docling/tests/data/groundtruth/docling_v1/2305.03393v1.json

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480.594, 243.71299999999997], "page": 1, "span": [0, 79], "__ref_s3_data": null}], "text": "Tables are ubiquitous in documents such as scientific papers, patents, reports,", "type": "paragraph", "payload": null, "name": "Text", "font": null}, {"prov": [{"bbox": [149.708, 151.05500000000006, 480.589, 159.85199999999998], "page": 1, "span": [0, 74], "__ref_s3_data": null}], "text": "In modern document understanding systems [1,15], table extraction is typi-", "type": "paragraph", "payload": null, "name": "Text", "font": null}, {"name": "Picture", "type": "figure", "$ref": "#/figures/0"}, {"prov": [{"bbox": [134.765, 330.889, 161.329, 339.686], "page": 2, "span": [0, 6], "__ref_s3_data": null}], "text": "today,", "type": "paragraph", "payload": null, "name": "Text", "font": null}, {"prov": [{"bbox": [149.709, 258.65200000000004, 187.471, 267.44900000000007], "page": 2, "span": [0, 8], "__ref_s3_data": null}], "text": "Recently", "type": "paragraph", "payload": null, "name": "Text", "font": null}, {"prov": [{"bbox": [149.709, 664.269, 480.592, 673.066], "page": 3, "span": [0, 74], "__ref_s3_data": null}], "text": "While the majority of research in TSR is currently focused on the develop-", "type": "paragraph", "payload": null, "name": "Text", "font": null}, {"prov": [{"bbox": [149.709, 568.367, 480.594, 577.164], "page": 3, "span": [0, 78], "__ref_s3_data": null}], "text": "The main contribution of this paper is the introduction of a new optimised ta-", "type": "paragraph", "payload": null, "name": "Text", "font": null}, {"prov": [{"bbox": [149.709, 448.555, 480.588, 457.352], "page": 3, "span": [0, 76], "__ref_s3_data": null}], "text": "The paper is structured as follows. In section 2, we give an overview of the", "type": "paragraph", "payload": null, "name": "Text", "font": null}, {"prov": [{"bbox": [134.765, 319.344, 141.489, 329.912], "page": 3, "span": [0, 1], "__ref_s3_data": null}], "text": "2", "type": "subtitle-level-1", "payload": null, "name": "Section-header", "font": null}, {"prov": [{"bbox": [134.765, 294.517, 480.591, 303.314], "page": 3, "span": [0, 80], "__ref_s3_data": null}], "text": "Approaches to formalize the logical structure and layout of tables in electronic", "type": "paragraph", "payload": null, "name": "Text", "font": null}, {"prov": [{"bbox": [134.765, 664.269, 480.594, 673.066], "page": 4, "span": [0, 81], "__ref_s3_data": null}], "text": "Other work [20] aims at predicting a grid for each table and deciding which cells", "type": "paragraph", "payload": null, "name": "Text", "font": null}, {"prov": [{"bbox": [149.709, 520.546, 199.213, 529.343], "page": 4, "span": [0, 10], "__ref_s3_data": null}], "text": "Within the", "type": "paragraph", "payload": null, "name": "Text", "font": null}, {"prov": [{"bbox": [149.709, 293.137, 480.594, 301.934], "page": 4, "span": [0, 75], "__ref_s3_data": null}], "text": "Im2Seq approaches have shown to be well-suited for the TSR task and allow a", "type": "paragraph", "payload": null, "name": "Text", "font": null}, {"prov": [{"bbox": [134.765, 175.88200000000006, 141.489, 186.45000000000005], "page": 4, "span": [0, 1], "__ref_s3_data": null}], "text": "3", "type": "subtitle-level-1", "payload": null, "name": "Section-header", "font": null}, {"prov": [{"bbox": [134.765, 151.05500000000006, 480.591, 159.85199999999998], "page": 4, "span": [0, 73], "__ref_s3_data": null}], "text": "All known Im2Seq based models for TSR fundamentally work in similar ways.", "type": "paragraph", "payload": null, "name": "Text", "font": null}, {"prov": [{"bbox": [134.765, 664.269, 480.586, 673.066], "page": 5, "span": [0, 77], "__ref_s3_data": null}], "text": "ulary and can be interpreted