	"whatcotyisnotdoing"	"what coty is not doing"	{ "segmentation": [ "what COTY is not doing" ] }
76	"qanda"	"q and a"	{ "segmentation": [ "Q and A" ] }
77	"starwars"	"star wars"	{ "segmentation": [ "Star Wars" ] }
78	"auremix"	"au remix"	{ "segmentation": [] }
79	"phillycodecamp"	"philly code camp"	{ "segmentation": [] }
80	"3wordsaftersex"	"3 words after sex"	{ "segmentation": [] }
81	"spoonies"	"spoonies"	{ "segmentation": [] }
82	"gfree"	"gfree"	{ "segmentation": [ "Gfree", "g free" ] }
83	"bacon"	"bacon"	{ "segmentation": [] }
84	"lostthegame"	"lost the game"	{ "segmentation": [] }
85	"DRWHO"	"DR WHO"	{ "segmentation": [] }
86	"electrohouse"	"electro house"	{ "segmentation": [] }
87	"eurovision"	"eurovision"	{ "segmentation": [] }
88	"Letmego"	"Let me go"	{ "segmentation": [] }
89	"3aaah"	"3 aaah"	{ "segmentation": [] }
90	"bck5"	"bck5"	{ "segmentation": [] }
91	"MusicMonday"	"Music Monday"	{ "segmentation": [ "music monday" ] }
92	"vitaminwater"	"vitamin water"	{ "segmentation": [] }
93	"symp09"	"symp 09"	{ "segmentation": [ "symp09", "SYMP 09" ] }
94	"dissertation"	"dissertation"	{ "segmentation": [] }
95	"Nambu"	"Nambu"	{ "segmentation": [] }
96	"asylum"	"asylum"	{ "segmentation": [] }
97	"thegreendeath"	"the green death"	{ "segmentation": [] }
98	"bittorrent"	"bit torrent"	{ "segmentation": [ "bittorrent", "Bit Torrent" ] }
99	"omgimpatient"	"omg impatient"	{ "segmentation": [ "OMG impatient" ] }

End of preview (truncated to 100 rows)

YAML Metadata Warning: The task_categories "structure-prediction" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, conversational, feature-extraction, text-generation, text2text-generation, fill-mask, sentence-similarity, text-to-speech, automatic-speech-recognition, audio-to-audio, audio-classification, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-retrieval, time-series-forecasting, text-to-video, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, other

YAML Metadata Warning: The task_categories "conditional-text-generation" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, conversational, feature-extraction, text-generation, text2text-generation, fill-mask, sentence-similarity, text-to-speech, automatic-speech-recognition, audio-to-audio, audio-classification, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-retrieval, time-series-forecasting, text-to-video, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, other

Dataset Card for STAN Small

Dataset Summary

Manually Annotated Stanford Sentiment Analysis Dataset by Bansal et al..

Languages

English

Dataset Structure

Data Instances

{
    "index": 300,
    "hashtag": "microsoftfail",
    "segmentation": "microsoft fail",
    "alternatives": {
        "segmentation": [
            "Microsoft fail"
        ]
    }
}

Data Fields

index: a numerical index.
hashtag: the original hashtag.
segmentation: the gold segmentation for the hashtag.
alternatives: other segmentations that are also accepted as a gold segmentation.

Although segmentation has exactly the same characters as hashtag except for the spaces, the segmentations inside alternatives may have characters corrected to uppercase.

Dataset Creation

All hashtag segmentation and identifier splitting datasets on this profile have the same basic fields: hashtag and segmentation or identifier and segmentation.
The only difference between hashtag and segmentation or between identifier and segmentation are the whitespace characters. Spell checking, expanding abbreviations or correcting characters to uppercase go into other fields.
There is always whitespace between an alphanumeric character and a sequence of any special characters ( such as _ , :, ~ ).
If there are any annotations for named entity recognition and other token classification tasks, they are given in a spans field.

Additional Information

Citation Information

@misc{bansal2015deep,
      title={Towards Deep Semantic Analysis Of Hashtags}, 
      author={Piyush Bansal and Romil Bansal and Vasudeva Varma},
      year={2015},
      eprint={1501.03210},
      archivePrefix={arXiv},
      primaryClass={cs.IR}
}

Contributions

This dataset was added by @ruanchaves while developing the hashformers library.

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Repository:

mounicam/hashtag_master

Paper:

Multi-task Pairwise Neural Ranking for Hashtag Segmentation