{"id":29181,"date":"2025-09-09T00:00:29","date_gmt":"2025-09-08T21:00:29","guid":{"rendered":"https:\/\/fatihsoysal.com\/blog\/chatgpt-gemini-ve-perplexityde-nasil-alinti-alinir\/"},"modified":"2025-09-09T00:00:29","modified_gmt":"2025-09-08T21:00:29","slug":"chatgpt-gemini-ve-perplexityde-nasil-alinti-alinir","status":"publish","type":"post","link":"https:\/\/fatihsoysal.com\/blog\/chatgpt-gemini-ve-perplexityde-nasil-alinti-alinir\/","title":{"rendered":"ChatGPT, Gemini ve Perplexity’de Nas\u0131l Al\u0131nt\u0131 Al\u0131n\u0131r?"},"content":{"rendered":"

ChatGPT, Gemini ve Perplexity’de Nas\u0131l Al\u0131nt\u0131 Al\u0131n\u0131r?<\/p>\n

B\u00fcy\u00fck dil modelleri (LLM’ler) \u00e7a\u011f\u0131yla birlikte, yapay zeka taraf\u0131ndan \u00fcretilen i\u00e7eriklerin akademik ve profesyonel ortamlarda kullan\u0131m\u0131 h\u0131zla art\u0131yor. Ancak bu i\u00e7erikleri do\u011fru bir \u015fekilde nas\u0131l kaynak g\u00f6sterir ve al\u0131nt\u0131 yapar\u0131z? ChatGPT, Gemini ve Perplexity gibi modellerden elde edilen bilgileri nas\u0131l belgelendiririz? Bu makale, bu sorulara ad\u0131m ad\u0131m cevap vererek, LLM’lerden al\u0131nt\u0131 yapman\u0131n en iyi uygulamalar\u0131n\u0131, tekniklerini ve ileri d\u00fczey stratejilerini ele alacakt\u0131r.<\/p>\n

Temel Kavramlar: B\u00fcy\u00fck Dil Modelleri ve Kaynak G\u00f6sterme<\/h2>\n

\u00d6ncelikle, b\u00fcy\u00fck dil modellerinin (ChatGPT, Gemini, Perplexity gibi) nas\u0131l \u00e7al\u0131\u015ft\u0131\u011f\u0131n\u0131 anlamak \u00f6nemlidir. Bu modeller, devasa veri k\u00fcmeleri \u00fczerinde e\u011fitilmi\u015f ve insan dilini anlama ve \u00fcretme yetene\u011fine sahip karma\u015f\u0131k algoritmalard\u0131r. Ancak, orijinal bir fikir kayna\u011f\u0131 de\u011fillerdir. Var olan bilgileri i\u015fleyerek yeni metinler, kodlar veya di\u011fer i\u00e7erik t\u00fcrleri olu\u015ftururlar. Bu nedenle, bu modellerden elde edilen bilgileri kaynak g\u00f6stermek, akademik d\u00fcr\u00fcstl\u00fck ve bilgi b\u00fct\u00fcnl\u00fc\u011f\u00fc a\u00e7\u0131s\u0131ndan kritik \u00f6neme sahiptir.<\/p>\n

Geleneksel kaynak g\u00f6sterim y\u00f6ntemleri, kitaplar, makaleler ve web siteleri gibi belirli yazarlar\u0131 ve yay\u0131nc\u0131lar\u0131 belirlemeyi ama\u00e7lar. LLM’ler ise bu kriterlere uymazlar. Dolay\u0131s\u0131yla, LLM’lerden elde edilen bilgileri kaynak g\u00f6stermek i\u00e7in \u00f6zel bir yakla\u015f\u0131m gereklidir. Bu yakla\u015f\u0131m, modele ait bilgileri a\u00e7\u0131k\u00e7a belirterek, okuyucunun bilgi kayna\u011f\u0131n\u0131 anlamas\u0131n\u0131 sa\u011flar.<\/p>\n

