feat: improve reading order (#2219)

Closes GH Issue #2208.

.gitignore

@@ -12,6 +12,7 @@ build/
 develop-eggs/
 dist/
 downloads/
+figures/
 eggs/
 .eggs/
 lib/

CHANGELOG.md

@@ -1,4 +1,4 @@
-## 0.11.4-dev5
+## 0.11.4-dev6
 
 ### Enhancements
 

test_unstructured_ingest/expected-structured-output/azure/Core-Skills-for-Biomedical-Data-Scientists-2-pages.pdf.json

@@ -154,7 +154,7 @@
     "type": "ListItem"
   },
   {
-    "element_id": "ff686e6046cd8176988d8dec0d8adac4",
+    "element_id": "c2036e04407827dd9f895cce7fdb8674",
     "metadata": {
       "data_source": {
         "date_created": "2023-03-10T09:32:44+00:00",

test_unstructured_ingest/expected-structured-output/biomed-api/65/11/main.PMC6312790.pdf.json

@@ -325,7 +325,7 @@
     "type": "NarrativeText"
   },
   {
-    "element_id": "82391aed75376c2c3bc734ad52ec73e4",
+    "element_id": "63ffdff8ce24056d9d776dda2adcc934",
     "metadata": {
       "data_source": {},
       "filetype": "application/pdf",
@@ -334,7 +334,7 @@
       ],
       "page_number": 2
     },
-    "text": "How data were acquired The cleaned and weighed specimen was suspended in beakers con- taining 0.5 M H2SO4 solution of different concentrations of egg shell powder. The pre-weighed stainless steel samples were retrieved from the test solutions after every 24 h, cleaned appropriately, dried and reweighed. Raw, analyzed The difference between the weight at a given time and the initial weight of the specimen was taken as the weight loss, which was used to calculate the corrosion rate and inhibition efficiency. Inhibitor concentration, exposure time Department of Chemical, Metallurgical and Materials Engineering, Tshwane University of Technology, Pretoria, South Africa Data are available within this article O. Sanni, A. P. I. Popoola, and O. S. I. Fayomi, Enhanced corrosion resistance of stainless steel type 316 in sulphuric acid solution using eco-friendly waste product, Results in Physics, 9 (2018) 225–230. Data format Experimental factors Experimental features Data source location Accessibility Related research article",
+    "text": "How data were acquired Data format Experimental factors Experimental features Data source location Accessibility Related research article The cleaned and weighed specimen was suspended in beakers con- taining 0.5 M H2SO4 solution of different concentrations of egg shell powder. The pre-weighed stainless steel samples were retrieved from the test solutions after every 24 h, cleaned appropriately, dried and reweighed. Raw, analyzed The difference between the weight at a given time and the initial weight of the specimen was taken as the weight loss, which was used to calculate the corrosion rate and inhibition efficiency. Inhibitor concentration, exposure time Department of Chemical, Metallurgical and Materials Engineering, Tshwane University of Technology, Pretoria, South Africa Data are available within this article O. Sanni, A. P. I. Popoola, and O. S. I. Fayomi, Enhanced corrosion resistance of stainless steel type 316 in sulphuric acid solution using eco-friendly waste product, Results in Physics, 9 (2018) 225–230.",
     "type": "Table"
   },
   {
@@ -429,7 +429,7 @@
     "type": "NarrativeText"
   },
   {
-    "element_id": "ba559032c2f9f98c24e4c547af135b8e",
+    "element_id": "3fcf35e8b67240541d3f2bf3bc0a39c5",
     "metadata": {
       "data_source": {},
