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            "data/quads-f8f1bbec7b0666d14af34b0653f8f8d0c158fb44d4db6c26c8efb3fd92cca8d8-00000.parquet",
            "data/quads-cb87178268131aa586cafbc69de635e4dbf7f6d8d43c597662845562ab4b00db-00000.parquet",
            "data/quads-e48e73a798680b57ce024747202983cd1bd13b9883abbed2dc2bdac772985388-00000.parquet",
            "data/quads-bfebf46b48c53d1f6f001157357944645d2e5e5ac39f72fa971649948392ad5a-00000.parquet",
            "data/quads-fd485de1ab85b722132fd653f862f1dc225b7ef655a70770e2da42a4db4892a9-00000.parquet",
            "data/quads-fa6ce85a5b259daacc8d3b22291fbd6d5aff86a5fab937b094d1120bcfe037ed-00000.parquet",
            "data/quads-55d4e8e0686332a8bf07cef184b322a856e2a75f1e36b6fbbd4e2dd233bf2aba-00000.parquet",
            "data/quads-bacbd491ea1769cc133e04b804c1921d55902a568d054026ddfb6099eacb43f8-00000.parquet",
            "data/quads-efe0648eb9846a0b28f3b2dfeebd8d105fef26b2cbd5f0947decb9f7b8489d74-00000.parquet",
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            "data/quads-55fd661e42f8c0f93a4053e9168b47304bc2ebfe748a4981eee2f40502d40720-00000.parquet",
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            "data/quads-265449f2a06f9f3009fc30fab6b4284fb937c51de5c65b4d9ef10099e426dfc6-00000.parquet",
            "data/quads-94ee305a188a9314328730d452d764f7566945c806dde18f0e41511dbecbb418-00000.parquet",
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            "data/quads-27a13c3214c1e4e261ec028b1c9d177cede640185e718bd002eafb4b856f57b8-00000.parquet",
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            "data/quads-c40e75027e7de16c2029908cfaee03deb0bc9b97681172e331782952aff12bb7-00000.parquet",
            "data/quads-d5f308601097a4bed6499dddeae2e4117ea5ebcd71d28f358c0520b039f52dad-00000.parquet",
            "data/quads-6e4bd4315b69a3484430effa4ef260458e3d3fe0873140b86313f22e3bcfffb2-00000.parquet",
            "data/quads-8059d16eeed81bba642c5153321b85f513ed290c75f1a4aca1a6e07d328e6e88-00000.parquet",
            "data/quads-d69b882e6d3caf6fb522254585819c80c0329ef1d168b20c0af2ad8a66fe2c74-00000.parquet",
            "data/quads-60e335fb5ea1db11996d50271cb46b187caf1cc73fcaf42294ee8aaef514d835-00000.parquet",
            "data/quads-044689545b0c396f30a4266dd4090ad4aab8d597eb4bfc6a79b878e7dc140294-00000.parquet",
            "data/quads-b5dfab05638be6cb7a53c02fc94fe5123030beda841aaf2173e07e34bac54fd4-00000.parquet",
            "data/quads-225088a4d80f49ab441a85c8a62036e1340d3c6522a32792302ea213daffd842-00000.parquet",
            "data/quads-35f75613c5336d0b3c6491491f80f353e6a75178f4990fab3e1438284b2275b2-00000.parquet",
            "data/quads-5ba4a69bf1d4be72fa7b939ec69b71a4bed73021785bec84eb07bc37997d8077-00000.parquet",
            "data/quads-435e0f3af8829dc9ac74a9269202827e83cccc54ab2b184c1f3ad69504aae199-00000.parquet",
            "data/quads-0c3df67ad0ca2c9142cd7d73d5edbefb27ee43399904fb44c0992db9aeecf93b-00000.parquet",
            "data/quads-098ab4f49df8715323409b096e9312d208d089c2ae4ec76a6c55c7e1022cdcfe-00000.parquet",
            "data/quads-872049a30badd5b65f558c93c8008881584382a5bd6376b6395ba11b83394279-00000.parquet",
            "data/quads-45f2d7fcb8f91d73f0807a68f5d6971cc65d82bb8763ca6ab0e42e5a9333ff36-00000.parquet",
