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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 25 new columns ({'weighted_top1_wer', 'num_unique_wer', 'oracle_pred', 'top1_pred', 'top1_is_best', 'len', 'num_unique_hypotheses', 'ess_uniform', 'top1_wer', 'weighted_oracle_wer', 'mode_collapse', 'num_hypotheses', 'expected_uniform_wer', 'wer_var', 'Unnamed: 0', 'identical_wer_rate', 'duplicate_rate', 'oracle_wer', 'reference', 'gradient_signal_uniform', 'oracle_diff', 'wer_std', 'oracle_gap', 'all_wers_same', 'preds'}) and 9 missing columns ({'filesize_bytes', 'age_bucket', 'iter', 'md5_hash', 'audio_duration_sec', 'pred', 'child_id', 'session_id', 'orthographic_text'}).
This happened while the csv dataset builder was generating data using
hf://datasets/quinnlue/mwer-hypos/mwer_exs.csv (at revision 08bdfe310591067c196beb6d2ca17c1bfc1997a4), [/tmp/hf-datasets-cache/medium/datasets/30463613955819-config-parquet-and-info-quinnlue-mwer-hypos-b04e1fee/hub/datasets--quinnlue--mwer-hypos/snapshots/08bdfe310591067c196beb6d2ca17c1bfc1997a4/8_samples.csv (origin=hf://datasets/quinnlue/mwer-hypos@08bdfe310591067c196beb6d2ca17c1bfc1997a4/8_samples.csv), /tmp/hf-datasets-cache/medium/datasets/30463613955819-config-parquet-and-info-quinnlue-mwer-hypos-b04e1fee/hub/datasets--quinnlue--mwer-hypos/snapshots/08bdfe310591067c196beb6d2ca17c1bfc1997a4/beam-search.csv (origin=hf://datasets/quinnlue/mwer-hypos@08bdfe310591067c196beb6d2ca17c1bfc1997a4/beam-search.csv), /tmp/hf-datasets-cache/medium/datasets/30463613955819-config-parquet-and-info-quinnlue-mwer-hypos-b04e1fee/hub/datasets--quinnlue--mwer-hypos/snapshots/08bdfe310591067c196beb6d2ca17c1bfc1997a4/mwer_exs.csv (origin=hf://datasets/quinnlue/mwer-hypos@08bdfe310591067c196beb6d2ca17c1bfc1997a4/mwer_exs.csv), /tmp/hf-datasets-cache/medium/datasets/30463613955819-config-parquet-and-info-quinnlue-mwer-hypos-b04e1fee/hub/datasets--quinnlue--mwer-hypos/snapshots/08bdfe310591067c196beb6d2ca17c1bfc1997a4/results.csv (origin=hf://datasets/quinnlue/mwer-hypos@08bdfe310591067c196beb6d2ca17c1bfc1997a4/results.csv)]
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 "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1890, in _prepare_split_single
writer.write_table(table)
File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 760, in write_table
pa_table = table_cast(pa_table, self._schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2272, in table_cast
return cast_table_to_schema(table, schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2218, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
Unnamed: 0: int64
utterance_id: string
num_hypotheses: int64
num_unique_hypotheses: int64
duplicate_rate: double
num_unique_wer: int64
identical_wer_rate: double
top1_pred: string
top1_wer: double
oracle_pred: string
oracle_wer: double
oracle_gap: double
oracle_diff: bool
top1_is_best: bool
wer_var: double
wer_std: double
expected_uniform_wer: double
gradient_signal_uniform: double
ess_uniform: double
mode_collapse: bool
all_wers_same: bool
reference: string
preds: string
