{"id":478093,"date":"2023-08-09T09:27:19","date_gmt":"2023-08-09T09:27:19","guid":{"rendered":""},"modified":"2023-09-05T11:16:02","modified_gmt":"2023-09-05T11:16:02","slug":"named-entity-recognition-ner","status":"publish","type":"wiki","link":"https:\/\/oneproxy.pro\/vn\/wiki\/named-entity-recognition-ner\/","title":{"rendered":"Nh\u1eadn d\u1ea1ng th\u1ef1c th\u1ec3 \u0111\u01b0\u1ee3c \u0111\u1eb7t t\u00ean (NER)"},"content":{"rendered":"<p>Th\u00f4ng tin t\u00f3m t\u1eaft v\u1ec1 Nh\u1eadn d\u1ea1ng th\u1ef1c th\u1ec3 \u0111\u01b0\u1ee3c \u0111\u1eb7t t\u00ean (NER): Nh\u1eadn d\u1ea1ng th\u1ef1c th\u1ec3 \u0111\u01b0\u1ee3c \u0111\u1eb7t t\u00ean (NER) l\u00e0 m\u1ed9t tr\u01b0\u1eddng con c\u1ee7a X\u1eed l\u00fd ng\u00f4n ng\u1eef t\u1ef1 nhi\u00ean (NLP) t\u1eadp trung v\u00e0o vi\u1ec7c x\u00e1c \u0111\u1ecbnh v\u00e0 ph\u00e2n lo\u1ea1i c\u00e1c th\u1ef1c th\u1ec3 \u0111\u01b0\u1ee3c \u0111\u1eb7t t\u00ean trong v\u0103n b\u1ea3n. C\u00e1c th\u1ef1c th\u1ec3 \u0111\u01b0\u1ee3c \u0111\u1eb7t t\u00ean c\u00f3 th\u1ec3 l\u00e0 ng\u01b0\u1eddi, t\u1ed5 ch\u1ee9c, \u0111\u1ecba \u0111i\u1ec3m, bi\u1ec3u th\u1ee9c v\u1ec1 th\u1eddi gian, s\u1ed1 l\u01b0\u1ee3ng, gi\u00e1 tr\u1ecb ti\u1ec1n t\u1ec7, t\u1ef7 l\u1ec7 ph\u1ea7n tr\u0103m, v.v.<\/p>\n<h2>L\u1ecbch s\u1eed v\u1ec1 ngu\u1ed3n g\u1ed1c c\u1ee7a vi\u1ec7c nh\u1eadn d\u1ea1ng th\u1ef1c th\u1ec3 \u0111\u01b0\u1ee3c \u0111\u1eb7t t\u00ean (NER) v\u00e0 s\u1ef1 \u0111\u1ec1 c\u1eadp \u0111\u1ea7u ti\u00ean v\u1ec1 n\u00f3<\/h2>\n<p>Nh\u1eadn d\u1ea1ng th\u1ef1c th\u1ec3 \u0111\u01b0\u1ee3c \u0111\u1eb7t t\u00ean b\u1eaft \u0111\u1ea7u h\u00ecnh th\u00e0nh v\u00e0o \u0111\u1ea7u nh\u1eefng n\u0103m 1990. M\u1ed9t trong nh\u1eefng tr\u01b0\u1eddng h\u1ee3p \u0111\u1ea7u ti\u00ean c\u1ee7a NER l\u00e0 t\u1ea1i H\u1ed9i ngh\u1ecb hi\u1ec3u bi\u1ebft th\u00f4ng \u0111i\u1ec7p l\u1ea7n th\u1ee9 s\u00e1u (MUC-6) n\u0103m 1995. T\u1eeb th\u1eddi \u0111i\u1ec3m \u0111\u00f3, nghi\u00ean c\u1ee9u trong l\u0129nh v\u1ef1c n\u00e0y b\u1eaft \u0111\u1ea7u ph\u00e1t tri\u1ec3n, do nhu c\u1ea7u cho ph\u00e9p m\u00e1y t\u00ednh hi\u1ec3u v\u00e0 di\u1ec5n gi\u1ea3i ng\u00f4n ng\u1eef con ng\u01b0\u1eddi hi\u1ec7u qu\u1ea3 h\u01a1n.