{"id":478916,"date":"2023-08-09T09:40:22","date_gmt":"2023-08-09T09:40:22","guid":{"rendered":""},"modified":"2023-09-05T11:17:48","modified_gmt":"2023-09-05T11:17:48","slug":"semantic-role-labeling","status":"publish","type":"wiki","link":"https:\/\/oneproxy.pro\/vn\/wiki\/semantic-role-labeling\/","title":{"rendered":"Ghi nh\u00e3n vai tr\u00f2 ng\u1eef ngh\u0129a"},"content":{"rendered":"<p>Th\u00f4ng tin t\u00f3m t\u1eaft v\u1ec1 Ghi nh\u00e3n vai tr\u00f2 ng\u1eef ngh\u0129a<\/p>\n<p>Ghi nh\u00e3n vai tr\u00f2 ng\u1eef ngh\u0129a (SRL) l\u00e0 m\u1ed9t quy tr\u00ecnh trong X\u1eed l\u00fd ng\u00f4n ng\u1eef t\u1ef1 nhi\u00ean (NLP) g\u00e1n vai tr\u00f2 ho\u1eb7c nh\u00e3n cho c\u00e1c t\u1eeb ho\u1eb7c c\u1ee5m t\u1eeb trong c\u00e2u, gi\u1ea3i th\u00edch ai \u0111\u00e3 l\u00e0m g\u00ec v\u1edbi ai, khi n\u00e0o, \u1edf \u0111\u00e2u, t\u1ea1i sao, v.v. N\u00f3 gi\u00fap hi\u1ec3u \u0111\u01b0\u1ee3c ngh\u0129a ng\u1eef ngh\u0129a c\u1ee7a c\u00e2u, x\u00e1c \u0111\u1ecbnh m\u1ed1i quan h\u1ec7 gi\u1eefa c\u00e1c y\u1ebfu t\u1ed1 kh\u00e1c nhau v\u00e0 do \u0111\u00f3 cho ph\u00e9p m\u00e1y t\u00ednh hi\u1ec3u ng\u00f4n ng\u1eef con ng\u01b0\u1eddi ch\u00ednh x\u00e1c h\u01a1n.<\/p>\n<h2>L\u1ecbch s\u1eed ngu\u1ed3n g\u1ed1c c\u1ee7a vi\u1ec7c g\u1eafn nh\u00e3n vai tr\u00f2 ng\u1eef ngh\u0129a v\u00e0 s\u1ef1 \u0111\u1ec1 c\u1eadp \u0111\u1ea7u ti\u00ean v\u1ec1 n\u00f3<\/h2>\n<p>Vi\u1ec7c g\u1eafn nh\u00e3n vai tr\u00f2 ng\u1eef ngh\u0129a c\u00f3 ngu\u1ed3n g\u1ed1c t\u1eeb cu\u1ed1i nh\u1eefng n\u0103m 1960 khi c\u00e1c nh\u00e0 nghi\u00ean c\u1ee9u ng\u00f4n ng\u1eef h\u1ecdc b\u1eaft \u0111\u1ea7u ph\u00e1t tri\u1ec3n c\u00e1c m\u00f4 h\u00ecnh ng\u1eef ph\u00e1p th\u1ec3 hi\u1ec7n c\u00e1c vai tr\u00f2 theo ch\u1ee7 \u0111\u1ec1 nh\u01b0 t\u00e1c nh\u00e2n, m\u1ee5c ti\u00eau, ngu\u1ed3n, v.v. N\u00f3 \u0111\u00e3 \u0111\u1ea1t \u0111\u01b0\u1ee3c \u0111\u1ed9ng l\u1ef1c v\u00e0o nh\u1eefng n\u0103m 1990 v\u1edbi s\u1ef1 ph\u00e1t tri\u1ec3n c\u1ee7a ng\u00f4n ng\u1eef h\u1ecdc t\u00ednh to\u00e1n v\u00e0 s\u1ef1 t\u1eadp trung v\u00e0o s\u1ef1 hi\u1ec3u bi\u1ebft c\u1ee7a m\u00e1y v\u1ec1 ng\u00f4n ng\u1eef con ng\u01b0\u1eddi.<\/p>\n<p>D\u1ef1 \u00e1n FrameNet, \u0111\u01b0\u1ee3c kh\u1edfi x\u01b0\u1edbng t\u1ea1i \u0110\u1ea1i h\u1ecdc California, Berkeley v\u00e0o n\u0103m 1997, \u0111\u00e3 \u0111\u00f3ng g\u00f3p \u0111\u00e1ng k\u1ec3 v\u00e0o s\u1ef1 ph\u00e1t tri\u1ec3n c\u1ee7a SRL b\u1eb1ng c\u00e1ch cung c\u1ea5p kho v\u0103n b\u1ea3n c\u00f3 ch\u00fa th\u00edch v\u00e0 c\u01a1 s\u1edf d\u1eef li\u1ec7u t\u1eeb v\u1ef1ng \u0111\u00e3 m\u1edf \u0111\u01b0\u1eddng cho c\u00e1c k\u1ef9 thu\u1eadt SRL hi\u1ec7n \u0111\u1ea1i.