Merge pull request #3592 from vespa-engine/kkraune/remove-stale-doc

remove stale file

_data/sidebar.yml

@@ -24,9 +24,6 @@ docs:
       - page: "Use case: Shopping"
         url: /en/use-case-shopping.html
         sidebar_exclude: true
-      - page: "Use case: Text-Image Search"
-        url: /en/use-case-text-image-search.html
-        sidebar_exclude: true
       - page: "Frequently Asked Questions - FAQ"
         url: /en/faq.html
       - page: Glossary

questions.jsonl

@@ -1770,8 +1770,6 @@
 {"update": "id:open-p:paragraph::open/en/use-case-question-answering.html-", "fields": {"questions": {"assign": ["What is the open-domain QA use case?", "What is Dense Passage Retriever?", "How does the application retrieve passages?", "What is the BERT model used for?", "What is the Natural Questions dataset?", "What kind of questions can be asked with the deployed application?"]}}}
 {"update": "id:open-p:paragraph::open/en/use-case-question-answering.html-highlighted-features", "fields": {"questions": {"assign": ["What is multi-threaded ranking?", "What is multi-phased ranking?", "What are Transformer models used for?"]}}}
 {"update": "id:open-p:paragraph::open/en/use-case-shopping.html-", "fields": {"questions": {"assign": ["What is the e-commerce use case?", "What is the shopping sample app about?", "Where do I navigate to browse the application?", "What is the Amazon product data set?", "How do I convert data to Vespa format?", "How is the review rating of an item stored?", "What is the recommended way to handle reviews?"]}}}
-{"update": "id:open-p:paragraph::open/en/use-case-text-image-search.html-", "fields": {"questions": {"assign": ["What is the text-image use case?", "What does CLIP enable?", "What are the two ways to use the sample application?"]}}}
-{"update": "id:open-p:paragraph::open/en/use-case-text-image-search.html-highlighted-features", "fields": {"questions": {"assign": ["What is PyVespa?"]}}}
 {"update": "id:open-p:paragraph::open/en/using-wand-with-vespa.html-", "fields": {"questions": {"assign": ["What is the WAND algorithm?", "How does WAND work?", "What are the benefits of WAND?", "When should WAND be used?", "What are the differences between weakAnd and wand operators?", "Does wand operator integrate with linguistic processing?", "How can WAND be evaluated?"]}}}
 {"update": "id:open-p:paragraph::open/en/using-wand-with-vespa.html-weakand", "fields": {"questions": {"assign": ["What is the weakAnd operator?", "What fields can weakAnd retrieve?", "What is the effect of tuning targetHits?", "What are some ranking features that correlate well with weakAnd scoring?", "What should you do to get the best hits possible with weakAnd?", "What can cause weakAnd queries to become slower?", "What is the query example expressed in YQL?"]}}}
 {"update": "id:open-p:paragraph::open/en/using-wand-with-vespa.html-weakand-inner-scoring", "fields": {"questions": {"assign": ["What is the weakAnd query operator?", "What ranking features does weakAnd use?", "How is term significance calculated?", "What is the purpose of weakAnd.replace?", "How does weakAnd handle documents that can't compete with top hits?", "Does weakAnd use the number of times a term occurs in a document for inner scoring?", "Can term significance and weight be overridden in the query using annotations?", "Does weakAnd expose all evaluated hits or just the top k hits?"]}}}