<\/p>\n<h2>Th\u00f4ng tin chi ti\u1ebft v\u1ec1 Nh\u1eadn d\u1ea1ng th\u1ef1c th\u1ec3 \u0111\u01b0\u1ee3c \u0111\u1eb7t t\u00ean (NER): M\u1edf r\u1ed9ng ch\u1ee7 \u0111\u1ec1<\/h2>\n<p>Nh\u1eadn d\u1ea1ng th\u1ef1c th\u1ec3 \u0111\u01b0\u1ee3c \u0111\u1eb7t t\u00ean (NER) ph\u1ee5c v\u1ee5 nhi\u1ec1u ch\u1ee9c n\u0103ng kh\u00e1c nhau trong vi\u1ec7c x\u1eed l\u00fd ng\u00f4n ng\u1eef t\u1ef1 nhi\u00ean. C\u00e1c \u1ee9ng d\u1ee5ng c\u1ee7a n\u00f3 m\u1edf r\u1ed9ng tr\u00ean nhi\u1ec1u l\u0129nh v\u1ef1c nh\u01b0 truy xu\u1ea5t th\u00f4ng tin, d\u1ecbch m\u00e1y v\u00e0 khai th\u00e1c d\u1eef li\u1ec7u. NER bao g\u1ed3m hai ph\u1ea7n ch\u00ednh:<\/p>\n<ol>\n<li><strong>Nh\u1eadn d\u1ea1ng th\u1ef1c th\u1ec3<\/strong>: \u0110\u1ecbnh v\u1ecb v\u00e0 ph\u00e2n lo\u1ea1i c\u00e1c nguy\u00ean t\u1ed1 nguy\u00ean t\u1eed trong v\u0103n b\u1ea3n th\u00e0nh c\u00e1c danh m\u1ee5c \u0111\u01b0\u1ee3c x\u00e1c \u0111\u1ecbnh tr\u01b0\u1edbc nh\u01b0 t\u00ean ng\u01b0\u1eddi, t\u1ed5 ch\u1ee9c, \u0111\u1ecba \u0111i\u1ec3m, v.v.<\/li>\n<li><strong>Ph\u00e2n lo\u1ea1i th\u1ef1c th\u1ec3<\/strong>: Ph\u00e2n lo\u1ea1i c\u00e1c th\u1ef1c th\u1ec3 \u0111\u01b0\u1ee3c x\u00e1c \u0111\u1ecbnh th\u00e0nh c\u00e1c l\u1edbp \u0111\u01b0\u1ee3c x\u00e1c \u0111\u1ecbnh tr\u01b0\u1edbc kh\u00e1c nhau.<\/li>\n<\/ol>\n<p>NER c\u00f3 th\u1ec3 \u0111\u01b0\u1ee3c ti\u1ebfp c\u1eadn th\u00f4ng qua c\u00e1c h\u1ec7 th\u1ed1ng d\u1ef1a tr\u00ean quy t\u1eafc, h\u1ecdc c\u00f3 gi\u00e1m s\u00e1t, h\u1ecdc b\u00e1n gi\u00e1m s\u00e1t v\u00e0 h\u1ecdc kh\u00f4ng gi\u00e1m s\u00e1t.<\/p>\n<h2>C\u1ea5u tr\u00fac b\u00ean trong c\u1ee7a nh\u1eadn d\u1ea1ng th\u1ef1c th\u1ec3 \u0111\u01b0\u1ee3c \u0111\u1eb7t t\u00ean (NER): C\u00e1ch th\u1ee9c ho\u1ea1t \u0111\u1ed9ng c\u1ee7a nh\u1eadn d\u1ea1ng th\u1ef1c th\u1ec3 \u0111\u01b0\u1ee3c \u0111\u1eb7t t\u00ean (NER)<\/h2>\n<p>C\u1ea5u tr\u00fac b\u00ean trong c\u1ee7a NER bao g\u1ed3m m\u1ed9t s\u1ed1 giai \u0111o\u1ea1n:<\/p>\n<ol>\n<li><strong>M\u00e3 th\u00f4ng b\u00e1o<\/strong>: Chia nh\u1ecf v\u0103n b\u1ea3n th\u00e0nh c\u00e1c t\u1eeb ho\u1eb7c m\u00e3 th\u00f4ng b\u00e1o ri\u00eang l\u1ebb.<\/li>\n<li><strong>G\u1eafn th\u1ebb m\u1ed9t ph\u1ea7n c\u1ee7a b\u00e0i ph\u00e1t bi\u1ec3u<\/strong>: X\u00e1c \u0111\u1ecbnh c\u00e1c lo\u1ea1i ng\u1eef ph\u00e1p c\u1ee7a c\u00e1c m\u00e3 th\u00f4ng b\u00e1o.<\/li>\n<li><strong>Ph\u00e2n t\u00edch c\u00fa ph\u00e1p<\/strong>: Ph\u00e2n t\u00edch c\u1ea5u tr\u00fac ng\u1eef ph\u00e1p c\u1ee7a c\u00e2u.<\/li>\n<li><strong>Nh\u1eadn d\u1ea1ng v\u00e0 ph\u00e2n lo\u1ea1i th\u1ef1c th\u1ec3<\/strong>: X\u00e1c \u0111\u1ecbnh c\u00e1c th\u1ef1c th\u1ec3 v\u00e0 ph\u00e2n lo\u1ea1i ch\u00fang th\u00e0nh c\u00e1c danh m\u1ee5c \u0111\u01b0\u1ee3c x\u00e1c \u0111\u1ecbnh tr\u01b0\u1edbc.