len: int64
weighted_oracle_wer: double
weighted_top1_wer: double
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 3482
to
{'utterance_id': Value('string'), 'child_id': Value('string'), 'session_id': Value('string'), 'audio_duration_sec': Value('float64'), 'age_bucket': Value('string'), 'md5_hash': Value('string'), 'filesize_bytes': Value('int64'), 'orthographic_text': Value('string'), 'pred': Value('string'), 'iter': Value('int64')}
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 1347, 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 980, in convert_to_parquet
builder.download_and_prepare(
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 884, in download_and_prepare
self._download_and_prepare(
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 947, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1739, in _prepare_split
for job_id, done, content in self._prepare_split_single(
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1892, 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 25 new columns ({'weighted_top1_wer', 'num_unique_wer', 'oracle_pred', 'top1_pred', 'top1_is_best', 'len', 'num_unique_hypotheses', 'ess_uniform', 'top1_wer', 'weighted_oracle_wer', 'mode_collapse', 'num_hypotheses', 'expected_uniform_wer', 'wer_var', 'Unnamed: 0', 'identical_wer_rate', 'duplicate_rate', 'oracle_wer', 'reference', 'gradient_signal_uniform', 'oracle_diff', 'wer_std', 'oracle_gap', 'all_wers_same', 'preds'}) and 9 missing columns ({'filesize_bytes', 'age_bucket', 'iter', 'md5_hash', 'audio_duration_sec', 'pred', 'child_id', 'session_id', 'orthographic_text'}).
This happened while the csv dataset builder was generating data using
hf://datasets/quinnlue/mwer-hypos/mwer_exs.csv (at revision 08bdfe310591067c196beb6d2ca17c1bfc1997a4), [/tmp/hf-datasets-cache/medium/datasets/30463613955819-config-parquet-and-info-quinnlue-mwer-hypos-b04e1fee/hub/datasets--quinnlue--mwer-hypos/snapshots/08bdfe310591067c196beb6d2ca17c1bfc1997a4/8_samples.csv (origin=hf://datasets/quinnlue/mwer-hypos@08bdfe310591067c196beb6d2ca17c1bfc1997a4/8_samples.csv), /tmp/hf-datasets-cache/medium/datasets/30463613955819-config-parquet-and-info-quinnlue-mwer-hypos-b04e1fee/hub/datasets--quinnlue--mwer-hypos/snapshots/08bdfe310591067c196beb6d2ca17c1bfc1997a4/beam-search.csv (origin=hf://datasets/quinnlue/mwer-hypos@08bdfe310591067c196beb6d2ca17c1bfc1997a4/beam-search.csv), /tmp/hf-datasets-cache/medium/datasets/30463613955819-config-parquet-and-info-quinnlue-mwer-hypos-b04e1fee/hub/datasets--quinnlue--mwer-hypos/snapshots/08bdfe310591067c196beb6d2ca17c1bfc1997a4/mwer_exs.csv (origin=hf://datasets/quinnlue/mwer-hypos@08bdfe310591067c196beb6d2ca17c1bfc1997a4/mwer_exs.csv), /tmp/hf-datasets-cache/medium/datasets/30463613955819-config-parquet-and-info-quinnlue-mwer-hypos-b04e1fee/hub/datasets--quinnlue--mwer-hypos/snapshots/08bdfe310591067c196beb6d2ca17c1bfc1997a4/results.csv (origin=hf://datasets/quinnlue/mwer-hypos@08bdfe310591067c196beb6d2ca17c1bfc1997a4/results.csv)]
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.
