autojudge-annotate 0.3.3

Manual relevance annotation tools for TREC AutoJudge

Autojudge Annotate

A tool for human annotation of RAG report quality. Generates a self-contained HTML file that annotators open in a browser — no server required.

Annotators highlight relevant passages, rate report quality, and add comments. All work is auto-saved to the browser's localStorage and can be exported as JSONL.

Installation

uv pip install ./auto-judge-annotate

Requires autojudge-base and click.

Usage

autojudge-annotate \
    --rag-responses path/to/runs/ \
    --rag-topics path/to/topics.jsonl \
    --output annotator.html \
    --dataset my-dataset \
    --show-documents

Then open annotator.html in a browser.

Options

Flag	Description
--rag-responses	Directory containing report files (any extension, JSONL format)
--rag-topics	JSONL file with evaluation topics/requests
--output	Output HTML file path
--dataset	Freetext label included in annotation output
--show-documents	Enable citation document popups (increases file size)
--topic ID	Filter to specific topics (repeatable)

Filtering topics

For large datasets, pass only the topics you need:

autojudge-annotate \
    --rag-responses runs/ \
    --rag-topics topics.jsonl \
    --output annotator.html \
    --dataset my-dataset \
    --topic 1101 --topic 1102 --topic 1103

Annotation worksflow

Before you begin, enter your username, which persists across sessions and is exported to annotation file.

The topbar Mode selector switches between three annotation modes:

Reports mode

Annotate full report text per topic/run.

1. Select a topic from the sidebar, then a run
2. Read the request (title, problem statement, background) and the report
3. Highlight relevant passages by selecting text — selections crossing sentence boundaries are automatically split into per-sentence subspans with sentence_idx
4. Click [DocId] citation markers to view source documents in a popup (when --show-documents is enabled)
5. Choose a rating and add optional comments

Documents mode

Annotate individual source documents per topic.

1. Select a topic, then a run, then a document from the sidebar
2. Read the document text (title + body)
3. Highlight relevant passages
4. Choose a rating and add optional comments

Citations mode

Step through report sentences and annotate the relationship between each sentence and its cited documents with dual spans (report spans + document spans).

1. Select a topic, then a run from the sidebar; sentences appear in the sidebar
2. Use the sentence stepper (Prev/Next buttons) or click a sentence in the sidebar
3. The current sentence is displayed in a yellow box; highlight text to create report spans
4. If the sentence has citations, the cited document appears below; highlight text to create document spans
5. For sentences with multiple citations, use the citation tabs to switch between documents
6. Choose a rating and add optional comments
7. The sidebar shows checkmarks on fully annotated sentences (all citations rated)

Common features

• Auto-save: every change is saved to localStorage immediately
• Progress tracking: sidebar shows checkmarks on annotated items and completion counts per topic
• Ratings: Perfect, Mostly Good, So-so, Bad, or Not rated
• Download: click Download JSONL to export all annotations
• Clear all: small button at the bottom of the sidebar to reset all annotations (with confirmation)
• Username: persists across sessions via localStorage

Output format

Each annotation is a JSON line. The format varies by mode:

Report annotation

{
  "dataset": "my-dataset",
  "request_id": "1101",
  "run_id": "run1",
  "team_id": "teamA",
  "topic_id": "1101",
  "username": "alice",
  "rating": "Mostly Good",
  "comment": "Good coverage but missing key detail",
  "spans": [
    {"start": 0, "end": 45, "text": "First relevant passage", "sentence_idx": 0},
    {"start": 46, "end": 120, "text": "Second passage from next sentence", "sentence_idx": 1}
  ],
  "report": { ... }
}

Document annotation

{
  "dataset": "my-dataset",
  "request_id": "1101",
  "docid": "doc-abc-123",
  "topic_id": "1101",
  "username": "alice",
  "rating": "So-so",
  "comment": "",
  "spans": [
    {"start": 10, "end": 85, "text": "Relevant passage from document"}
  ],
  "document": { ... }
}

Citation annotation

{
  "dataset": "my-dataset",
  "request_id": "1101",
  "topic_id": "1101",
  "username": "alice",
  "rating": "Perfect",
  "comment": "Sentence accurately reflects source",
  "spans": [
    {"start": 0, "end": 50, "text": "Document passage supporting the claim"}
  ],
  "report_spans": [
    {"start": 0, "end": 30, "text": "Sentence text being verified"}
  ],
  "citation": {
    "report": { ... },
    "sentence_idx": 2,
    "sentence": {"text": "The full sentence text.", "citations": ["doc-abc-123"]},
    "docid": "doc-abc-123",
    "document": { ... }
  }
}