<\/li>\n<\/ol>\n<h2>Ph\u00e2n t\u00edch c\u00e1c t\u00ednh n\u0103ng ch\u00ednh c\u1ee7a nh\u1eadn d\u1ea1ng th\u1ef1c th\u1ec3 \u0111\u01b0\u1ee3c \u0111\u1eb7t t\u00ean (NER)<\/h2>\n<p>C\u00e1c t\u00ednh n\u0103ng ch\u00ednh c\u1ee7a NER bao g\u1ed3m:<\/p>\n<ol>\n<li><strong>S\u1ef1 ch\u00ednh x\u00e1c<\/strong>: Kh\u1ea3 n\u0103ng x\u00e1c \u0111\u1ecbnh v\u00e0 ph\u00e2n lo\u1ea1i ch\u00ednh x\u00e1c c\u00e1c th\u1ef1c th\u1ec3.<\/li>\n<li><strong>T\u1ed1c \u0111\u1ed9<\/strong>: Th\u1eddi gian x\u1eed l\u00fd v\u0103n b\u1ea3n.<\/li>\n<li><strong>Kh\u1ea3 n\u0103ng m\u1edf r\u1ed9ng<\/strong>: Kh\u1ea3 n\u0103ng x\u1eed l\u00fd c\u00e1c t\u1eadp d\u1eef li\u1ec7u l\u1edbn.<\/li>\n<li><strong>\u0110\u1ed9c l\u1eadp ng\u00f4n ng\u1eef<\/strong>: Kh\u1ea3 n\u0103ng \u0111\u01b0\u1ee3c s\u1eed d\u1ee5ng tr\u00ean c\u00e1c ng\u00f4n ng\u1eef kh\u00e1c nhau.<\/li>\n<li><strong>Kh\u1ea3 n\u0103ng th\u00edch \u1ee9ng<\/strong>: C\u00f3 th\u1ec3 \u0111\u01b0\u1ee3c t\u00f9y ch\u1ec9nh cho c\u00e1c l\u0129nh v\u1ef1c ho\u1eb7c ng\u00e0nh c\u1ee5 th\u1ec3.<\/li>\n<\/ol>\n<h2>C\u00e1c lo\u1ea1i nh\u1eadn d\u1ea1ng th\u1ef1c th\u1ec3 \u0111\u01b0\u1ee3c \u0111\u1eb7t t\u00ean (NER): S\u1eed d\u1ee5ng b\u1ea3ng v\u00e0 danh s\u00e1ch<\/h2>\n<p>C\u00e1c lo\u1ea1i NER c\u00f3 th\u1ec3 \u0111\u01b0\u1ee3c ph\u00e2n lo\u1ea1i th\u00e0nh:<\/p>\n<table>\n<thead>\n<tr>\n<th>Ki\u1ec3u<\/th>\n<th>S\u1ef1 mi\u00eau t\u1ea3<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>NER d\u1ef1a tr\u00ean quy t\u1eafc<\/td>\n<td>S\u1eed d\u1ee5ng c\u00e1c quy t\u1eafc ng\u1eef ph\u00e1p \u0111\u01b0\u1ee3c x\u00e1c \u0111\u1ecbnh tr\u01b0\u1edbc<\/td>\n<\/tr>\n<tr>\n<td>NER \u0111\u01b0\u1ee3c gi\u00e1m s\u00e1t<\/td>\n<td>S\u1eed d\u1ee5ng d\u1eef li\u1ec7u \u0111\u01b0\u1ee3c d\u00e1n nh\u00e3n cho c\u00e1c m\u00f4 h\u00ecnh \u0111\u00e0o t\u1ea1o<\/td>\n<\/tr>\n<tr>\n<td>NER b\u00e1n gi\u00e1m s\u00e1t<\/td>\n<td>K\u1ebft h\u1ee3p d\u1eef li\u1ec7u \u0111\u01b0\u1ee3c d\u00e1n nh\u00e3n v\u00e0 kh\u00f4ng \u0111\u01b0\u1ee3c g\u1eafn nh\u00e3n<\/td>\n<\/tr>\n<tr>\n<td>NER kh\u00f4ng \u0111\u01b0\u1ee3c gi\u00e1m s\u00e1t<\/td>\n<td>Kh\u00f4ng y\u00eau c\u1ea7u d\u1eef li\u1ec7u \u0111\u01b0\u1ee3c d\u00e1n nh\u00e3n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h2>C\u00e1c c\u00e1ch s\u1eed d\u1ee5ng Nh\u1eadn d\u1ea1ng th\u1ef1c th\u1ec3 \u0111\u01b0\u1ee3c \u0111\u1eb7t t\u00ean (NER), c\u00e1c v\u1ea5n \u0111\u1ec1 v\u00e0 gi\u1ea3i ph\u00e1p li\u00ean quan \u0111\u1ebfn vi\u1ec7c s\u1eed d\u1ee5ng<\/h2>\n<p>C\u00e1c c\u00e1ch s\u1eed d\u1ee5ng NER bao g\u1ed3m c\u00f4ng c\u1ee5 t\u00ecm ki\u1ebfm, h\u1ed7 tr\u1ee3 kh\u00e1ch h\u00e0ng, ch\u0103m s\u00f3c s\u1ee9c kh\u1ecfe, v.v. M\u1ed9t s\u1ed1 v\u1ea5n \u0111\u1ec1 v\u00e0 gi\u1ea3i ph\u00e1p c\u1ee7a h\u1ecd l\u00e0:<\/p>\n<ul>\n<li><strong>V\u1ea5n \u0111\u1ec1<\/strong>: Thi\u1ebfu d\u1eef li\u1ec7u \u0111\u01b0\u1ee3c d\u00e1n nh\u00e3n.