Inconsistent output on Dolly NER

Here is a block of example.yml:
```
- text: Jack and Jill went up the hill.
spans:
- text: Jack
is_entity: true
label: PERSON
reason: is the name of a person
- text: Jill
is_entity: true
label: PERSON
reason: is the name of a person
- text: went up
is_entity: false
label: ==NONE==
reason: is a verb
- text: hill
is_entity: true
label: LOCATION
reason: is a location
```

Block of fewshot.cfg
```
[paths]

[nlp]
lang = "en"
pipeline = ["llm"]
batch_size = 128

[components]

[components.llm]
factory = "llm"

[components.llm.model]
@llm_models = "spacy.Dolly.v1"
name = "dolly-v2-3b"

[components.llm.task]
@llm_tasks = "spacy.NER.v3"
labels = PERSON,ORGANISATION,LOCATION

[components.llm.task.examples]
@misc = "spacy.FewShotReader.v1"
path = "example.yml"

[components.llm.task.normalizer]
@misc = "spacy.LowercaseNormalizer.v1"
```

Block of pipeline run:
```
from spacy_llm.util import assemble
nlp = assemble(
"fewshot.cfg"
)
doc = nlp("Jack and Jill went up the hill.")

print(f"Text: {doc.text}")
print(doc.ents)
print(f"Entities: {[(ent.text, ent.label_) for ent in doc.ents]}")
```

There are inconsistencies in output, and how do i resolve it?
```
python spacyllmtry.py
Text: Jack and Jill went up the hill.
(Jack, Jill, hill)
Entities: [('Jack', 'PERSON'), ('Jill', 'PERSON'), ('hill', 'LOCATION')]
python spacyllmtry.py
Text: Jack and Jill went up the hill.
()
Entities: []
```