README.md

---
configs:
- config_name: gift_ctx
  data_files:
  - split: train
    path: gift_ctx/train.parquet
---

## Gift-EvalCTX Parquet
This repository hosts the GIFT-EvalCTX dataset in parquet format, highly compatible with LLMs. Each row is a sample of the dataset and contain the following fields:
- **idx**: unique id of the sample
- **source**: source of the same 
- **skill**: the types of context
- **frequency**: frequency of the sample
- **history_values**: a string containing values of the history
- **history_start**: starting timestamp of the history
- **history_end**: ending timestamp of the history
- **future_values**: a string containing values of the forecasting future
- **future_start**: starting timestamp of the future
- **future_end**: ending timestamp of the future
- **entry_sep**: separator used to split the string in history_values, future_values, and roi into array of floats
- **roi**: region of interest, indicating the indices of the timestamp that are affected by the context and used in evaluation
- **pred_length**: number of timestamps to forecast
- **system_prompt**: default system prompt
- **user_instruct**: query to forecast
- **context_info**: context for the current sample
- **prompt**: a complete prompt to query LLM

Note that all fields contain string only, you need to convert them into the appropriate format (array of floats, or datetime).

## Example usage
```python
from datasets import load_dataset

ds = load_dataset(
    "Salesforce/GiftEvalCTX",
    "gift_ctx",
    split="train"
)
print(len(ds))
print(ds[0].keys())
```

This repository is made public for research purposes only.