<br \/>\n<strong>Gi\u1ea3i ph\u00e1p<\/strong>: S\u1eed d\u1ee5ng ph\u01b0\u01a1ng ph\u00e1p h\u1ecdc b\u00e1n gi\u00e1m s\u00e1t ho\u1eb7c kh\u00f4ng gi\u00e1m s\u00e1t.<\/li>\n<li><strong>V\u1ea5n \u0111\u1ec1<\/strong>: C\u00e1c r\u00e0ng bu\u1ed9c v\u1ec1 ng\u00f4n ng\u1eef c\u1ee5 th\u1ec3.<br \/>\n<strong>Gi\u1ea3i ph\u00e1p<\/strong>: \u0110i\u1ec1u ch\u1ec9nh m\u00f4 h\u00ecnh theo ng\u00f4n ng\u1eef ho\u1eb7c mi\u1ec1n c\u1ee5 th\u1ec3.<\/li>\n<\/ul>\n<h2>C\u00e1c \u0111\u1eb7c \u0111i\u1ec3m ch\u00ednh v\u00e0 nh\u1eefng so s\u00e1nh kh\u00e1c v\u1edbi c\u00e1c thu\u1eadt ng\u1eef t\u01b0\u01a1ng t\u1ef1<\/h2>\n<table>\n<thead>\n<tr>\n<th>T\u00ednh n\u0103ng<\/th>\n<th>NER<\/th>\n<th>C\u00e1c nhi\u1ec7m v\u1ee5 NLP kh\u00e1c<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>T\u1eadp trung<\/td>\n<td>Th\u1ef1c th\u1ec3 \u0111\u01b0\u1ee3c \u0111\u1eb7t t\u00ean<\/td>\n<td>V\u0103n b\u1ea3n chung<\/td>\n<\/tr>\n<tr>\n<td>\u0110\u1ed9 ph\u1ee9c t\u1ea1p<\/td>\n<td>Trung b\u00ecnh \u0111\u1ebfn cao<\/td>\n<td>Kh\u00e1c nhau<\/td>\n<\/tr>\n<tr>\n<td>\u1ee8ng d\u1ee5ng<\/td>\n<td>C\u1ee5 th\u1ec3<\/td>\n<td>R\u1ed9ng l\u1edbn<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h2>Quan \u0111i\u1ec3m v\u00e0 c\u00f4ng ngh\u1ec7 c\u1ee7a t\u01b0\u01a1ng lai li\u00ean quan \u0111\u1ebfn nh\u1eadn d\u1ea1ng th\u1ef1c th\u1ec3 \u0111\u01b0\u1ee3c \u0111\u1eb7t t\u00ean (NER)<\/h2>\n<p>Tri\u1ec3n v\u1ecdng trong t\u01b0\u01a1ng lai bao g\u1ed3m vi\u1ec7c t\u00edch h\u1ee3p NER v\u1edbi h\u1ecdc s\u00e2u, t\u0103ng kh\u1ea3 n\u0103ng th\u00edch \u1ee9ng v\u1edbi nhi\u1ec1u ng\u00f4n ng\u1eef kh\u00e1c nhau v\u00e0 kh\u1ea3 n\u0103ng x\u1eed l\u00fd th\u1eddi gian th\u1ef1c.<\/p>\n<h2>C\u00e1ch s\u1eed d\u1ee5ng ho\u1eb7c li\u00ean k\u1ebft m\u00e1y ch\u1ee7 proxy v\u1edbi nh\u1eadn d\u1ea1ng th\u1ef1c th\u1ec3 \u0111\u01b0\u1ee3c \u0111\u1eb7t t\u00ean (NER)<\/h2>\n<p>C\u00e1c m\u00e1y ch\u1ee7 proxy gi\u1ed1ng nh\u01b0 m\u00e1y ch\u1ee7 do OneProxy cung c\u1ea5p c\u00f3 th\u1ec3 \u0111\u01b0\u1ee3c s\u1eed d\u1ee5ng \u0111\u1ec3 thu th\u1eadp d\u1eef li\u1ec7u cho NER. B\u1eb1ng c\u00e1ch \u1ea9n danh c\u00e1c y\u00eau c\u1ea7u, ch\u00fang cho ph\u00e9p thu th\u1eadp d\u1eef li\u1ec7u v\u0103n b\u1ea3n m\u1ed9t c\u00e1ch hi\u1ec7u qu\u1ea3 v\u00e0 c\u00f3 \u0111\u1ea1o \u0111\u1ee9c \u0111\u1ec3 \u0111\u00e0o t\u1ea1o v\u00e0 tri\u1ec3n khai c\u00e1c m\u00f4 h\u00ecnh NER.