as a table structure. For example, with the HTML", "type": "paragraph", "payload": null, "name": "Text", "font": null}, {"name": "Picture", "type": "figure", "$ref": "#/figures/1"}, {"prov": [{"bbox": [149.709, 414.996, 480.593, 423.793], "page": 5, "span": [0, 71], "__ref_s3_data": null}], "text": "Obviously, HTML and other general-purpose markup languages were not de-", "type": "paragraph", "payload": null, "name": "Text", "font": null}, {"prov": [{"bbox": [149.709, 247.15999999999997, 480.593, 255.957], "page": 5, "span": [0, 76], "__ref_s3_data": null}], "text": "Additionally, it would be desirable if the representation would easily allow", "type": "paragraph", "payload": null, "name": "Text", "font": null}, {"prov": [{"bbox": [149.709, 198.87599999999998, 480.593, 207.673], "page": 5, "span": [0, 74], "__ref_s3_data": null}], "text": "In a valid HTML table, the token sequence must describe a 2D grid of table", "type": "paragraph", "payload": null, "name": "Text", "font": null}, {"prov": [{"bbox": [134.765, 664.269, 480.595, 673.066], "page": 6, "span": [0, 78], "__ref_s3_data": null}], "text": "generation. Implicitly, this also means that Im2Seq models need to learn these", "type": "paragraph", "payload": null, "name": "Text", "font": null}, {"prov": [{"bbox": [149.709, 639.72, 480.59, 648.517], "page": 6, "span": [0, 76], "__ref_s3_data": null}], "text": "In practice, we observe two major issues with prediction quality when train-", "type": "paragraph", "payload": null, "name": "Text", "font": null}, {"prov": [{"bbox": [134.765, 460.801, 141.489, 471.369], "page": 6, "span": [0, 1], "__ref_s3_data": null}], "text": "4", "type": "subtitle-level-1", "payload": null, "name": "Section-header", "font": null}, {"prov": [{"bbox": [134.765, 434.086, 480.591, 442.883], "page": 6, "span": [0, 76], "__ref_s3_data": null}], "text": "To mitigate the issues with HTML in Im2Seq-based TSR models laid out before,", "type": "paragraph", "payload": null, "name": "Text", "font": null}, {"prov": [{"bbox": [134.765, 317.321, 149.402, 326.128], "page": 6, "span": [0, 3], "__ref_s3_data": null}], "text": "4.1", "type": "subtitle-level-1", "payload": null, "name": "Section-header", "font": null}, {"prov": [{"bbox": [134.765, 294.205, 480.589, 303.002], "page": 6, "span": [0, 80], "__ref_s3_data": null}], "text": "In Figure 3, we illustrate how the OTSL is defined. In essence, the OTSL defines", "type": "paragraph", "payload": null, "name": "Text", "font": null}, {"prov": [{"bbox": [149.709, 257.701, 409.311, 266.49800000000005], "page": 6, "span": [0, 57], "__ref_s3_data": null}], "text": "The OTSL vocabulary is comprised of the following tokens:", "type": "paragraph", "payload": null, "name": "Text", "font": null}, {"prov": [{"bbox": [140.993, 235.22299999999996, 146.72, 244.02999999999997], "page": 6, "span": [0, 1], "__ref_s3_data": null}], "text": "- -", "type": "paragraph", "payload": null, "name": "List-item", "font": null}, {"prov": [{"bbox": [140.993, 222.63, 146.72, 231.437], "page": 6, "span": [0, 1], "__ref_s3_data": null}], "text": "- -", "type": "paragraph", "payload": null, "name": "List-item", "font": null}, {"prov": [{"bbox": [140.993, 198.08100000000002, 146.72, 206.88800000000003], "page": 6, "span": [0, 1], "__ref_s3_data": null}], "text": "- -", "type": "paragraph", "payload": null, "name": "List-item", "font": null}, {"prov": [{"bbox": [140.993, 173.53300000000002, 146.72, 182.34000000000003], "page": 6, "span": [0, 1], "__ref_s3_data": null}], "text": "- -", "type": "paragraph", "payload": null, "name": "List-item", "font": null}, {"prov": [{"bbox": [140.993, 160.93899999999996, 146.72, 169.74599999999998], "page": 6, "span": [0, 1], "__ref_s3_data": null}], "text": "- -", "type": "paragraph", "payload": null, "name": "List-item", "font": null}, {"prov": [{"bbox": [149.709, 