id stringlengths 25 57 | doc_id stringlengths 8 40 | source stringclasses 1
value | html_opus stringlengths 538 10.8k | html_wtw_original stringlengths 78 3.32k | image dict |
|---|---|---|---|---|---|
wtw_hybrid_pairs_11fa2e60a52cb248346955ed3ca39b25 | 11fa2e60a52cb248346955ed3ca39b25 | wtw_hybrid_pairs | "<table>\n<tr><td rowspan=\"4\" colspan=\"2\"></td><td rowspan=\"6\" colspan=\"2\"></td></tr>\n<tr><(...TRUNCATED) | "<table><tr><td></td><td></td></tr><tr><td></td><td></td></tr><tr><td></td><td></td></tr><tr><td></t(...TRUNCATED) | {"bytes":"/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAIBAQEBAQIBAQECAgICAgQDAgICAgUEBAMEBgUGBgYFBgYGBwkIBgcJBw(...TRUNCATED) |
wtw_hybrid_pairs_11968509 | 11968509 | wtw_hybrid_pairs | "<table>\n<tr>\n<td rowspan=\"2\" colspan=\"2\">购买方</td>\n<td rowspan=\"2\" colspan=\"6\">纳(...TRUNCATED) | "<table><tr><td></td><td colspan=\"5\"></td><td></td><td colspan=\"4\"></td></tr><tr><td colspan=\"2(...TRUNCATED) | {"bytes":"/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAIBAQEBAQIBAQECAgICAgQDAgICAgUEBAMEBgUGBgYFBgYGBwkIBgcJBw(...TRUNCATED) |
wtw_hybrid_pairs_00066065e908b430935d747fd257a706 | 00066065e908b430935d747fd257a706 | wtw_hybrid_pairs | "<table>\n<tr><td rowspan=\"2\" colspan=\"2\">权 利 人</td><td rowspan=\"2\" colspan=\"2\"></td><(...TRUNCATED) | "<table><tr><td></td><td></td></tr><tr><td></td><td></td></tr><tr><td></td><td></td></tr><tr><td></t(...TRUNCATED) | {"bytes":"/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAIBAQEBAQIBAQECAgICAgQDAgICAgUEBAMEBgUGBgYFBgYGBwkIBgcJBw(...TRUNCATED) |
wtw_hybrid_pairs_-uIghvkuTrGAlnUVHihDJgAAACMAAQED | -uIghvkuTrGAlnUVHihDJgAAACMAAQED | wtw_hybrid_pairs | "<table>\n<tbody>\n<tr>\n<td rowspan=\"2\" colspan=\"2\">购买方</td>\n<td rowspan=\"2\" colspan=\(...TRUNCATED) | "<table><tr><td></td><td colspan=\"5\"></td><td></td><td colspan=\"4\"></td></tr><tr><td colspan=\"2(...TRUNCATED) | {"bytes":"/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAIBAQEBAQIBAQECAgICAgQDAgICAgUEBAMEBgUGBgYFBgYGBwkIBgcJBw(...TRUNCATED) |
wtw_hybrid_pairs_11a4058b29551a73c1d42f29ff73ec8d | 11a4058b29551a73c1d42f29ff73ec8d | wtw_hybrid_pairs | "<table>\n<tr>\n<td></td>\n<td rowspan=\"4\" colspan=\"2\"></td>\n</tr>\n<tr>\n<td rowspan=\"3\" col(...TRUNCATED) | "<table><tr><td></td><td></td></tr><tr><td></td><td></td></tr><tr><td></td><td></td></tr><tr><td></t(...TRUNCATED) | {"bytes":"/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAIBAQEBAQIBAQECAgICAgQDAgICAgUEBAMEBgUGBgYFBgYGBwkIBgcJBw(...TRUNCATED) |
wtw_hybrid_pairs_11219ab51103f103289422e16344003c | 11219ab51103f103289422e16344003c | wtw_hybrid_pairs | "<table>\n<tbody>\n<tr>\n<td rowspan=\"2\" colspan=\"2\">权利人</td>\n<td rowspan=\"3\" colspan=\(...TRUNCATED) | "<table><tr><td></td><td></td></tr><tr><td></td><td></td></tr><tr><td></td><td></td></tr><tr><td></t(...TRUNCATED) | {"bytes":"/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAIBAQEBAQIBAQECAgICAgQDAgICAgUEBAMEBgUGBgYFBgYGBwkIBgcJBw(...TRUNCATED) |