            "data/quads-0e894f738f1435bd0861ab81208ba950c54a26121b903587013b70130fd4cc73-00000.parquet",
            "data/quads-b74f6d142f389ba0944e9ec01489e12ae3de4340e706ff598e460d4a51a18b71-00000.parquet",
            "data/quads-7116c9368da6e132c36e57aca29b4c72541a50e06a97cc9c0f38fb2a74867120-00000.parquet",
            "data/quads-29386367aee092a26137ac86310631f2e377176c12224b9af4fa8d94dc90cccb-00000.parquet",
            "data/quads-abf98c686342027f3042cf65ac5e5c805d73f38bbfd621562984b07fdc7b6f14-00000.parquet",
            "data/quads-69aa0d8ffd8f08173c46b7aa40b8fbe767730c8cb50e1a153eeb33f1ac5e58e8-00000.parquet",
            "data/quads-8d9fc2d595db123d15bc99cc80ca8dcbf96e28aa07b70926d2d09a4e9d869790-00000.parquet",
            "data/quads-3ff2b0eeefa38065fc65976a6278db7cf9c6254ee21ce04326c66f456b4570a2-00000.parquet",
            "data/quads-e03d16a5af64439df4baa8a2d4e6c02e876e3b6277e927c25e8d296b829232cc-00000.parquet",
            "data/quads-ce019c01806febc12384cfbef002fca21f3ffa421146c79019555a8fce74cfc0-00000.parquet",
            "data/quads-b46a0e8507b2af62bbda9e8c7f82a8e875018729edbf2921e3d64c38ab7cf30a-00000.parquet",
            "data/quads-1aa88a19cabfc0325e2352c899173db2868aeb837748ee4a03a0b308bb7306ad-00000.parquet",
            "data/quads-ad0b8aa61b2a58faaff09d10065a85a8ae40d3df600afec73ade5e24f40243ae-00000.parquet",
            "data/quads-df4c1da575b1d34bd98aa957e8ea1c90502982524189a8805806706892b91432-00000.parquet",
            "data/quads-3758c1c723cca3a8990327515af3cb31c82d7fe74e59b4c7f9c9b264fa3fdb17-00000.parquet",
            "data/quads-d375373f2c2ad7d4485a865b4c3bcb40cb5d88e303eca2939e3397725a15a51d-00000.parquet",
            "data/quads-81366fc0194c71da2665810f4eafe194f018d25306bf5e8991c07e7351c40854-00000.parquet",
            "data/quads-ec23caea41b17b544c0cf72dccef9318d643b2cf9ad32e8f062d89ecdf413a5a-00000.parquet",
            "data/quads-8d99fc24c0a5ad85d78cda95f36c8b88a9a850641f25832e8b12e859b3491ce3-00000.parquet",
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            "data/quads-5d00c0a61c49b81fb9f2ca5f3fdf8b089e9978f28850f8a21464283ca2490971-00000.parquet",
            "data/quads-8ec959e4c1acfb570524710e8335a5892567aec255036f4364b94f772a1abb00-00000.parquet",
            "data/quads-c2bab7e7a57be9f984371d9617f541b5029763b4f215e0ad5c9f945483d1b08f-00000.parquet",
            "data/quads-ba7822eb6fb951101f5892c10d9b300790087a9773e1e230460e9c80acb8b6d8-00000.parquet",
            "data/quads-feaf90bb76e6686ec874e69bfccf3f1fdef8e1d6cbf5da4e2d75099c958883ef-00000.parquet",
            "data/quads-1e5f3c91362f18001bae704dacd0dddd89b8b2e01880ca5d94ae4ad881b06270-00000.parquet",
            "data/quads-054cdf1d80eb45463c57c1d996ea7e00d593f3dc2af4a74341e1bc134105ab0f-00000.parquet",
            "data/quads-2e2f20cdf4d5712222e97ca76c95f4dfc99ef2495e7bef8c26e972bbe0fd3f1e-00000.parquet"
          ],
          "split": "train"
        }
      ]
    }
  ],
  "license": "cc-by-sa-4.0",
  "pretty_name": "Stack Overflow knowledge graph: Go",
  "size_categories": [
    "100M<n<1B"
  ],
  "tags": [
    "stackoverflow",
    "knowledge-graph",
    "rdf",
    "n-quads",
    "sparql",
    "parquet",
    "retrieval-augmented-generation"
  ],
  "task_categories": [
    "question-answering",
    "text-retrieval"
  ]
}
---