139.10000000000002, 480.593, 147.89699999999993], "page": 6, "span": [0, 79], "__ref_s3_data": null}], "text": "A notable attribute of OTSL is that it has the capability of achieving lossless", "type": "paragraph", "payload": null, "name": "Text", "font": null}, {"name": "Picture", "type": "figure", "$ref": "#/figures/2"}, {"prov": [{"bbox": [134.765, 477.897, 149.402, 486.704], "page": 7, "span": [0, 3], "__ref_s3_data": null}], "text": "4.2", "type": "subtitle-level-1", "payload": null, "name": "Section-header", "font": null}, {"prov": [{"bbox": [134.765, 457.955, 363.796, 466.752], "page": 7, "span": [0, 51], "__ref_s3_data": null}], "text": "The OTSL representation follows these syntax rules:", "type": "paragraph", "payload": null, "name": "Text", "font": null}, {"prov": [{"bbox": [138.973, 436.022, 146.72, 444.819], "page": 7, "span": [0, 2], "__ref_s3_data": null}], "text": "- 1.", "type": "paragraph", "payload": null, "name": "List-item", "font": null}, {"prov": [{"bbox": [138.973, 412.108, 146.72, 420.905], "page": 7, "span": [0, 2], "__ref_s3_data": null}], "text": "- 2.", "type": "paragraph", "payload": null, "name": "List-item", "font": null}, {"prov": [{"bbox": [138.973, 388.195, 146.72, 396.992], "page": 7, "span": [0, 2], "__ref_s3_data": null}], "text": "3.", "type": "subtitle-level-1", "payload": null, "name": "Section-header", "font": null}, {"prov": [{"bbox": [138.973, 340.367, 146.72, 349.164], "page": 7, "span": [0, 2], "__ref_s3_data": null}], "text": "- 4.", "type": "paragraph", "payload": null, "name": "List-item", "font": null}, {"prov": [{"bbox": [138.973, 328.409, 146.72, 337.206], "page": 7, "span": [0, 2], "__ref_s3_data": null}], "text": "- 5.", "type": "paragraph", "payload": null, "name": "List-item", "font": null}, {"prov": [{"bbox": [138.973, 304.496, 146.72, 313.293], "page": 7, "span": [0, 2], "__ref_s3_data": null}], "text": "- 6.", "type": "paragraph", "payload": null, "name": "List-item", "font": null}, {"prov": [{"bbox": [151.701, 376.236, 480.592, 385.033], "page": 7, "span": [0, 74], "__ref_s3_data": null}], "text": "- The left neighbour of an \"X\" cell must be either another \"X\" cell or a \"U\"", "type": "paragraph", "payload": null, "name": "List-item", "font": null}, {"prov": [{"bbox": [149.709, 270.61, 480.596, 279.4069999999999], "page": 7, "span": [0, 75], "__ref_s3_data": null}], "text": "The application of these rules gives OTSL a set of unique properties. First", "type": "paragraph", "payload": null, "name": "Text", "font": null}, {"prov": [{"bbox": [149.709, 139.10000000000002, 480.592, 147.89699999999993], "page": 7, "span": [0, 75], "__ref_s3_data": null}], "text": "These characteristics can be easily learned by sequence generator networks,", "type": "paragraph", "payload": null, "name": "Text", "font": null}, {"prov": [{"bbox": [134.765, 664.269, 480.589, 673.066], "page": 8, "span": [0, 78], "__ref_s3_data": null}], "text": "reduces significantly the column drift seen in the HTML based models (see Fig-", "type": "paragraph", "payload": null, "name": "Text", "font": null}, {"prov": [{"bbox": [134.765, 621.636, 149.402, 630.443], "page": 8, "span": [0, 3], "__ref_s3_data": null}], "text": "4.3", "type": "subtitle-level-1", "payload": null, "name": "Section-header", "font": null}, {"prov": [{"bbox": [134.765, 600.921, 480.596, 609.718], "page": 8, "span": [0, 79], "__ref_s3_data": null}], "text": "The design of OTSL allows to validate a table structure easily on an unfinished", "type": "paragraph", "payload": null, "name": "Text", "font": null}, {"prov": [{"bbox": [134.765, 460.268, 141.489, 470.836], "page": 8, "span": [0, 1], "__ref_s3_data": null}], "text": "5", "type": "subtitle-level-1", "payload": null, "name": "Section-header", "font": null}, {"prov": [{"bbox": [134.765, 