1993658fb2
Builds a relationship-rich finance dataset for text-to-RDF-triple extraction
from SEC fund disclosures, the dataset for the thesis 'Magical RDF Triples and
how to synthetize them'.
- build_rdf_dataset.py: gold (N-CEN graphs), fetch (EDGAR prospectus prose,
all books per trust), samples (per-fund segmentation, marker + plain
serializations), split (trust-level 80/10/10, no leakage)
- score_baseline.py: no-model string-match baseline + strong-model scorer
- dataset_description.{tex,pdf}: scientific description of the dataset
- data/rdf_poc/gold_graphs.jsonl: structured gold knowledge graph (2025Q3)
- Large prose/sample files and raw SEC downloads are gitignored (reproducible)
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
7 lines
142 B
Plaintext
7 lines
142 B
Plaintext
requests>=2.31.0
|
|
beautifulsoup4>=4.12.0
|
|
lxml>=5.1.0
|
|
pandas>=2.2.0
|
|
tqdm>=4.66.0
|
|
# SQLite3 is part of Python stdlib — no extra package needed
|