# Stack Overflow knowledge graph: Go

This dataset contains Stack Overflow discussions selected by the `go` programming-language tags using the release's selection registry. The selection refers to programming languages; posts can contain text in different natural languages.

The RDF export is produced by [stack2graph](https://github.com/tha-atlas/Stack2Graph).

This Hugging Face dataset provides Parquet tables of RDF quads and a reproducible RDF archive
for graph retrieval, SPARQL analysis and retrieval-augmented question answering.
It contains the same selected RDF shards, schema and shared documentation as the
corresponding Mozilla Data Collective (MDC) publication for the same export identity.
The root dataset card and schema image provide the Hugging Face presentation;
the archive retains its portable README and exact file inventory.

The programming-language selection is described below. It does not establish the
natural languages of post text. The `quads` configuration exposes the entire graph
as the `train` storage split; it is not an evaluation split or a curated training
corpus. Quad counts are not counts of unique questions or question-answer pairs.

## Files on Hugging Face

| Path | Contents |
| --- | --- |
| `data/quads-*.parquet` | Zstandard-compressed quad tables for the Dataset Viewer and streaming |
| `data/dataset.tar.gz` | Reproducible archive containing `graphs/` RDF shards, `README.md` and `publication.json` |
| `publication.json` | The same shard inventory as inside the archive, including stored-file SHA-256 values and export identity |
| `release.json` | Archive path, compressed byte count and SHA-256, plus card, inventory and diagram hashes |
| `assets/kg-schema.svg` | Schema diagram embedded in this card |
| `README.md` | This dataset card with Hugging Face metadata |

The RDF paths in `publication.json` are paths inside the archive. They are not
separate downloadable shard paths in this repository. The root `release.json`
identifies the compressed archive; individual RDF hashes identify its extracted
files. The export identity is a build fingerprint, not an archive checksum.

## Parquet schema and streaming

Each row is one RDF quad. The UTF-8 string columns `subject`, `predicate`,
`object` and `graph` use RDF term syntax: IRIs retain angle brackets, literals
retain quotes and language/datatype annotations, and blank nodes retain their
identifiers. An empty `graph` denotes the default graph. Reconstruct N-Quads by
joining these terms with spaces and appending ` .`; omit an empty graph term.
The original RDF archive preserves the original source bytes.

The generated YAML configuration lists the exact Parquet files for this release,
so historical files do not enter the current dataset. Use the repository's full
commit SHA to reproduce a release:

```python
from datasets import load_dataset

quads = load_dataset(
    "NAMESPACE/DATASET_REPOSITORY",
    name="quads",
    split="train",
    revision="FULL_COMMIT_SHA",
    streaming=True,
)
```

Parquet rows preserve graph statements, including duplicates and shared-shard
overlap. Their count agrees with the quad count in the source publication inventory.
The four columns are RDF terms, not flattened natural-language question/answer fields.