435.953, 480.594, 444.75], "page": 8, "span": [0, 77], "__ref_s3_data": null}], "text": "To evaluate the impact of OTSL on prediction accuracy and inference times, we", "type": "paragraph", "payload": null, "name": "Text", "font": null}, {"name": "Picture", "type": "figure", "$ref": "#/figures/3"}, {"prov": [{"bbox": [149.709, 163.01, 480.588, 171.80700000000002], "page": 8, "span": [0, 71], "__ref_s3_data": null}], "text": "We rely on standard metrics such as Tree Edit Distance score (TEDs) for", "type": "paragraph", "payload": null, "name": "Text", "font": null}, {"prov": [{"bbox": [134.765, 664.269, 480.594, 673.066], "page": 9, "span": [0, 76], "__ref_s3_data": null}], "text": "order to compute the TED score. Inference timing results for all experiments", "type": "paragraph", "payload": null, "name": "Text", "font": null}, {"prov": [{"bbox": [134.765, 614.007, 149.402, 622.814], "page": 9, "span": [0, 3], "__ref_s3_data": null}], "text": "5.1", "type": "subtitle-level-1", "payload": null, "name": "Section-header", "font": null}, {"prov": [{"bbox": [134.765, 597.617, 480.592, 606.414], "page": 9, "span": [0, 73], "__ref_s3_data": null}], "text": "We have chosen the PubTabNet data set to perform HPO, since it includes a", "type": "paragraph", "payload": null, "name": "Text", "font": null}, {"name": "Table", "type": "table", "$ref": "#/tables/0"}, {"prov": [{"bbox": [134.765, 509.002, 160.118, 516.928], "page": 9, "span": [0, 5], "__ref_s3_data": null}], "text": "Table", "type": "caption", "payload": null, "name": "Caption", "font": null}, {"prov": [{"bbox": [134.765, 275.04099999999994, 149.402, 283.848], "page": 9, "span": [0, 3], "__ref_s3_data": null}], "text": "5.2", "type": "subtitle-level-1", "payload": null, "name": "Section-header", "font": null}, {"prov": [{"bbox": [134.765, 258.65200000000004, 480.591, 267.44900000000007], "page": 9, "span": [0, 77], "__ref_s3_data": null}], "text": "We picked the model parameter configuration that produced the best prediction", "type": "paragraph", "payload": null, "name": "Text", "font": null}, {"prov": [{"bbox": [149.709, 163.01, 205.597, 171.80700000000002], "page": 9, "span": [0, 13], "__ref_s3_data": null}], "text": "Additionally,", "type": "paragraph", "payload": null, "name": "Text", "font": null}, {"name": "Table", "type": "table", "$ref": "#/tables/1"}, {"prov": [{"bbox": [134.765, 668.238, 173.094, 676.164], "page": 10, "span": [0, 8], "__ref_s3_data": null}], "text": "Table 2.", "type": "caption", "payload": null, "name": "Caption", "font": null}, {"prov": [{"bbox": [134.765, 494.278, 149.402, 503.085], "page": 10, "span": [0, 3], "__ref_s3_data": null}], "text": "5.3", "type": "subtitle-level-1", "payload": null, "name": "Section-header", "font": null}, {"prov": [{"bbox": [134.765, 473.342, 189.59, 482.139], "page": 10, "span": [0, 13], "__ref_s3_data": null}], "text": "To illustrate", "type": "paragraph", "payload": null, "name": "Text", "font": null}, {"name": "Picture", "type": "figure", "$ref": "#/figures/4"}, {"name": "Picture", "type": "figure", "$ref": "#/figures/5"}, {"prov": [{"bbox": [134.765, 663.883, 141.489, 674.451], "page": 12, "span": [0, 1], "__ref_s3_data": null}], "text": "6", "type": "subtitle-level-1", "payload": null, "name": "Section-header", "font": null}, {"prov": [{"bbox": [134.765, 636.339, 480.595, 645.136], "page": 12, "span": [0, 77], "__ref_s3_data": null}], "text": "We demonstrated that representing tables in HTML for the task of table struc-", "type": "paragraph", "payload": null, "name": "Text", "font": null}, {"prov": [{"bbox": [149.709, 575.759, 480.593, 584.556], "page": 12, "span": [0, 76], "__ref_s3_data": null}], "text": "First and 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