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Análisis sintáctico de estructuras JSON generadas por la extracción de texto
Análisis sintáctico de estructuras JSON generadas por la extracción de texto
Última actualización: 20 mar 2025
El texto que se extrae de un documento o archivo de imagen mediante la API de extracción de texto se escribe en un archivo JSON que contiene detalles sobre diversos elementos textuales y visuales del documento. Puede seguir procesando el JSON generado para extraer la información que desee.
Los siguientes objetos JSON se devuelven siempre que se extrae texto utilizando la API de extracción de texto. Las estructuras dentro de estos objetos raíz son opcionales, lo que significa que pueden o no ser devueltas en la salida.
La clave ' styles ' es otro objeto de nivel raíz que se devuelve a menudo, pero es opcional. El objeto ' styles ' contiene una lista de diccionarios, cada uno de los cuales contiene detalles sobre la fuente, como el tamaño y el estilo de letra, utilizados en el documento.
Puede escribir código para extraer texto de las estructuras que le interesen. Para más información, consulte las secciones siguientes:
- Cómo se representan los párrafos
- Cómo se representa el texto de las imágenes
- Cómo se representan las listas
- Cómo se representan las tablas
Para más detalles sobre el esquema JSON, vaya a Esquema JSON de extracción de texto.
Metadatos
La clave " metadata " es un diccionario que contiene los siguientes detalles sobre los metadatos del documento procesado:
num_pages: Número de páginas del documento.title: Título del documento.keywords: Palabras clave relacionadas con el documento.author: Autor del documento.publication_date: Fecha de creación o publicación del documento.subject: Asunto del documento.charset: Estándar del conjunto de caracteres que se utilizan en el documento.
La siguiente salida JSON es un ejemplo de la estructura de objetos de metadatos para un archivo PDF.
"metadata":{
"num_pages":28,
"title":"Put AI to work for HR and talent transformation for the retail industry",
"keywords":"",
"author":"IBM",
"publication_date":"",
"subject":"Apply AI capabilities to drive your HR and talent transformation and generate better business outcomes in the retail industry.",
"charset":"UTF-8"
}
Estructuras
Hay dos claves que hacen referencia a las estructuras de datos del documento analizado:
top_level_structures: Una lista de los ID de las estructuras de datos de nivel superior.all_structures: Una lista de todos los tipos de estructuras de datos.
La clave " all_structures " contiene una lista de todos los tipos posibles de las estructuras de datos del documento analizado. Estas estructuras son opcionales, por lo que pueden o no estar incluidas en el resultado. Algunas de las estructuras de datos que puede contener un documento analizado son las siguientes:
sections: Lista de todas las secciones del documento.section_titles: Lista de títulos de las secciones detectadas.lists: Una colección de todas las listas del documento.list_items: Una colección de los elementos de lista presentes en los objetos de lista detectados.list_identifiers: Una colección de identificadores de lista de los objetos de lista detectados.tables: Lista de todas las tablas del documento.table_rows: Una lista de filas de tablas presentes en las tablas detectadas.table_cells: Lista de las celdas de tabla presentes en las filas de tabla detectadas.tokens: Una lista de los tokens de texto plano.subscripts: Lista de instancias de texto de subíndice relacionadas con tokens detectados en el documento.superscripts: Lista de instancias de texto en superíndice relacionadas con los tokens detectados en el documentofootnotes: Lista de las notas a pie de página.paragraphs: Una lista de los párrafos.
Trabajar con el JSON extraído
Puede utilizar una biblioteca de procesadores JSON para extraer el texto de diferentes estructuras en el archivo JSON generado.
El siguiente comando devuelve el número de páginas del PDF, que es un valor que se almacena en un único objeto JSON:
cat output_retail.json | jq '.metadata.num_pages'
Nota: Este comando utiliza jq, que es un procesador JSON de línea de comandos que debe instalarse por separado.
Para algunas estructuras, como tablas y listas, el texto extraído se almacena en varios objetos dentro del JSON generado. Puede utilizar código para recorrer los objetos y extraer el texto que le interese.