## Download and unpack

Download the archive and manifests from the **Files and versions** tab. For a
reproducible download, select a specific repository commit and obtain all files
from that same commit. The following Python example uses the official
[`huggingface_hub` download API](https://huggingface.co/docs/huggingface_hub/en/guides/download).
Replace the repository placeholder with this dataset's ID and the revision with
its full commit SHA:

```python
from huggingface_hub import snapshot_download

snapshot_path = snapshot_download(
    repo_id="NAMESPACE/DATASET_REPOSITORY",
    repo_type="dataset",
    revision="FULL_COMMIT_SHA",
    allow_patterns=[
        "README.md",
        "assets/kg-schema.svg",
        "data/dataset.tar.gz",
        "publication.json",
        "release.json",
    ],
    local_dir="dataset-download",
)
```

Check the downloaded archive's byte count and SHA-256 against `release.json`,
then unpack it into a new directory:

```sh
mkdir dataset-unpacked
tar -xzf dataset-download/data/dataset.tar.gz -C dataset-unpacked
```

Check extracted RDF file sizes and SHA-256 values against `publication.json`
before loading. Preserve the directory layout and named graph IRIs. Load these
files into an RDF dataset or quad store; this release is an N-Quads archive
alongside the Parquet projection configured for `datasets.load_dataset()`.
RDF loading and SPARQL examples follow below.

## Release

| Field | Value |
| --- | --- |
| Source snapshot | `stackexchange_20260630_sakura` |
| Source release date | 2026-06 |
| Source archive | `stackexchange_20260630/stackoverflow.com.7z` |
| RDF format | N-Quads |
| RDF shards | 829 |
| Quads across all included shards | 19880367 |
| Named graphs | 41 |
| Stored RDF shard bytes | 4251653864 |
| Shard compression | none |
| Mapping version | `kg-map-5-streamed-count-acceptance` |

The byte count is the sum of the RDF files as stored inside the archive. The
size of the downloadable archive also depends on compression and the
included metadata.

## Contents and selection

The selected language graph is `http://stackoverflow.com/go`. Schema statements are
stored in `http://stackoverflow.com/schema`. The package also includes the full set of shared
tag-documentation shards, including documentation assigned to other language
graphs. The counts below cover every included shard.

