Dependency Parse Tree
This MicroSim visualizes the dependency parse tree for the example sentence "Show me the sales report for the last quarter." Dependency parsing reveals the grammatical relationships between words: which word is the head (governor) and which words depend on it. Hover over any word to see its part-of-speech tag and its grammatical role.
About This Diagram
A dependency parse tree is a directed graph in which each word points to the word it grammatically depends on. This MicroSim turns the abstract idea of "grammatical structure" into a concrete, color-coded tree so learners can see how a conversational AI system recovers meaning from word order.
Interactive Demo
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How It Works
The verb Show (VB) is the root of the sentence. Every other word ultimately depends on it. Each edge is labeled with a Universal Dependencies relation and color-coded by category:
- Red edges are core arguments:
dative(the recipient "me") anddobj(the direct object "report"). - Blue edges are modifiers:
det(determiner "the"),compound("sales report"), andamod(adjective "last"). - Green edges are prepositional attachments:
prep(the preposition "for") andpobj(its object "quarter").
Reading the tree top-down shows how a chatbot's NLP layer turns a flat string of tokens into a structured grammar that downstream intent and entity extraction can exploit.
Lesson Plan
- Identify the root. Ask students which word governs the whole sentence and why a verb is usually the root.
- Trace a phrase. Follow the green
prep/pobjedges to see how the prepositional phrase "for the last quarter" attaches to "report". - Classify relations. Have students sort the eight edges into core arguments, modifiers, and prepositional attachments using the color key.
- Compare to POS tagging. Discuss how POS tags (shown in parentheses) are a prerequisite for building this dependency structure.