---
title: "Frames, semantic net; sakti gauchan"
subject: "Artificial Intelligence"
chapter: 5
key: "semester_6/artificial_intelligence:frames-semantic-net-convert-sentences"
source: https://www.bctengineer.com/q/semester_6/artificial_intelligence/frames-semantic-net-convert-sentences
site: BCT Engineering
---

# Frames, semantic net; sakti gauchan

Artificial Intelligence · Chapter 5: Structured Knowledge Representation

- Asked in: 2072 Magh, 7 marks
- Video: [Knowledge Representation || Semantic Networks || Frames || Artificial Intelligence(Hindi)#31](https://www.youtube.com/watch?v=nRMLTHDAVqc) — Exam Aasaan Hai !!!
- Answer checked by Claude Opus 5.5 (high effort) on 2026-10-14
- Page: https://www.bctengineer.com/q/semester_6/artificial_intelligence/frames-semantic-net-convert-sentences
- Whole chapter: https://www.bctengineer.com/md/semester_6/artificial_intelligence/chapter-5

## Question

What are Frames and Semantic Net? Convert the given sentences in semantic net.
i) A person is a mammal.
ii) Sakti Gauchan is a person.
iii) Person has nose.
iv) Sakti Gauchan is in Nepalese team.
v) Uniform color of Sakti Gauchan is Red/Blue.

## Short answer

Frames use slots and defaults; semantic nets are graphs with labeled arcs. Conversion: Person --is-a--> Mammal; Person --has-part--> Nose; Sakti Gauchan --instance--> Person, --team--> Nepalese Team, --uniform-colour--> Red/Blue. Sakti Gauchan inherits nose and mammal status.

## Answer

#### Frame
A **frame** is a structure to represent a stereotyped object or situation. It has a name and **slots** with values, defaults and attached procedures, organised in an `is-a` hierarchy so slots are inherited (Minsky).

Example: Frame *Person* (is-a Mammal; has: nose; legs: 2).

#### Semantic net
A **semantic net** is a graph with nodes for objects/concepts and labelled arcs for relations. Properties are inherited via `is-a` and `instance` arcs.

#### Conversion of the given sentences
Each sentence becomes nodes and arcs:

| Sentence | Arc |
|---|---|
| i) A person is a mammal | Person --is-a--> Mammal |
| ii) Sakti Gauchan is a person | Sakti Gauchan --instance--> Person |
| iii) Person has nose | Person --has-part--> Nose |
| iv) Sakti Gauchan is in Nepalese team | Sakti Gauchan --team--> Nepalese Team |
| v) Uniform colour is Red/Blue | Sakti Gauchan --uniform-colour--> Red/Blue |

```text
      [Mammal]
         ^
         | is-a
      [Person] --has-part--> [Nose]
         ^
         | instance
 [Sakti Gauchan] --team--------------> [Nepalese Team]
         |
         +--uniform-colour----------> [Red/Blue]
```
Assumption: "Red/Blue" is kept as one value node (red and blue are the two colours of the Nepali uniform). It could also be two nodes.

**Inference:** Sakti Gauchan has a nose (inherited from Person) and is a mammal (Person → Mammal).

**Frame form of the same facts:**
```text
Frame: Person        is-a: Mammal;  has-part: Nose
Frame: Sakti_Gauchan instance-of: Person
                     team: Nepalese Team
                     uniform_colour: Red/Blue
```

## Check yourself

The answer's key points as multiple-choice questions, with the correct option and why.

1. How is 'Sakti Gauchan is a person' drawn in the net?
   A. Sakti Gauchan --instance--> Person
   B. Sakti Gauchan --is-a--> Person
   C. Person --instance--> Sakti Gauchan
   D. Sakti Gauchan --has-part--> Person
   Answer: A. An individual is linked to its class by instance; is-a links one class to another. (Key point: Instance link)

2. How is 'A person is a mammal' drawn?
   A. Mammal --instance--> Person
   B. Person --is-a--> Mammal
   C. Person --has-part--> Mammal
   D. Person --team--> Mammal
   Answer: B. A class-superclass relation uses an is-a arc. (Key point: Class link)

3. What can be inferred about Sakti Gauchan from the net?
   A. He has no nose since it is not linked to him directly
   B. He is a Nepalese Team
   C. He has a nose and is a mammal, by inheritance through Person
   D. Nothing, since inheritance is not supported
   Answer: C. Properties of Person (has-part Nose) and its superclass Mammal are inherited by its instance. (Key point: Inference)

## Related in Artificial Intelligence

- [Semantic network: baseball player](https://www.bctengineer.com/question.md?key=semester_6%2Fartificial_intelligence%3Asemantic-network-baseball-pee-wee) — Artificial Intelligence, chapter 5
- [Frames and semantic nets importance](https://www.bctengineer.com/question.md?key=semester_6%2Fartificial_intelligence%3Aframes-and-semantic-nets-examples) — Artificial Intelligence, chapter 5, asked 3×
- [Frame vs semantic net](https://www.bctengineer.com/question.md?key=semester_6%2Fartificial_intelligence%3Aframe-vs-semantic-net) — Artificial Intelligence, chapter 5
- [Semantic nets with example](https://www.bctengineer.com/question.md?key=semester_6%2Fartificial_intelligence%3Asemantic-net-with-example) — Artificial Intelligence, chapter 5, asked 3×

## Related in other subjects

- [Cupric salts blue, cuprous colourless](https://www.bctengineer.com/question.md?key=semester_2%2Fengineering_chemistry%3Acu2-cu1-colour) — Engineering Chemistry, chapter 5
- [Rewrite sentences correctly (pronoun, concord) set 2082](https://www.bctengineer.com/question.md?key=semester_5%2Fcommunication_english%3Arewrite-sentences-pronoun-kartik) — Communication English, chapter 3
- [Rewrite sentences correctly set 2081](https://www.bctengineer.com/question.md?key=semester_5%2Fcommunication_english%3Arewrite-sentences-pronoun-chaitra) — Communication English, chapter 3
- [Webster signal: 450 and 350 PCU/hr, all-red 15 s](https://www.bctengineer.com/question.md?key=semester_7%2Ftransportation_engineering_ii%3Awebster-two-phase-450-350-pcu) — Transportation Engineering II, chapter 1