Bir\u00e7ok akademik kurulu\u015f, LLM’lerden elde edilen bilgilerin nas\u0131l kaynak g\u00f6sterilece\u011fi konusunda hen\u00fcz net bir k\u0131lavuz yay\u0131nlamam\u0131\u015ft\u0131r. Ancak genel olarak, \u015feffafl\u0131k ve do\u011frulu\u011fu sa\u011flamak i\u00e7in a\u015fa\u011f\u0131daki prensipler izlenmelidir. Daha fazla bilgi i\u00e7in \u00fcniversite k\u00fct\u00fcphanelerinizin ve akademik yay\u0131nlar\u0131n kaynak g\u00f6sterme k\u0131lavuzlar\u0131n\u0131 incelemenizi \u00f6neririz. Ayr\u0131ca, konu hakk\u0131nda g\u00fcncel geli\u015fmeleri takip etmek i\u00e7in (https:\/\/fatihsoysal.com) adresini ziyaret edebilirsiniz.<\/p>\n

LLM’lerden Elde Edilen Bilgileri Nas\u0131l Kaynak G\u00f6steririm? (Yeni Ba\u015flayanlar \u0130\u00e7in)<\/h2>\n

Yeni ba\u015flayanlar i\u00e7in, LLM’lerden elde edilen bilgileri kaynak g\u00f6stermenin en basit y\u00f6ntemi, metnin k\u00f6kenini a\u00e7\u0131k\u00e7a belirtmektir. \u00d6rne\u011fin, ChatGPT’den elde edilen bir bilgiyi \u015fu \u015fekilde kaynak g\u00f6sterebilirsiniz:<\/p>\n

“ChatGPT b\u00fcy\u00fck dil modeli kullan\u0131larak elde edilen bilgilere g\u00f6re, [bilgi]…”<\/p>\n

Bu y\u00f6ntem, okuyucunun bilginin bir LLM taraf\u0131ndan \u00fcretildi\u011fini anlamas\u0131n\u0131 sa\u011flar. Daha detayl\u0131 bilgi i\u00e7in, kullan\u0131lan LLM’nin s\u00fcr\u00fcm numaras\u0131n\u0131 (e\u011fer mevcutsa) da ekleyebilirsiniz. \u00d6rnek olarak: “ChatGPT (GPT-4) b\u00fcy\u00fck dil modeli kullan\u0131larak elde edilen bilgilere g\u00f6re…”<\/p>\n

Ayr\u0131ca, elde edilen bilgilerin tarihini de belirtmek faydal\u0131 olabilir. Bu, bilginin zaman i\u00e7inde de\u011fi\u015febilece\u011fi durumlarda \u00f6nemlidir. \u00d6rnek: “ChatGPT (GPT-4) b\u00fcy\u00fck dil modeli, 2024-10-27 tarihinde yap\u0131lan sorgulamaya g\u00f6re, [bilgi]…” <\/p>\n

LLM’lerden Elde Edilen Bilgileri Nas\u0131l Kaynak G\u00f6steririm? (Orta D\u00fczey)<\/h2>\n

Orta d\u00fczeyde bilgiye sahip kullan\u0131c\u0131lar i\u00e7in, kaynak g\u00f6sterme y\u00f6ntemini biraz daha geli\u015ftirmek \u00f6nemlidir. Sadece LLM’nin ad\u0131n\u0131 ve tarihini belirtmek yerine, sorulan soruyu da belirtebilirsiniz. Bu, okuyucunun sorunun ba\u011flam\u0131n\u0131 anlamas\u0131na ve LLM’nin cevab\u0131n\u0131n do\u011frulu\u011funu de\u011ferlendirmesine yard\u0131mc\u0131 olur. <\/p>\n

\u00d6rnek: “2024-10-27 tarihinde ChatGPT (GPT-4) modelini kullanarak, ‘iklim de\u011fi\u015fikli\u011finin etkileri nelerdir?’ sorusuna verilen yan\u0131t \u015fu \u015fekildedir: [bilgi]…” <\/p>\n

Bu y\u00f6ntem, kaynak g\u00f6stermenin \u015feffafl\u0131\u011f\u0131n\u0131 art\u0131r\u0131r ve bilginin yeniden \u00fcretilebilirli\u011fini sa\u011flar. Ayr\u0131ca, kaynak g\u00f6stermenin hangi stil k\u0131lavuzuna (APA, MLA, Chicago vb.) uydu\u011funu da belirtmek \u00f6nemlidir. \u00d6rne\u011fin, APA stil k\u0131lavuzuna uygun bir kaynak g\u00f6steriminde tarih, model ad\u0131 ve verilen bilgi bir parantez i\u00e7ine al\u0131n\u0131r. Bu uygulama, akademik \u00e7al\u0131\u015fmalarda yayg\u0131n olarak kullan\u0131l\u0131r.<\/p>\n

