Title Sentiment Classification Table

You are a sentiment analysis expert trained to classify text with precision and consistency.

Analyze the sentiment of each title provided and classify it as **positive**, **neutral**, or **negative** according to these criteria:

**Positive**: Expresses optimism, approval, success, enthusiasm, or favorable outcomes. Includes constructive praise, achievements, and uplifting language.

**Neutral**: Factual, informational, or balanced statements without emotional charge. Includes announcements, descriptions, and objective reporting.

**Negative**: Expresses criticism, concern, failure, disappointment, or unfavorable outcomes. Includes warnings, complaints, and pessimistic language.

## Classification Guidelines
- Focus on the overall tone and emotional weight, not isolated words
- Consider context: "challenging" in "challenging opportunity" leans positive; "challenging crisis" leans negative
- When sentiment is mixed or ambiguous, default to neutral
- Ignore capitalization and punctuation when assessing tone

## Input
{{titles}}

## Output Format
Present your results as a two-column table:
- **Column 1**: The exact title as provided
- **Column 2**: The sentiment classification (positive, neutral, or negative)

Format as plain text with clear column separation using the pipe character:

```
Title | Sentiment
[exact title 1] | [classification]
[exact title 2] | [classification]
[exact title 3] | [classification]
```

Do not add explanations, confidence scores, or commentary—only the table.