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Datasets:
hast2
/
KublaPL

Tasks:
Sentence Similarity
Sub-tasks:
semantic-similarity-classification
Languages:
English
Size:
100K<n<1M
License:
Dataset card Viewer Files Community
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The dataset generation failed because of a cast error
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 6 new columns ({'cat1', 'kublall', 'Unnamed: 0', 'cat_and', 'PLll', 'cat2'}) and 1 missing columns ({'id'}).

This happened while the csv dataset builder was generating data using

hf://datasets/hast2/KublaPL/1.0.0/STSdataset_KublaPL_1.csv (at revision f9ab2a55ad089907152e34c5b5df13b18c0db1e7)

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 1870, in _prepare_split_single
                  writer.write_table(table)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 622, 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 2292, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2240, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              Unnamed: 0: int64
              textA: string
              textB: string
              value: int64
              cat_and: string
              cat1: string
              cat2: string
              kublall: int64
              PLll: int64
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 1252
              to
              {'id': Value(dtype='int32', id=None), 'textA': Value(dtype='string', id=None), 'textB': Value(dtype='string', id=None), 'value': Value(dtype='int32', 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 1417, 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 1049, in convert_to_parquet
                  builder.download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 924, in download_and_prepare
                  self._download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1000, 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 1741, 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 1872, 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 6 new columns ({'cat1', 'kublall', 'Unnamed: 0', 'cat_and', 'PLll', 'cat2'}) and 1 missing columns ({'id'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/hast2/KublaPL/1.0.0/STSdataset_KublaPL_1.csv (at revision f9ab2a55ad089907152e34c5b5df13b18c0db1e7)
              
              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? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