LLM’lerden Elde Edilen Bilgileri Nas\u0131l Kaynak G\u00f6steririm? (\u0130leri D\u00fczey)<\/h2>\n

\u0130leri d\u00fczey kullan\u0131c\u0131lar i\u00e7in, kaynak g\u00f6sterme, LLM’nin \u00e7\u0131kt\u0131s\u0131na yap\u0131lan herhangi bir d\u00fczenlemeyi de kapsamal\u0131d\u0131r. LLM taraf\u0131ndan \u00fcretilen metni d\u00fczenlerken, bu d\u00fczenlemeleri a\u00e7\u0131k\u00e7a belirtmek \u00f6nemlidir. \u00d6rne\u011fin, LLM’nin \u00fcretti\u011fi bir c\u00fcmleyi k\u0131salt\u0131r veya yeniden ifade ederseniz, bunu belirtmelisiniz. <\/p>\n

\u00d6rnek: “ChatGPT (GPT-4) taraf\u0131ndan \u00fcretilen orijinal metin \u015fu \u015fekildeydi: [orijinal metin]. Bu metin, anla\u015f\u0131l\u0131rl\u0131\u011f\u0131 art\u0131rmak i\u00e7in [\u015fekilde] d\u00fczenlenmi\u015ftir.” <\/p>\n

Ayr\u0131ca, ileri d\u00fczey kullan\u0131c\u0131lar LLM’nin yan\u0131tlar\u0131n\u0131 ba\u011f\u0131ms\u0131z kaynaklarla do\u011frulamal\u0131d\u0131r. LLM’ler m\u00fckemmel de\u011fildir ve hatal\u0131 bilgiler \u00fcretebilirler. Bu nedenle, LLM’den elde edilen bilgileri di\u011fer g\u00fcvenilir kaynaklarla do\u011frulamak, bilginin do\u011frulu\u011funu ve g\u00fcvenilirli\u011fini art\u0131r\u0131r. Bu do\u011frulama i\u015flemi, kaynak g\u00f6steriminde de belirtilmelidir.<\/p>\n

Bir di\u011fer ileri d\u00fczey teknik ise, LLM’nin hangi parametrelerle kullan\u0131ld\u0131\u011f\u0131n\u0131 belirtmektir. \u00d6rne\u011fin, modelin s\u0131cakl\u0131k (temperature) ve maksimum uzunluk (max_tokens) gibi parametrelerinin sonu\u00e7lar\u0131 nas\u0131l etkiledi\u011fini belirtmek, okuyucunun \u00e7\u0131kt\u0131y\u0131 daha iyi anlamas\u0131na yard\u0131mc\u0131 olabilir.<\/p>\n

Vaka Analizi 1: Akademik Makale<\/h2>\n

Bir \u00f6\u011frenci, iklim de\u011fi\u015fikli\u011fi \u00fczerine bir akademik makale yaz\u0131yor ve ChatGPT’den iklim de\u011fi\u015fikli\u011finin etkileri hakk\u0131nda bilgi al\u0131yor. \u00d6\u011frenci, ChatGPT’den ald\u0131\u011f\u0131 bilgileri do\u011frudan kopyalamak yerine, \u00f6zetleyerek ve kendi c\u00fcmleleriyle yeniden ifade ederek makalesine dahil ediyor. Makalesinin kaynak\u00e7a b\u00f6l\u00fcm\u00fcnde ise, \u015f\u00f6yle bir kaynak g\u00f6sterim kullan\u0131yor:<\/p>\n

“ChatGPT (GPT-4), 2024-10-28. \u0130klim de\u011fi\u015fikli\u011finin etkileri hakk\u0131nda bilgi edinmek i\u00e7in sorgulama yap\u0131lm\u0131\u015ft\u0131r.”<\/p>\n

