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README.md

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+---
+license: cc-by-4.0
+language:
+- en
+pretty_name: NAPEval Spreadsheet Trajectories
+size_categories:
+- n<1K
+tags:
+- spreadsheets
+- excel
+- next-action-prediction
+- autocomplete
+- symbolic
+configs:
+- config_name: default
+  data_files:
+  - split: test
+    path: data/test.jsonl
+dataset_info:
+  features:
+  - name: name
+    dtype: string
+  - name: operations
+    sequence: string
+  - name: num_operations
+    dtype: int64
+  splits:
+  - name: test
+    num_examples: 52
+---
+
+# NAPEval Spreadsheet Trajectories
+
+Benchmark trajectories for **predictive auto-completion in spreadsheets**. Each
+record is one spreadsheet-building session represented as an *ordered* sequence
+of symbolic cell operations. Given a prefix of a trajectory, the task is to
+predict the next operation(s) the user will perform.
+
+This is the evaluation data for the
+[`next_action_pred_eval`](https://github.com/napeval/next_action_pred_eval)
+framework. See the [project page](https://napeval.github.io) and
+[paper](https://arxiv.org/abs/2606.13802).
+
+## Dataset summary
+
+- **52 trajectories** (single `test` split — this is an evaluation benchmark).
+- **11907 total operations**; per-trajectory length ranges 35–821.
+- **23 operation types**: `ALIGN_HORIZONTAL`, `ALIGN_VERTICAL`, `AUTOFILL`, `BORDER_ALL`, `BORDER_BOTTOM`, `BORDER_INSIDE_VERTICAL`, `BORDER_LEFT`, `BORDER_OUTSIDE`, `BORDER_RIGHT`, `BORDER_TOP`, `FILL_COLOR`, `FONT_BOLD`, `FONT_COLOR`, `FONT_ITALIC`, `FONT_NAME`, `FONT_SIZE`, `FONT_UNDERLINE`, `INPUT`, `MERGE`, `NUMBER_FORMAT`, `PASTE_FROM`, `TEXT_ORIENTATION`, `WRAP_TEXT`.
+
+## Fields
+
+| Field | Type | Description |
+|---|---|---|
+| `name` | string | Trajectory id (stable, anonymised). |
+| `operations` | list[string] | Ordered editing history; each entry is one symbolic operation. |
+| `num_operations` | int | Convenience length of `operations`. |
+
+## The symbolic DSL
+
+Every spreadsheet edit is a pipe-delimited string:
+
+```
+OPERATION_TYPE | Sheet!Range | value
+```
+
+Examples:
+
+| Symbolic string | Meaning |
+|---|---|
+| `INPUT \| Sheet1!A1 \| "Title"` | Set A1 to a string value |
+| `INPUT \| Sheet1!A1:B2 \| [[1, 2], [3, 4]]` | Bulk-input a 2×2 block |
+| `FONT_BOLD \| Sheet1!A5 \| True` | Bold A5 |
+| `MERGE \| Sheet1!A1:G1 \| true` | Merge a range |
+| `BORDER_TOP \| Sheet1!A8:G8 \| Thin, Continuous, #000000` | Top border on a row |
+
+The canonical parsing/serialisation logic lives in the framework's
+`core/operations/` module.
+
+## Usage
+
+```python
+from datasets import load_dataset
+
+ds = load_dataset("Tej-a55/napeval", split="test")
+print(ds[0]["name"], ds[0]["num_operations"])
+prefix = ds[0]["operations"][:10]   # history fed to a solver
+```
+
+## What is *not* here
+
+The GitHub repository additionally ships per-trajectory raw artifacts under
+`data/raw/<id>/` (`spreadsheet.xlsx`, a rendered `sheet_image.png`,
+`predictable_state.json` annotations, and an `operations.txt` mirror). These are
+supplementary and are **not** required to run the benchmark, so they are omitted
+from this dataset.
+
+## License
+
+[Creative Commons Attribution 4.0 International (CC BY 4.0)](https://creativecommons.org/licenses/by/4.0/).