       "filetype": "application/pdf",
@@ -438,7 +438,7 @@
       ],
       "page_number": 2
     },
-    "text": "30  10g 8g 6g 4g 2g Control  ) g m  (     s s o  20  l     t h g e W  i  10  48  96  144  192 ",
+    "text": "30  ) g m  (     s s o  l     t h g e W  i  20  10g 8g 6g 4g 2g Control  10  48  96  144  192 ",
     "type": "Image"
   },
   {
@@ -481,7 +481,7 @@
     "type": "NarrativeText"
   },
   {
-    "element_id": "f2e384e79a4fbce052f262a93ec46102",
+    "element_id": "9fd8126152fe50909dc643c92ff6cd4c",
     "metadata": {
       "data_source": {},
       "filetype": "application/pdf",
@@ -490,7 +490,7 @@
       ],
       "page_number": 3
     },
-    "text": "2.7  1.8  10g 8g 6g 4g 2g Control  0.9  24  48  72  96  120  144  168  192  Exposure time ",
+    "text": "2.7  1.8  0.9  10g 8g 6g 4g 2g Control  24  48  72  96  120  144  168  192  Exposure time ",
     "type": "Image"
   },
   {
@@ -585,7 +585,7 @@
     "type": "UncategorizedText"
   },
   {
-    "element_id": "00c6c21aa97f59dc84190f023eaaf769",
+    "element_id": "c1daf0ef9e2135894ab832147233a7f3",
     "metadata": {
       "data_source": {},
       "filetype": "application/pdf",
@@ -594,7 +594,7 @@
       ],
       "page_number": 3
     },
-    "text": "90  2g 4g 6g 8g 10g  80  )  %  70  (     y c n e c i f f  60  i  50  E n o i t i b h n I     40  i  30  20  10  0  20  40  60  80  100  120  140  160  180 ",
+    "text": "90  )  %  (     y c n e c i f f  i  E n o i t i b h n I     i  80  70  60  50  40  30  2g 4g 6g 8g 10g  20  10  0  20  40  60  80  100  120  140  160  180 ",
     "type": "Image"
   },
   {
@@ -715,7 +715,7 @@
     "type": "UncategorizedText"
   },
   {
-    "element_id": "150b064badb909ac7549f8064cf2caba",
+    "element_id": "a31f676a690660014de4c38544212163",
     "metadata": {
       "data_source": {},
       "filetype": "application/pdf",
@@ -724,7 +724,7 @@
       ],
       "page_number": 4
     },
-    "text": "icorr (A/cm2) Polarization resistance (Ω) Inhibitor concentration (g) bc (V/dec) ba (V/dec) Ecorr (V) (cid:3) 0.9393 (cid:3) 0.8276 (cid:3) 0.8825 (cid:3) 0.8027 (cid:3) 0.5896 (cid:3) 0.5356 0 2 4 6 8 10 0.0335 1.9460 0.0163 0.3233 0.1240 0.0382 0.0409 0.0596 0.2369 0.0540 0.0556 0.0086 0.0003 0.0002 0.0001 5.39E-05 5.46E-05 1.24E-05 24.0910 121.440 42.121 373.180 305.650 246.080 2.8163 1.5054 0.9476 0.4318 0.3772 0.0919",
+    "text": "Inhibitor concentration (g) bc (V/dec) ba (V/dec) Ecorr (V) icorr (A/cm2) Polarization resistance (Ω) 0 2 4 6 8 10 0.0335 1.9460 0.0163 0.3233 0.1240 0.0382 0.0409 0.0596 0.2369 0.0540 0.0556 0.0086 (cid:3) 0.9393 (cid:3) 0.8276 (cid:3) 0.8825 (cid:3) 0.8027 (cid:3) 0.5896 (cid:3) 0.5356 0.0003 0.0002 0.0001 5.39E-05 5.46E-05 1.24E-05 24.0910 121.440 42.121 373.180 305.650 246.080 2.8163 1.5054 0.9476 0.4318 0.3772 0.0919",
     "type": "Table"
   },
   {
@@ -1092,7 +1092,7 @@
     "type": "Formula"
   },
   {
-    "element_id": "aa63e6aba52eb53a896d01e2c7ccc133",
+    "element_id": "13bc6e646e1dea06c3836e074c7fe40f",
     "metadata": {
       "data_source": {},
       "filetype": "application/pdf",
@@ -1101,7 +1101,7 @@
       ],
       "page_number": 6
     },
-    "text": "IE ð%Þ ¼ CRo (cid:3) CR 100 1 x CRo",
+    "text": "IE ð%Þ ¼ CRo (cid:3) CR CRo x 100 1",
     "type": "Formula"
   },
   {

test_unstructured_ingest/expected-structured-output/biomed-api/75/29/main.PMC6312793.pdf.json

