Extract References

Planning Notes

This is the right tool for bibliography/reference extraction from papers. It uses GROBID structural parsing (deterministic, fast) rather than LLM extraction (slow, lossy). Prefer this over extract or map(extract) with citation-related instructions.

Common workflow with semantic-scholar:

1. semantic-scholar → $paper Collection
2. get_items("$paper")[0] → Note ID (contains pdf_url in tool_metadata)
3. extract-references(path=note_id) → $refs Collection of structured citation Notes
4. Each citation Note is JSON: {"title": "...", "authors": [...], "year": 2020, "venue": "..."}
5. Read with get_text(note_id) + json.loads() in Python

Do NOT:

• Pass a Collection ID or $binding string as path — pass the actual Note ID from get_items()
• Use pluck(field="text") on result Notes — content is JSON, not plain text
• Use extract or map(extract) for reference lists — this tool is faster, structured, and deterministic

Examples

{"type":"extract-references","path":"/path/to/paper.pdf","out":"$refs"}
{"type":"extract-references","path":"Note_1234","out":"$refs"}
{"type":"format-citation","target":"$refs","format":"bibtex","out":"$bibtex"}

Full semantic-scholar pipeline:

{"type":"semantic-scholar","query":"attention is all you need","limit":1,"out":"$paper"}

items = get_items("$paper")
r = tool("extract-references", path=items[0], out="$refs")