<\/p>\n<h2>Li\u00ean k\u1ebft li\u00ean quan<\/h2>\n<ul>\n<li><a href=\"https:\/\/nlp.stanford.edu\/software\/CRF-NER.shtml\" target=\"_new\" rel=\"noopener nofollow\">C\u00f4ng c\u1ee5 nh\u1eadn d\u1ea1ng th\u1ef1c th\u1ec3 \u0111\u01b0\u1ee3c \u0111\u1eb7t t\u00ean c\u1ee7a Stanford NLP<\/a><\/li>\n<li><a href=\"https:\/\/www.nltk.org\/book\/ch07.html\" target=\"_new\" rel=\"noopener nofollow\">Nh\u1eadn d\u1ea1ng th\u1ef1c th\u1ec3 \u0111\u01b0\u1ee3c \u0111\u1eb7t t\u00ean NLTK<\/a><\/li>\n<li><a href=\"https:\/\/spacy.io\/usage\/linguistic-features#named-entities\" target=\"_new\" rel=\"noopener nofollow\">Nh\u1eadn d\u1ea1ng th\u1ef1c th\u1ec3 c\u00f3 t\u00ean Spacy<\/a><\/li>\n<li><a href=\"https:\/\/oneproxy.pro\/vn\/\" target=\"_new\" rel=\"noopener\">OneProxy<\/a>: \u0110\u1ec3 s\u1eed d\u1ee5ng m\u00e1y ch\u1ee7 proxy k\u1ebft h\u1ee3p v\u1edbi NER.<\/li>\n<\/ul>","protected":false},"featured_media":468975,"menu_order":0,"template":"","meta":{"_acf_changed":false,"content-type":"","inline_featured_image":false,"footnotes":""},"class_list":["post-478093","wiki","type-wiki","status-publish","has-post-thumbnail","hentry"],"acf":{"faq_title":"Frequently Asked Questions about <mark>Named Entity Recognition (NER): A Comprehensive Overview<\/mark>","faq_items":[{"question":"What is Named Entity Recognition (NER)?","answer":"<p>Named Entity Recognition (NER) is a subfield of Natural Language Processing (NLP) that identifies and classifies named entities in text. These entities can include persons, organizations, locations, expressions of times, quantities, monetary values, percentages, and more.<\/p>"},{"question":"What are the main applications of Named Entity Recognition?","answer":"<p>Named Entity Recognition is used in various domains such as information retrieval, machine translation, data mining, search engines, customer support, and healthcare.<\/p>"},{"question":"How does Named Entity Recognition (NER) work?","answer":"<p>The process of NER involves several stages including tokenization, part-of-speech tagging, parsing, and finally identifying and classifying the entities into predefined categories such as names of persons, organizations, locations, etc.