@@ -416,7 +416,7 @@
     "type": "UncategorizedText"
   },
   {
-    "element_id": "4e5faed345ed29d23513a466e412ec0a",
+    "element_id": "d022b06e927bb8ee92ff9034e08e62de",
     "metadata": {
       "data_source": {},
       "filetype": "application/pdf",
@@ -425,7 +425,7 @@
       ],
       "page_number": 2
     },
-    "text": "i , a start location, ls i , and an end location, le i , i , an end time, te and",
+    "text": "i , a start location, ls i , an end time, te i , and an end location, le i , and",
     "type": "NarrativeText"
   },
   {
@@ -637,7 +637,7 @@
     "type": "Title"
   },
   {
-    "element_id": "ff667ddf988229560eaac54fc38ddc66",
+    "element_id": "cf21fea12c5e4fac7b8606af479c6edf",
     "metadata": {
       "data_source": {},
       "filetype": "application/pdf",
@@ -646,7 +646,7 @@
       ],
       "page_number": 4
     },
-    "text": "Number of lines Number of columns in each line Description 1 1 n 3 m 4 The number of depots, the number of trips, and the number of locations. The number of vehicles rd at each depot d. One line for each trip, i ¼ 1; 2; …; n. Each line provides the start location ls time ts i and the end time te i for the corresponding trip. Each element, δij; where i; j A 1; 2; …; l, refers to the travel time between location i and location j. i , the start i , the end location le l l",
+    "text": "Number of lines Number of columns in each line Description 1 1 n l 3 m 4 l The number of depots, the number of trips, and the number of locations. The number of vehicles rd at each depot d. One line for each trip, i ¼ 1; 2; …; n. Each line provides the start location ls time ts i and the end time te i for the corresponding trip. Each element, δij; where i; j A 1; 2; …; l, refers to the travel time between location i and location j. i , the start i , the end location le",
     "type": "Table"
   },
   {

test_unstructured_ingest/expected-structured-output/local-single-file-with-pdf-infer-table-structure/layout-parser-paper.pdf.json

@@ -760,7 +760,7 @@
     "type": "FigureCaption"
   },
   {
-    "element_id": "c57f2166778009c6ccc9032ee8883253",
+    "element_id": "4577aebb24ff9c0fd98387936d5ef4a7",
     "metadata": {
       "data_source": {
         "permissions_data": [
@@ -777,7 +777,7 @@
       "page_number": 5,
       "text_as_html": "<table><thead><th>Dataset</th><th>| Base Model'|</th><th>| Notes</th></thead><tr><td>PubLayNet B8]|</td><td>F/M</td><td>Layouts of modern scientific documents</td></tr><tr><td>PRImA</td><td>M</td><td>Layouts of scanned modern magazines and scientific report</td></tr><tr><td>Newspaper</td><td>F</td><td>Layouts of scanned US newspapers from the 20th century</td></tr><tr><td>TableBank</td><td>F</td><td>Table region on modern scientific and business document</td></tr><tr><td>HJDataset</td><td>F/M</td><td>Layouts of history Japanese documents</td></tr></table>"
     },
-    "text": "Base Model1 Large Model Notes Dataset PubLayNet [38] PRImA [3] Newspaper [17] TableBank [18] HJDataset [31] F / M M F F F / M M - - F - Layouts of modern scientific documents Layouts of scanned modern magazines and scientific reports Layouts of scanned US newspapers from the 20th century Table region on modern scientific and business document Layouts of history Japanese documents",
+    "text": "Dataset Base Model1 Large Model Notes PubLayNet [38] PRImA [3] Newspaper [17] TableBank [18] HJDataset [31] F / M M F F F / M M - - F - Layouts of modern scientific documents Layouts of scanned modern magazines and scientific reports Layouts of scanned US newspapers from the 20th century Table region on modern scientific and business document Layouts of history Japanese documents",
