---
title: "Semantic network: baseball player"
subject: "Artificial Intelligence"
chapter: 5
key: "semester_6/artificial_intelligence:semantic-network-baseball-pee-wee"
source: https://www.bctengineer.com/q/semester_6/artificial_intelligence/semantic-network-baseball-pee-wee
site: BCT Engineering
---

# Semantic network: baseball player

Artificial Intelligence · Chapter 5: Structured Knowledge Representation

- Asked in: 2073 Bhadra, 7 marks
- Answer checked by Claude Opus 5.5 (high effort) on 2026-10-14
- Page: https://www.bctengineer.com/q/semester_6/artificial_intelligence/semantic-network-baseball-pee-wee
- Whole chapter: https://www.bctengineer.com/md/semester_6/artificial_intelligence/chapter-5

## Question

Convert given sentences into Semantic Network.
i) The height of the adult male is 5.10
ii) Baseball player is an adult male.
iii) Adult male is a person.
iv) Batting average of Baseball players is 0.252
v) Pee-wee-Reese is a Fielder.
vi) Fielder is Baseball player.
vii) Team of pee-wee-Reese is Brooklyn Dodger.

## Short answer

Semantic net conversion: Adult-Male --is-a--> Person, --height--> 5.10; Baseball-Player --is-a--> Adult-Male, --batting-average--> 0.252; Fielder --is-a--> Baseball-Player; Pee-Wee-Reese --instance--> Fielder, --team--> Brooklyn-Dodger. Pee-Wee-Reese inherits height 5.10 and batting average 0.252.

## Answer

A semantic network uses nodes for objects/values and labelled arcs for relations. Property values are inherited through `is-a` and `instance` arcs.

#### Conversion of the sentences
| Sentence | Arcs |
|---|---|
| i) Height of adult male is 5.10 | Adult-Male --height--> 5.10 |
| ii) Baseball player is an adult male | Baseball-Player --is-a--> Adult-Male |
| iii) Adult male is a person | Adult-Male --is-a--> Person |
| iv) Batting average of baseball players is 0.252 | Baseball-Player --batting-average--> 0.252 |
| v) Pee-Wee-Reese is a Fielder | Pee-Wee-Reese --instance--> Fielder |
| vi) Fielder is baseball player | Fielder --is-a--> Baseball-Player |
| vii) Team of Pee-Wee-Reese is Brooklyn Dodger | Pee-Wee-Reese --team--> Brooklyn-Dodger |

#### Semantic network
```text
          [Person]
             ^
             | is-a
        [Adult-Male] --height--> [5.10]
             ^
             | is-a
      [Baseball-Player] --batting-avg--> [0.252]
             ^
             | is-a
         [Fielder]
             ^
             | instance
      [Pee-Wee-Reese] --team--> [Brooklyn-Dodger]
```

#### Inheritance
- Pee-Wee-Reese's batting average is 0.252 (inherited from Baseball-Player).
- His height is 5.10 (inherited from Adult-Male).
- He is a person (via Fielder, Baseball-Player, Adult-Male).

Assumption: 5.10 means 5 feet 10 inches; the values are class defaults and can be overridden by a value stored on the individual.

## Check yourself

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

1. How are Fielder, Baseball-Player and Adult-Male connected?
   A. Fielder is-a Baseball-Player is-a Adult-Male
   B. Adult-Male is-a Baseball-Player is-a Fielder
   C. Fielder instance Baseball-Player
   D. They are unlinked nodes with a height arc
   Answer: A. Each 'X is a Y' class statement is an is-a arc from X up to Y. (Key point: Chain of links)

2. How is Pee-Wee-Reese attached to the net?
   A. By an is-a arc to Person
   B. By an instance arc to Fielder, with a team arc to Brooklyn-Dodger
   C. By an instance arc to Brooklyn-Dodger
   D. By a height arc to 0.252
   Answer: B. He is an individual, so he is an instance of Fielder. (Key point: Pee-Wee-Reese link)

3. What is Pee-Wee-Reese's batting average according to the net?
   A. 5.10, inherited from Adult-Male
   B. Unknown, since it is not stored on him
   C. 0.252, inherited from Baseball-Player
   D. 0.252, stored on the team node
   Answer: C. Values on a superclass are inherited unless overridden; 5.10 is the height from Adult-Male. (Key point: Inherited values)

## Related in Artificial Intelligence

- [Frames, semantic net; sakti gauchan](https://www.bctengineer.com/question.md?key=semester_6%2Fartificial_intelligence%3Aframes-semantic-net-convert-sentences) — 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×

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