| Named graph IRI | Shards | Quads | Stored bytes |
| --- | ---: | ---: | ---: |
| `http://stackoverflow.com/.net` | 1 | 509,802 | 106,946,489 |
| `http://stackoverflow.com/abap` | 1 | 28,199 | 7,135,975 |
| `http://stackoverflow.com/assembly` | 1 | 108,506 | 24,486,120 |
| `http://stackoverflow.com/bash` | 1 | 269,740 | 58,415,774 |
| `http://stackoverflow.com/c` | 1 | 397,463 | 82,602,742 |
| `http://stackoverflow.com/c%23` | 2 | 747,572 | 154,579,782 |
| `http://stackoverflow.com/c%2B%2B` | 1 | 547,224 | 115,565,769 |
| `http://stackoverflow.com/cobol` | 1 | 22,806 | 5,905,661 |
| `http://stackoverflow.com/css` | 1 | 377,632 | 79,878,757 |
| `http://stackoverflow.com/dart` | 1 | 173,422 | 38,418,337 |
| `http://stackoverflow.com/elixir` | 1 | 53,770 | 13,214,613 |
| `http://stackoverflow.com/erlang` | 1 | 70,831 | 17,015,911 |
| `http://stackoverflow.com/extra-languages` | 4 | 1,946,660 | 411,030,194 |
| `http://stackoverflow.com/f%23` | 1 | 99,577 | 23,061,999 |
| `http://stackoverflow.com/fortran` | 1 | 69,210 | 16,302,861 |
| `http://stackoverflow.com/go` | 782 | 6,652,225 | 1,426,762,326 |
| `http://stackoverflow.com/haskell` | 1 | 130,034 | 29,549,858 |
| `http://stackoverflow.com/html` | 1 | 564,991 | 118,397,694 |
| `http://stackoverflow.com/java` | 2 | 852,778 | 175,779,641 |
| `http://stackoverflow.com/javascript` | 2 | 835,318 | 176,973,616 |
| `http://stackoverflow.com/julia` | 1 | 78,196 | 18,129,118 |
| `http://stackoverflow.com/kotlin` | 1 | 235,993 | 51,596,215 |
| `http://stackoverflow.com/lisp` | 1 | 51,116 | 12,303,281 |
| `http://stackoverflow.com/lua` | 1 | 121,394 | 27,520,033 |
| `http://stackoverflow.com/matlab` | 1 | 192,261 | 42,328,114 |
| `http://stackoverflow.com/objective-c` | 1 | 295,433 | 65,168,125 |
| `http://stackoverflow.com/perl` | 1 | 199,111 | 43,997,237 |
| `http://stackoverflow.com/php` | 1 | 599,966 | 124,416,158 |
| `http://stackoverflow.com/powershell` | 1 | 246,683 | 54,868,728 |
| `http://stackoverflow.com/prolog` | 1 | 52,218 | 12,630,513 |
| `http://stackoverflow.com/python` | 2 | 832,615 | 172,503,416 |
| `http://stackoverflow.com/r` | 1 | 309,658 | 65,272,221 |
| `http://stackoverflow.com/ruby` | 1 | 332,599 | 71,344,012 |
| `http://stackoverflow.com/rust` | 1 | 141,564 | 31,460,455 |
| `http://stackoverflow.com/scala` | 1 | 225,800 | 49,890,758 |
| `http://stackoverflow.com/schema` | 1 | 246 | 42,209 |
| `http://stackoverflow.com/shell` | 1 | 231,941 | 51,162,808 |
| `http://stackoverflow.com/sql` | 1 | 385,479 | 82,063,553 |
| `http://stackoverflow.com/swift` | 1 | 305,458 | 65,138,858 |
| `http://stackoverflow.com/typescript` | 1 | 303,648 | 66,849,340 |
| `http://stackoverflow.com/vb.net` | 1 | 281,228 | 60,944,593 |

Questions with tags for several programming languages can appear in several
language packages. Totals from different packages therefore overlap.

## Graph model

Each N-Quads statement contains a subject, predicate, object and named graph IRI.
The named graph records the language selection that contains the statement.
Entities keep the same IRIs across language graphs, so the same question can be
queried in several contexts without introducing a separate question identity.
Files are storage shards; splitting a graph across files does not create new
logical graphs.

The vocabulary uses the namespace `http://stackoverflow.com/schema#`, abbreviated
as `so:` below. Its RDF/OWL definitions are included in `http://stackoverflow.com/schema`.

Questions connect to answers, comments, tags and other questions. The relationship
table below gives the direction of each predicate and its exported inverse.
An accepted answer is also an answer, and acceptance edges are present only when
resolved from the source. Comments can also belong to tag documentation posts.
The diagram below shows these entities and relationships.

![Stack Overflow knowledge graph schema: questions, answers, comments, tags and their relationships](assets/kg-schema.svg)

The diagram's combined "Other question" node illustrates the possible directions of
`so:duplicateOf`. It does not assert that a pair of questions is marked as a
duplicate in both directions. Each arrow requires its own source PostLinks
record. Neither `so:duplicateOf` nor `so:linkedTo` has an automatically
exported inverse; an incoming edge is a separate source relation, not a generated
reverse of the outgoing edge. An incoming edge is stored in its source question's
language graph, so displaying it can require loading another language package.