<\/p>\n<h2>Th\u00f4ng tin chi ti\u1ebft v\u1ec1 Ghi nh\u00e3n vai tr\u00f2 ng\u1eef ngh\u0129a: M\u1edf r\u1ed9ng ch\u1ee7 \u0111\u1ec1<\/h2>\n<p>Ghi nh\u00e3n vai tr\u00f2 ng\u1eef ngh\u0129a ho\u1ea1t \u0111\u1ed9ng \u1edf \u0111i\u1ec3m giao nhau gi\u1eefa c\u00fa ph\u00e1p v\u00e0 ng\u1eef ngh\u0129a. N\u00f3 x\u00e1c \u0111\u1ecbnh c\u00e1c m\u1ed1i quan h\u1ec7 ng\u1eef ngh\u0129a gi\u1eefa \u0111\u1ed9ng t\u1eeb (v\u1ecb ng\u1eef) v\u00e0 c\u00e1c c\u1ee5m danh t\u1eeb li\u00ean quan (\u0111\u1ed1i s\u1ed1) trong m\u1ed9t c\u00e2u. C\u00e1c vai tr\u00f2 th\u01b0\u1eddng \u0111\u01b0\u1ee3c x\u00e1c \u0111\u1ecbnh tr\u01b0\u1edbc v\u00e0 bao g\u1ed3m c\u00e1c nh\u00e3n nh\u01b0 \u0110\u1ea1i l\u00fd, B\u1ec7nh nh\u00e2n, D\u1ee5ng c\u1ee5, \u0110\u1ecba \u0111i\u1ec3m, Th\u1eddi gian, v.v.<\/p>\n<h3>C\u00e1ch ti\u1ebfp c\u1eadn d\u1ef1a tr\u00ean khung<\/h3>\n<p>M\u1ed9t khung trong SRL \u0111\u1ec1 c\u1eadp \u0111\u1ebfn m\u1ed9t lo\u1ea1i s\u1ef1 ki\u1ec7n, m\u1ed1i quan h\u1ec7 ho\u1eb7c th\u1ef1c th\u1ec3 c\u1ee5 th\u1ec3 v\u00e0 nh\u1eefng ng\u01b0\u1eddi tham gia. M\u1ed9t c\u00e2u \u0111\u01b0\u1ee3c kh\u1edbp v\u1edbi m\u1ed9t khung c\u1ee5 th\u1ec3 v\u00e0 c\u00e1c vai tr\u00f2 \u0111\u01b0\u1ee3c g\u1eafn nh\u00e3n t\u01b0\u01a1ng \u1ee9ng.<\/p>\n<h3>C\u1ea5u tr\u00fac v\u1ecb ng\u1eef-\u0111\u1ed1i s\u1ed1<\/h3>\n<p>SRL x\u00e1c \u0111\u1ecbnh c\u1ea5u tr\u00fac v\u1ecb ng\u1eef-\u0111\u1ed1i s\u1ed1, x\u00e1c \u0111\u1ecbnh m\u1ed1i quan h\u1ec7 gi\u1eefa \u0111\u1ed9ng t\u1eeb v\u00e0 c\u00e1c th\u1ef1c th\u1ec3 li\u00ean quan c\u1ee7a ch\u00fang.<\/p>\n<h2>C\u1ea5u tr\u00fac b\u00ean trong c\u1ee7a vi\u1ec7c g\u1eafn nh\u00e3n vai tr\u00f2 ng\u1eef ngh\u0129a: C\u00e1ch th\u1ee9c ho\u1ea1t \u0111\u1ed9ng<\/h2>\n<p>Qu\u00e1 tr\u00ecnh SRL bao g\u1ed3m m\u1ed9t s\u1ed1 b\u01b0\u1edbc:<\/p>\n<ol>\n<li><strong>Ph\u00e2n t\u00edch c\u00e2u:<\/strong> Chia c\u00e2u th\u00e0nh c\u00e1c m\u00e3 th\u00f4ng b\u00e1o v\u00e0 ph\u00e2n t\u00edch c\u00fa ph\u00e1p th\u00e0nh c\u1ea5u tr\u00fac c\u00e2y c\u00fa ph\u00e1p.<\/li>\n<li><strong>Nh\u1eadn d\u1ea1ng v\u1ecb ng\u1eef:<\/strong> X\u00e1c \u0111\u1ecbnh \u0111\u1ed9ng t\u1eeb ho\u1eb7c v\u1ecb ng\u1eef trong c\u00e2u.