I asked ChatGPT for a quick refresher on Subject, Object, and Topic markers.

Subject Markers: 이/가

  • 이 (i): Used after a noun ending in a consonant.
  • 가 (ga): Used after a noun ending in a vowel.
  • Purpose: These particles indicate the subject of the sentence, essentially who or what is performing the action.
  • Example:
    • 고양이가 뛰어요. (The cat runs.)

Object Markers: 을/를

  • 을 (eul): Used after a noun ending in a consonant.
  • 를 (reul): Used after a noun ending in a vowel.
  • Purpose: These particles indicate the direct object of the sentence, essentially what receives the action.
  • Example:
    • 나는 사과를 먹어요. (I eat an apple.)

Topic Markers: 은/는

  • 은 (eun): Used after a noun ending in a consonant.
  • 는 (neun): Used after a noun ending in a vowel.
  • Purpose: These particles indicate the topic of the sentence or the general context being discussed. The topic might not necessarily be the subject of the sentence. It provides context or contrast and often indicates what the sentence is mainly about.
  • Example:
    • 나는 학생이에요. (As for me, I am a student.)
      • In this sentence, “나” (I) is the topic, but not necessarily the subject in a strict sense. The use of the topic marker helps to emphasize or contrast the information that follows.

Key Differences:

  • The subject marker indicates who or what is carrying out an action.
  • The object marker indicates what is affected by the action.
  • The topic marker sets the scene or provides context for what the sentence will discuss. Often, sentences with topic markers might be providing new, contrasting, or emphasized information about the noun they are attached to.

Note: While this provides a basic understanding of these markers, Korean grammar often possesses nuances that require exposure and practice to fully grasp. The same noun can sometimes be used as both the topic and the subject of a sentence, leading to different nuances in meaning and emphasis.


My Korean Diary generated this text in part with GPT-4, OpenAI’s large-scale language-generation model. Upon generating draft language, the author reviewed, edited, and revised the language to their own liking and takes ultimate responsibility for the content of this publication.