### Timestamps

Timestamps are datatype properties whose objects are `xsd:dateTime` literals.
Each field is a separate RDF statement. In the diagram, rectangular
panels group these properties beside their entities; the panels are not RDF
entities. Missing source values produce no statement.

| Property | Meaning | Applicable entities |
| --- | --- | --- |
| `so:creationDate` | Creation time | Questions, answers, tag documentation and comments |
| `so:lastEditDate` | Last edit time | Questions, answers and tag documentation |
| `so:lastActivityDate` | Last activity time | Questions, answers and tag documentation |
| `so:communityOwnedDate` | Conversion to community wiki | Questions, answers and tag documentation |
| `so:closedDate` | Closure time | Questions |

The embedded SVG shows representative panels for the question, an answer and a comment.
The same rules apply to accepted answers, answer comments and tag documentation
as listed above. For example, a question's creation time is represented as the
following triple, within its named graph (the value is illustrative):

```turtle
@prefix so: <http://stackoverflow.com/schema#> .
@prefix xsd: <http://www.w3.org/2001/XMLSchema#> .

<http://stackoverflow.com/q/123>
    so:creationDate "2024-03-15T10:30:00Z"^^xsd:dateTime .
```

These fields describe the source snapshot, not a complete revision history.
Last activity or last edit dates alone do not establish technical freshness.

| Entity | Representation |
| --- | --- |
| Question | `so:Question`, identified by `http://stackoverflow.com/q/{post_id}` |
| Answer | `so:Answer`, identified by `http://stackoverflow.com/a/{post_id}` |
| Comment | `so:Comment`, with `so:QuestionComment` or `so:AnswerComment` for comments on discussions |
| Tag | `so:Tag`, identified by `http://stackoverflow.com/tags/{encoded_tag}` |
| Tag documentation | `so:TagWiki` and `so:TagExcerpt`, connected to their tag |

Questions, answers and documentation posts carry source post IDs. Available
properties include titles, original HTML bodies, scores, aggregated upvote and
downvote counts, timestamps and content licenses. Comments carry text, scores,
creation dates and licenses. Question-specific properties include source answer,
view and favorite counts. Missing source values are omitted. Individual voters
and user-profile entities are not represented by this mapping.

| Relationship | Meaning | Exported inverse |
| --- | --- | --- |
| `so:hasAnswer` | Question to one of its answers | `so:answersQuestion` |
| `so:acceptedAnswer` | Question to its resolved accepted answer | `so:acceptedAnswerOf` |
| `so:hasComment` | Post to a comment on it | `so:commentOn` |
| `so:taggedWith` | Question to one of its source tags | `so:tagsQuestion` |
| `so:hasTagWiki` | Tag to its documentation post | `so:tagWikiOf` |
| `so:hasTagExcerpt` | Tag to its short description | `so:tagExcerptOf` |
| `so:linkedTo` | Directed source PostLinks relation of type 1 | None |
| `so:duplicateOf` | Directed source PostLinks relation of type 3 | None |

The listed inverse relationships are written as triples, so querying them does
not require an inference engine. A link or duplicate edge does not imply a reverse
edge. The mapper also writes applicable superclass types. Answer status uses
classes such as `so:AnsweredQuestion`, `so:UnansweredQuestion` and
`so:QuestionWithAcceptedAnswer`; missing edges alone do not establish unanswered
status. An accepted answer or a high score does not establish technical correctness.
The ontology defines `so:possibleBetterAnswer`, but this exporter does not generate
that assessment.

## How the language graphs connect

Language membership is determined from question tags using the release's selection
registry. Matching covers configured base tags, version patterns and aliases.
Answers and discussion comments inherit their question's graph membership; their
bodies are not classified independently. Questions without a registry match are
routed to the `http://stackoverflow.com/extra-languages` graph in the full export.
This category is not an additional match for questions already assigned to a
registered language.

### The additional extra-languages dataset

`extra-languages` can be published as its own dataset alongside the 39 language
datasets. Its graph IRI is `http://stackoverflow.com/extra-languages`. It contains
questions with no match in the release's configured language registry, including
their answers, comments and outgoing question links. This can include questions
about unconfigured languages and questions without a recognized language tag;
it is not a classification into one additional programming language.