utterance_id string | child_id string | session_id string | audio_duration_sec float64 | age_bucket string | md5_hash string | filesize_bytes int64 | orthographic_text string | pred string | iter int64 |
|---|---|---|---|---|---|---|---|---|---|
U_0033a1d48af5b7c4 | C_58700818bbf27285 | S_45e89a775c7ea4d8 | 0.501 | 3-4 | e5ffef264d94f6f49972d16b424690a8 | 36,940 | yeah | yeah | 0 |
U_0554a9c620c314e8 | C_2110bcde951786da | S_d9b7e8d86964a35a | 0.501 | 5-7 | ff68a85eb8d80cdbd926958ea63633b4 | 28,980 | and then two | and then two | 0 |
U_075300830689f00f | C_91f30b6960aeb958 | S_e128f0da1effc1cc | 0.501 | 8-11 | ab5cdf2d9ca8435f40fc4772213da99f | 26,272 | vacuum | vacuum | 0 |
U_0816d822ef1d9e85 | C_cf195bf70920fc05 | S_d63421d515c6ffc4 | 0.501 | 8-11 | dc09da10c251e79a19aaa902b9827303 | 34,357 | guitar | guitar | 0 |
U_0d2560460f759c81 | C_6d00a78a212b3455 | S_cc4d1e16b9a79744 | 0.501 | 8-11 | 4c72aa4e69da125a4de890563914c900 | 27,613 | pig | pig | 0 |
U_0daf8a99ab388137 | C_c0f6d7f6a5068e6e | S_b10fb164961b42e1 | 0.501 | 3-4 | e89bdd3dd67031d143af5921a3127ed0 | 36,945 | no | no | 0 |
U_0dead4ba29f09285 | C_1d17d52f22457f91 | S_5a8215bb1d80a4e8 | 0.501 | 5-7 | 5be695cdff579baa63d5db714968025e | 28,061 | what | what | 0 |
U_165332d63ac22b63 | C_98dccffbe963a36c | S_a3b8758b6b93eda0 | 0.501 | 8-11 | b7633f87a63f7b48894e7f9a506001f4 | 30,385 | truck | truck | 0 |
U_199cb803ca9a02d3 | C_6723ca6619f60756 | S_d390b40a9a7a3a83 | 0.501 | 8-11 | 7f0072dacf985710d1c1eef732cfada3 | 29,472 | go | go | 0 |
U_1e81c50c0ff42184 | C_82cdd1c99a652d2a | S_533e212ba1bac5fd | 0.501 | 8-11 | 4ea534b510d357466f53a5328fb55c0c | 30,863 | ring | ring | 0 |
U_2195967f70572552 | C_88df4e177c926cf8 | S_d895d72e1f5ac75d | 0.501 | 8-11 | 09bec7645115877f61c97cf44e922ac9 | 30,403 | quack | quack | 0 |
U_2711dec21ff62264 | C_015141f3326a0992 | S_db8d36b1799b6924 | 0.501 | 5-7 | d9b3451b7b781670290e872aa5d883fa | 15,511 | okay | okay | 0 |
U_2abd8db4655ba841 | C_e880e1f244ae4b2e | S_ac330233a267ee55 | 0.501 | 3-4 | 930305613c75cd6c50d411dbc65eef45 | 38,860 | oh | no | 0 |
U_2cb3655bcef94ddd | C_40f28349a8487c14 | S_f3dcece1c15ad1fe | 0.501 | 5-7 | 85b822e75cba3ce5474fcd01a32655ac | 38,252 | bird | boy | 0 |
U_330eee92ebbc20d3 | C_273d6b19e3d481d5 | S_7e7eefd54c37869c | 0.501 | 8-11 | 58dfea1cea0a9eddffe11f8e23d9650a | 33,299 | duck | duck | 0 |