Cómo se representan los párrafos
Lo más habitual es que un mismo párrafo esté asociado a varios tokens en secuencia, donde cada token representa una palabra.
En algunos casos, los párrafos están asociados a otras estructuras, como secciones y listas.
La siguiente salida JSON ilustra cómo se relacionan un párrafo y los tokens en la frase, Recopilar, organizar, aumentar datos cuando el texto se extrae de un PDF.
//The section is listed in the top_level_structures array.
"top_level_structures":["PARA_fbdcdd",...,"SECTION_a2ab08",...],
//The section has a list of parapraphs.
{"id":"SECTION_9a3dda","parent_id":"SECTION_a2ab08","children_ids":["PARA_09384c",...
//The paragraph contains a section title.
{"id":"PARA_09384c","parent_id":"SECTION_9a3dda",
"text_alignment":"left","children_ids":["SECTION_TITLE_a5e3c2"],
//Token IDs listed for the section title.
{"id":"SECTION_TITLE_a5e3c2","parent_id":"PARA_09384c",
"text_alignment":"TBD","children_ids":[
"TOKEN_48bbae","TOKEN_cc0b9c","TOKEN_d57d27","TOKEN_a7d6da"
]},
//Consecutive tokens with a shared parent_id contain the text from the sentence of interest.
{"id":"TOKEN_48bbae","parent_id":"SECTION_TITLE_a5e3c2","style_id":"IBM_Plex_Sans_Light_Black_32_0",
"text":"Collect,",
"bbox":{"page_number":8,"x":283.0,"y":775.2945,"width":106.43201,"height":21.44}},
{"id":"TOKEN_cc0b9c","parent_id":"SECTION_TITLE_a5e3c2","style_id":"IBM_Plex_Sans_Light_Black_32_0",
"text":"organize,",
"bbox":{"page_number":8,"x":396.984,"y":775.2945,"width":126.78082,"height":21.44}},
{"id":"TOKEN_d57d27","parent_id":"SECTION_TITLE_a5e3c2","style_id":"IBM_Plex_Sans_Light_Black_32_0",
"text":"grow",
"bbox":{"page_number":8,"x":531.31683,"y":775.2945,"width":69.823975,"height":21.44}},
{"id":"TOKEN_a7d6da","parent_id":"SECTION_TITLE_a5e3c2","style_id":"IBM_Plex_Sans_Light_Black_32_0",
"text":"data",
"bbox":{"page_number":8,"x":608.6928,"y":775.2945,"width":62.880005,"height":21.44}},
Cómo se representa el texto de las imágenes
Cuando envías un archivo PDF con imágenes o un archivo de imagen al método de extracción de texto de la API watsonx.ai, el texto de la imagen se representa mediante ' tokens. Los ' tokens ' suelen estar contenidos por objetos ' paragraph o ' section '.
El siguiente extracto JSON ilustra cómo se representa en la salida JSON un archivo PNG que se envía al método de extracción de texto. Los objetos párrafos que contienen los tokens de texto están disponibles tanto en el objeto raíz ' top_level_structures como en el objeto raíz ' all_structures '.
"top_level_structures":
[
"PARA_bc9320","PARA_8e9e62","PARA_b7f5cc","PARA_c75980","PARA_61a6a5","PARA_c8c2a8","PARA_8b8dd6","PARA_8c7c77","PARA_61aa92","PARA_1e6d2a","PARA_6eaa8d","PARA_cc6df5","PARA_4a9fb2"
],
"all_structures":{"sections":[],"section_titles":[],"lists":[],
"list_items":[],"list_identifiers":[],"tables":[],"table_rows":[],
"table_cells":[],"subscripts":[],"superscripts":[],"footnotes":[],
"paragraphs":
[
{"id":"PARA_bc9320","parent_id":"root","text_alignment":"center",
"children_ids":["TOKEN_132783","TOKEN_f0e333","TOKEN_dd48c3",
"TOKEN_c9b25e","TOKEN_080303","TOKEN_ce1aa0","TOKEN_97bf62"]...
