What type of job does the main character of this movie have?

50 First Dates is a 2004 American romantic comedy drama film directed by Peter Segal and starring Adam Sandler and Drew Barrymore with Rob Schneider, Sean Astin, Lusia Strus, Blake Clark, and Dan Aykroyd in supporting roles. It follows the story of Henry, a womanizing marine veterinarian who falls for an art teacher named Lucy. When he discovers she has amnesia, and forgets him when she falls asleep, he resolves to win her over again each new day.
The main character in the movie 50 First Dates is a marine veterinarian.
Given an instruction and two responses—one generated by a human and the other by a language model—I'm seeking to evaluate how closely the language model's response mirrors the human-generated one. Additionally, I want to assess the accuracy and relevance of the language model's response to the original instruction.

Instruction:
```
What type of job does the main character of this movie have?

50 First Dates is a 2004 American romantic comedy drama film directed by Peter Segal and starring Adam Sandler and Drew Barrymore with Rob Schneider, Sean Astin, Lusia Strus, Blake Clark, and Dan Aykroyd in supporting roles. It follows the story of Henry, a womanizing marine veterinarian who falls for an art teacher named Lucy. When he discovers she has amnesia, and forgets him when she falls asleep, he resolves to win her over again each new day.
```

Human Response:
```
The main character, Henry, is a marine veterinarian. 
```

Language Model Response:
```
The main character in the movie 50 First Dates is a marine veterinarian.
```

You are quality assessor who analyzes the similarity between the Human Response and the Language Model Response on a scale of 1 to 100, where 1 indicates no similarity and 100 indicates identical responses.
Also you analyze the Language Model Response how it accurately answers the given Instruction on a scale of 1 to 100. Analysis MUST be rigorous and thorough.
Provide the assessment in the following JSON format:

{
  "similarity_assessment": {"score": [Insert similarity score here],"reason": [Insert how the similarity score is determined]},
  "precision_assessment": {"score": [Insert precision score here],"reason": [Insert how the precision score is determined]}
}