U_3ba703522da009b6 | C_3b8c847c66708a5f | S_ff358d60151d1283 | 0.501 | 5-7 | 40fcc4934ac5982e514ac9040ef720ac | 24,900 | yeah | yeah | 0 |
U_3c8340dd2168c760 | C_deff5bac29f2fe09 | S_7f632c743ac60897 | 0.501 | 12+ | 02b014c1895f1099dd21b93a29a002af | 29,843 | zoo | zoo | 0 |
U_3e291a066e6fd9e0 | C_f081cef723e845ab | S_60d5fc9831ae106b | 0.501 | 8-11 | 1add89bf70a2557cf7fc419cfdc7b2e3 | 30,667 | puzzle | puzzle | 0 |
U_512a1432bc018af3 | C_98dccffbe963a36c | S_a3b8758b6b93eda0 | 0.501 | 8-11 | 89fd0efd17613adafec83889c5fd1731 | 27,321 | shoe | shoe | 0 |
U_58efc9c707c56ef7 | C_084ae7901ab59402 | S_250be5e69f6b83e1 | 0.501 | 8-11 | b2b452d092faa73bad69047af545a972 | 21,953 | card | card | 0 |
U_5998c0cac96e7d4e | C_3eb45fe7e2a91f4c | S_b18d6248f85611a8 | 0.501 | 5-7 | 49f685c3fbc105dafb159b708ebb25e8 | 25,549 | mhm | i am | 0 |
U_5f205377c55de0ad | C_40f28349a8487c14 | S_f3dcece1c15ad1fe | 0.501 | 5-7 | aff848e46b759c904dda49cfc87e57c8 | 40,416 | cry | fly | 0 |
U_60b34c150b81ca4b | C_436a7814cf0b6d6f | S_d5d3f5742e16480a | 0.501 | 3-4 | 79e3a51c8386459ba11f11913b56cf86 | 46,671 | yeah | yes | 0 |
U_6291c0a5d66f1152 | C_28b83d0b8801dc1c | S_4168672f5a3a4366 | 0.501 | 5-7 | 0794d94772a73aa61f6589c7d4d9ff7b | 28,291 | yeah | yeah | 0 |
U_62a8709eaaff75ef | C_84298a67e6131160 | S_f470e0d8593457ef | 0.501 | 3-4 | 9ec8ef6205d5b971eb31b91ced37f5cd | 22,979 | ow | o | 0 |
U_649224dc93246101 | C_ba7880040bebb186 | S_3f572e3a3990edf1 | 0.501 | 8-11 | af7b638d0500a1dbba37763daf6976cb | 33,822 | duck | duck | 0 |
U_6656ae5d345ce31c | C_fba9007a9da1567e | S_ffa8900393d8f0ed | 0.501 | 12+ | 7064ba8a30f751a4c194e739cf68ee0c | 27,338 | air | air | 0 |
U_7a1da37f5cd7a785 | C_084ae7901ab59402 | S_250be5e69f6b83e1 | 0.501 | 8-11 | 71e9be4fb001b69f8afc2e864b282947 | 22,674 | yarn | yard | 0 |
U_7de1a89119cd4491 | C_9f4936ccf4b22337 | S_9d4b164fee213a15 | 0.501 | 5-7 | b9b03ac0ed1ddfd160c7efe5fcd886e6 | 25,677 | tuck under | condor | 0 |
U_7df07e8bc00758b2 | C_82cdd1c99a652d2a | S_30f9b50cdd921c80 | 0.501 | 8-11 | 5f9a08f9c5f1c93f06140600efc9274f | 29,496 | mother | mother | 0 |
U_82ceaaed4ae7f3ea | C_d229b50bd64d02cb | S_9f6c293343133f1e | 0.501 | 8-11 | 5e2037aa51c80213b7ee692f1fd3378e | 25,670 | mhm | mhm | 0 |
U_864d4e226a9d3ca5 | C_a625dd8b6e181b6c | S_33ec43f95e2f1974 | 0.501 | 12+ | d51719af9d6362da6e0c530ab02e974f | 27,398 | tiger | tiger | 0 |