{"id":"PARA_8e9e62","parent_id":"root",...
...
{"id":"PARA_4a9fb2","parent_id":"root",...
]
El texto extraído se especifica en los tokens dentro del párrafo. Los siguientes tokens representan las palabras The AI Ladder® de la imagen como sigue:
"tokens":[
{"id":"TOKEN_132783","parent_id":"PARA_bc9320","style_id":"Arial_Black_10_0",
"text":"The","bbox":{"page_number":1,"x":250.65,"y":109.3,"width":38.880005,"height":21.48999}},
{"id":"TOKEN_f0e333","parent_id":"PARA_bc9320","style_id":"Arial_Black_10_0",
"text":"AI","bbox":{"page_number":1,"x":295.82,"y":114.67,"width":24.109985,"height":16.290009}},
{"id":"TOKEN_dd48c3","parent_id":"PARA_bc9320","style_id":"Arial_Black_10_0",
"text":"Ladder®","bbox":{"page_number":1,"x":325.74,"y":110.24,"width":82.66,"height":22.030006}}
Cómo se representan las listas
La estructura de una lista está representada por tres objetos distintos que forman parte del objeto raíz ' all_structures ':
lists: Conjunto de elementos de lista con formato de lista numerada o con viñetas.list_items: Elemento único de una lista que puede contener tokens con texto, párrafos o listas anidadas.list_identifiers: Contiene un token con un símbolo, como un guión o un número, que identifica el elemento de la lista.
La siguiente salida JSON ilustra cómo se representa el texto - Proporcionar transparencia en la primera viñeta de una lista.
//The lists object contains the list where the listitem is located.
"lists":[{"id":"LIST_ed036e","parent_id":"SECTION_9a3dda","children_ids":[
"LISTITEM_c802c4",...
//The list_item object contains the list item which contains a list ID followed by several tokens.
"list_items":[{"id":"LISTITEM_c802c4","parent_id":"LIST_ed036e","children_ids":[
"LIST_ID_781ee7","TOKEN_1df44f","TOKEN_1bcdbf",...
//The list_identifiers object contains list IDs with tokens.
"list_identifiers":[{"id":"LIST_ID_781ee7","parent_id":"LISTITEM_c802c4",
"children_ids":["TOKEN_4a66cb"]}
//The list ID token includes a token with a hyphen.
{"id":"TOKEN_4a66cb","parent_id":"LIST_ID_781ee7","style_id":"IBM_Plex_Sans_Black_20_0",
"text":"–","bbox":{"page_number":10,"x":994.0,"y":500.36,"width":11.76001,"height":13.639999}}
//The list item tokens include the text *Providing transparency* in them.
{"id":"TOKEN_1df44f","parent_id":"LISTITEM_c802c4","style_id":"IBM_Plex_Sans_Black_20_0",
"text":"Providing","bbox":{"page_number":10,"x":1014.0,"y":500.36,"width":83.55994,"height":13.639999}},
{"id":"TOKEN_1bcdbf","parent_id":"LISTITEM_c802c4","style_id":"IBM_Plex_Sans_Black_20_0",
"text":"transparency","bbox":{"page_number":10,"x":1102.2799,"y":500.36,"width":117.95801,"height":13.639999}}...
El siguiente código Python extrae texto de una lista y reconstruye la lista para ilustrar cómo se puede recorrer en bucle los elementos de la lista para extraer texto de token.
