# Technical Document Extraction: Image Analysis
## Diagram Components and Flow
The image depicts a **text generation and evaluation pipeline** with three core components:
1. **Critic LM** (Language Model)
2. **Augmented Output**
3. **Retriever**
### Component Connections
- **Critic LM** → **Augmented Output** (via dashed arrow)
- **Critic LM** → **Retriever** (via dashed arrow)
- **Retriever** → **Augmented Output** (via solid arrow)
### Annotation Labels
- **Relevant** (green box)
- **Supported** (green box)
- **Partially** (orange box)
- **Util: 5** (green box)
- **No Retrieval** (gray box)
## Textual Content Extraction
### Essay Generation Task
**Input**:
"Write an essay of your best summer vacation"
**Output**:
"My best summer vacation was a magical escape to the coastal town of Santorini. The azure waters, charming white-washed buildings are unforgettable."
**Augmented Output**:
- **No Retrieval** (flagged section)
"My best summer vacation was a magical escape to the coastal town of Santorini. The azure waters, charming white-washed buildings are unforgettable experience."
- **Util: 5** (annotation)
### US State Naming Task
**Input**:
"How did US states get their names?"
**Output**:
"1 of 50 states names come from persons. For instance, Louisiana was named in honor of King Louis XIV of France and Georgia was named after King George II."
**Augmented Output**:
- **Retrieve** (flagged section)
"<p>Of the fifty states, eleven are named after an individual person</p>"
- **Relevant** (annotation)
- **Retrieve** (flagged section)
"<p>LOUISIANA: Named in honor of Louis XIV of France.</p>"
- **Relevant** (annotation)
"<p>Georgia was named after King George II.</p>"
- **Partially** (annotation)
- **Util: 5** (annotation)
## Diagram Details
### Critic LM Output Analysis
- **Relevant**:
"11 of 50 states’ names come from person."
- **Supported**:
"Louisiana was named after King Louis XIV of France."
- **Partially**:
"Georgia was named after King George II."
### Retriever Steps
1. **Step 1**:
- Retrieval action: `<p>Of the fifty states, eleven are named after an individual person</p>`
- Annotation: **Relevant**
2. **Step 2**:
- Retrieval action:
- `<p>LOUISIANA: Named in honor of Louis XIV of France.</p>` (Relevant)
- `<p>Georgia was named after King George II.</p>` (Partially)
- Annotation: **Util: 5**
## Key Trends and Data Points
- **Essay Task**:
- Original output lacked retrieval (flagged as "No Retrieval").
- Augmented output added contextual details (e.g., "unforgettable experience").
- **State Naming Task**:
- 11/50 states named after individuals (supported by retrieval).
- Louisiana and Georgia examples demonstrate partial relevance (Util: 5).
## Critical Observations
1. **Annotation Consistency**:
- "Relevant" and "Supported" annotations align with factual accuracy.
- "Partially" indicates partial alignment with the input query.
2. **Utility Scores**:
- "Util: 5" suggests high utility for the augmented output in both tasks.
3. **Retrieval Process**:
- Stepwise retrieval (Step 1 → Step 2) improves output relevance.
## Conclusion
The diagram illustrates a feedback loop where the Critic LM evaluates outputs, triggers retrieval actions, and refines the augmented output. Annotations quantify relevance and utility, ensuring alignment with input queries.
