Datasets:
dataset card: v2.0.1 RDF + full-record Parquet release
Browse files
README.md
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- knowledge-graph
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- rdf
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- n-triples
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- llm-generated
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pretty_name: GPTKB v2
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size_categories:
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- 10M<n<100M
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---
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# GPTKB v2
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**[gptkb.org](https://gptkb.org/)**.
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| --- | --- |
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| License | [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) |
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## What this is
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The graph served by the SPARQL endpoint at
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[gptkb.org/query](https://gptkb.org/query/). Entities, predicates and
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concepts are ID-based IRIs:
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`xsd:integer`) are deferred. Concepts carry no `rdfs:subClassOf`: the
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source has no hierarchy to export.
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A fact in GPTKB v2 has **six** terms, not three: alongside the
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disambiguated subject, predicate and object, it records the *wording*
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each was stated with, and the provenance of how that wording was
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resolved. A triple has nowhere to put either
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```
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```
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the
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## Earlier versions
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- knowledge-graph
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- rdf
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- n-triples
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- parquet
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- llm-generated
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pretty_name: GPTKB v2
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size_categories:
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- 10M<n<100M
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---
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# GPTKB v2
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Browse, query or ask the full knowledge base at
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**[gptkb.org](https://gptkb.org/)**.
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Two artifact lines, one knowledge base (snapshot `gpt51_270226`,
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38,450,135 source facts):
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| File | What it is |
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| --- | --- |
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| `gptkb_v2.0.1_rdf.nt.gz` | **Simplified RDF export — use this one.** |
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| `gptkb_v2.0_full_record/` | **The full six-term record**, as Parquet. |
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| `gptkb_v2.0_rdf.nt.gz` | Superseded interim RDF export, kept for citability. |
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## Simplified RDF export (`gptkb_v2.0.1_rdf.nt.gz`)
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| --- | --- |
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| Format | N-Triples, gzipped (425 MB; 4.1 GB uncompressed) |
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| Size | 42,327,043 lines → **41,511,580 distinct triples** once loaded |
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| sha256 | `202d9e32f28548ae661b3f8cf9db83411fe18a063702f9c98df4b553d750e801` |
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| License | [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) |
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The graph served by the SPARQL endpoint at
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[gptkb.org/query](https://gptkb.org/query/). Entities, predicates and
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concepts are ID-based IRIs:
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`xsd:integer`) are deferred. Concepts carry no `rdfs:subClassOf`: the
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source has no hierarchy to export.
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**v2.0.1 vs the interim v2.0 file.** Same knowledge base, same
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snapshot — the difference is how much of it the pipeline had
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disambiguated at export time. The interim file was cut when roughly
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half of the named-entity objects had been resolved to entity IDs;
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facts whose object was still unresolved could mint no IRI and were
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skipped. This re-export was cut after the disambiguation pipeline
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completed: about one million further entities exist in the catalog,
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named-entity coverage is ~99.8%, and only 62,600 of the 38,450,135
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source facts remain unexportable. Concretely: the loaded graph grows
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from 32.8M to 41.5M triples, and `E14` (United States of America) now
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carries 168 `skos:altLabel` surface forms where the interim file had
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127.
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### Loading
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```bash
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# Virtuoso, QLever, Jena, rdflib — anything that reads N-Triples
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gunzip -c gptkb_v2.0.1_rdf.nt.gz | head
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```
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Load into a named graph of `<https://gptkb.org/gptkb>` to match the
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IRIs the file already carries.
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## The full record (`gptkb_v2.0_full_record/`)
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A fact in GPTKB v2 has **six** terms, not three: alongside the
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disambiguated subject, predicate and object, it records the *wording*
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each was stated with, and the provenance of how that wording was
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resolved. A triple has nowhere to put either — in the RDF export,
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`<E0> <P0> <C0>` appears five times because five differently worded
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facts about Vannevar Bush resolve to it, and RDF set semantics keep
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one. That collapse is the entire difference between the `.nt` file's
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42,327,043 lines and the 41,511,580 triples a store loads from it.
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This directory is the release the RDF export cannot be: the relational
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tables themselves, streamed to Parquet (zstd) with every surface form,
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pipeline status and batch id intact.
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| Table | Rows | Contents |
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| --- | --- | --- |
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| `triples-0000*.parquet` (8 shards) | 38,450,135 | one row per fact: ids **and** surface labels for subject/predicate/object, object type + statuses, `object_description`, the 7 pipeline batch ids, `created_at` |
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| `instance_triples.parquet` | 2,528,556 | the instanceOf specialization (entity → concept, + CD/CDG batch ids) |
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| `entities.parquet` | 2,297,995 | entity catalog: id, canonical label, description, status, provenance |
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| `predicates.parquet` | 207,633 | predicate catalog |
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| `concepts.parquet` | 66,523 | concept catalog |
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| `batches.parquet` | 123,444 | the provenance containers the batch-id columns point into |
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| `manifest.json` | — | row counts, shard list, source snapshot |
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Surface-form variation is preserved as distinct rows: "John Smith,
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bornIn, NYC" and "Jane Smith, bornIn, Big Apple" are two rows even
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when both objects resolve to the same `E…` id — the wording is the
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disambiguation evidence, and it is the point of the project.
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### Loading
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```python
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import duckdb
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con = duckdb.connect()
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con.sql("SELECT subject_label, predicate_label, object_label, object_id "
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"FROM 'gptkb_v2.0_full_record/triples-*.parquet' "
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"WHERE object_id = 'E14' LIMIT 10")
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```
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```python
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import pandas as pd
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entities = pd.read_parquet("gptkb_v2.0_full_record/entities.parquet")
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```
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All columns are nullable strings, faithful to the source; `created_at`
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is the raw pipeline timestamp text.
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## Earlier versions
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