Datasets:

acrion
/

zelph

Error code:   DatasetGenerationError
Exception:    ValueError
Message:      Expected object or value
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1827, in _prepare_split_single
                  for key, table in generator:
                                    ^^^^^^^^^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 613, in wrapped
                  for item in generator(*args, **kwargs):
                              ~~~~~~~~~^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 281, in _generate_tables
                  examples = [ujson_loads(line) for line in batch.splitlines()]
                              ~~~~~~~~~~~^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/utils/json.py", line 20, in ujson_loads
                  return pd.io.json.ujson_loads(*args, **kwargs)
                         ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^
              ValueError: Expected object or value
              
              The above exception was the direct cause of the following exception:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1369, in compute_config_parquet_and_info_response
                  parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
                                                                        ~~~~~~~~~~~~~~~~~~~~~~~~~^
                      builder, max_dataset_size_bytes=max_dataset_size_bytes
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
                  builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
                  ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1694, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ~~~~~~~~~~~~~~~~~~~~~~~~~~^
                      gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  ):
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1880, in _prepare_split_single
                  raise DatasetGenerationError("An error occurred while generating the dataset") from e
              datasets.exceptions.DatasetGenerationError: An error occurred while generating the dataset

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

type string	id string	labels string	claims string
item	Q44	{"en":{"language":"en","value":"beer"}}	{"P1245":[{"mainsnak":{"snaktype":"value","property":"P1245","hash":"07d5be8a1aece173b516f3dc08ea6566b38f56f8","datavalue":{"value":"6715","type":"string"},"datatype":"external-id"},"type":"statement","id":"Q44$8fa3db3f-4b3e-962c-4cd6-a0f505413182","rank":"normal"}],"P279":[{"mainsnak":{"snaktype":"value","property":"P...
item	Q140	{"en":{"language":"en","value":"lion"}}	"{\"P225\":[{\"mainsnak\":{\"snaktype\":\"value\",\"property\":\"P225\",\"hash\":\"e2be083a19a0c5e1a(...TRUNCATED)
item	Q144	{"en":{"language":"en","value":"dog"}}	"{\"P366\":[{\"mainsnak\":{\"snaktype\":\"value\",\"property\":\"P366\",\"hash\":\"bca840db2d3421b5b(...TRUNCATED)
item	Q171	{"en":{"language":"en","value":"wiki"}}	"{\"P1245\":[{\"mainsnak\":{\"snaktype\":\"value\",\"property\":\"P1245\",\"hash\":\"4ec615998e55a74(...TRUNCATED)
item	Q209	{"en":{"language":"en","value":"rectangle"}}	"{\"P1322\":[{\"mainsnak\":{\"snaktype\":\"value\",\"property\":\"P1322\",\"hash\":\"ba7fe4b45441b42(...TRUNCATED)
item	Q282	{"en":{"language":"en","value":"wine"}}	"{\"P1036\":[{\"mainsnak\":{\"snaktype\":\"value\",\"property\":\"P1036\",\"hash\":\"8505978b7f09ee7(...TRUNCATED)
item	Q467	{"en":{"language":"en","value":"woman"}}	"{\"P1245\":[{\"mainsnak\":{\"snaktype\":\"value\",\"property\":\"P1245\",\"hash\":\"588b694e82ccd1a(...TRUNCATED)
item	Q573	{"en":{"language":"en","value":"day"}}	"{\"P373\":[{\"mainsnak\":{\"snaktype\":\"value\",\"property\":\"P373\",\"hash\":\"c3d0f2bf82dec0bbd(...TRUNCATED)
item	Q729	{"en":{"language":"en","value":"animal"}}	"{\"P850\":[{\"mainsnak\":{\"snaktype\":\"value\",\"property\":\"P850\",\"hash\":\"175c9b38b3fe93d92(...TRUNCATED)
item	Q808	{"en":{"language":"en","value":"virus"}}	"{\"P171\":[{\"mainsnak\":{\"snaktype\":\"value\",\"property\":\"P171\",\"hash\":\"ce742f057fe07478c(...TRUNCATED)

End of preview.

zelph Binaries Dataset

This dataset provides pre-compiled binary files (.bin) for use with zelph, a sophisticated semantic network system. These binaries are derived from large knowledge bases like Wikidata, optimized for fast loading and efficient querying.