# Import required libraries
import json
import numpy as np
import pandas as pd
# Define helper functions
## Function, which finds entry in collection by key-value pair
def find_by_key(key: str, value, collection: list, unique=True):
find = list(filter(lambda x: x[key] == value, collection))
if unique:
if len(find) > 1:
raise ValueError(f"Found non-unique key-value pair.\n{find}")
return find[0]
else:
return find
## Function, which flattens iterable collection of dicts
def flatten_collection(collection):
result = []
for val in collection.values():
result.extend(val)
return result
# Load the file with the extracted text
with open("/Users/janedoe/Downloads/output_retail.json") as f:
raw_output = json.load(f)
# Get all list-related structures
all_lists = raw_output['all_structures']['lists']
all_list_items = raw_output['all_structures']['list_items']
all_list_identifiers = raw_output['all_structures']['list_identifiers']
# Get all list items from the first list in the file
list_1 = all_lists[0]
list_1_items = []
for list_item_id in list_1['children_ids']:
list_1_items.append(find_by_key('id', list_item_id, all_list_items))
# Reconstruct the list
recon_list = []
flat_col = flatten_collection(raw_output['all_structures'])
for list_item in list_1_items:
val = []
for list_value_id in list_item['children_ids']:
list_value = find_by_key('id', list_value_id, flat_col)
#print(list_value['id'])
if list_value['id'].startswith("LIST_ID"):
for list_id_value_id in list_value['children_ids']:
list_id_value = find_by_key('id', list_id_value_id, flat_col)
if 'text' in list_id_value:
val.append(list_id_value['text'])
elif list_value['id'].startswith("PARA"):
val.append("\n")
for para_value_id in list_value['children_ids']:
para_value = find_by_key('id', para_value_id, flat_col)
if 'text' in para_value:
val.append(para_value['text'])
elif list_value['id'].startswith("TOKEN"):
val.append(list_value['text'])
else:
pass
print(' '.join(val))
Cómo se representan las tablas
La estructura de una tabla está representada por tres objetos distintos que forman parte del objeto raíz ' all_structures ':
tables: Asociado a varias filas de la tabla.table_rows: Cada fila de la tabla está asociada a varias celdas de la tabla.table_cells: Cada celda de la tabla contiene una secuencia de fichas, una secuencia mixta de párrafos y fichas, o una secuencia mixta de listas, párrafos y fichas.
La siguiente salida JSON ilustra cómo se representa el título de la columna de la tabla Flujos de trabajo.
//The all_structures root object contains the table, which has many rows.
"all_structures":{
...
"tables":[{"id":"TABLE_3bfabb","children_ids":[
"ROW_39aa6f",...,"ROW_63472c"]}
//A separate table rows array contains table cells.
"all_structures":{
...
"table_rows":[{"id":"ROW_39aa6f","parent_id":"TABLE_3bfabb","children_ids":[
"CELL_bc1c4b","CELL_3a8cdd","CELL_03b6d3"]}
//One of the table cells is identified as a column header and contains a paragraph.
{"id":"CELL_3a8cdd","parent_id":"ROW_39aa6f","is_row_header":false,
"is_col_header":true,"col_span":1,"row_span":1,"col_start":2,"row_start":1,
"children_ids":["PARA_088d08"]}
//The paragraph has a token.
{"id":"PARA_088d08","parent_id":"CELL_3a8cdd","children_ids":[
"TOKEN_b99851"],"indentation":1}
//The token contains the text *Workflows*.
{"id":"TOKEN_b99851","parent_id":"PARA_088d08","style_id":"IBM_Plex_Sans_SmBld_Black_20_0_bold",
"text":"Workflows","bbox":{"page_number":14,"x":757.0,"y":291.44003,"width":99.15997,"height":13.96}}
El siguiente código Python extrae texto de una tabla y reconstruye la tabla para ilustrar cómo puede recorrer las filas y celdas de la tabla para extraer texto simbólico.
