Tablassert

Extract knowledge assertions from tabular data into NCATS Translator-compliant KGX NDJSON — declaratively, with entity resolution built in and optional quality control.

Tablassert turns biomedical spreadsheets (Excel, CSV, TSV) into knowledge graphs ready for NCATS Translator. Declare how your columns map to subject–predicate–object statements in YAML; Tablassert resolves free text to standard CURIEs, attaches provenance and statistical annotations, and emits KGX-compliant nodes and edges.

Full Documentation — installation guides, tutorial, configuration reference, and API docs.

Quick Start

pip install tablassert

Given a CSV of gene–disease associations with p-values and sample sizes, declare the mapping in a table config (table.yaml):

template:
  source:
    kind: text
    local: ./gene-disease.csv
    url: https://example.com/data.csv
    row_slice: [1, auto]
    delimiter: ","
  statement:
    subject: { method: column, encoding: A, prioritize: [Gene] }
    predicate: associated_with
    object: { method: column, encoding: B, prioritize: [Disease] }
  provenance: { repo: PMID, publication: "12345678" }
  annotations:
    - { annotation: p_value, method: column, encoding: C }
    - { annotation: supporting_study_size, method: column, encoding: D }

Wrap it in a graph config (graph.yaml) pointing at your fullmap entity-resolution database:

name: MY_KG
version: 1.0.0
description: Gene–disease associations extracted from tabular sources.
tables:
  - ./table.yaml
fullmap: /path/to/fullmap

Build the knowledge graph:

tablassert build-kg graph.yaml

Output is one JSON object per line — nodes with Biolink categories, edges with annotations:

{"id":"HGNC:11998","name":"TP53","category":["biolink:Gene"],"taxon":"NCBITaxon:9606"}
{"id":"MONDO:0008903","name":"lung cancer","category":["biolink:Disease"]}

{"subject":"HGNC:11998","predicate":"biolink:associated_with","object":"MONDO:0008903","p_value":"1.0000e-03","supporting_study_size":"450"}

See the Tutorial for the full walkthrough.

Key Features

Declarative YAML configuration — define data transformations without writing code
Built-in entity resolution — map free text to genes, diseases, and chemicals with standard CURIEs, taxonomic filtering, and provenance, backed by an embedded redb database
Optional quality control — a three-stage audit (exact → fuzzy → BioBERT embeddings) flags low-confidence mappings
KGX compliance — emits NCATS Translator-compatible node/edge NDJSON with Biolink categories and predicates
Autonomous agent — tablassert agent derives, builds, and refines configs for whole papers
Performance & reproducibility — lazy Polars pipelines and a deterministic UV-based development environment

Installation

pip install tablassert

Or with uv: uv tool install tablassert. The base install builds knowledge graphs from CSV/TSV/Excel sources; optional extras add runtime and pipeline capabilities:

Extra	Adds	Install
`rt`	CPU-compatible Polars runtime	`pip install "tablassert[rt]"`
`qc`	three-stage QC audit (exact → fuzzy → BioBERT embeddings)	`pip install "tablassert[qc]"`
`agent`	autonomous agent (smolagents, litellm, PDF context)	`pip install "tablassert[agent]"`
`optimize`	GEPA prompt optimization for `agent --optimize` (dspy)	`pip install "tablassert[optimize]"`

QC is opt-in at build time (build-kg --qc). See the Installation guide for the full matrix and the CLI Reference for every flag.

Entity Resolution API

from pathlib import Path
from tablassert.lib import resolve_many

results = resolve_many(
    col="gene",
    entities=["TP53", "BRCA1"],
    fullmap=Path("/path/to/fullmap"),
    taxon="9606",
)
# [{"original_gene": "TP53", "gene": "HGNC:11998", "gene_name": "TP53", ...}, ...]

Point resolve_many() at a fullmap database to resolve any iterable of entity strings to CURIEs — no LazyFrame setup or NLP preprocessing required. See the Batch Resolution API for the full reference.

Documentation

Installation — install methods, extras, and development setup
Tutorial — step-by-step example with synthetic data
CLI Reference — complete command-line flag reference
Use Case Gallery — real-world configuration patterns
Configuration — graph and table configuration reference
Agent — the autonomous agent pipeline
API Reference — core functions documentation

Developing

uv sync --group dev --extra qc
uv run maturin develop --manifest-path rust/Cargo.toml
make check

See CONTRIBUTING.md for the full development loop, quality gates, and pull request guidelines.

Citation

If you use Tablassert, please cite it as described in CITATION.cff. The approach is described in:

Skye Lane Goetz, Alex K. Glen, and Gwênlyn Glusman. “MicrobiomeKG: bridging microbiome research and host health through knowledge graphs.” Frontiers in Systems Biology 5 (2025). doi:10.3389/fsysb.2025.1544432

License

Apache License 2.0

Contributors

Skye Lane Goetz — Institute for Systems Biology
Gwênlyn Glusman — Institute for Systems Biology
Jared C. Roach — Institute for Systems Biology

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- Statement type: https://in-toto.io/Statement/v1
- Predicate type: https://docs.pypi.org/attestations/publish/v1
- Subject name: tablassert-8.2.0-cp311-cp311-macosx_11_0_arm64.whl
- Subject digest: 15a85716b2289061afff664d201b76f3c8cf47e630858d80f7df444a8bfd0537
- Sigstore transparency entry: 2414482203
- Sigstore integration time: Aug 10, 2026
Source repository:
- Permalink: SkyeAv/Tablassert@4dd3351066973eeb5182ee73386fa3239ec2d7d9
- Branch / Tag: refs/heads/main
- Owner: https://github.com/SkyeAv
- Access: public
Publication detail:
- Token Issuer: https://token.actions.githubusercontent.com
- Runner Environment: github-hosted
- Publication workflow: pipy.yml@4dd3351066973eeb5182ee73386fa3239ec2d7d9
- Trigger Event: push

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This release

8.2.0

Aug 10, 2026

8.1.0

Aug 3, 2026

8.0.1

Jul 30, 2026

8.0.0

Jul 30, 2026

7.5.2

Jul 1, 2026

7.5.1

Jul 1, 2026

7.5.0

Jul 1, 2026

7.4.14

Jun 30, 2026

7.4.13

Jun 30, 2026

7.4.12

Jun 29, 2026

7.4.11

Jun 29, 2026

7.4.10

May 30, 2026

7.4.9

May 27, 2026

7.4.8

May 12, 2026

7.4.7

May 11, 2026

7.4.6

May 11, 2026

7.4.5

May 11, 2026

7.4.4

May 11, 2026

7.4.3

May 11, 2026

7.4.2

May 8, 2026

7.4.1

May 6, 2026

7.4.0

May 6, 2026

7.3.6

Apr 29, 2026

7.3.5

Apr 29, 2026

7.3.4

Apr 29, 2026

7.3.3

Apr 20, 2026

7.3.2

Apr 4, 2026

7.3.1

Apr 3, 2026

7.3.0

Apr 3, 2026

7.2.2

Apr 2, 2026

7.2.1

Apr 2, 2026

7.2.0

Apr 2, 2026

7.1.0

Mar 26, 2026

7.0.2

Mar 23, 2026

7.0.1

Mar 17, 2026

7.0.0

Mar 17, 2026

tablassert 8.2.0

Tablassert

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