Data annotation
VideoChat3-Training-Data-Annotations
VideoChat3-Stage3-Training-Data
This repository includes all annotation files used across the four training stages of VideoChat3, from Stage 0 to Stage 3.
You can refer to the provided source-data links to download videos, images, and other multimedia data for training. In videochat3_data_annotations, we also provide a source field to indicate the source dataset for each entry.
To facilitate Stage 3 training reproduction using the high-quality open-source datasets we collected… See the full description on the dataset page: https://huggingface.co/datasets/MCG-NJU/VideoChat3-Training-Data-Annotations.probe-tip-annotations-dataLocateAnything-Data-ShareGPT-Annotationmap-annotation-tool-data
Map Annotation Tool Media
This dataset contains Docling-extracted figure crops grouped by source PDF. It is the
media input for map-annotation-tool; human annotations are maintained separately in
the application repository and submitted through pull requests.
Contents
media/figures/brgm-v1/: 1,512 figures from the earlier BRGM parsing batch,
of which 156 had legacy annotations at migration time.
media/figures/brgm-v2/: 6,046 figures from the newer BRGM parsing… See the full description on the dataset page: https://huggingface.co/datasets/marijanic/map-annotation-tool-data.annotation_app_data
Dataset Card for Systematic Review of Acceptability Judgments data
A curated dataset of research articles used in a systematic review of judgment tasks in linguistics. Each entry records article-level metadata and experiment-level methodological features, supporting structured comparison and analysis across studies.
Dataset Description
This annotation dataset comprises systematically coded observations from a corpus of published studies employing judgment tasks in… See the full description on the dataset page: https://huggingface.co/datasets/jasongraf1/annotation_app_data.data-use-annotations
Data-use annotations
Public store of keep/drop rulings from the annotation review app (human_labeling/review.html).
Files
rulings/<annotator>.jsonl — one file per annotator, one JSON object per ruling: key (span UID), ruling (DATA_MENTION keep / NON_MENTION drop), queue (gold / sample), annotator (required, set in the UI), ts. Last write per (queue, key, annotator) wins.
from datasets import load_dataset
ds = load_dataset("rafmacalaba/data-use-annotations") #… See the full description on the dataset page: https://huggingface.co/datasets/rafmacalaba/data-use-annotations.