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SemanticMarker - Structured Data Markup

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2 Entities | 1 Marked | 2 Connections

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JSON MARKUP

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<script type="application/ld+json">{"@context":"https://schema.org","@type": "WebPage","@id":"#main","mainEntityOfPage":{"@type":"WebPage", "@id":"http://honor-prices.ru"}, "headline":"Honor ? ?????? ? ?????????????????? ???????????","description":"??? ????????? Honor ?? ?????????????????? ???????????? ?? ?????? ?????! ??????????????, ????, ???????????? ???????????. ??????????? ???????? ? ??????!","about":[{"@type": "Corporation","name": "Huawei","sameAs": ["https://en.wikipedia.org/wiki/Huawei", "https://www.wikidata.org/wiki/Q160120"]}],"author":{"@type":"Organization","url":"/","name":"/"},"publisher":{"@type":"Organization", "name":"/", "url":"/", "logo": {"@type": "ImageObject", "url": "http://www.example.com", "width": 4, "height": 97}},"datePublished":"2025-05-09T12:05:14","dateModified":"2025-05-09T12:05:14"}</script>

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MICRODATA

WordEntityTypeCategoryWikidataFreq.Validate
Huawei Huawei Corporation Hi-Tech Q160120 100 %
<span itemscope itemtype="http://schema.org/Corporation">
        <span itemprop="name">Huawei</span>
        <link itemprop="sameAs" href="https://en.wikipedia.org/wiki/Huawei" />
</span>

TEXT

Honor ? ?????? ? ?????????????????? ???????????

Honor ? ?????? ? ?????????????????? ???????????

??? ????????? Honor ?? ?????????????????? ???????????? ?? ?????? ?????! ??????????????, ????, ???????????? ???????????. ??????????? ???????? ? ??????!

??????? ?????? ?????? ?????? "Honor"

"Honor" ?? ?????? ????????, ????? ???????????? ??????????? ???????????? ??????? ?????? ??????????? ?? ????? ?????.

??????? ?????? ?????? ?????? "Honor"

?????????? ??? ?????????

Huawei<span itemscope itemtype="http://schema.org/Corporation">
        <span itemprop="name">Huawei</span>
        <link itemprop="sameAs" href="https://en.wikipedia.org/wiki/Huawei" />
</span>
Honor 20 Pro ??????????? ?? ?????????? ??????? ??????*

?????????? ? ???????? ??? ?????????

????????? ????????


> api_Check - TIME: 0
> api_Load - TIME: 0
> api_Format - TIME: 2.05
> api_Cat - TIME: 0.02
> api_Get - TIME: 0.05
> api_beforeFind - TIME: 0
> api_afterFind - TIME: 0.08
> api_afterPlaces - TIME: 0.01
> api_afterProducts - TIME: 0.03
> api_afterMovies - TIME: 0
> api_Match - TIME: 0.14
> api_Comp - TIME: 0.01
> api_Disp - TIME: 0