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  ---
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- license:
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- - cc-by-sa-4.0
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- - gfdl
 
 
 
 
 
 
 
 
 
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  size_categories:
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  - 1M<n<10M
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- task_ids:
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- - language-modeling
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- - masked-language-modeling
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- language:
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- - en
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- - fr
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  configs:
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- - config_name: data
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  data_files:
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  - split: train
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- path: data/dataset.zip
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- - name: images
814
- list:
815
- - name: content_url
816
- dtype: string
817
- - name: width
818
- dtype: int64
819
- - name: height
820
- dtype: int64
821
- - name: alternative_text
822
- dtype: string
823
- - name: values
824
- sequence: string
825
- - name: images
826
- list:
827
- - name: content_url
828
- dtype: string
829
- - name: width
830
- dtype: int64
831
- - name: height
832
- dtype: int64
833
- - name: alternative_text
834
- dtype: string
835
- - name: caption
836
- dtype: string
837
- - name: main_entity
838
- struct:
839
- - name: identifier
840
- dtype: string
841
- - name: url
842
- dtype: string
843
- - name: additional_entities
844
- list:
845
- - name: identifier
846
- dtype: string
847
- - name: url
848
- dtype: string
849
- - name: aspects
850
- sequence: string
851
- - name: image
852
- struct:
853
- - name: content_url
854
- dtype: string
855
- - name: width
856
- dtype: int64
857
- - name: height
858
- dtype: int64
859
- - name: alternate_text
860
- dtype: string
861
- - name: caption
862
- dtype: string
863
  ---
864
 
865
- this is a testing dataset for myself.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
  ---
2
+ pretty_name: Wikimedia Enterprise Structured Contents — cywiki_namespace_0
3
+ language:
4
+ - cy
5
+ license: cc-by-sa-4.0
6
+ task_categories:
7
+ - text-generation
8
+ - question-answering
9
+ - text-retrieval
10
+ tags:
11
+ - wikipedia
12
+ - wikimedia-enterprise
13
+ - structured-contents
14
  size_categories:
15
  - 1M<n<10M
 
 
 
 
 
 
16
  configs:
17
+ - config_name: default
18
  data_files:
19
  - split: train
20
+ path: data/*.parquet
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
21
  ---
22
 
