| --- |
| license: cc-by-4.0 |
| language: |
| - vi |
| task_categories: |
| - question-answering |
| - text-retrieval |
| tags: |
| - legal |
| - knowledge-graph |
| - neo4j |
| - vietnamese |
| pretty_name: Vietnamese legal knowledge graph |
| size_categories: |
| - 10M<n<100M |
| configs: |
| - config_name: about_act |
| data_files: |
| - split: train |
| path: data/about_act/train-*.parquet |
| - config_name: about_concept |
| data_files: |
| - split: train |
| path: data/about_concept/train-*.parquet |
| - config_name: about_subject |
| data_files: |
| - split: train |
| path: data/about_subject/train-*.parquet |
| - config_name: act_chains |
| data_files: |
| - split: train |
| path: data/act_chains/train-*.parquet |
| - config_name: act_participants |
| data_files: |
| - split: train |
| path: data/act_participants/train-*.parquet |
| - config_name: acts |
| data_files: |
| - split: train |
| path: data/acts/train-*.parquet |
| - config_name: cites |
| data_files: |
| - split: train |
| path: data/cites/train-*.parquet |
| - config_name: components |
| data_files: |
| - split: train |
| path: data/components/train-*.parquet |
| - config_name: concepts |
| data_files: |
| - split: train |
| path: data/concepts/train-*.parquet |
| - config_name: conflicts |
| data_files: |
| - split: train |
| path: data/conflicts/train-*.parquet |
| - config_name: contains |
| data_files: |
| - split: train |
| path: data/contains/train-*.parquet |
| - config_name: defines |
| data_files: |
| - split: train |
| path: data/defines/train-*.parquet |
| - config_name: differs_from |
| data_files: |
| - split: train |
| path: data/differs_from/train-*.parquet |
| - config_name: documents |
| data_files: |
| - split: train |
| path: data/documents/train-*.parquet |
| - config_name: events |
| data_files: |
| - split: train |
| path: data/events/train-*.parquet |
| - config_name: has_norm |
| data_files: |
| - split: train |
| path: data/has_norm/train-*.parquet |
| - config_name: has_version |
| data_files: |
| - split: train |
| path: data/has_version/train-*.parquet |
| - config_name: instance_of |
| data_files: |
| - split: train |
| path: data/instance_of/train-*.parquet |
| - config_name: involves |
| data_files: |
| - split: train |
| path: data/involves/train-*.parquet |
| - config_name: mentions |
| data_files: |
| - split: train |
| path: data/mentions/train-*.parquet |
| - config_name: merged_concepts |
| data_files: |
| - split: train |
| path: data/merged_concepts/train-*.parquet |
| - config_name: norm_details |
| data_files: |
| - split: train |
| path: data/norm_details/train-*.parquet |
| - config_name: norm_edges |
| data_files: |
| - split: train |
| path: data/norm_edges/train-*.parquet |
| - config_name: norms |
| data_files: |
| - split: train |
| path: data/norms/train-*.parquet |
| - config_name: relations |
| data_files: |
| - split: train |
| path: data/relations/train-*.parquet |
| - config_name: subject_parents |
| data_files: |
| - split: train |
| path: data/subject_parents/train-*.parquet |
| - config_name: subjects |
| data_files: |
| - split: train |
| path: data/subjects/train-*.parquet |
| - config_name: temporal_edges |
| data_files: |
| - split: train |
| path: data/temporal_edges/train-*.parquet |
| - config_name: temporal_versions |
| data_files: |
| - split: train |
| path: data/temporal_versions/train-*.parquet |
| - config_name: term_use_edges |
| data_files: |
| - split: train |
| path: data/term_use_edges/train-*.parquet |
| - config_name: term_uses |
| data_files: |
| - split: train |
| path: data/term_uses/train-*.parquet |
| - config_name: terms |
| data_files: |
| - split: train |
| path: data/terms/train-*.parquet |
| - config_name: text_versions |
| data_files: |
| - split: train |
| path: data/text_versions/train-*.parquet |
| --- |
| |
