The dataset viewer is not available for this subset.
Exception: SplitsNotFoundError
Message: The split names could not be parsed from the dataset config.
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 246, in _generate_tables
pa_table = paj.read_json(
^^^^^^^^^^^^^^
File "pyarrow/_json.pyx", line 342, in pyarrow._json.read_json
File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
pyarrow.lib.ArrowInvalid: JSON parse error: Column(/train/[]/dialogue/executed_answers/[]) changed from number to string in row 0
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 286, in get_dataset_config_info
for split_generator in builder._split_generators(
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 97, in _split_generators
pa_table = next(iter(self._generate_tables(**splits[0].gen_kwargs, allow_full_read=False)))[1]
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 260, in _generate_tables
batch = json_encode_fields_in_json_lines(original_batch, json_field_paths)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/utils/json.py", line 106, in json_encode_fields_in_json_lines
examples = [ujson_loads(line) for line in original_batch.splitlines()]
^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/utils/json.py", line 20, in ujson_loads
return pd.io.json.ujson_loads(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
ValueError: Expected object or value
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 65, in compute_split_names_from_streaming_response
for split in get_dataset_split_names(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 340, in get_dataset_split_names
info = get_dataset_config_info(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 291, in get_dataset_config_info
raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err
datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.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.
ConvFinQA (Tomoro pre-cleaned)
Re-host of the pre-cleaned ConvFinQA dataset distributed as part of Tomoro AI's "Applied AI Solution Engineer" take-home exercise. ConvFinQA itself is the conversational QA benchmark over single-page financial documents from Chen et al. (EMNLP 2022).
The data is a single JSON file with two splits, train (3,037 records) and dev (421 records). Each record carries:
id: stable per-record identifierdoc: a 10-K page split intopre_text,post_text, and a column-keyedtable(nested dict: column header → row header → cell value)dialogue:conv_questions,conv_answers,turn_program(FinQA DSL),executed_answers(the dataset's gold executed values, numeric or'yes'/'no'), andqa_split(origin flag for hybrid two-source dialogues)features: precomputed flags (num_dialogue_turns,has_type2_question,has_duplicate_columns,has_non_numeric_values)
Loading
import json
from huggingface_hub import hf_hub_download
path = hf_hub_download(
repo_id="sharick008/convfinqa",
filename="convfinqa_dataset.json",
repo_type="dataset",
)
data = json.load(open(path))
print(len(data["train"]), len(data["dev"]))
Citation
Chen, Z., Li, S., Smiley, C., Ma, Z., Shah, S., & Wang, W. Y. (2022). ConvFinQA: Exploring the Chain of Numerical Reasoning in Conversational Finance Question Answering. EMNLP.
Licence
ConvFinQA upstream is MIT-licensed. This re-host preserves that licence and the original attribution to the ConvFinQA authors. Tomoro's pre-cleaning passes (column disambiguation, scale normalisation, numeric coercion) are applied on top.
- Downloads last month
- 32