23
+ # cywiki_namespace_0
24
+
25
+ Structured Contents snapshot of `cywiki_namespace_0` from the
26
+ [Wikimedia Enterprise API](https://enterprise.wikimedia.com/docs/snapshot/),
27
+ repackaged as Parquet with a pinned schema.
28
+
29
+ The upstream Wikimedia Foundation dataset
30
+ ([`wikimedia/structured-wikipedia`](https://huggingface.co/datasets/wikimedia/structured-wikipedia))
31
+ ships NDJSON which has known issues loading via
32
+ `datasets.load_dataset()` — see discussions
33
+ [#5](https://huggingface.co/datasets/wikimedia/structured-wikipedia/discussions/5),
34
+ [#15](https://huggingface.co/datasets/wikimedia/structured-wikipedia/discussions/15),
35
+ [#16](https://huggingface.co/datasets/wikimedia/structured-wikipedia/discussions/16).
36
+ This dataset is the same upstream content, normalised so
37
+ `load_dataset(...)` works without specifying a `Features` override.
38
+
39
+ ## Source
40
+
41
+ - Upstream: [Wikimedia Enterprise Structured Contents API](https://enterprise.wikimedia.com/docs/snapshot/#structured-contents-snapshot-download-beta)
42
+ - Snapshot identifier: `cywiki_namespace_0`
43
+ - Format at source: `.tar.gz` containing sharded `.ndjson`
44
+ - Shards in this release: 1
45
+
46
+ ## File layout
47
+
48
+ ```
49
+ README.md ← this file
50
+ schema.json ← pinned Arrow schema (IPC + field-name index)
51
+ data/
52
+ cywiki_namespace_0_0.parquet
53
+ cywiki_namespace_0_1.parquet
54
+ ... (1 files total)
55
+ ```
56
+
57
+ One Parquet file per upstream NDJSON shard. Files are independently
58
+ downloadable, so consumers can parallelise downloads or pull only the
59
+ subset they need rather than the whole dataset.
60
+
61
+ ## Loading the dataset
62
+
63
+ Every shard has a byte-identical embedded schema (alphabetised
64
+ recursively so struct field order is stable across shards). All of
65
+ these load without extra config:
66
+
67
+ ```python
68
+ # Hugging Face datasets
69
+ from datasets import load_dataset
70
+ ds = load_dataset("VoeTheDon/testing-wiki-structured", split="train", streaming=True)
71
+
72
+ # Polars
73
+ import polars as pl
74
+ df = pl.read_parquet("hf://datasets/VoeTheDon/testing-wiki-structured/data/*.parquet")
75
+
76
+ # DuckDB
77
+ import duckdb
78
+ duckdb.sql(
79
+ "SELECT name, url FROM 'hf://datasets/VoeTheDon/testing-wiki-structured/data/*.parquet' LIMIT 10"
80
+ )
81
+
82
+ # pyarrow
83
+ import pyarrow.dataset as pads
84
+ table = pads.dataset("hf://datasets/VoeTheDon/testing-wiki-structured/data/", format="parquet").to_table()
85
+ ```
86
+
87
+ Four columns are stored as JSON-encoded strings (see *Schema notes*
88
+ below). Decode on read:
89
+
90
+ ```python
91
+ import json
92
+
93
+ row = next(iter(ds))
94
+ sections = json.loads(row["sections"]) # list[dict]
95
+ infoboxes = json.loads(row["infoboxes"]) # list[dict]
96
+ tables = json.loads(row["tables"]) # list[dict]
97
+ for ref in row["references"]:
98
+ ref_meta = json.loads(ref["metadata"]) # dict
99
+ ```
100
+
101
+ If you need the canonical Arrow schema explicitly (e.g. for a
102
+ validation step in a downstream pipeline), it's published as
103
+ `schema.json` at the repo root in Arrow IPC format:
104
+
105
+ ```python
106
+ import json, pyarrow as pa
107
+ payload = json.loads(open("schema.json").read())
108
+ schema = pa.ipc.read_schema(pa.py_buffer(bytes.fromhex(payload["arrow_ipc_hex"])))
109
+ ```
110
+
111
+ ## Schema notes
112
+
113
+ Four fields are JSON-encoded rather than stored as native Arrow structs:
114
+
115
+ | Field | Why |
116
+ |---|---|
117
+ | `sections` | Recursive `has_parts[].has_parts[]…` nesting reaches depth ~100 in real articles. Apache Arrow's C Data Interface caps struct recursion at 64 levels; `datasets.load_dataset()` round-trips schemas through that interface and rejects deeper structures. |
118
+ | `infoboxes` | Same recursive shape as `sections`. |
119
+ | `tables` | Shallower today but the same recursive structure — pre-emptively encoded so future upstream changes don't break the schema. |
120
+ | `references[].metadata` | Open dict of Wikipedia citation-template parameters (`rft.jtitle`, `chapter-url`, `first1`, positional `"1"`, …). Hundreds of ad-hoc keys appear across articles, producing a different inferred Arrow `struct` per shard, which breaks cross-shard schema unification. |
121
+
122
+ All other fields (`name`, `url`, `abstract`, `event`, `license[]`,
123
+ `version`, `image`, `main_entity`, `references[]` excluding metadata,
124
+ etc.) retain native Arrow struct/list types and are queryable without
125
+ decoding.
126
+
127
+ Struct field order is alphabetised recursively so every shard has a
128
+ byte-identical embedded schema — pyarrow's JSON inference otherwise
129
+ captures keys in encounter order, which makes Arrow treat
130
+ `struct<a, b>` and `struct<b, a>` as different types.
131
+
132
+ ## Known limitations
133
+
134
+ - **Article categories are not included.** The upstream Structured
135
+ Contents snapshot does not expose categories. If you need them,
136
+ query the regular [WME Snapshots API](https://enterprise.wikimedia.com/docs/snapshot/)
137
+ or the [MediaWiki API:Categories](https://www.mediawiki.org/wiki/API:Categories)
138
+ endpoint.
139
+ - License passes through the upstream Wikipedia license
140
+ (CC-BY-SA-4.0) for article text.
141
+ - This is a Beta-tier upstream snapshot — schema can change between
142
+ WME releases. Each version of this dataset re-pins `schema.json`;
143
+ consumers who want a stable contract should pin to a specific
144
+ dataset revision.