| # luatdo-graph |
|
|
| A knowledge graph over Vietnamese law, built from about 128,000 documents by [luatdo](https://github.com/tamnd/luatdo). |
|
|
| This is the result of running the pipeline, published so that nobody has to run it again. |
| The pipeline takes days and several hundred dollars of model calls, and the output is the same for everyone. |
|
|
| ## What is in it |
|
|
| | | | |
| | --- | --- | |
| | Nodes | 8,175,346 | |
| | Relationships | 9,119,011 | |
| | Node tables | 14 | |
| | Relationship tables | 19 | |
| | Node labels | 13 | |
| | Parquet | 623MB across 47 files | |
| | Neo4j archive | 550MB gzipped, about 3.4GB unpacked | |
|
|
| The labels present in the data are Act, Component, Condition, Document, Event, LegalConcept, Norm, Provision, Subject, TemporalVersion, Term, TermUse, TextVersion. |
| That is counted from the rows rather than read off the schema, which defines more labels than the extraction has so far filled. |
|
|
| The graph is not a shadow of the document structure. |
| Definitions, normative statements, temporal versions and act chains are all extracted by language models reading the text, with the provision each claim came from recorded on the claim. |
|
|
| ## Two shapes of the same graph |
|
|
| The Parquet files under `data/` are the graph as tables, one directory per table, and they are what the viewer above is showing. |
| Node tables have an `id` and a `labels` list. |
| Relationship tables have a `start_id`, an `end_id` and a `type`, and the endpoints join to node `id`. |
| Every table is typed, so numbers are numbers and an absent value is null rather than an empty string. |
|
|
| `luatdo-graph-2026.08.1.tar.gz` is the same graph as a Neo4j offline import set, which is what to download if you want to run queries over it rather than read it as tables. |
| It is not a Neo4j database directory, so it does not depend on a Neo4j version. |
|
|
| ## Reading the tables |
|
|
| ```python |
| import pandas as pd |
| |
| url = "hf://datasets/open-index/luatdo-graph/data" |
| docs = pd.read_parquet(f"{url}/documents/train-00000-of-00001.parquet") |
| ``` |
|
|
| Or with the datasets library, one config per table: |
|
|
| ```python |
| from datasets import load_dataset |
| |
| docs = load_dataset("open-index/luatdo-graph", "documents", split="train") |
| ``` |
|
|
| Or in duckdb, which will read the whole set of shards from a glob and join across tables: |
|
|
| ```sql |
| select d.title, count(*) as citations |
| from 'data/documents/train-*.parquet' d |
| join 'data/cites/train-*.parquet' c on c.start_id = d.id |
| group by 1 order by 2 desc limit 10; |
| ``` |
|
|
| ## Loading it into Neo4j |
|
|
| ```sh |
| luatdo neo4j install |
| ``` |
|
|
| That downloads the archive, checks it against a pinned checksum, imports it into a local Neo4j, and waits until the database answers a query. |
| It works the same on Linux, macOS and Windows. |
|
|
| By hand, with any Neo4j 5 and a container runtime: |
|
|
| ```sh |
| curl -fLO https://huggingface.co/datasets/open-index/luatdo-graph/resolve/main/luatdo-graph-2026.08.1.tar.gz |
| tar -xzf luatdo-graph-2026.08.1.tar.gz |
| docker volume create luatdo-neo4j-data |
| docker run --rm -v "$PWD/neo4j:/import:ro" -v luatdo-neo4j-data:/data -w /import \ |
| neo4j:5.26 sh ./import.sh --report-file=/data/import.report |
| docker run -d --name luatdo-neo4j -p 7474:7474 -p 7687:7687 \ |
| -v luatdo-neo4j-data:/data \ |
| -e NEO4J_AUTH=neo4j/luatdo-local \ |
| -e NEO4J_initial_dbms_default__database=luatdo \ |
| neo4j:5.26 |
| ``` |
|
|
| `import.sh` passes anything you give it through to `neo4j-admin`, where a repeated option takes the last value. |
| That is how the report is moved off the read only mount above. |
| The export belongs to whoever downloaded it and the image runs as its own user, so on a rootful docker host the report is the one file the import cannot write. |