U_86539e44d36dad32 | C_c8dea8e91282e78d | S_4886741f5e0d75dd | 0.501 | 5-7 | 2617ea67851ad71f64fd92778b7bcd76 | 45,208 | no | oh | 0 |
U_8c32aa969fb18fac | C_243d5edbf4972180 | S_be2db7c26cf09779 | 0.501 | 5-7 | 77a069f727c745d5b3509118a09677a3 | 25,397 | yeah | yeah | 0 |
U_9a8146b9294730cc | C_34267915b84bc67c | S_66790158d0ba8d1d | 0.501 | 5-7 | 33a9c1c20ac7408ee0deeaa89d1aec91 | 25,974 | yeah | yeah | 0 |
U_a39ed46de15c5b2d | C_5d85546e1eb1283c | S_7d51535f61116712 | 0.501 | 5-7 | c9669f438ad565d7d697c8c8a57aba97 | 27,742 | leaf | leaf | 0 |
U_ade8489ca2a74cd0 | C_851402803cdd80be | S_08ba1604369b2936 | 0.501 | 5-7 | fe99acd54dab5112df54f9f4b2bb6a1b | 27,034 | one | one | 0 |
U_b1af39d109266bb1 | C_084ae7901ab59402 | S_250be5e69f6b83e1 | 0.501 | 8-11 | 5c016954a183ead257e244b8ef61b0f1 | 23,205 | deer | deer | 0 |
U_b59f051e895a27cf | C_0621802aa5e836d3 | S_183fd4502ac07a7a | 0.501 | 8-11 | 016d367d0c7cef7ceedd304d7a3aa0aa | 27,241 | and another | and another | 0 |
U_be0afd12a6e20f7d | C_ba7880040bebb186 | S_3f572e3a3990edf1 | 0.501 | 8-11 | c326b0695641caaea35efa398d80dc59 | 36,584 | drum | drum | 0 |
U_cc536fef2e9be0b2 | C_331740110882c0cc | S_c0a21c39372f1e2e | 0.501 | 12+ | 98a9e4488669226895e066c2b4d24f29 | 33,272 | swing | swing | 0 |
U_cc694029abe5494c | C_1ee353848527a253 | S_3dea9ca7deecb100 | 0.501 | 8-11 | 924517463fe7c46691a7a90edd0e1634 | 29,551 | ring | ring | 0 |
U_ceee951f4185d193 | C_f80285e797921a37 | S_f9f873e4c34e7dfb | 0.501 | 12+ | ffd4e84d0feeee930fc738dc78392dad | 32,301 | duck | duck | 0 |
U_d04fdfa3034c8850 | C_30402c0c48cb93c0 | S_b431270e9ca13296 | 0.501 | 8-11 | a38370f2a8bc46016612622328a7c846 | 41,517 | lamp | lamp | 0 |
U_d2e071950006c97c | C_963dfea8c96b0c98 | S_abc7123e2d863576 | 0.501 | 8-11 | 5897d8d2244f7edb7a521adc059f7f0b | 49,555 | no | no | 0 |
U_dc72288128859c93 | C_307729a9d5ccacb3 | S_e15ab659be16ea75 | 0.501 | 8-11 | 5d3e3a8832ce375bcc33e130aa31e257 | 27,584 | yes | yes | 0 |
U_df4e2169397abcfb | C_fba9007a9da1567e | S_a9190d4d806ddcd1 | 0.501 | 12+ | 313d93debad6ac1265341aa9223399c3 | 27,546 | or | or | 0 |
U_ecc449f3d9601585 | C_2a0f1248c7349c5a | S_fcb1ca3900677a59 | 0.501 | 5-7 | 64695eebef44ed00f0cb4779c809a72e | 27,544 | i know | i know | 0 |
U_ee35e9d33d384567 | C_f55a1c1d6a43b149 | S_3266c2d5b53c3107 | 0.501 | 5-7 | 36004c1a06e2e80470d7d40f5cf03812 | 27,428 | yeah | yeah | 0 |