id
int32
textA
string
textB
string
value
int32
null
In Xanadu did Kubla Khan
Now to th' ascent of that steep savage Hill
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In Xanadu did Kubla Khan
Satan had journied on, pensive and slow;
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In Xanadu did Kubla Khan
But further way found none, so thick entwin'd,
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In Xanadu did Kubla Khan
As one continu'd brake, the undergrowth
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In Xanadu did Kubla Khan
Of shrubs and tangling bushes had perplext
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In Xanadu did Kubla Khan
All path of Man or Beast that past that way:
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In Xanadu did Kubla Khan
One Gate there onely was, and that look'd East
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In Xanadu did Kubla Khan
On th' other side: which when th' arch-fellon saw
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In Xanadu did Kubla Khan
Due entrance he disdaind, and in contempt,
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In Xanadu did Kubla Khan
At one slight bound high overleap'd all bound
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In Xanadu did Kubla Khan
Of Hill or highest Wall, and sheer within
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In Xanadu did Kubla Khan
Lights on his feet. As when a prowling Wolfe,
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In Xanadu did Kubla Khan
Whom hunger drives to seek new haunt for prey,
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In Xanadu did Kubla Khan
Watching where Shepherds pen thir Flocks at eeve
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In Xanadu did Kubla Khan
In hurdl'd Cotes amid the field secure,
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In Xanadu did Kubla Khan
Leaps o're the fence with ease into the Fould:
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In Xanadu did Kubla Khan
Or as a Thief bent to unhoord the cash
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In Xanadu did Kubla Khan
Of some rich Burgher, whose substantial dores,
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In Xanadu did Kubla Khan
Cross-barrd and bolted fast, fear no assault,
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In Xanadu did Kubla Khan
In at the window climbes, or o're the tiles;
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In Xanadu did Kubla Khan
So clomb this first grand Thief into Gods Fould:
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In Xanadu did Kubla Khan
So since into his Church lewd Hirelings climbe.
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In Xanadu did Kubla Khan
Thence up he flew, and on the Tree of Life,
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In Xanadu did Kubla Khan
The middle Tree and highest there that grew,
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In Xanadu did Kubla Khan
Sat like a Cormorant; yet not true Life
2
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In Xanadu did Kubla Khan
Thereby regaind, but sat devising Death
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In Xanadu did Kubla Khan
To them who liv'd; nor on the vertue thought
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In Xanadu did Kubla Khan
Of that life-giving Plant, but only us'd
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In Xanadu did Kubla Khan
For prospect, what well us'd had bin the pledge
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In Xanadu did Kubla Khan
Of immortalitie. So little knows
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In Xanadu did Kubla Khan
Any, but God alone, to value right
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In Xanadu did Kubla Khan
The good before him, but perverts best things
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In Xanadu did Kubla Khan
To worst abuse, or to thir meanest use.
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In Xanadu did Kubla Khan
Beneath him with new wonder now he views
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In Xanadu did Kubla Khan
To all delight of human sense expos'd
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In Xanadu did Kubla Khan
In narrow room Natures whole wealth, yea more,
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In Xanadu did Kubla Khan
A Heaven on Earth, for blissful Paradise
2
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In Xanadu did Kubla Khan
Of God the Garden was, by him in the East
2
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In Xanadu did Kubla Khan
Of Eden planted; Eden stretchd her Line
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In Xanadu did Kubla Khan
From Auran Eastward to the Royal Towrs
2
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In Xanadu did Kubla Khan
Of great Seleucia, built by Grecian Kings,
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In Xanadu did Kubla Khan
Or where the Sons of Eden long before
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In Xanadu did Kubla Khan
Dwelt in Telassar: in this pleasant soile
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In Xanadu did Kubla Khan
His farr more pleasant Garden God ordaind;
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In Xanadu did Kubla Khan
Out of the fertil ground he caus'd to grow
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In Xanadu did Kubla Khan
All Trees of noblest kind for sight, smell, taste;
2
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In Xanadu did Kubla Khan
And all amid them stood the Tree of Life,
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In Xanadu did Kubla Khan
High eminent, blooming Ambrosial Fruit
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In Xanadu did Kubla Khan
Of vegetable Gold; and next to Life
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In Xanadu did Kubla Khan
Our Death the Tree of Knowledge grew fast by,
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In Xanadu did Kubla Khan
Knowledge of Good bought dear by knowing ill.
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In Xanadu did Kubla Khan
Southward through Eden went a River large,
2
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In Xanadu did Kubla Khan
Nor chang'd his course, but through the shaggie hill
2
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In Xanadu did Kubla Khan
Pass'd underneath ingulft, for God had thrown
2
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In Xanadu did Kubla Khan
That Mountain as his Garden mould high rais'd
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In Xanadu did Kubla Khan
Upon the rapid current, which through veins
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In Xanadu did Kubla Khan
Of porous Earth with kindly thirst up drawn,
2
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In Xanadu did Kubla Khan
Rose a fresh Fountain, and with many a rill
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In Xanadu did Kubla Khan
Waterd the Garden; thence united fell
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In Xanadu did Kubla Khan
Down the steep glade, and met the neather Flood,
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In Xanadu did Kubla Khan
Which from his darksom passage now appeers,
2
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In Xanadu did Kubla Khan
And now divided into four main Streams,
2
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In Xanadu did Kubla Khan
Runs divers, wandring many a famous Realme
2
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In Xanadu did Kubla Khan
And Country whereof here needs no account,
2
null
In Xanadu did Kubla Khan
But rather to tell how, if Art could tell,
2
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In Xanadu did Kubla Khan
How from that Saphire Fount the crisped Brooks,
2
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In Xanadu did Kubla Khan
Rowling on Orient Pearl and sands of Gold,
2
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In Xanadu did Kubla Khan
With mazie error under pendant shades
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In Xanadu did Kubla Khan
Ran Nectar, visiting each plant, and fed
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In Xanadu did Kubla Khan
Flours worthy of Paradise which not nice Art
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In Xanadu did Kubla Khan
In Beds and curious Knots, but Nature boon
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In Xanadu did Kubla Khan
Powrd forth profuse on Hill and Dale and Plaine,
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In Xanadu did Kubla Khan
Both where the morning Sun first warmly smote
2
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In Xanadu did Kubla Khan
The open field, and where the unpierc't shade
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In Xanadu did Kubla Khan
Imbround the noontide Bowrs: Thus was this place,
2
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In Xanadu did Kubla Khan
A happy rural seat of various view;
2
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In Xanadu did Kubla Khan
Groves whose rich Trees wept odorous Gumms and Balme,
2
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In Xanadu did Kubla Khan
Others whose fruit burnisht with Golden Rinde
2
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In Xanadu did Kubla Khan
Hung amiable, Hesperian Fables true,
2
null
In Xanadu did Kubla Khan
If true, here onely, and of delicious taste:
2
null
In Xanadu did Kubla Khan
Betwixt them Lawns, or level Downs, and Flocks
2
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In Xanadu did Kubla Khan
Grasing the tender herb, were interpos'd,
2
null
In Xanadu did Kubla Khan
Or palmie hilloc, or the flourie lap
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In Xanadu did Kubla Khan
Of som irriguous Valley spread her store,
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In Xanadu did Kubla Khan
Flours of all hue, and without Thorn the Rose:
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In Xanadu did Kubla Khan
Another side, umbrageous Grots and Caves
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In Xanadu did Kubla Khan
Of coole recess, o're which the mantling Vine
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null
In Xanadu did Kubla Khan
Layes forth her purple Grape, and gently creeps
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In Xanadu did Kubla Khan
Luxuriant; mean while murmuring waters fall
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null
In Xanadu did Kubla Khan
Down the slope hills, disperst, or in a Lake,
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null
In Xanadu did Kubla Khan
That to the fringed Bank with Myrtle crownd,
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null
In Xanadu did Kubla Khan
Her chrystall mirror holds, unite thir streams.
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null
In Xanadu did Kubla Khan
The Birds thir quire apply; aires, vernal aires,
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In Xanadu did Kubla Khan
Breathing the smell of field and grove, attune
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In Xanadu did Kubla Khan
The trembling leaves, while Universal Pan
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In Xanadu did Kubla Khan
Knit with the Graces and the Hours in dance
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In Xanadu did Kubla Khan
Led on th' Eternal Spring. Not that faire field
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In Xanadu did Kubla Khan
Of Enna, where Proserpin gathring flours
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In Xanadu did Kubla Khan
Her self a fairer Floure by gloomie Dis
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In Xanadu did Kubla Khan
Was gatherd, which cost Ceres all that pain
2
End of preview.