|
|
| The database name matters. |
| Neo4j Community runs one user database, and the import writes into `luatdo`, so a server started without that setting comes up healthy and holds nothing. |
|
|
| ## The tables |
|
|
| Nodes: |
|
|
| | Table | Rows | Size | Labels | |
| | --- | --- | --- | --- | |
| | `acts` | 362 | 39KB | Act | |
| | `components` | 4,360,083 | 51MB | Component, Provision | |
| | `concepts` | 43 | 3KB | LegalConcept | |
| | `conflicts` | 0 | 1KB | | |
| | `documents` | 128,097 | 8MB | Document | |
| | `events` | 52 | 9KB | Event | |
| | `merged_concepts` | 0 | 1KB | | |
| | `norm_details` | 631 | 30KB | Condition | |
| | `norms` | 849 | 89KB | Norm | |
| | `subjects` | 168 | 8KB | Subject | |
| | `temporal_versions` | 2,031 | 96KB | TemporalVersion | |
| | `term_uses` | 337 | 89KB | TermUse | |
| | `terms` | 2,315 | 43KB | Term | |
| | `text_versions` | 3,680,378 | 467MB | TextVersion | |
|
|
| Relationships: |
|
|
| | Table | Rows | Size | |
| | --- | --- | --- | |
| | `about_act` | 247 | 10KB | |
| | `about_concept` | 0 | 1KB | |
| | `about_subject` | 305,481 | 3MB | |
| | `act_chains` | 100 | 13KB | |
| | `act_participants` | 0 | 1KB | |
| | `cites` | 758,912 | 9MB | |
| | `contains` | 4,360,083 | 30MB | |
| | `defines` | 2,555 | 29KB | |
| | `differs_from` | 0 | 1KB | |
| | `has_norm` | 849 | 11KB | |
| | `has_version` | 3,680,378 | 59MB | |
| | `instance_of` | 0 | 1KB | |
| | `involves` | 0 | 1KB | |
| | `mentions` | 0 | 1KB | |
| | `norm_edges` | 2,579 | 24KB | |
| | `relations` | 0 | 1KB | |
| | `subject_parents` | 144 | 3KB | |
| | `temporal_edges` | 7,002 | 40KB | |
| | `term_use_edges` | 681 | 15KB | |
|
|
| ## Versions |
|
|
| | Version | What changed | |
| | --- | --- | |
| | 2026.08.1 | The import scripts pass their arguments through to `neo4j-admin`, so the report can be moved off a read only mount. Later republished as Parquet as well, with the archive unchanged, so there is nothing to download again | |
| | 2026.08 | First publication | |
|
|
| ## Versioning |
|
|
| The dataset is versioned apart from the code, as `luatdo-graph-YYYY.MM.tar.gz`. |
| A corpus grows when somebody runs the pipeline over more of it, and the tool changes when somebody changes the tool, and tying the two together would mean re-uploading half a gigabyte to publish a one line fix. |
| Each luatdo release records the dataset version it was built against. |
|
|
| ## Provenance and limits |
|
|
| The source documents come from public Vietnamese legal corpora on the Hub, and the extraction on top of them is machine made. |
| Every extracted claim carries the provision it was read out of, so anything here can be checked against its source text, and anything here can be wrong. |
| Do not treat it as legal advice. |
|
|
| Some layers are much further along than others, and the row counts above are the honest account of which. |
| The document, provision, text version, citation, definition, subject, norm, temporal and act layers are populated. |
| The concept layer is not. |
| Concept mentions, concept relations, instance links, concept merges and the recorded conflicts are all empty, and the concept table itself holds a few dozen rows rather than the thousands the pipeline is capable of producing. |
| Those layers sit behind a human review queue that has not been worked through, so a query about concepts will return nothing rather than something wrong. |
|
|
| A table with no rows is published as an empty table rather than left out. |
| A layer that came out empty and a layer that was never exported are different things, and the file list is the only place that difference shows. |
|
|
| ## License |
|
|
| CC BY 4.0. |
| The underlying legal texts are Vietnamese government documents. |
|
|