U_f01a98dce0f32db1 | C_0fa2a4bb5524629b | S_6ade989fd37215e0 | 0.501 | 5-7 | eb113603c321c704615608dac3ac32d9 | 28,161 | wait | wait | 0 |
U_f516fd45431dd132 | C_688db18a71ae3390 | S_5066a2453c6f7f4e | 0.501 | 5-7 | d5580976250ada21785c89a8b6ad8c60 | 30,000 | and a mm | and a ma | 0 |
U_ff620ac0e1fabf9f | C_cf9e931e2588baff | S_64e860b2a770f104 | 0.501 | 8-11 | 93ace89b927273bfe5fcd863a6542e2b | 19,216 | ree | ree | 0 |
U_154bb0209dd41b41 | C_28574c84406adb1c | S_fe49db6b3ab7ce42 | 0.501 | 8-11 | 9b235d5501c14457173093c79f447ba7 | 18,609 | bye | bye | 0 |
U_2c83a1b23c1072b7 | C_c789749d86a344e0 | S_1c462ed03f580fe8 | 0.501 | 8-11 | a926eac68b9fab35c04e5b546ffbf3a6 | 19,356 | a | a | 0 |
U_9e9621befbc4f412 | C_516e18ec41011983 | S_6ff763fea121d910 | 0.501 | 8-11 | 77558d0ad229e338d74f826ff1e9a709 | 16,322 | not | no | 0 |
U_b2e4b9ab09648716 | C_6c687ee0c1dfff41 | S_21b5443a45f2b887 | 0.501 | 8-11 | 0248555596d10a794f4ea5e2d10878c7 | 20,212 | okay | okay | 0 |
U_01d95f6ce7996873 | C_cf9e931e2588baff | S_bfe6da842dbbffe7 | 0.502 | 8-11 | 2f4ccf3dd340a95c7d049e95766c2a0b | 18,263 | rah | rah | 0 |
U_0a5d06ed78b5d0a1 | C_e8c0a43d943f10e4 | S_d779974bf39056fb | 0.502 | 8-11 | 41b65937e21fd2233f8ba32a1f9c1a12 | 27,164 | eating | teen | 0 |
U_1724bc4ee3f86b00 | C_75f8093d79b28298 | S_13d5b9593829b051 | 0.502 | 8-11 | f0c2c9c9f717f4ce660f33f9ce0ccfa8 | 26,216 | mm | hm | 0 |
U_2767f4bdd7633453 | C_63e75214911251ca | S_aaf81c6389ef6ada | 0.502 | 3-4 | d7bb960b1144996a905660e7fe99c9f6 | 42,832 | mhm | we | 0 |
U_2f796926a47108b9 | C_8b22e51b2b7330a5 | S_1ec0801819ae8a32 | 0.502 | 3-4 | 541411e48c7cc79b068c1902d4f472fb | 38,169 | nice | nice | 0 |
U_33c7731fe2c2a307 | C_307729a9d5ccacb3 | S_e15ab659be16ea75 | 0.502 | 8-11 | 75db38a5f4a49685184d70cc6bc57fc5 | 25,572 | no | no | 0 |
U_365f9cdb96e4a705 | C_9535ba756e681479 | S_e8992cfa0812ce3a | 0.502 | 5-7 | dc3bc4bfcbe3f2ab64786a221892ea62 | 30,047 | s | s | 0 |
U_3a8be1694c809d7d | C_d212518a7a45c0b6 | S_67910608f6e85177 | 0.502 | 12+ | 49450bb3b52032eacc6400da046995cc | 30,181 | seven | seven | 0 |
U_4314ed6ca8596645 | C_e04e54b01b1c652b | S_65af7e8ec376f088 | 0.502 | 3-4 | abe3d09733f180ca5e6be261d4d8cbe8 | 35,952 | yeah | yeah | 0 |
U_43f816061f3f49dc | C_165b9340ca934b44 | S_bd250296b6621efc | 0.502 | 5-7 | 6cd5f807df95ffddbeeb9ecf4efda316 | 25,041 | mhm | mhm | 0 |
U_4aa07db11298ca98 | C_d2fbddadbe604bc4 | S_a2ba075d43756a4f | 0.502 | 5-7 | bb8d6adc0882354b4e37bf43ae7c6652 | 28,494 | a boy | a boy | 0 |