<\/li>\n<li><strong>Nh\u1eadn d\u1ea1ng \u0111\u1ed1i s\u1ed1:<\/strong> X\u00e1c \u0111\u1ecbnh v\u1ecb tr\u00ed c\u00e1c c\u1ee5m danh t\u1eeb ho\u1eb7c \u0111\u1ed1i s\u1ed1 li\u00ean quan \u0111\u1ebfn v\u1ecb ng\u1eef.<\/li>\n<li><strong>Ph\u00e2n lo\u1ea1i vai tr\u00f2:<\/strong> G\u00e1n vai tr\u00f2 ng\u1eef ngh\u0129a cho c\u00e1c \u0111\u1ed1i s\u1ed1 \u0111\u01b0\u1ee3c x\u00e1c \u0111\u1ecbnh.<\/li>\n<\/ol>\n<h2>Ph\u00e2n t\u00edch c\u00e1c t\u00ednh n\u0103ng ch\u00ednh c\u1ee7a vi\u1ec7c g\u1eafn nh\u00e3n vai tr\u00f2 ng\u1eef ngh\u0129a<\/h2>\n<p>C\u00e1c t\u00ednh n\u0103ng ch\u00ednh c\u1ee7a SRL bao g\u1ed3m:<\/p>\n<ul>\n<li><strong>\u0110\u1ed9 ch\u00ednh x\u00e1c trong vi\u1ec7c bi\u1ec3u di\u1ec5n \u00fd ngh\u0129a:<\/strong> Gi\u00fap th\u1ec3 hi\u1ec7n ch\u00ednh x\u00e1c \u00fd ngh\u0129a c\u1ee7a c\u00e2u.<\/li>\n<li><strong>Hi\u1ec3u bi\u1ebft v\u1ec1 m\u00e1y n\u00e2ng cao:<\/strong> T\u1ea1o \u0111i\u1ec1u ki\u1ec7n cho s\u1ef1 ph\u00e1t tri\u1ec3n c\u1ee7a c\u00e1c h\u1ec7 th\u1ed1ng hi\u1ec3u v\u00e0 \u0111\u00e1p \u1ee9ng v\u1edbi ng\u00f4n ng\u1eef c\u1ee7a con ng\u01b0\u1eddi.<\/li>\n<li><strong>Kh\u00e1i qu\u00e1t h\u00f3a qua c\u00e1c ng\u00f4n ng\u1eef:<\/strong> C\u00f3 th\u1ec3 \u0111\u01b0\u1ee3c \u00e1p d\u1ee5ng tr\u00ean nhi\u1ec1u ng\u00f4n ng\u1eef kh\u00e1c nhau v\u1edbi s\u1ef1 th\u00edch \u1ee9ng.<\/li>\n<\/ul>\n<h2>C\u00e1c lo\u1ea1i ghi nh\u00e3n vai tr\u00f2 ng\u1eef ngh\u0129a<\/h2>\n<p>B\u1ea3ng sau minh h\u1ecda c\u00e1c lo\u1ea1i SRL kh\u00e1c nhau:<\/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>SRL t\u1eeb \u0111i\u1ec3n<\/td>\n<td>T\u1eadp trung v\u00e0o c\u00e1c v\u1ecb t\u1eeb ri\u00eang l\u1ebb v\u00e0 l\u1eadp lu\u1eadn c\u1ee5 th\u1ec3 c\u1ee7a ch\u00fang.<\/td>\n<\/tr>\n<tr>\n<td>SRL n\u00f4ng<\/td>\n<td>Xem x\u00e9t c\u1ea5u tr\u00fac c\u00e2u nh\u01b0ng kh\u00f4ng \u0111i s\u00e2u v\u00e0o c\u00e2y c\u00fa ph\u00e1p.<\/td>\n<\/tr>\n<tr>\n<td>SRL s\u00e2u<\/td>\n<td>Li\u00ean quan \u0111\u1ebfn vi\u1ec7c ph\u00e2n t\u00edch to\u00e0n di\u1ec7n c\u1ea5u tr\u00fac c\u00fa ph\u00e1p v\u00e0 m\u1ed1i quan h\u1ec7 gi\u1eefa c\u00e1c th\u00e0nh ph\u1ea7n.