Vaka Analizi 2: Blog Yaz\u0131s\u0131<\/h2>\n

Bir blog yazar\u0131, yeni bir web sitesi olu\u015fturmak i\u00e7in gereken ad\u0131mlar\u0131 anlat\u0131yor ve ChatGPT’den kod \u00f6rnekleri al\u0131yor. Yazar, ChatGPT’den ald\u0131\u011f\u0131 kodlar\u0131 do\u011frudan blog yaz\u0131s\u0131na kopyal\u0131yor ancak her kod blo\u011funun alt\u0131na “ChatGPT (GPT-4) taraf\u0131ndan \u00fcretilmi\u015ftir” yaz\u0131yor. Bu y\u00f6ntem, kaynak g\u00f6sterme a\u00e7\u0131s\u0131ndan yeterli olmayabilir. Daha iyi bir yakla\u015f\u0131m, her kod blo\u011funun ne yapt\u0131\u011f\u0131n\u0131 a\u00e7\u0131klayarak ve ChatGPT’nin hangi parametrelerle kullan\u0131ld\u0131\u011f\u0131n\u0131 belirterek, \u015feffafl\u0131\u011f\u0131 art\u0131rmak olacakt\u0131r.<\/p>\n

Performans Kar\u015f\u0131la\u015ft\u0131rmas\u0131: Kaynak G\u00f6sterme Y\u00f6ntemleri<\/h2>\n

| Y\u00f6ntem | \u015eeffafl\u0131k | Do\u011fruluk | Yeniden \u00dcretilebilirlik |
\n|—————————————|————|———–|————————-|
\n| Sadece LLM’nin ad\u0131 | D\u00fc\u015f\u00fck | D\u00fc\u015f\u00fck | D\u00fc\u015f\u00fck |
\n| LLM’nin ad\u0131 + Tarih | Orta | Orta | Orta |
\n| LLM’nin ad\u0131 + Tarih + Soru | Y\u00fcksek | Y\u00fcksek | Y\u00fcksek |
\n| LLM’nin ad\u0131 + Tarih + Soru + Parametreler | \u00c7ok Y\u00fcksek | \u00c7ok Y\u00fcksek | \u00c7ok Y\u00fcksek |<\/p>\n

G\u00fcvenlik Uyar\u0131lar\u0131<\/h2>\n
\n Dikkat:<\/strong> LLM’lerden elde edilen bilgilerin her zaman do\u011fru ve g\u00fcvenilir olmad\u0131\u011f\u0131n\u0131 unutmay\u0131n. LLM’lerin \u00fcretti\u011fi bilgileri her zaman ba\u011f\u0131ms\u0131z kaynaklarla do\u011frulamal\u0131s\u0131n\u0131z. Yanl\u0131\u015f veya eksik bilgiler kullanmak, akademik \u00e7al\u0131\u015fman\u0131z\u0131n veya profesyonel projenizin g\u00fcvenilirli\u011fini zedeleyebilir.\n<\/div>\n

Sonu\u00e7<\/h2>\n

B\u00fcy\u00fck dil modellerinden elde edilen bilgileri do\u011fru ve \u015feffaf bir \u015fekilde kaynak g\u00f6stermek, akademik d\u00fcr\u00fcstl\u00fck ve bilgi b\u00fct\u00fcnl\u00fc\u011f\u00fc a\u00e7\u0131s\u0131ndan son derece \u00f6nemlidir. Bu makalede, yeni ba\u015flayanlardan ileri d\u00fczey kullan\u0131c\u0131lara kadar farkl\u0131 seviyelerdeki kullan\u0131c\u0131lar i\u00e7in kaynak g\u00f6sterme y\u00f6ntemleri anlat\u0131lm\u0131\u015ft\u0131r. Ancak, kaynak g\u00f6stermenin en iyi uygulamalar\u0131, kurumunuzun veya yay\u0131nc\u0131n\u0131z\u0131n belirledi\u011fi kurallara g\u00f6re de de\u011fi\u015febilir. Bu nedenle, ilgili kurallar\u0131 dikkate alarak kaynak g\u00f6steriminizi d\u00fczenlemeniz tavsiye edilir.<\/p>\n

