README.md

---
language:
- en
license: mit
tags:
- tables
- benchmark
- qa
- llms
- document-understanding
- multimodal
pretty_name: Human Centric Tables Question Answering (HCTQA)
size_categories:
- 10K<n<100K
task_categories:
- question-answering
task_ids:
- document-question-answering
- visual-question-answering
annotations_creators:
- expert-generated

configs:
- config_name: default
  data_files:
  - split: train
    path: train.parquet
  - split: validation
    path: val.parquet
  - split: test
    path: test.parquet

dataset_info:
- config_name: default
  features:
    - name: table_id
      dtype: string
    - name: dataset_type
      dtype: string
    - name: table_as_csv
      dtype: string
    - name: table_as_html
      dtype: string
    - name: table_as_markdown
      dtype: string
    - name: table_image_local_path_within_github_repo
      dtype: string
    - name: table_image_url
      dtype: string
    - name: table_properties_metadata
      dtype: string
    - name: question_id
      dtype: string
    - name: question
      dtype: string
    - name: question_template_for_synthetic_only
      dtype: string
    - name: question_properties_metadata
      dtype: string
    - name: answer
      dtype: string
    - name: prompt
      dtype: string
    - name: prompt_without_system
      dtype: string
  description: >
    Human Centric Tables Question Answering (HCTQA) is a benchmark designed for evaluating
    the performance of LLMs on question answering over complex, real-world and synthetic tables.
    This dataset contains both real-world and synthetic tables with associated images, CSVs, 
    and structured metadata. The dataset includes questions with varying levels of complexity, 
    requiring models to handle reasoning across complex structures, numeric aggregation, and context-dependent 
    understanding. The `dataset_type` field indicates whether a sample is from the real world data sources
    (`realWorldHCTs`) or synthetically created (`syntheticHCTs`).
---

# HCT-QA: Human-Centric Tables Question Answering

**HCT-QA** is a benchmark dataset designed to evaluate large language models (LLMs) on question answering over complex, human-centric tables (HCTs). These tables often appear in documents such as research papers, reports, and webpages and present significant challenges for traditional table QA due to their non-standard layouts and compositional structure.

The dataset includes:

- **2,188 real-world tables** with **9,835 human-annotated QA pairs**
- **4,679 synthetic tables** with **67,500 programmatically generated QA pairs**
- Logical and structural metadata for each table and question

> 📄 **Paper**: [Title TBD]  
> _The associated paper is currently under review and will be linked here once published._

---

## 📊 Dataset Splits

| Config     | Split | # Examples (Placeholder) |
|------------|-------|--------------------------|
| RealWorld  | Train | 7,500                    |
| RealWorld  | Test  | 2,335                    |
| Synthetic  | Train | 55,000                   |
| Synthetic  | Test  | 12,500                   |

---

## 🏆 Leaderboard

| Model Name      | FT (Finetuned) | Recall | Precision |
|-----------------|----------------|--------|-----------|
| Model-A         | True           | 0.81   | 0.78      |
| Model-B         | False          | 0.64   | 0.61      |
| Model-C         | True           | 0.72   | 0.69      |

> 📌 If you're evaluating on this dataset, open a pull request to update the leaderboard.

---

## Dataset Structure

Each entry in the dataset is a dictionary with the following structure:

### Sample Entry

```json
{
  "table_id": "arxiv--1--1118",
  "dataset_type": "arxiv",
  "table_data": {
    "table_as_csv": ",0,1,2\n0,Domain,Average Text Length,Aspects Identified\n1,Journalism,50,44\n...",
    "table_as_html": "<table><tr><th>Domain</th><th>Average Text Length</th>...",
    "table_as_markdown": "| Domain | Average Text Length | Aspects Identified |...",
    "table_image_local_path_within_github_repo": "tables/images/arxiv--1--1118.jpg",
    "table_image_url": "https://hcsdtables.qcri.org/datasets/all_images/arxiv_1_1118.jpg",
    "table_properties_metadata": {
      "Standard Relational Table": true,
      "Row Nesting": false,
      "Column Aggregation": false
    }
  },
  "questions": [
    {
      "question_id": "arxiv--1--1118--M0",
      "question": "Report the Domain and the Average Text Length where the Aspects Identified equals 72",
      "question_template_for_synthetic_only": "Report [column_1] and [column_2] where [column_3] equals [value]",
      "question_properties_metadata": {
        "Row Filter": true,
        "Aggregation": false,
        "Returned Columns": true
      },
      "answer": "{Psychology | 86} || {Linguistics | 90}",
      "prompt": "<system>...</system><user>...</user>",
      "prompt_without_system": "<user>...</user>"
    }
  ]
}
```

### Ground Truth Format

<b> Explain the GT format here </b>  
Example: {value1 | value2} || {value3 | value4}


### Table Properties

For details on table and question properties please see our [paper](https://openreview.net/pdf?id=eaW6OtD4HR)

<!-- | Property Name                         | Definition |
|--------------------------------------|------------|
| Standard Relational Table            | TBD        |
| Multi Level Column                   | TBD        |
| Balanced Multi Level Column          | TBD        |
| Symmetric Multi Level Column         | TBD        |
| Unbalanced Multi Level Column        | TBD        |
| Asymmetric Multi Level Column        | TBD        |
| Column Aggregation                   | TBD        |
| Global Column Aggregation            | TBD        |
| Local Column-Group Aggregation       | TBD        |
| Explicit Column Aggregation Terms    | TBD        |
| Implicit Column Aggregation Terms    | TBD        |
| Row Nesting                          | TBD        |
| Balanced Row Nesting                 | TBD        |
| Symmetric Row Nesting                | TBD        |
| Unbalanced Row Nesting              | TBD        |
| Asymmetric Row Nesting               | TBD        |
| Row Aggregation                      | TBD        |
| Global Row Aggregation               | TBD        |
| Local Row-Group Aggregation          | TBD        |
| Explicit Row Aggregation Terms       | TBD        |
| Implicit Row Aggregation Terms       | TBD        |
| Split Header Cell                    | TBD        |
| Row Group Label                      | TBD        |

### Question Properties

| Property Name                          | Definition |
|----------------------------------------|------------|
| Row Filter                             | TBD        |
| Row Filter Condition Type Lookup       | TBD        |
| Row Filter Condition Type Expression   | TBD        |
| Row Filter Involved Columns Single     | TBD        |
| Row Filter Involved Columns Multiple   | TBD        |
| Row Filter Max Depth Of Involved Columns | TBD      |
| Row Filter Retained Rows Single        | TBD        |
| Row Filter Retained Rows Multiple      | TBD        |
| Row Filter Num Of Conditions           | TBD        |
| Returned Columns                       | TBD        |
| Returned Columns Project On Plain      | TBD        |
| Returned Columns Project On Expression| TBD        |
| Returned Columns Max Depth             | TBD        |
| Returned Columns Expression In Table Present | TBD  |
| Returned Columns Expression In Table Not Present | TBD |
| Returned Columns Num Of Output Columns | TBD        |
| Yes/No                                 | TBD        |
| Aggregation                            | TBD        |
| Aggregation Type Sum                   | TBD        |
| Aggregation Type Avg                   | TBD        |
| Aggregation Grouping Global            | TBD        |
| Aggregation Grouping Local             | TBD        |
| Rank                                   | TBD        |
| Rank Type                              | TBD        | -->