# Import required libraries
import json
import numpy as np
import pandas as pd
# Define helper functions
## Function, which finds entry in collection by key-value pair
def find_by_key(key: str, value, collection: list, unique=True):
find = list(filter(lambda x: x[key] == value, collection))
if unique:
if len(find) > 1:
raise ValueError(f"Found non-unique key-value pair.\n{find}")
return find[0]
else:
return find
## Function, which flattens iterable collection of dicts
def flatten_collection(collection):
result = []
for val in collection.values():
result.extend(val)
return result
# Load the file with the extracted text
with open("/Users/janedoe/Downloads/output_retail.json") as f:
raw_output = json.load(f)
# Get all table-related structures
all_tables = raw_output['all_structures']['tables']
all_table_rows = raw_output['all_structures']['table_rows']
all_table_cells = raw_output['all_structures']['table_cells']
# Get all of the cells from the first table
table_1 = all_tables[0]
table_1_cells = []
for row_id in table_1['children_ids']:
row = find_by_key('id', row_id, all_table_rows)
for cell_id in row['children_ids']:
table_1_cells.append(find_by_key('id', cell_id, all_table_cells))
# Reconstruct the first table
last_col = table_1_cells[-1]['col_start']
last_row = table_1_cells[-1]['row_start']
recon_table = np.empty([last_row, last_col], dtype=object)
flat_col = flatten_collection(raw_output['all_structures'])
for cell in all_table_cells:
cell_col, cell_row = cell['col_start'], cell['row_start']
for cell_value in cell['children_ids']:
value = find_by_key('id', cell_value, flat_col)
entries = []
for cell_entry in value['children_ids']:
entry = find_by_key('id', cell_entry, flat_col)
if 'text' in entry:
entries.append(entry['text'])
cell_content = " ".join(entries)
recon_table[cell_row-1][cell_col-1] = str(cell_content)
pd.DataFrame(data=recon_table[1:,:], columns=recon_table[0,:])
Extracción de texto Esquema JSON
Puedes referirte al esquema JSON cuando escribas código para extraer información del JSON que se genera para tu documento.
Nota:
Cualquier estructura con una descripción que mencione " Not required " podría eliminarse en futuras iteraciones del esquema. Si decide hacer referencia a estructuras opcionales en su código, es posible que tenga que actualizar el código más adelante cuando se realicen cambios posteriores en el esquema.
{ "$defs": {
"AssemblyJsonOutput": {
"type": "object",
"properties": {
"metadata": {
"description": "Metadata about this document.",
"$ref": "#/$defs/Metadata"
},
"styles": {
"description": "Font styles used in this document. Not required.",
"type": "array",
"items": {
"$ref": "#/$defs/Style"
}
},
"top_level_structures": {
"type": "array",
"description": "Array of ids of the top level structures which belong directly under the document",
"items": {
"type": "string"
}
},
"all_structures": {
"type": "object",
"description": "An object containing lists of all structures identified in this document.",
"$ref": "#/$defs/Structures"
}
},
"required": [
"metadata",
"top_level_structures",
"all_structures"
]
},
"Metadata": {
"type": "object",
"additionalProperties": true,
"title": "Metadata",
"properties": {
"num_pages": {
"type": "integer",
"description": "Total number of pages in the document"
},
"title": {
"type": "string",
"description": "Document title as obtained from source document. Not required."
},
"keywords": {
"type": "string",
"description": "Keywords associated with document. Not required."
},
"author": {
"type": "string",
"description": "Author of the document. Not required."
},
"publication_date": {
"type": "string",
"description": "Best effort bases for a publication date (may be the creation date). Not required."
},
"subject": {
"type": "string",
"description": "Subject as obtained from the source document. Not required."
},
"charset": {
"type": "string",
"description": "Character set used for the output"
}
},
"required": []
},
"Style": {
"type": "object",
"title": "Style",
"properties": {
"style_id": {
"type": "string",
"description": "Style Identifier which will be used for reference in other objects"
},
"font_size": {
"type": "string",
"description": "Font size"
},
"font_name": {
"type": "string",
"description": "Font name"
},
"is_bold": {
"type": "string",
"description": "Whether or not the the font is bold"
},
"is_italic": {
"type": "string",
"description": "Whether or not the the font is italic"
}
}
},
"Structures": {
"type": "object",
"description": "An object containing all of the flattened structures identified in the document.
