| |
|
|
| """ |
| Run this script as ./conversion_script.py to convert the Causal News Corpus |
| (CNC) "V1" (2022) DIRECTLY from its original repository -- ``UniCausal2HF`` |
| already reads a CSV given any path/URL pandas' own ``read_csv`` accepts, so |
| no manual download/caching step is needed; point it straight at the raw |
| GitHub URLs. Previously this dataset had 0 parquet files on disk (the old |
| script expected a manually-placed ``cnc_train.csv`` that was never |
| provided) -- this had never once been run. |
| |
| Citation / original source |
| --------------------------- |
| Tan, F. A., Ng, S.-K., & Ong, A. R. (2022). "The Causal News Corpus: |
| Annotating Causal Relations in Event Sentences from News." LREC 2022. |
| https://aclanthology.org/2022.lrec-1.246/ |
| Repo (verified live, public, no login): github.com/tanfiona/CausalNewsCorpus |
| License: CC0-1.0 (verified via GitHub API) -- public domain, no restrictions. |
| |
| This is the original 2022 release -- see ../CNCv2/conversion_script.py for |
| "V2" (published as RECESS), the actively-maintained version the |
| maintainers themselves now recommend ("For 2023 Shared Task, please use |
| V2" -- repo README): V1's span annotations (subtask 2, Cause/Effect/Signal) |
| are much sparser, only 183 causal relations total vs. V2's 2257 (verified: |
| `train_subtask2_grouped.csv` + `dev_subtask2_grouped.csv` row counts). Kept |
| as its own separate dataset rather than silently overwritten, so both |
| remain available for comparison. |
| |
| Format: the ``_grouped`` CSVs already match causalatee's ``UniCausal2HF`` |
| grouped format exactly (one row per sentence; ``causal_text_w_pairs`` is a |
| Python-repr'd list of 0+ independently <ARG0>/<ARG1>/<SIGn>-tagged copies |
| of that row's ``text``, one per causal relation -- ARG0=cause, ARG1=effect, |
| confirmed against real "because"/"due to" examples) -- see |
| causalatee/data/conversion/_unicausal2hf.py for the shared parsing logic |
| (also used by BECauSEv2, AltLex). |
| |
| No usable test split: the real held-out test set (``test_subtask2_text.csv``) |
| has NO gold labels at all and never will -- confirmed directly from |
| data/V1's upstream README: labels are withheld for a recurring shared |
| task. Mapped here as: upstream train -> causalatee train, upstream dev -> |
| causalatee dev.parquet -- written as ``dev.parquet``, NOT ``test.parquet`` |
| (fixed 2026-07-20; previously written as test.parquet, which claimed a |
| real held-out test set exists when it's actually the upstream dev split). |
| `with_validation_split` in the evaluation harness treats a dataset with |
| dev but no test as: promote this dev to serve as the final eval target, |
| and carve a FRESH validation split out of train for early stopping |
| instead, so the promoted dev is never touched during training either way |
| -- see its docstring. |
| """ |
|
|
| from pathlib import Path |
|
|
| from causalatee.data.constants import Task |
| from causalatee.data.conversion import UniCausal2HF |
|
|
| _BASE_URL = "https://raw.githubusercontent.com/tanfiona/CausalNewsCorpus/master/data/V1" |
|
|
| converter = UniCausal2HF( |
| { |
| "train": f"{_BASE_URL}/train_subtask2_grouped.csv", |
| "dev": f"{_BASE_URL}/dev_subtask2_grouped.csv", |
| }, |
| Path.cwd(), |
| ) |
|
|
| for split in ["train", "dev"]: |
| converter.convert(Task.CausalityDetection, split) |
| converter.convert(Task.CausalCandidateExtraction, split) |
| converter.convert(Task.CausalityIdentification, split) |
|
|