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h2>C\u00e1c c\u00e1ch s\u1eed d\u1ee5ng nh\u00e3n vai tr\u00f2 ng\u1eef ngh\u0129a, c\u00e1c v\u1ea5n \u0111\u1ec1 v\u00e0 gi\u1ea3i ph\u00e1p c\u1ee7a ch\u00fang<\/h2>\n<h3>C\u00f4ng d\u1ee5ng:<\/h3>\n<ul>\n<li>Khai th\u00e1c th\u00f4ng tin<\/li>\n<li>D\u1ecbch m\u00e1y<\/li>\n<li>Tr\u1ea3 l\u1eddi c\u00e2u h\u1ecfi<\/li>\n<\/ul>\n<h3>C\u00e1c v\u1ea5n \u0111\u1ec1:<\/h3>\n<ul>\n<li>S\u1ef1 m\u01a1 h\u1ed3 trong ng\u00f4n ng\u1eef<\/li>\n<li>D\u1eef li\u1ec7u \u0111\u00e0o t\u1ea1o \u0111\u01b0\u1ee3c d\u00e1n nh\u00e3n h\u1ea1n ch\u1ebf<\/li>\n<li>Kh\u1ea3 n\u0103ng th\u00edch \u1ee9ng \u0111a ng\u00f4n ng\u1eef<\/li>\n<\/ul>\n<h3>C\u00e1c gi\u1ea3i ph\u00e1p:<\/h3>\n<ul>\n<li>K\u1ef9 thu\u1eadt h\u1ecdc m\u00e1y n\u00e2ng cao<\/li>\n<li>T\u1eadn d\u1ee5ng v\u0103n b\u1ea3n c\u00f3 ch\u00fa th\u00edch<\/li>\n<li>M\u00f4 h\u00ecnh \u0111a ng\u00f4n ng\u1eef<\/li>\n<\/ul>\n<h2>C\u00e1c \u0111\u1eb7c \u0111i\u1ec3m ch\u00ednh v\u00e0 so s\u00e1nh 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>Ghi nh\u00e3n vai tr\u00f2 ng\u1eef ngh\u0129a<\/th>\n<th>Ph\u00e2n t\u00edch c\u00fa ph\u00e1p<\/th>\n<th>Ph\u00e2n t\u00edch ph\u1ee5 thu\u1ed9c<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>T\u1eadp trung<\/td>\n<td>M\u1ed1i quan h\u1ec7 ng\u1eef ngh\u0129a<\/td>\n<td>C\u1ea5u tr\u00fac c\u00fa ph\u00e1p<\/td>\n<td>ph\u1ee5 thu\u1ed9c<\/td>\n<\/tr>\n<tr>\n<td>Nh\u00e3n<\/td>\n<td>\u0110\u1ea1i l\u00fd, B\u1ec7nh nh\u00e2n, v.v.<\/td>\n<td>Ph\u1ea7n c\u1ee7a b\u00e0i ph\u00e1t bi\u1ec3u<\/td>\n<td>Ph\u1ee5 thu\u1ed9c v\u00e0o \u0111\u1ea7u<\/td>\n<\/tr>\n<tr>\n<td>\u1ee8ng d\u1ee5ng<\/td>\n<td>Nhi\u1ec7m v\u1ee5 NLP<\/td>\n<td>Ph\u00e2n t\u00edch ng\u1eef ph\u00e1p<\/td>\n<td>C\u1ea5u tr\u00fac c\u00e2u<\/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 vi\u1ec7c g\u1eafn nh\u00e3n vai tr\u00f2 ng\u1eef ngh\u0129a<\/h2>\n<ul>\n<li>T\u00edch h\u1ee3p v\u1edbi c\u00e1c m\u00f4 h\u00ecnh h\u1ecdc s\u00e2u<\/li>\n<li>M\u1edf r\u1ed9ng sang c\u00e1c ng\u00f4n ng\u1eef \u00edt \u0111\u01b0\u1ee3c bi\u1ebft \u0111\u1ebfn h\u01a1n<\/li>\n<li>\u1ee8ng d\u1ee5ng th\u1eddi gian th\u1ef1c trong tr\u1ee3 l\u00fd gi\u1ecdng n\u00f3i v\u00e0 AI \u0111\u00e0m tho\u1ea1i<\/li>\n<\/ul>\n<h2>C\u00e1ch s\u1eed d\u1ee5ng ho\u1eb7c li\u00ean k\u1ebft m\u00e1y ch\u1ee7 proxy v\u1edbi vi\u1ec7c g\u1eafn nh\u00e3n vai tr\u00f2 ng\u1eef ngh\u0129a<\/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 trong c\u00e1c t\u00e1c v\u1ee5 SRL \u0111\u1ec3 thu th\u1eadp v\u00e0 x\u1eed l\u00fd d\u1eef li\u1ec7u t\u1eeb nhi\u1ec1u ngu\u1ed3n kh\u00e1c nhau m\u1ed9t c\u00e1ch an to\u00e0n v\u00e0 \u1ea9n danh. Nh\u1eefng m\u00e1y ch\u1ee7 n\u00e0y c\u00f3 th\u1ec3 t\u1ea1o \u0111i\u1ec1u ki\u1ec7n thu\u1eadn l\u1ee3i cho vi\u1ec7c thu th\u1eadp kho d\u1eef li\u1ec7u \u0111a ng\u00f4n ng\u1eef, cho ph\u00e9p ph\u00e1t tri\u1ec3n v\u00e0 n\u00e2ng cao c\u00e1c m\u00f4 h\u00ecnh SRL tr\u00ean nhi\u1ec1u ng\u00f4n ng\u1eef kh\u00e1c nhau.