<\/p>"},{"question":"What are the key features of Named Entity Recognition (NER)?","answer":"<p>Key features of NER include accuracy in identifying and classifying entities, speed in processing text, scalability, language independence, and adaptability to specific domains or industries.<\/p>"},{"question":"What types of Named Entity Recognition (NER) exist?","answer":"<p>There are several types of NER, including Rule-Based NER, which utilizes predefined grammatical rules, Supervised NER that uses labeled data for training models, Semi-Supervised NER that combines labeled and unlabeled data, and Unsupervised NER that does not require labeled data.<\/p>"},{"question":"What are some problems with Named Entity Recognition, and how can they be solved?","answer":"<p>Some common problems include a lack of labeled data and language-specific constraints. These can be solved by utilizing semi-supervised or unsupervised learning methods and adapting the model to specific languages or domains.<\/p>"},{"question":"What are the future perspectives and technologies related to Named Entity Recognition (NER)?","answer":"<p>Future perspectives include integration with deep learning, adaptability to various languages, and the development of real-time processing capabilities.<\/p>"},{"question":"How can proxy servers be used with Named Entity Recognition (NER)?","answer":"<p>Proxy servers, such as those provided by OneProxy, can be used to scrape data for NER. They allow for efficient and ethical gathering of text data by anonymizing the requests, facilitating the training and implementation of NER models.<\/p>"},{"question":"Where can I find more information about Named Entity Recognition (NER)?","answer":"<p>You can learn more about NER from resources such as Stanford NLP Named Entity Recognizer, NLTK Named Entity Recognition, Spacy Named Entity Recognition, and OneProxy's website for utilizing proxy servers in conjunction with NER.<\/p>"}]},"_links":{"self":[{"href":"https:\/\/oneproxy.pro\/vn\/wp-json\/wp\/v2\/wiki\/478093","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/oneproxy.pro\/vn\/wp-json\/wp\/v2\/wiki"}],"about":[{"href":"https:\/\/oneproxy.pro\/vn\/wp-json\/wp\/v2\/types\/wiki"}],"version-history":[{"count":0,"href":"https:\/\/oneproxy.pro\/vn\/wp-json\/wp\/v2\/wiki\/478093\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/oneproxy.pro\/vn\/wp-json\/wp\/v2\/media\/468975"}],"wp:attachment":[{"href":"https:\/\/oneproxy.pro\/vn\/wp-json\/wp\/v2\/media?parent=478093"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}