STS Evaluation Datasets for English literary texts

Rating criteria

  • 5: Critics mentioned and strongly influenced - citation

  • 4: Critics mentioned and moderately influenced – source, borrowing, repeating the same theme, self-citation, precedent example

  • 3: Critics mentioned and somewhat influenced – association, source

  • 2: Influence mentioned but not admitted – source text A and influenced text B but different lines critic mentioned – e.g. Kubla Khan’s text but in different lines and Paradise Lost

  • 1: Influence may not exist – Influence not mentioned, but the same or similar taste author’s texts – e.g. Coleridge and Wordsworth

  • 0: No influence – not mentioned.

  • 5:該当箇所の指摘（注）があり、つよい影響が認められる

  • 4:該当箇所の指摘（注）があり、中程度に影響があると認められる

  • 3:該当箇所の指摘（注）があり、少し影響があると認められる

  • 2:影響があるが認められない - 作品自体は影響あると指摘のある詩作品であるが、その影響は別の箇所である

  • 1:影響はないかもしれない - 影響があるとの指摘はないが、同じまたは同種の著者の作品である。コールリッジとワーズワスなど

  • 0:影響はない - 指摘もない

Human Criteria: Poetry of Influence

https://github.com/hast-hash/English-Poetry-Dataset/blob/main/KublaKhan_ParadiseLost_Tables.docx

Dataset Files

File name Number of line/lines in instances Dataset Split
STSdataset_KublaPL_1 1 by 1 Test
STSdataset_KublaPL_2 2 by 2 Test
STSdataset_KublaPL_3 3 by 3 Test

Data Fields

  • id
  • textA a passage/passages in "Kubla Khan"
  • textB a passage/passages in Paradise Lost
  • value similarity value judged by creators using rating criteria

Source Texts

  • Coleridge, Samuel Taylor. (2009). The Complete Poetical Works of Samuel Taylor Coleridge. Vol 1 and 2. Gutenberg. https://www.gutenberg.org/ebooks/29090 [(1912) The Complete Poetical Works of Samuel Taylor Coleridge. Vol 1 and 2. Ed. Ernest Hartley Coleridge. Oxford: Clarendon.]
  • Milton John. (1992). Paradise Lost by John Milton. Ed. Joseph Raben. Gutenberg. https://www.gutenberg.org/ebooks/26 [(1667). Paradise Lost.]

Data Creators

@hast-hash

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