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 1 new columns ({'ed4af92b-0039-453e-8f25-f359225da8e0'}) and 1 missing columns ({'93e291b3-0216-4a48-941e-01476e703311'}).
This happened while the csv dataset builder was generating data using
hf://datasets/andreaschari/neuclir-mappings/ru_doc_id_mapping.tsv (at revision 96c291a20ede4445868324d228207e3ead9aef61)
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
ed4af92b-0039-453e-8f25-f359225da8e0: string
0: int64
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 534
to
{'93e291b3-0216-4a48-941e-01476e703311': Value(dtype='string', id=None), '0': Value(dtype='int64', 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 1 new columns ({'ed4af92b-0039-453e-8f25-f359225da8e0'}) and 1 missing columns ({'93e291b3-0216-4a48-941e-01476e703311'}).
This happened while the csv dataset builder was generating data using
hf://datasets/andreaschari/neuclir-mappings/ru_doc_id_mapping.tsv (at revision 96c291a20ede4445868324d228207e3ead9aef61)
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.
93e291b3-0216-4a48-941e-01476e703311
string | 0
int64 |
|---|---|
27033bf9-891f-4cf6-98ab-e8633d397d69
| 1 |
4488d25e-fe8a-4529-a976-46b23db208ae
| 2 |
b5c4c2b1-456f-404f-9fa1-aa3bb3b9d9e6
| 3 |
0ed886fe-bab9-416b-9190-4dfecc415022
| 4 |
0802c4cf-c1d9-4c9d-8fa4-cae333ced699
| 5 |
bd452f34-5b54-4437-b052-dc3b006e9737
| 6 |
d52d8a23-2311-4268-a52e-8f919123c550
| 7 |
7a603342-50f9-4fce-b465-1a36d139cf38
| 8 |
cb951d74-0b5c-42e4-b94b-6338e53759f1
| 9 |
b2840e50-10a9-41ad-859a-7f00220b4422
| 10 |
f84a2978-2456-424a-a9f7-bbcfc278b3f7
| 11 |
3f4f13af-4d94-4373-8fb8-5f3224407bb7
| 12 |
d070d136-e858-424b-8f5d-926a96808fd7
| 13 |
da37f615-a8e8-45cd-b69d-d07beae65680
| 14 |
eeb5c320-b95b-4a95-8dbf-9b95ca1b0e89
| 15 |
dc34f9b1-5c41-43d6-984d-f40d52e457fc
| 16 |
1d658928-1d4c-4c00-9f3f-e1199cf48d56
| 17 |
5e0c9673-2c08-4bd9-8207-16e0eedd8e41
| 18 |
ef31ef52-c25d-4791-bdf4-43c2fcd45d9c
| 19 |
bc88d518-d3b5-4d5e-aedb-f1bd0b946677
| 20 |
ee7cf370-3cc5-4669-a1c9-b57c7fd82f42
| 21 |
67599767-233e-439e-ab29-1b86c6fc8faa
| 22 |
32e3fd21-8dc1-41df-b7e7-ca39e9054fd7
| 23 |
a0e1d94e-dce3-404f-8638-e5b9aea8c9d0
| 24 |
d33b1696-ab90-4ac5-8568-075e0ba1910b
| 25 |
8bf6eefa-06ab-45ab-9332-0a5c88a01595
| 26 |
de2f025e-a726-45ef-ad63-034e8531f6d0
| 27 |
ff3c9943-b442-47cf-a375-d1a2bb9b21d3
| 28 |
6a0c861a-d760-474d-b3ff-7a974a964fab
| 29 |
7b3918e7-746c-4dde-a290-859c2d7466c1
| 30 |
5d9707fc-a13f-4589-9273-a07ca639aff2
| 31 |
26ba3d8f-9bda-4ccf-bc36-44bce1efce93
| 32 |
7f6471cd-7bd7-4eb5-af69-f7d56ee171ee
| 33 |
7457da33-c983-40b3-bfbd-271f89f4360b
| 34 |
5629ae19-79de-4850-82d0-ec3d4e0efa1e
| 35 |
9547aa93-e922-452a-8c57-fb0e30678dd5
| 36 |
aa1be5d6-1b3c-46b0-98a6-f09f09a43d01
| 37 |
cb0437cb-d7b9-4fec-84a1-23a1128b1148
| 38 |
b6dcfe77-4927-4078-a01e-d68ce942f314
| 39 |
6b171a8d-a468-41b4-abbe-caaaa94a41f2