<\/p>\n<h2>Li\u00ean k\u1ebft li\u00ean quan<\/h2>\n<ul>\n<li><a href=\"https:\/\/framenet.icsi.berkeley.edu\" target=\"_new\" rel=\"noopener nofollow\">D\u1ef1 \u00e1n FrameNet<\/a><\/li>\n<li><a href=\"https:\/\/nlp.stanford.edu\/software\/srl.html\" target=\"_new\" rel=\"noopener nofollow\">Ghi nh\u00e3n vai tr\u00f2 ng\u1eef ngh\u0129a \u2013 Stanford NLP Group<\/a><\/li>\n<li><a href=\"https:\/\/oneproxy.pro\/vn\/\" target=\"_new\" rel=\"noopener\">OneProxy \u2013 Gi\u1ea3i ph\u00e1p proxy an to\u00e0n<\/a><\/li>\n<\/ul>","protected":false},"featured_media":470451,"menu_order":0,"template":"","meta":{"_acf_changed":false,"content-type":"","inline_featured_image":false,"footnotes":""},"class_list":["post-478916","wiki","type-wiki","status-publish","has-post-thumbnail","hentry"],"acf":{"faq_title":"Frequently Asked Questions about <mark>Semantic Role Labeling: A Comprehensive Guide<\/mark>","faq_items":[{"question":"What is Semantic Role Labeling (SRL)?","answer":"<p>Semantic Role Labeling (SRL) is a process in Natural Language Processing (NLP) that assigns specific roles or labels to words or phrases in a sentence. It helps to understand who did what to whom, when, where, why, etc., enabling computers to understand human language more accurately.<\/p>"},{"question":"What are the historical origins of Semantic Role Labeling?","answer":"<p>Semantic Role Labeling originated in the late 1960s in linguistic research, and it gained prominence in the 1990s with the rise of computational linguistics. The FrameNet project, initiated in 1997 at the University of California, Berkeley, played a significant role in its development.<\/p>"},{"question":"How does Semantic Role Labeling work?","answer":"<p>Semantic Role Labeling works by parsing the sentence into tokens and constructing a syntactic tree structure. It then identifies the verbs or predicates, locates the noun phrases or arguments related to those predicates, and assigns semantic roles to the identified arguments, such as Agent, Patient, Instrument, etc.