S\u0131k\u00e7a Sorulan Sorular<\/h3>\n
    \n
  • LLM’lerden elde edilen bilgileri kaynak g\u00f6stermezsem ne olur?<\/b> Akademik \u00e7al\u0131\u015fman\u0131zda veya profesyonel projenizde intihal su\u00e7lamas\u0131yla kar\u015f\u0131 kar\u015f\u0131ya kalabilirsiniz.<\/li>\n
  • Hangi kaynak g\u00f6sterme stilini kullanmal\u0131y\u0131m?<\/b> Kurumunuzun veya yay\u0131nc\u0131n\u0131z\u0131n belirledi\u011fi stil k\u0131lavuzuna uymal\u0131s\u0131n\u0131z. Yayg\u0131n kullan\u0131lan stiller aras\u0131nda APA, MLA ve Chicago bulunur.<\/li>\n
  • LLM’lerin \u00fcretti\u011fi bilgilerin do\u011frulu\u011fundan nas\u0131l emin olabilirim?<\/b> LLM’lerden elde edilen bilgileri her zaman ba\u011f\u0131ms\u0131z ve g\u00fcvenilir kaynaklarla do\u011frulamal\u0131s\u0131n\u0131z.<\/li>\n
  • LLM’lerden elde edilen kodlar\u0131 nas\u0131l kaynak g\u00f6steririm?<\/b> Kod bloklar\u0131n\u0131n alt\u0131na veya yan\u0131na “ChatGPT (GPT-4) taraf\u0131ndan \u00fcretilmi\u015ftir” gibi bir a\u00e7\u0131klama ekleyerek kaynak g\u00f6sterebilirsiniz. Ancak daha detayl\u0131 bilgi i\u00e7in ilgili parametreleri de belirtmelisiniz.<\/li>\n
  • LLM’ler i\u00e7in \u00f6zel bir kaynak g\u00f6sterme standard\u0131 var m\u0131?<\/b> Hen\u00fcz yayg\u0131n olarak kabul g\u00f6rm\u00fc\u015f bir standart yok ancak \u015feffafl\u0131k ve do\u011frulu\u011fu sa\u011flayan bir y\u00f6ntem tercih etmelisiniz.<\/li>\n<\/ul>\n

    Yazar: Fatih Soysal<\/p>\n","protected":false},"excerpt":{"rendered":"ChatGPT, Gemini ve Perplexity’de Nas\u0131l Al\u0131nt\u0131 Al\u0131n\u0131r? B\u00fcy\u00fck dil modelleri (LLM’ler) \u00e7a\u011f\u0131yla birlikte, yapay zeka taraf\u0131ndan \u00fcretilen i\u00e7eriklerin…","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"csco_page_header_type":"","csco_page_load_nextpost":"","csco_page_subscribe_form":"","csco_page_contact_form":"","footnotes":""},"categories":[1],"tags":[],"class_list":{"0":"post-29181","1":"post","2":"type-post","3":"status-publish","4":"format-standard","6":"category-genel","7":"cs-entry","8":"cs-video-wrap"},"yoast_head":"\nChatGPT, Gemini ve Perplexity'de Nas\u0131l Al\u0131nt\u0131 Al\u0131n\u0131r?<\/title>\n<meta name=\"description\" content=\"B\u00fcy\u00fck dil modelleri (LLM'ler) \u00e7a\u011f\u0131yla birlikte, yapay zeka taraf\u0131ndan \u00fcretilen i\u00e7eriklerin akademik ve profesyonel ortamlarda kullan\u0131m\u0131 h\u0131zla art\u0131yor. Ancak bu i\u00e7erikleri do\u011fru bir \u015fekilde nas\u0131l kaynak g\u00f6sterir ve al\u0131nt\u0131 yapar\u0131z? ChatGPT, Gemini ve Perplexity gibi modellerden elde edilen bilgileri nas\u0131l belgelendiririz? Bu makale, bu sorulara ad\u0131m ad\u0131m cevap vererek, LLM'lerden al\u0131nt\u0131 yapman\u0131n en iyi uygulamalar\u0131n\u0131, tekniklerini ve ileri d\u00fczey stratejilerini ele alacakt\u0131r.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/fatihsoysal.com\/blog\/chatgpt-gemini-ve-perplexityde-nasil-alinti-alinir\/\" \/>\n<meta property=\"og:locale\" content=\"tr_TR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"ChatGPT, Gemini ve Perplexity'de Nas\u0131l Al\u0131nt\u0131 Al\u0131n\u0131r?\" \/>\n<meta property=\"og:description\" content=\"B\u00fcy\u00fck dil modelleri (LLM'ler) \u00e7a\u011f\u0131yla birlikte, yapay zeka taraf\u0131ndan \u00fcretilen i\u00e7eriklerin akademik ve profesyonel ortamlarda kullan\u0131m\u0131 h\u0131zla art\u0131yor. Ancak bu i\u00e7erikleri do\u011fru bir \u015fekilde nas\u0131l kaynak g\u00f6sterir ve al\u0131nt\u0131 yapar\u0131z? ChatGPT, Gemini ve Perplexity gibi modellerden elde edilen bilgileri nas\u0131l belgelendiririz? 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