The graph also holds tags without recorded graph usage and tag documentation
without a resolved owner. Its publication package includes its discussion shards,
the schema and all shared documentation shards. Regular language packages include
shared documentation from this graph, but not its complete discussion collection.
Load the extra-languages dataset from the same export identity to resolve links
whose target discussions are in that graph. It complements the configured
language selections without assigning those discussions to another language.

There are three ways language graphs share or connect content:

1. **The same discussion in several graphs.** If a question matches both Python
   and Java, its question, answer and comment statements are emitted into both
   language graphs with the same entity IRIs. This overlap follows source tags;
   it is not a translation or an inferred similarity relationship.
2. **Shared tags and documentation.** Tags retain their identities across graphs.
   Their definitions, wikis, excerpts and documentation comments are routed to
   the graphs of questions using those tags. Tags without recorded usage, and
   documentation without a resolved tag owner, go to `extra-languages`.
3. **Links between different questions.** `so:linkedTo` and `so:duplicateOf` point
   from a question to another question's IRI. The edge is stored in the source
   question's language graphs. Its target can belong to another language graph.

For example, Q1 has tags matching both Python and Java, so its discussion is
represented in both graphs. Q2 belongs to Java and is the target of a source link
from Q1. The following statements illustrate this arrangement:

| Named graph | Subject | Predicate | Object |
| --- | --- | --- | --- |
| `http://stackoverflow.com/python` | Q1 | `so:linkedTo` | Q2 |
| `http://stackoverflow.com/java` | Q1 | `so:linkedTo` | Q2 |
| `http://stackoverflow.com/java` | Q2 | `rdf:type` | `so:Question` |

Q1 stands for `http://stackoverflow.com/q/1` in both graphs; Q2 stands for
`http://stackoverflow.com/q/2`. The two Q1 entries describe the same entity.
There is no additional "same entity" edge. The two `so:linkedTo` statements are
copies of the same source link stored in different named graphs.

These IDs are illustrative. Q2's reference in the Python graph
does not by itself include Q2's title, body or answers there. Those descriptions
are available when the package containing Q2's discussion has been loaded.

Each language package contains the selected language's discussion shards plus
all shared tag-documentation shards and the schema. A Java graph appearing in a
Python package's inventory can therefore contain shared documentation without
containing Java's full question-and-answer collection. The same applies to
`extra-languages`: its shared documentation can be present without its discussion
shards. A referenced question can have no local description when its discussion
is only in another package.

To follow these connections across languages, load the relevant packages from
the same export identity into one RDF dataset and preserve the named graphs.
Shared shards occur in multiple packages; avoid importing them repeatedly into
stores that retain duplicate statements. For entity counts across graphs, use
`COUNT(DISTINCT ?question)`. Summing quad counts measures graph statements,
including repeated statements in different language graphs, rather than unique
discussions.

`publication.json` records each file's path, stored byte count, SHA-256 checksum
and graph key, together with the export identity. RDF files are under `graphs/`.
Internal run manifests, QLever indexes, credentials and uploader source are
excluded from the archive.

## Loading and querying

Load the `.nq` files as N-Quads and preserve their embedded named graph IRIs.
For `.nq.gz` files, decompress them first if your RDF store cannot read gzip.

The following query counts loaded quads by graph. Use the graph inventory above
to check the result, or restrict queries to `http://stackoverflow.com/go` when working
with the selected language.

```sparql
SELECT ?graph (COUNT(*) AS ?quads)
WHERE { GRAPH ?graph { ?s ?p ?o } }
GROUP BY ?graph
```

Retrieve questions and their available answers in this language graph:

```sparql
PREFIX so: <http://stackoverflow.com/schema#>

SELECT ?question ?title ?answer
WHERE {
  GRAPH <http://stackoverflow.com/go> {
    ?question a so:Question .
    OPTIONAL { ?question so:hasTitle ?title }
    OPTIONAL { ?question so:hasAnswer ?answer }
  }
}
LIMIT 25
```