U_4b0dee29e407b56f | C_58700818bbf27285 | S_1f0fa56416a649de | 0.502 | 3-4 | 3a9d28b1c7e53929acbad08fdf05543b | 36,374 | where | here we go | 0 |
U_4dda9cbd01d0f4ed | C_2a0f1248c7349c5a | S_fcb1ca3900677a59 | 0.502 | 5-7 | 999439b7af0c9cf4239c428ea30e4dfa | 27,685 | art | it hurts | 0 |
U_50b1345b3652f89e | C_369248fed274c7f5 | S_15b87ee01cd43178 | 0.502 | unknown | 08b74f80a28143245c45b4f4d7a71b44 | 25,320 | eh | no | 0 |
U_5d6901aef5ab2631 | C_f5c61ded6961cc60 | S_723382a14428a6e6 | 0.502 | 5-7 | b2b2bac624567db3cf69d29f4678bffa | 27,273 | brib | brib | 0 |
U_69df3bf45ce2ba81 | C_2aee6ba62cf585bc | S_3f4a39b5cf1af4c4 | 0.502 | 12+ | f275da2a7a1868680cf22159264d3a0a | 30,743 | hammer | hammer | 0 |
U_74a243d67e84e361 | C_2156467322a038b8 | S_9d2efbf3bd34bf4e | 0.502 | 3-4 | 3fc3c301b83dd9f9751ce2125c4fab76 | 22,061 | blue | blue | 0 |
U_78c13242e7efcfc1 | C_340b5882a6c76cec | S_d825399f9baf9688 | 0.502 | 8-11 | f9c6ddb85e8e40ba891009b82c63e17c | 35,797 | worm | worm | 0 |
U_78f3e1fa9ae327cd | C_243d5edbf4972180 | S_be2db7c26cf09779 | 0.502 | 5-7 | 5c7f5abf62d8474875807af62bb5bb62 | 25,078 | no | nope | 0 |
U_7cce4e63400d66b2 | C_cf9e931e2588baff | S_bfe6da842dbbffe7 | 0.502 | 8-11 | baa9b54ddb412b95b9d3297601075f6d | 18,854 | ray | ray | 0 |
U_808fa634cbb0fa62 | C_2aee6ba62cf585bc | S_d2af077a36323673 | 0.502 | 12+ | 0f6f47661fb8141a86847a2ae82c5b6e | 32,334 | chair | chair | 0 |
U_8b4428608195e555 | C_1ee353848527a253 | S_4292367ffef08b27 | 0.502 | 8-11 | e3309f82534a321664a58265c6a113ed | 28,778 | ladder | ladder | 0 |
U_92c0beadccaf59d1 | C_00ad9123833bf1cb | S_4117617467ee8e62 | 0.502 | 5-7 | bea0f2be910a26596a10cf47e44c478f | 34,861 | sharp | sharp | 0 |
U_92cea4a51cfbb8eb | C_0b03744aff1b4e67 | S_b6c5951c604a321d | 0.502 | 12+ | 617e8cca1609b3b27c6f9c0455ff3d9c | 28,580 | plate | plate | 0 |
U_9354d157ca7ab1e9 | C_3e9aa0e6b0779f01 | S_0298e0d08c46f59b | 0.502 | 3-4 | 3fcea0e15ffa345a2681eb3c950a47fe | 37,421 | get off | get up | 0 |
U_9407c8682121b6eb | C_c48420d4a300bda0 | S_874bec88fdcae979 | 0.502 | 8-11 | 6411b1208288152e5d8067b4a8dc25fa | 34,699 | truck | truck | 0 |
U_986d83a2c8c48338 | C_fc35aea54a8cc67c | S_38a5f95608deb427 | 0.502 | 12+ | e6e5503ccf5831a62182d7c47db9d5a1 | 30,459 | go | go | 0 |