| 40 |
1c3e1233-6132-4c3d-817e-ab0e26111e28
| 41 |
c66c4132-6ede-45ef-92d1-d0e660a165ce
| 42 |
1847a967-f0ff-40c7-afe0-2b0c1de6b71a
| 43 |
c1e48209-99de-4f11-a73e-573136c4053b
| 44 |
5e2a1379-1bf4-493b-b4a0-5fb78c6e1616
| 45 |
bc8770ad-769c-46f2-b688-06c9d98a6792
| 46 |
18eeabc6-f890-40ee-9c87-920435b8aa6c
| 47 |
e89eb9fc-e614-4103-8a78-28db0d576d64
| 48 |
c86b71d9-b226-47e9-b76a-9eedfa90c26a
| 49 |
582cb95f-0497-4eb5-897f-86aa36edbb6b
| 50 |
12463a7c-071a-4aca-92cd-0941aed5630b
| 51 |
03405117-4d7a-4da7-915c-812872b0525c
| 52 |
55c33e60-1f6b-4c7f-9049-3ef56051fc5b
| 53 |
387a754e-2a4c-4b34-acdc-d03766c8e100
| 54 |
51d0a57c-1d1a-422a-9c0f-f02e99700d4f
| 55 |
936c4114-e968-4e02-8ace-5e334027e79a
| 56 |
b8b3bda9-b7d0-429c-a096-b332c000edcc
| 57 |
082634ea-808c-4299-8593-b90e0f1d444b
| 58 |
5740f4fb-bff1-44df-93e0-6072aa491143
| 59 |
184b033e-839b-44f4-85c4-aa69408f8f87
| 60 |
b9b96274-f60a-4cb2-a3b7-01dc378b41f4
| 61 |
a2d5be62-99e6-42e3-adf1-a196120c07f5
| 62 |
580a42cd-3cf1-48bf-8c5d-93bc8ace0a2e
| 63 |
4a44b524-f938-42a1-8467-8ce57df8b167
| 64 |
4a6c7631-3024-4c4c-b078-8f42953628dc
| 65 |
bd51e817-519f-4540-b55c-9b52fb45d906
| 66 |
c5e81f82-910f-41af-a496-09397015a9f8
| 67 |
7c2366c4-18c6-4433-82db-76398fd8bf2b
| 68 |
2f2e1c49-9100-4eb4-b547-00429799fce8
| 69 |
45ed98fb-30ba-4e28-9d10-2dcb5efa705e
| 70 |
34d52252-d717-46d2-afe6-8ee6049c254a
| 71 |
138fd0f9-264b-4948-82e8-711b08d587f2
| 72 |
f5132d8f-1b92-481c-b397-3680ec897c1b
| 73 |
0ed01e58-5f6e-411f-bb28-7466f5c5b52d
| 74 |
dd0cdf56-05a9-4692-a4e4-acb75864f4ef
| 75 |
48bb401a-7d9d-487f-b24f-3dda1c70ce0f
| 76 |
2275358d-ab57-4837-be0d-4017fcbc34fa
| 77 |
56b1652c-2809-4600-a7ab-2e82f8bfc0fe
| 78 |
74c02ebc-23a5-4429-9a3c-6b242571311a
| 79 |
d1d7df58-55f1-4028-9010-74a35137640c
| 80 |
e0993dc8-555c-4c87-8125-fd2f9c574598
| 81 |
9f22c0eb-a5e0-44bd-a625-902db32c12ec
| 82 |
074b2786-1c4b-4dbc-8bd0-40086cfab8c2
| 83 |
0fffb83b-3a1a-4578-a38b-672ae0c0635f
| 84 |
175f8f51-e358-41e3-9bab-0ec3395f2ae9
| 85 |
b7ec5983-0d47-4f15-9e59-2daa915186ef
| 86 |
04d16cc0-3441-4308-9a4d-d7cc8320d164
| 87 |
b18c734c-ec4a-4df6-a31c-31906f1deaa3
| 88 |
c249e5bb-9782-47e8-b5a9-4c5653a1ad10
| 89 |
0ffa7744-bb85-4599-b51a-0c4f5a18583c
| 90 |
81e5f372-3115-4e5c-a90c-d193e23fa33d
| 91 |
62ffb456-0360-4ee2-9199-5ed23940a928
| 92 |
27fb7bd3-010d-4e90-a852-037d6bd2b5b0
| 93 |
b26ce71c-b835-4301-b391-0363f327d7f1
| 94 |
313674dc-37b9-47be-9125-d9a85014ad75
| 95 |
2ebd53b3-1f4f-4c1f-92dd-f26bc586bc15
| 96 |
7a2b4a4e-ad71-4b46-8591-54da5a38ef31
| 97 |
0aaeede7-443b-447a-9763-edf09be3fa07
| 98 |
01bbfede-5dcb-499d-9c92-34a8f6ae57cc
| 99 |
ab44fab0-b50d-4f8c-b6f3-e9d3955d7944
| 100 |
These mappings were used for ColBERT-XM experiments of the "Improving Low-Resource Retrieval Effectiveness using Zero-Shot Linguistic Similarity Transfer" ECIR2025 paper. The source code for the paper can be found here