| --- |
| language: |
| - en |
| license: mit |
| task_categories: |
| - question-answering |
| - table-question-answering |
| tags: |
| - finance |
| - conversational-qa |
| - numerical-reasoning |
| - financial-tables |
| - 10-k |
| pretty_name: ConvFinQA (Tomoro pre-cleaned) |
| size_categories: |
| - 1K<n<10K |
| --- |
| |
| # 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 identifier |
| - `doc`: a 10-K page split into `pre_text`, `post_text`, and a column-keyed `table` (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'`), and `qa_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 |
|
|
| ```python |
| 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. |
|
|