     "type": "Table"
   },
   {
@@ -1261,7 +1261,7 @@
     "type": "NarrativeText"
   },
   {
-    "element_id": "b35cc086edca679ccc52fa6701857549",
+    "element_id": "35adc4ddaef6ffb21b754c9c350c856f",
     "metadata": {
       "data_source": {
         "permissions_data": [
@@ -1278,7 +1278,7 @@
       "page_number": 8,
       "text_as_html": "<table><thead><th>block.pad(top, bottom,</th><th>right,</th><th>left)</th><th>Enlarge the current block according to the input</th></thead><tr><td>block.scale(fx, fy)</td><td></td><td></td><td>Scale the current block given the ratio in x and y direction</td></tr><tr><td>block.shift(dx, dy)</td><td></td><td></td><td>Move the current block with the shift distances in x and y direction</td></tr><tr><td>block1.is_in(block2)</td><td></td><td></td><td>Whether block] is inside of block2</td></tr><tr><td>block1. intersect (block2)</td><td></td><td></td><td>Return the intersection region of blockl and block2. Coordinate type to be determined based on the inputs</td></tr><tr><td>block1.union(block2)</td><td></td><td></td><td>Return the union region of blockl and block2. Coordinate type to be determined based on the inputs</td></tr><tr><td>block1.relative_to(block2)</td><td></td><td></td><td>Convert the absolute coordinates of block to relative coordinates to block2</td></tr><tr><td>block1.condition_on(block2)</td><td></td><td></td><td>Calculate the absolute coordinates of blockl given the canvas block2’s absolute coordinates</td></tr><tr><td>block. crop_image (image)</td><td></td><td></td><td>Obtain the image segments in the block region</td></tr></table>"
     },
-    "text": "Operation Name Description block.pad(top, bottom, right, left) Enlarge the current block according to the input Scale the current block given the ratio in x and y direction block.scale(fx, fy) Move the current block with the shift distances in x and y direction block.shift(dx, dy) Whether block1 is inside of block2 block1.is in(block2) Return the intersection region of block1 and block2. Coordinate type to be determined based on the inputs. block1.intersect(block2) Return the union region of block1 and block2. Coordinate type to be determined based on the inputs. block1.union(block2) Convert the absolute coordinates of block1 to relative coordinates to block2 block1.relative to(block2) Calculate the absolute coordinates of block1 given the canvas block2’s absolute coordinates block1.condition on(block2) Obtain the image segments in the block region block.crop image(image)",
+    "text": "Operation Name Description block.pad(top, bottom, right, left) Enlarge the current block according to the input block.scale(fx, fy) Scale the current block given the ratio in x and y direction block.shift(dx, dy) Move the current block with the shift distances in x and y direction block1.is in(block2) Whether block1 is inside of block2 block1.intersect(block2) Return the intersection region of block1 and block2. Coordinate type to be determined based on the inputs. block1.union(block2) Return the union region of block1 and block2. Coordinate type to be determined based on the inputs. block1.relative to(block2) Convert the absolute coordinates of block1 to relative coordinates to block2 block1.condition on(block2) Calculate the absolute coordinates of block1 given the canvas block2’s absolute coordinates block.crop image(image) Obtain the image segments in the block region",
     "type": "Table"
   },
   {

