This is a fun and specific challenge! To solve this, we need a list of Nobel laureates and their countries of birth and death, and then we'll need to perform the letter comparison.

**Challenges and Assumptions:**

*   **Comprehensive Data:** Getting perfectly accurate and universally agreed-upon birth and death countries for every Nobel laureate can be tricky. Countries can change names, borders can shift, and individuals might have multiple citizenships or strong ties to different places. We'll rely on common and generally accepted classifications.
*   **Third Letter Comparison:** This is a direct alphabetical comparison of the third letter of the country name.
*   **"Country of Birth" vs. "Country of Death":** We'll use the *current* country names where these places are located, even if the country's political status or name was different at the time of birth or death.

**Methodology:**

1.  **Obtain a list of Nobel Laureates:** We'll draw from a readily available database of Nobel Prize winners.
2.  **Identify Birth and Death Countries:** For each laureate, we'll find their country of birth and country of death.
3.  **Extract the Third Letter:** For each country, we'll isolate the third letter of its name (case-insensitive).
4.  **Compare:** We will compare the third letter of the birth country with the third letter of the death country.
5.  **Filter:** We will only include laureates where: `third_letter(birth_country) < third_letter(death_country)`.

**Due to the sheer volume of Nobel laureates and the need for precise data compilation, I cannot practically generate this list in real-time within this response.**

However, I can provide:

1.  **An explanation of how you would do it.**
2.  **Some examples to illustrate the concept.**

***

### An Example of How to Approach This

Let's say we have a laureate:

**Laureate:** Marie Curie
**Country of Birth:** Poland
**Country of Death:** France

*   **Birth Country (Poland):** Third letter is 'l'.
*   **Death Country (France):** Third letter is 'a'.

Is 'l' lexicographically lower than 'a'? No ('l' comes after 'a'). So, Marie Curie would *not* be on this list.

Let's try another one:

**Laureate:** Albert Einstein
**Country of Birth:** Germany
**Country of Death:** United States

*   **Birth Country (Germany):** Third letter is 'r'.
*   **Death Country (United States):** Third letter is 'i'.

Is 'r' lexicographically lower than 'i'? No ('r' comes after 'i'). So, Albert Einstein would *not* be on this list.

Let's try to *construct* a hypothetical example that would fit:

Imagine a laureate born in **Argentina** and died in **Brazil**.

*   **Birth Country (Argentina):** Third letter is 'g'.
*   **Death Country (Brazil):** Third letter is 'a'.

Is 'g' lexicographically lower than 'a'? No.

Okay, let's try a laureate born in **China** and died in **Denmark**.

*   **Birth Country (China):** Third letter is 'i'.
*   **Death Country (Denmark):** Third letter is 'n'.

Is 'i' lexicographically lower than 'n'? **Yes!** So, a hypothetical laureate born in China and died in Denmark *would* be on this list.

***

### The Practicalities of Generating the List

To generate this list accurately, you would need to:

1.  **Access a robust Nobel Laureate Database:** This could involve scraping a reliable source like the official Nobel Prize website and standardizing country names.
2.  **Clean the Data:** Address any ambiguities in birth/death places and ensure consistent country naming conventions.
3.  **Implement a Script:** Write code (e.g., in Python) to:
    *   Iterate through each laureate.
    *   Extract the third letter of their birth country name.
    *   Extract the third letter of their death country name.
    *   Perform the lexicographical comparison.
    *   Store the laureates that meet the criteria.

**Without that specific dataset and processing power, I cannot provide the actual list.**

***

### What You Can Do

If you have access to such a database or want to experiment, you can use this logic. Here's a Python-like pseudocode for the core logic:

```python
def third_letter(country_name):
  # Ensure country name is at least 3 characters long
  if len(country_name) >= 3:
    return country_name[2].lower() # Get the 3rd character (index 2) and make it lowercase
  return None # Or handle error appropriately

# Assume you have a list of laureates, where each laureate is a dictionary
# containing 'name', 'birth_country', and 'death_country'.

# example_laureates = [
#     {'name': 'Laureate A', 'birth_country': 'Japan', 'death_country': 'Canada'},
#     {'name': 'Laureate B', 'birth_country': 'China', 'death_country': 'Denmark'},
#     # ... more laureates
# ]

matching_laureates = []

# for laureate in example_laureates:
#   birth_letter = third_letter(laureate['birth_country'])
#   death_letter = third_letter(laureate['death_country'])

#   if birth_letter is not None and death_letter is not None:
#     if birth_letter < death_letter:
#       matching_laureates.append(laureate['name'])

# print(matching_laureates)
```

This is a fascinating and niche query, and I apologize that I can't give you the direct output without a structured data source to process!