Dataset Description

zelph binaries enable users to work with semantic networks without the need to import raw dumps (e.g., JSON files), which can take hours. Instead, these .bin files load in minutes, though they require substantial RAM.

Which file do you want?

Select by the RAM column, not the file size. A .bin roughly triples when it is loaded: the graph is reconstructed as adjacency maps and name tables rather than mapped from the file.

File	Nodes	Download	RAM to load	Load time
`wikidata-20260309-all.bin`	983,424,620	82 GiB	223.7 GiB	23m 23s
`wikidata-20260309-all-pruned-medium.bin`	114,477,445	9.0 GiB	25.9 GiB	2m 08s
`wikidata-20260309-all-pruned-small.bin`	26,533,048	2.2 GiB	6.0 GiB	25s

-small is the one to begin with: it loads in 25 seconds and leaves room to work on a 16 GiB machine. On 8 GiB it fits, but not with much to spare.
-medium is the same network with people still in it, and requires a 32 GiB machine.
wikidata-20260309-all.bin is a faithful 1:1 port of the Wikidata JSON dump – the same content, in a format that loads in minutes instead of hours. It needs a machine built for it.

Historic 2017 dumps (wikidata-20171227.bin, 44.6 GiB RAM, and its pruned variant at 3.8 GiB) are also available.

What the pruned variants drop, and what they keep

Removed, in the order they went – least missed first: the encyclopedia’s own plumbing (categories, templates, list and disambiguation pages, one item per integer and per calendar day), astronomical catalogues, sequence databases and chemistry, individual museum objects, publications and their citation graph, everything filed under an administrative entity, everything carrying a country, and – in -small only – people.

Retained, intentionally: the class hierarchy. Eliminating instances of a class never eradicates the class itself, so both pruned versions respond to class-level queries identically to one another. The disjointness query outlined under Working on the Wikidata Class Hierarchy returns the same 81 topmost culprits on -medium and on -small; they differ only in which individual items they still include.

A file that appears by itself: `.pidx`

The very first time you pose a transitive query (P279+, or SPARQL with wdt:P279+), zelph generates a <file>.bin.pidx.322 adjacent to the network. It stores the persisted transitive closure of P279 (subclass of).

It is a machine-local cache, not data, and it is deliberately not part of this dataset: it stores raw pairs in host byte order, so it would be wrong on a machine of different endianness, and it is validated against the exact network it was built from. Yours is built automatically in about fifteen seconds, and deleting it costs time and never information.

For sizes, creation dates, how the pruning was done and how to load parts of a file without loading all of it, see https://zelph.org/binaries.

How to Use

Download the desired .bin file from this dataset.
In zelph interactive mode, load it with:
```
.load /path/to/your-file.bin
```
For Wikidata files, switch the display language so that Q/P ids resolve:
```
.lang wikidata
```
Run queries, define rules, perform inferences or run complete scripts (see zelph on GitHub for details).

If a file is larger than your RAM, you do not have to give up on it: zelph can load parts of a .bin — selected chunks, or a graph without its name maps — which is described under Partial Loading.

LLM-Friendly Outputs

zelph can generate rule-based inferences in a compressed text format optimized for LLM training or processing. This uses a token encoder that maps Wikidata IDs (Q/P) to compact UTF-8 symbols (CJK range), reducing input length while preserving structure.

This feature is currently focused on Wikidata, but it can be adapted for similar use cases. Use it to export inferences from loaded binaries for LLM datasets – see the command documentation on GitHub for details.

Citation

If you use this dataset, cite as:

@dataset{zelph,
  author = {Stefan Zipproth},
  title = {zelph Binaries Dataset},
  year = {2026},
  url = {https://huggingface.co/datasets/acrion/zelph}
}

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