Japanese and Chinese: language choices, examples, eight-language description

README.md

@@ -9,7 +9,7 @@ app_file: app.py
 pinned: true
 license: apache-2.0
 python_version: "3.11"
-short_description: Multilingual NER + NED Entity Linking (EN/IT/FR/DE/ES/PT)
+short_description: Entity linking (NER + NED) in 8 languages, incl. JA/ZH
 env:
   - GRADIO_SSR_MODE=false
 ---
@@ -18,12 +18,12 @@ env:
 
 Elevate your website's performance with our AI-powered entity extraction and disambiguation tool.
 
-Ready to turbocharge your SEO efforts and see your organic search performance soar? Look no further than our next-generation AI-powered entity linker — now with multilingual support across **six languages**!
+Ready to turbocharge your SEO efforts and see your organic search performance soar? Look no further than our next-generation AI-powered entity linker — now with multilingual support across **eight languages**!
 
 With our intelligent solution powered by **GLiNER** and **BGE-M3**, you can analyze your content — whether raw text or any URL — and instantly identify all relevant entities within it. Each entity is automatically linked to its corresponding **Wikidata entry**, complete with descriptions and confidence scores.
 
 This powerful combination helps search engines like Google better understand your content and rank it higher in search results. But that's not all! With precise entity disambiguation, our tool distinguishes between entities that share the same name, ensuring accurate knowledge graph connections that amplify your SEO benefits.
 
-**Supported languages:** English 🇬🇧 · Italian 🇮🇹 · French 🇫🇷 · German 🇩🇪 · Spanish 🇪🇸 · Portuguese 🇵🇹
+**Supported languages:** English 🇬🇧 · Italian 🇮🇹 · French 🇫🇷 · German 🇩🇪 · Spanish 🇪🇸 · Portuguese 🇵🇹 · Japanese 🇯🇵 · Chinese 🇨🇳
 
 This demo is embedded at **[wordlift.io/entity-extraction](https://wordlift.io/entity-extraction/)**, the canonical page for it.

app.py

@@ -474,6 +474,8 @@ EXAMPLES_TEXT = [
     ["A Petrobras e a Vale estão listadas na B3, a bolsa de São Paulo.", "Auto-detect", 0.5],
     ["Luís de Camões escreveu Os Lusíadas, a maior epopeia da literatura portuguesa.", "Auto-detect", 0.5],
     ["WordLift is an Italian company that builds an AI-powered SEO platform used by publishers. It is based in Rome.", "Auto-detect", 0.5],
+    ["黒澤明は『七人の侍』を監督した。羽田空港は東京の空の玄関口である。", "Auto-detect", 0.5],
+    ["周杰伦是台湾著名歌手。鲁迅写了《阿Q正传》。", "Auto-detect", 0.5],
 ]
 
 EXAMPLES_URL = [
@@ -516,7 +518,7 @@ with gr.Blocks(
                     )
                 with gr.Column(scale=1):
                     lang_dropdown = gr.Dropdown(
-                        choices=["Auto-detect", "en", "it", "fr", "de", "es", "pt"],
+                        choices=["Auto-detect", "en", "it", "fr", "de", "es", "pt", "ja", "zh"],
                         value="Auto-detect",
                         label="Language",
                     )
@@ -553,7 +555,7 @@ with gr.Blocks(
                     )
                 with gr.Column(scale=1):
                     url_lang = gr.Dropdown(
-                        choices=["Auto-detect", "en", "it", "fr", "de", "es", "pt"],
+                        choices=["Auto-detect", "en", "it", "fr", "de", "es", "pt", "ja", "zh"],
                         value="Auto-detect",
                         label="Language",
                     )