None of the items in this object are required.",
"sections": {
"type": "array",
"items": {
"$ref": "#/$defs/Section"
}
},
"section_titles": {
"type": "array",
"items": {
"$ref": "#/$defs/SectionTitle"
}
},
"lists":{
"type": "array",
"items": {
"$ref": "#/$defs/List"
}
},
"list_items":{
"type": "array",
"items": {
"$ref": "#/$defs/ListItem"
}
},
"list_identifiers":{
"type": "array",
"items": {
"$ref": "#/$defs/ListIdentifier"
}
},
"tables":{
"type": "array",
"items": {
"$ref": "#/$defs/Table"
}
},
"table_rows":{
"type": "array",
"items": {
"$ref": "#/$defs/TableRow"
}
},
"table_cells":{
"type": "array",
"items": {
"$ref": "#/$defs/TableCell"
}
},
"subscripts":{
"type": "array",
"items": {
"$ref": "#/$defs/Subscript"
}
},
"superscripts":{
"type": "array",
"items": {
"$ref": "#/$defs/Superscript"
}
},
"footnotes":{
"type": "array",
"items": {
"$ref": "#/$defs/Footnote"
}
},
"paragraphs":{
"type": "array",
"items": {
"$ref": "#/$defs/Paragraph"
}
},
"tokens":{
"type": "array",
"items": {
"$ref": "#/$defs/Token"
}
}
},
"Section": {
"type": "object",
"title": "Section",
"properties": {
"id": {
"type": "string",
"description": "Unique identifier for the section"
},
"parent_id": {
"type": "string",
"description": "Unique identifier which denotes parent of this structure"
},
"children_ids": {
"type": "array",
"description": "Unique Ids of first level children structures under this structure in correct sequence"
},
"section_number": {
"type": "string",
"description": "Section identifier identified in the document"
},
"section_level": {
"type": "string",
"description": "Nesting level of section identified in the document"
}
}
},
"SectionTitle": {
"type": "object",
"title": "SectionTitle",
"properties": {
"id": {
"type": "string",
"description": "Unique identifier for the section"
},
"parent_id": {
"type": "string",
"description": "Unique identifier which denotes parent of this structure"
},
"children_ids": {
"type": "array",
"description": "Unique Ids of first level children structures under this structure in correct sequence. Not required."
},
"text_alignment": {
"type": "string",
"description": "Text alignment of the section title. Not required."
}
}
},
"List": {
"type": "object",
"title": "List",
"properties": {
"id": {
"type": "string",
"description": "Unique identifier for the list "
},
"parent_id": {
"type": "string",
"description": "Unique identifier which denotes parent of this structure"
},
"children_ids": {
"type": "array",
"description": "Unique Ids of first level children structures under this structure in correct sequence"
}
}
},
"ListItem": {
"type": "object",
"title": "ListItem",
"properties": {
"id": {
"type": "string",
"description": "Unique identifier for the list item"
},
"parent_id": {
"type": "string",
"description": "Unique identifier which denotes parent of this structure"
},
"children_ids": {
"type": "array",
"description": "Unique Ids of first level children structures under this structure in correct sequence. Not required."
}
}
},
"ListIdentifier": {
"type": "object",
"title": "ListIdentifier",
"properties": {
"id": {
"type": "string",
"description": "Unique identifier for the list item"
},
"parent_id": {
"type": "string",
"description": "Unique identifier which denotes parent of this structure"
},
"children_ids": {
"type": "array",
"description": "Unique Ids of first level children structures under this structure in correct sequence"
}
}
},
"Table": {
"type": "object",
"title": "Table",
"properties": {
"id": {
"type": "string",
"description": "Unique identifier for the table"
},
"parent_id": {
"type": "string",
"description": "Unique identifier which denotes parent of this structure"
},
"children_ids": {
"type": "array",
"description": "Unique Ids of first level children structures under this structure in correct sequence, in this case, table rows"
}
}
},
"TableRow": {
"type": "object",
"title": "TableRow",
"properties": {
"id": {
"type": "string",
"description": "Unique identifier for the table row"
},
"parent_id": {
"type": "string",
"description": "Unique identifier which denotes parent of this structure"
},
"children_ids": {
"type": "array",
"description": "Unique Ids of first level children structures under this structure in correct sequence, in this case, table cells"
}
}
},
"TableCell": {
"type": "object",
"title": "TableCell",
"properties": {
"id": {
"type": "string",
"description": "Unique identifier for the table cell"
},
"parent_id": {
"type": "string",
"description": "Unique identifier which denotes parent of this structure"
},
"is_row_header": {
"type": "boolean",
"description": "Whether the cell is part of row header or not"
},
"is_column_header": {
"type": "boolean",
"description": "Whether the cell is part of column header or not"
},
"col_span": {
"type": "integer",
"description": "column span of the cell"
},
"row_span": {
"type": "integer",
"description": "row span of the cell"
},
"col_start": {
"type": "integer",
"description": "column start of the cell within the table"
},
"row_start": {
"type": "integer",
"description": "row start of the cell within the table"
},
"children_ids": {
"type": "array",
"description": "Unique Ids of first level children structures under this structure in correct sequence, in this case, underlying paragraphs. Not required."