wtw_hybrid_pairs_10389210 | 10389210 | wtw_hybrid_pairs | "<table>\n<tbody>\n<tr>\n<td rowspan=\"2\" colspan=\"2\"></td>\n<td rowspan=\"2\" colspan=\"6\">抵(...TRUNCATED) | "<table><tr><td></td><td colspan=\"5\"></td><td></td><td colspan=\"4\"></td></tr><tr><td colspan=\"2(...TRUNCATED) | {"bytes":"/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAIBAQEBAQIBAQECAgICAgQDAgICAgUEBAMEBgUGBgYFBgYGBwkIBgcJBw(...TRUNCATED) |
wtw_hybrid_pairs_11b6ed06820a8c9b31867d457fe8d4f5 | 11b6ed06820a8c9b31867d457fe8d4f5 | wtw_hybrid_pairs | "<table>\n<tr><td></td><td colspan=\"2\" rowspan=\"4\"></td></tr>\n<tr><td colspan=\"2\" rowspan=\"3(...TRUNCATED) | "<table><tr><td></td><td></td></tr><tr><td></td><td></td></tr><tr><td></td><td></td></tr><tr><td></t(...TRUNCATED) | {"bytes":"/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAIBAQEBAQIBAQECAgICAgQDAgICAgUEBAMEBgUGBgYFBgYGBwkIBgcJBw(...TRUNCATED) |
wtw_hybrid_pairs_04d87df44bf4175791df839365822f8d7bbace1f | 04d87df44bf4175791df839365822f8d7bbace1f | wtw_hybrid_pairs | "<table>\n<tr><td rowspan=\"2\" colspan=\"2\"></td><td rowspan=\"2\" colspan=\"3\"></td><td rowspan=(...TRUNCATED) | "<table><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><t(...TRUNCATED) | {"bytes":"/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAgGBgcGBQgHBwcJCQgKDBQNDAsLDBkSEw8UHRofHh0aHBwgJC4nICIsIx(...TRUNCATED) |
wtw_hybrid_pairs_11bad49759f1f8584bbbc1bae58aaa13 | 11bad49759f1f8584bbbc1bae58aaa13 | wtw_hybrid_pairs | "<table>\n<tbody>\n<tr><td></td><td colspan=\"2\" rowspan=\"4\"></td></tr>\n<tr><td colspan=\"2\" ro(...TRUNCATED) | "<table><tr><td></td><td></td></tr><tr><td></td><td></td></tr><tr><td></td><td></td></tr><tr><td></t(...TRUNCATED) | {"bytes":"/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAIBAQEBAQIBAQECAgICAgQDAgICAgUEBAMEBgUGBgYFBgYGBwkIBgcJBw(...TRUNCATED) |
YAML Metadata Warning:The task_categories "table-recognition" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, audio-text-to-text, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-ranking, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, image-text-to-image, image-text-to-video, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, video-text-to-text, keypoint-detection, visual-document-retrieval, any-to-any, video-to-video, other
wtw-table-annotations
WTW (Wild Table/Wild scanned documents) 表格的双标注版本: 每条样本同时给出
| column | 说明 |
|---|---|
| image | 图片字节 (struct {bytes, path}) |
| html_opus | 用 VLM(Opus) 从图片蒸馏出来的表格 HTML —— 这是训练用的标注 |
| html_wtw_original | WTW 数据集自带的官方 HTML 标注 —— 这是参照 |
背景: 2026-10-20 爬取数据时, WTW 的裁图经 VLM 蒸馏成了 HTML。2026-10-20 本机那份
中间数据被一个外部进程删掉, 图和蒸馏标注一度全丢; 后来从
WTW_image_html_pairs/*.tar 里按 id 把原图和 WTW 官方 HTML 一起找回来了
(src/recover_crawled_images.py / WTW tar 扫描), 蒸馏 HTML 则一直保存在 HF 的
CheneyWong/real-scene-tables 的 data/table_html-* 里。
两版 HTML 放在一起, 是为了能直接看「VLM 蒸馏」相对官方标注差在哪 (单元格划分、跨行跨列、空 cell 的处理) —— 这类差异在评测口径上影响很大。
同批数据的整页图版见 CheneyWong/real-scene-tables。
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