<\/p>"},{"question":"What are the key features of Semantic Role Labeling?","answer":"<p>The key features of SRL include its accuracy in representing the meaning of a sentence, enhancing machine understanding of human language, and its potential for generalization across various languages.<\/p>"},{"question":"What types of Semantic Role Labeling exist?","answer":"<p>Semantic Role Labeling exists in three main types: Lexical SRL, which focuses on specific predicates and arguments; Shallow SRL, which considers the sentence structure but not deeply; and Deep SRL, involving a comprehensive analysis of syntactic structures and relationships.<\/p>"},{"question":"How can Semantic Role Labeling be used, and what are its challenges?","answer":"<p>SRL is used in information extraction, machine translation, and question answering. The challenges include ambiguity in language, limited labeled training data, and cross-language adaptability. Solutions include advanced machine learning techniques and leveraging annotated corpora.<\/p>"},{"question":"What are the future perspectives and technologies related to Semantic Role Labeling?","answer":"<p>The future of SRL includes integration with deep learning models, expansion to lesser-known languages, and real-time applications in voice assistants and conversational AI.<\/p>"},{"question":"How are proxy servers like OneProxy associated with Semantic Role Labeling?","answer":"<p>Proxy servers like OneProxy can be used in SRL tasks to gather and process data securely and anonymously from various sources. They can facilitate the collection of multilingual corpora, enhancing the development of SRL models across diverse languages.<\/p>"},{"question":"Where can I find more information about Semantic Role Labeling?","answer":"<p>You can find more information about Semantic Role Labeling at the <a href=\"https:\/\/framenet.icsi.berkeley.edu\" target=\"_new\">FrameNet Project<\/a>, <a href=\"https:\/\/nlp.stanford.edu\/software\/srl.html\" target=\"_new\">Stanford NLP Group's SRL page<\/a>, and <a href=\"https:\/\/oneproxy.pro\" target=\"_new\">OneProxy's website<\/a>.<\/p>"}]},"_links":{"self":[{"href":"https:\/\/oneproxy.pro\/vn\/wp-json\/wp\/v2\/wiki\/478916","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\/478916\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/oneproxy.pro\/vn\/wp-json\/wp\/v2\/media\/470451"}],"wp:attachment":[{"href":"https:\/\/oneproxy.pro\/vn\/wp-json\/wp\/v2\/media?parent=478916"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}