}
}
},
"Subscript": {
"type": "object",
"title": "Subscript",
"properties": {
"id": {
"type": "string",
"description": "Unique identifier for the subscript"
},
"parent_id": {
"type": "string",
"description": "Unique identifier which denotes parent of this structure"
},
"children_ids": {
"type": "array",
"description": "Unique Ids of first level children structures under this structure in correct sequence. Not required."
},
"token_id_ref": {
"type": "string",
"description": "Id of the token to which the subscript belongs"
}
}
},
"Superscript": {
"type": "object",
"title": "Superscript",
"properties": {
"id": {
"type": "string",
"description": "Unique identifier for the superscript"
},
"parent_id": {
"type": "string",
"description": "Unique identifier which denotes parent of this structure"
},
"footnote_ref": {
"type": "string",
"description": "Matching footnote id found on the page"
},
"token_id_ref": {
"type": "string",
"description": "Id of the token to which the superscript belongs"
},
"children_ids": {
"type": "array",
"description": "Unique Ids of first level children structures under this structure in correct sequence. Not required."
}
}
},
"Footnote": {
"type": "object",
"title": "Footnote",
"properties": {
"id": {
"type": "string",
"description": "Unique identifier for the footnote"
},
"parent_id": {
"type": "string",
"description": "Unique identifier which denotes parent of this structure"
},
"children_ids": {
"type": "array",
"description": "Unique Ids of first level children structures under this structure in correct sequence. Not required."
}
}
},
"Paragraph": {
"type": "object",
"title": "Paragraph",
"properties": {
"id": {
"type": "string",
"description": "Unique identifier for the paragraph"
},
"parent_id": {
"type": "string",
"description": "Unique identifier which denotes parent of this structure"
},
"children_ids": {
"type": "array",
"description": "Unique Ids of first level children structures under this structure in correct sequence, in this case, tokens. Not required."
},
"text_alignment": {
"type": "string",
"description": "Text alignment of the paragraph. Not required."
},
"indentation": {
"type": "integer",
"description": "Paragraph indentation. Not required."
}
}
},
"Token": {
"type": "object",
"title": "Token",
"properties": {
"id": {
"type": "string",
"description": "Unique identifier for the list identifier"
},
"parent_id": {
"type": "string",
"description": "Unique identifier which denotes parent of this structure"
},
"style_id": {
"type": "string",
"description": "Identifier of the style object associated with this token. Not required."
},
"text": {
"type": "string",
"description": "Actual text of the token"
},
"bbox": {
"type":"object",
"description": "Not required.",
"$ref": "#/$defs/BoundingBox"
}
}
},
"BoundingBox": {
"type": "object",
"title": "BoundingBox",
"properties": {
"page_number": {
"description": "which page this represents",
"type": "integer"
},
"x": {
"description": "X coordinate of the bounding box",
"type": "float"
},
"y": {
"description": "X coordinate of the bounding box",
"type": "float"
},
"width": {
"description": "width of the bounding box",
"type": "float"
},
"height": {
"description": "height of the bounding box",
"type": "float"
}
}
}
},
"$ref": "#/$defs/AssemblyJsonOutput"
}
Tema principal: Extraer texto de documentos
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