test_unstructured_ingest/expected-structured-output/s3/2023-Jan-economic-outlook.pdf.json

@@ -1197,7 +1197,7 @@
     "type": "Title"
   },
   {
-    "element_id": "429d7ccdab398bfb2107fa00f9054272",
+    "element_id": "8174b87b76dfe8e8ddb31ab83abc6c33",
     "metadata": {
       "data_source": {
         "date_modified": "2023-02-14T07:31:28",
@@ -1214,7 +1214,7 @@
       ],
       "page_number": 7
     },
-    "text": "WEO Projections 1/ Estimate 2022 Projections 2023 Estimate 2022 Projections 2023 2021 2024 2023 2024 2024 6.2 3.4 2.9 3.1 0.2 –0.1 1.9 3.2 3.0 Advanced Economies United States Euro Area 5.4 5.9 5.3 2.6 6.8 6.7 5.5 2.1 7.6 5.0 5.3 2.7 2.0 3.5 1.9 2.6 3.9 5.2 1.4 4.1 3.5 2.8 1.2 1.4 0.7 0.1 0.7 0.6 1.1 1.8 –0.6 1.5 2.0 1.4 1.0 1.6 1.4 1.6 0.9 2.4 0.9 0.9 1.5 2.4 0.1 0.4 0.2 0.4 0.0 0.8 –0.1 0.2 –0.9 0.0 –0.3 –0.2 –0.2 –0.2 –0.1 0.0 –0.4 –0.2 –0.4 0.3 –0.1 –0.2 1.3 0.7 1.9 1.4 0.5 2.1 2.1 1.7 0.4 2.3 1.4 1.1 1.0 0.5 0.0 0.9 0.1 1.3 1.0 –0.5 1.2 2.1 1.6 1.3 2.1 2.3 1.8 1.0 2.8 1.0 1.8 1.9 2.2 Germany France Italy Spain Japan United Kingdom Canada Other Advanced Economies 3/ Emerging Market and Developing Economies Emerging and Developing Asia 6.7 7.4 8.4 8.7 6.9 4.7 7.0 5.0 4.7 4.5 3.2 4.7 3.6 4.9 3.9 4.3 3.0 6.8 0.7 –2.2 3.9 3.1 3.1 5.3 8.7 3.8 3.0 2.6 4.0 5.3 5.2 6.1 1.5 0.3 1.8 1.2 1.7 3.2 2.6 3.8 3.2 1.2 4.2 5.2 4.5 6.8 2.6 2.1 2.1 1.5 1.6 3.7 3.4 4.1 2.9 1.3 0.3 0.4 0.8 0.0 0.9 2.6 0.1 0.2 0.5 –0.4 –1.1 0.1 0.2 0.1 –0.1 0.0 0.0 0.0 0.1 0.6 –0.3 –0.4 –0.2 0.2 0.5 0.0 0.0 0.0 2.5 3.4 2.9 4.3 –2.0 –4.1 2.6 2.8 3.7 . . . 4.6 . . . 2.6 3.0 5.0 6.2 5.9 7.0 3.5 1.0 1.9 0.8 1.1 . . . 2.7 . . . 3.1 0.5 4.1 4.9 4.1 7.1 2.8 2.0 1.9 2.2 1.9 . . . 3.5 . . . 2.9 1.8 China India 4/ Emerging and Developing Europe Russia Latin America and the Caribbean Brazil Mexico Middle East and Central Asia Saudi Arabia Sub-Saharan Africa Nigeria South Africa Memorandum World Growth Based on Market Exchange Rates European Union ASEAN-5 5/ Middle East and North Africa Emerging Market and Middle-Income Economies Low-Income Developing Countries 6.0 5.5 3.8 4.1 7.0 4.1 3.1 3.7 5.2 5.4 3.8 4.9 2.4 0.7 4.3 3.2 4.0 4.9 2.5 1.8 4.7 3.5 4.1 5.6 0.3 0.0 –0.2 –0.4 0.4 0.0 –0.1 –0.3 –0.2 0.2 0.0 0.1 1.7 1.8 3.7 . . . 2.5 . . . 2.5 1.2 5.7 . . . 5.0 . . . 2.5 2.0 4.0 . . . 4.1 . . . 10.4 9.4 12.1 5.4 6.6 3.4 2.4 2.3 2.6 3.4 2.7 4.6 –0.1 0.0 –0.3 –0.3 –0.4 0.0 . . . . . . . . . . . . . . . . . . . . . . . . . . . 65.8 26.4 39.8 7.0 –16.2 –6.3 –7.1 –0.4 –3.3 –0.1 –0.9 0.3 11.2 –2.0 –9.8 1.4 –5.9 –0.2",
+    "text": "2021 Estimate 2022 Projections 2023 2024 WEO Projections 1/ 2023 2024 Estimate 2022 Projections 2023 2024 6.2 3.4 2.9 3.1 0.2 –0.1 1.9 3.2 3.0 Advanced Economies United States Euro Area Germany France Italy Spain Japan United Kingdom Canada Other Advanced Economies 3/ 5.4 5.9 5.3 2.6 6.8 6.7 5.5 2.1 7.6 5.0 5.3 2.7 2.0 3.5 1.9 2.6 3.9 5.2 1.4 4.1 3.5 2.8 1.2 1.4 0.7 0.1 0.7 0.6 1.1 1.8 –0.6 1.5 2.0 1.4 1.0 1.6 1.4 1.6 0.9 2.4 0.9 0.9 1.5 2.4 0.1 0.4 0.2 0.4 0.0 0.8 –0.1 0.2 –0.9 0.0 –0.3 –0.2 –0.2 –0.2 –0.1 0.0 –0.4 –0.2 –0.4 0.3 –0.1 –0.2 1.3 0.7 1.9 1.4 0.5 2.1 