Error when trying to parse multiple rows via Relational API `values`

### What happens?

When trying to utilize the `values()` function for converting a native Python object into a relation, I am unable to create a relation with multiple rows and columns.

### To Reproduce

```
import duckdb

conn = duckdb.connect()

# 1) Base `VALUES` query using straight SQL (correct/expected)
conn.execute("FROM (VALUES (1, 'a'), (2, 'b'))").df()

# 2) 1 row, multiple columns relation (correct/expected)
conn.values([1, 'a']).df()

# 3) 2 rows, multiple columns relation (multiple different attempts - same output below)
conn.values([1, 'a'], [2, 'b']).df()
conn.values([((1), ('a')), ((2), ('b'))]).df()
conn.values(([1, 'a']), ([2, 'b'])).df()
conn.values([[1, 'a'], [2, 'b']]).df()

# 4) 2 rows, multiple columns relation (works, but typed as lists)
conn.values(([1], ['a']), ([2], ['b'])).df()

# 5) Attempted to remove the lists 🤷🏼
conn.values((1, 'a'), (2, 'b'))
```

Outputs:
```
# 1)
col0 col1
0 1 a
1 2 b

# 2)
col0 col1
0 1 a

# 3)
col0 col1
0 [1, a] [2, b]

# 4)
[1] ['a']
0 [1] [a]
1 [2] [b]

# 5)
Traceback (most recent call last):
File "", line 1, in
duckdb.duckdb.BinderException: Binder Error: Referenced column "a" not found in FROM clause!
```

### OS:

OSX 15.6

### DuckDB Package Version:

1.4.0

### Python Version:

3.11

### Full Name:

Joe Rimsky

### Affiliation:

Gecko Robotics

### What is the latest build you tested with? If possible, we recommend testing with the latest nightly build.

I have tested with a stable release

### Did you include all relevant data sets for reproducing the issue?

Not applicable - the reproduction does not require a data set

### Did you include all code required to reproduce the issue?

- [x] Yes, I have

### Did you include all relevant configuration to reproduce the issue?

- [x] Yes, I have

Start by running the provided Python reproduction against conn.values() and compare its multi-row behavior with the SQL VALUES query. Trace the Relational API values entry point and identify how nested native objects are interpreted. Done means multiple rows and columns produce scalar columns with the same result shape as SQL VALUES, with coverage for the reported cases.

Written by the indexing model from the issue text.