After loading other language packages, find linked or duplicate questions whose
descriptions are available in another named graph:

```sparql
PREFIX so: <http://stackoverflow.com/schema#>

SELECT DISTINCT ?question ?relation ?target ?targetGraph ?targetTitle
WHERE {
  GRAPH <http://stackoverflow.com/go> {
    VALUES ?relation { so:linkedTo so:duplicateOf }
    ?question a so:Question ; ?relation ?target .
  }
  GRAPH ?targetGraph {
    ?target a so:Question ; so:hasTitle ?targetTitle .
  }
  FILTER (?targetGraph != <http://stackoverflow.com/go>)
}
LIMIT 25
```

The second query returns only targets with loaded descriptions and titles. A
target can occur in several graphs through overlapping tag selections; this
does not mean the source and target questions use different languages exclusively.

## Uses and limitations

The graph supports SPARQL analysis and retrieval over Stack Overflow discussions,
including retrieval-augmented question answering. It represents the source
snapshot; later edits and deletions on Stack Overflow are not reflected here.

## Quality notes

- Votes are represented as aggregated upvote and downvote counts. Individual
  vote events and voter identities are not included.
- The graph includes selected moderation-related fields, such as a question's
  closure date, but does not represent the full moderation context or revision
  history.
- Community-generated Stack Overflow content can contain errors, outdated
  information and bias. Changes in languages, libraries and development practices
  can make advice less applicable over time.
- Scores, accepted-answer status and recent activity are source signals; they
  do not establish that an answer is correct or current.

## License and attribution

This dataset is derived from Stack Overflow content. Its declared dataset license
is [CC BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/)
(`CC-BY-SA-4.0`). Preserve required attribution and license notices when
redistributing derived artifacts, and identify changes where required.

Individual source contributions retain their applicable license terms.
[Stack Overflow's licensing guidance](https://stackoverflow.com/help/licensing)
distinguishes CC BY-SA 2.5, 3.0 and 4.0 according to contribution date. A dataset-level
license declaration does not replace those source notices. The graph preserves
source-provided license labels in `so:contentLicense` where available. Consult the
original posts and revision records for author attribution and applicable terms.
The Hugging Face metadata declares `cc-by-sa-4.0`, consistent with the MDC
publication. For dataset questions, use this repository's Community discussion
page; source-post attribution and licensing remain attached to the original content.

## Citation

If you use this dataset, cite the Stack2Graph project. The research citation
accompanies the required attribution for the underlying Stack Overflow content.

Kleybolte, L. A., Ventura, V., & Zarcone, A. (2026). *Stack2Graph: A Structured
Knowledge Representation of Stack Overflow Data for Retrieval-based Question
Answering*. In *Proceedings of the Knowledge Graphs and Large Language Models
Workshop (KG-LLM) @ LREC26* (pp. 120-133). European Language Resources Association
(ELRA). [https://doi.org/10.63317/583q4d3mwbdu](https://doi.org/10.63317/583q4d3mwbdu).

## Export provenance

These fingerprints identify the inputs and exporter used for this release.
The export identity describes the build configuration and inputs; file checksums
are listed separately in `publication.json`.

| Component | Fingerprint |
| --- | --- |
| Export identity | `4d415cea2977835bf886c177f2bfc309a22738e145591f9c7ae4256e9bd086d5` |
| Source snapshot identity | `56fe643952cec74b17ea13d91edc8ad95181326156177c94cce48d3fed9834b9` |
| Language registry | `d2a7357c04e7f47d9bb598189aeeb7db0680d6b35f0d9695d8d2e544121afb8e` |
| Ontology | `1fc4dc1cc73a1baeddc0e1d70dc22ab95962581c6b61eb895ddcc70956621153` |
| Exporter | `8d9b9bac86b5e9c19bb0ce5af022e8a1ecd14c9f8e82e73169cbdb8455470422` |

Source code and documentation: [stack2graph](https://github.com/tha-atlas/Stack2Graph).