U_9f0d905bd020ddb1 | C_4c52ae7575d26b78 | S_34583e8e56146c9f | 0.502 | 3-4 | c7e820bedcbdf03efa6c279bfff514c2 | 35,411 | yep | hello | 0 |
U_a4c4a1a279d146a1 | C_636e4ba68c50ad2d | S_bd6da5f174f74876 | 0.502 | 3-4 | bddf8acbebe8a1d03f7075c2736bcf42 | 34,672 | fish | fish | 0 |
U_ace102e6ff318815 | C_00ad9123833bf1cb | S_4117617467ee8e62 | 0.502 | 5-7 | a17824a026b324a62baae0fee5b428c9 | 32,509 | bears | bear | 0 |
U_b4f91c1f0c05ad67 | C_82cdd1c99a652d2a | S_30f9b50cdd921c80 | 0.502 | 8-11 | 07e1c00d60d10c5114957b0fcf8171e6 | 28,399 | red | red | 0 |
U_b51e41eea9f81bfa | C_5182c2e2ea22056b | S_40d83381876fee45 | 0.502 | unknown | 7d4151467e3a97701533f6078a7f4530 | 24,001 | v | b | 0 |
U_be6c255a2f65ea57 | C_6799831728628309 | S_e883ce952f19bc79 | 0.502 | 5-7 | 19ed17ce70d3d8482cbfcea4b234dddf | 29,411 | a shoe | shoe | 0 |
U_c2d8d60e4119140d | C_be57f29be4ed8115 | S_863030a698a31772 | 0.502 | 12+ | d29aa59d6173be32d166c158699bdd11 | 35,108 | spoon | spoon | 0 |
U_c4a5d57ff126ca61 | C_687daee57e413f7e | S_732638e18745e200 | 0.502 | 8-11 | 3e944095883d8be51e9fdc0dd249822e | 27,439 | seven | seven | 0 |
U_ca99c480ebb095b0 | C_34267915b84bc67c | S_66790158d0ba8d1d | 0.502 | 5-7 | 963443ab5345e52aa33ff8c6fb111966 | 26,957 | wait | wait | 0 |
U_d291bc246d19fd83 | C_f86c7edbc46bc2fe | S_2882153c1a1d1331 | 0.502 | 5-7 | 5186d9d73d9a949d924dabe7cf9bf65e | 28,459 | mhm | mhm | 0 |
U_d5464a403339d56d | C_622ca64dbd671038 | S_47a5e0b638c79da8 | 0.502 | 5-7 | 7ce6f3c9ad0d8a4696be4afb5418be2a | 28,547 | snacks | six | 0 |
U_d7c7fd8095c1b981 | C_687daee57e413f7e | S_732638e18745e200 | 0.502 | 8-11 | f93b79d43dbd5e8be916758e2ef23327 | 27,638 | plate | plate | 0 |
U_d90431748fb8974a | C_5faf6987399a8628 | S_0905606a3ae21505 | 0.502 | 8-11 | 0d6c72c1bd034187629de2b7e3ad104c | 27,640 | swing | swing | 0 |
U_dccaa4ca8fbef7c4 | C_78c625a46184c002 | S_aacfd6d5d26f635b | 0.502 | 8-11 | 566dd45d580b39e45dd24c311298ebd4 | 28,026 | youtube | you too | 0 |
U_e061b91fdc33ca28 | C_c40c6d69c6809045 | S_d916664ad42cd70b | 0.502 | 5-7 | b00f9cc94eaafb7072c7b0635080f9c6 | 26,133 | twenty | thirty | 0 |
U_09dbd9873daad716 | C_d356c5e5589284df | S_b1b4164e0ac6b0c3 | 0.502 | 3-4 | 7f4a9d8295784e5f0abc6b9f93aa6ab9 | 39,291 | yeah | yeah | 0 |
U_7646e6c920a0badb | C_08b1f5b285bcbfdf | S_add872975a858a4e | 0.502 | 8-11 | e219a038e4af0e16fc878b5a5a884471 | 15,894 | we | we | 0 |
End of preview.
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