2.1 1.7 0.4 2.3 1.4 1.1 1.0 0.5 0.0 0.9 0.1 1.3 1.0 –0.5 1.2 2.1 1.6 1.3 2.1 2.3 1.8 1.0 2.8 1.0 1.8 1.9 2.2 Emerging Market and Developing Economies Emerging and Developing Asia China India 4/ Emerging and Developing Europe Russia Latin America and the Caribbean Brazil Mexico Middle East and Central Asia Saudi Arabia Sub-Saharan Africa Nigeria South Africa 6.7 7.4 8.4 8.7 6.9 4.7 7.0 5.0 4.7 4.5 3.2 4.7 3.6 4.9 3.9 4.3 3.0 6.8 0.7 –2.2 3.9 3.1 3.1 5.3 8.7 3.8 3.0 2.6 4.0 5.3 5.2 6.1 1.5 0.3 1.8 1.2 1.7 3.2 2.6 3.8 3.2 1.2 4.2 5.2 4.5 6.8 2.6 2.1 2.1 1.5 1.6 3.7 3.4 4.1 2.9 1.3 0.3 0.4 0.8 0.0 0.9 2.6 0.1 0.2 0.5 –0.4 –1.1 0.1 0.2 0.1 –0.1 0.0 0.0 0.0 0.1 0.6 –0.3 –0.4 –0.2 0.2 0.5 0.0 0.0 0.0 2.5 3.4 2.9 4.3 –2.0 –4.1 2.6 2.8 3.7 . . . 4.6 . . . 2.6 3.0 5.0 6.2 5.9 7.0 3.5 1.0 1.9 0.8 1.1 . . . 2.7 . . . 3.1 0.5 4.1 4.9 4.1 7.1 2.8 2.0 1.9 2.2 1.9 . . . 3.5 . . . 2.9 1.8 Memorandum World Growth Based on Market Exchange Rates European Union ASEAN-5 5/ Middle East and North Africa Emerging Market and Middle-Income Economies Low-Income Developing Countries 6.0 5.5 3.8 4.1 7.0 4.1 3.1 3.7 5.2 5.4 3.8 4.9 2.4 0.7 4.3 3.2 4.0 4.9 2.5 1.8 4.7 3.5 4.1 5.6 0.3 0.0 –0.2 –0.4 0.4 0.0 –0.1 –0.3 –0.2 0.2 0.0 0.1 1.7 1.8 3.7 . . . 2.5 . . . 2.5 1.2 5.7 . . . 5.0 . . . 2.5 2.0 4.0 . . . 4.1 . . . 10.4 9.4 12.1 5.4 6.6 3.4 2.4 2.3 2.6 3.4 2.7 4.6 –0.1 0.0 –0.3 –0.3 –0.4 0.0 . . . . . . . . . . . . . . . . . . . . . . . . . . . 65.8 26.4 39.8 7.0 –16.2 –6.3 –7.1 –0.4 –3.3 –0.1 –0.9 0.3 11.2 –2.0 –9.8 1.4 –5.9 –0.2",
     "type": "Table"
   },
   {
@@ -2310,7 +2310,7 @@
     "type": "NarrativeText"
   },
   {
-    "element_id": "5ad3e97ac0a2d759e059893765b81954",
+    "element_id": "d750b11efc2f858c7deadb09e3929e1c",
     "metadata": {
       "data_source": {
         "date_modified": "2023-02-14T07:31:28",
@@ -2327,7 +2327,7 @@
       ],
       "page_number": 11
     },
-    "text": "United States Euro area China Other AEs Other EMs  7  October 2022  GFSR  6  5  4  3  2  1  0  –1  –2  –3  2006     08 08  10   10    12   12    14      16   14    18   18     20     22 22  06  16  20 ",
+    "text": "7  6  5  4  United States Euro area China Other AEs Other EMs  October 2022  GFSR  3  2  1  0  –1  –2  –3  2006     08 08  06  10   10    12   12    14      16   14  16    18   18     20     22 22  20 ",
     "type": "Image"
   },
   {
@@ -2394,7 +2394,7 @@
     "type": "Title"
   },
   {
-    "element_id": "5728dbbab19d146278a6a3387e8e40d5",
+    "element_id": "6215d8f373972db90d05458d63af9efe",
     "metadata": {
       "data_source": {
         "date_modified": "2023-02-14T07:31:28",
@@ -2411,7 +2411,7 @@
       ],
       "page_number": 11
     },
-    "text": "Latest  October 2022 GFSR  5  6  2. Euro area  1. United States  5  4  4  3  3  2  2  1  1  Oct. 22  Apr. 23  Oct. 23  Dec. 24  Dec. 26  Oct. 22  Apr. 23  Oct. 23  Dec. 24  Dec. 26 ",
+    "text": "Latest  October 2022 GFSR  6  1. United States  2. Euro area  5  4  3  2  5  4  3  2  1  1  Oct. 22  Apr. 23  Oct. 23  Dec. 24  Dec. 26  Oct. 22  Apr. 23  Oct. 23  Dec. 24  Dec. 26 ",
     "type": "Image"
   },
   {